Multi-Omics Approaches to Improve Clubroot Resistance in Brassica with a Special Focus on Brassica oleracea L.

Shaw, Ranjan K.; Shen, Yusen; Yu, Huifang; Sheng, Xiaoguang; Wang, Jiansheng; Gu, Honghui

doi:10.3390/ijms23169280

Open AccessReview

Multi-Omics Approaches to Improve Clubroot Resistance in Brassica with a Special Focus on Brassica oleracea L.

by

Ranjan K. Shaw

,

Yusen Shen

,

Huifang Yu

,

Xiaoguang Sheng

,

Jiansheng Wang

and

Honghui Gu

^*

Institute of Vegetables, Zhejiang Academy of Agricultural Sciences, Hangzhou 310021, China

^*

Author to whom correspondence should be addressed.

Int. J. Mol. Sci. 2022, 23(16), 9280; https://doi.org/10.3390/ijms23169280

Submission received: 15 June 2022 / Revised: 4 August 2022 / Accepted: 13 August 2022 / Published: 17 August 2022

(This article belongs to the Special Issue Plant Disease Resistance 2.0)

Download

Browse Figures

Versions Notes

Abstract

:

Brassica oleracea is an agronomically important species of the Brassicaceae family, including several nutrient-rich vegetables grown and consumed across the continents. But its sustainability is heavily constrained by a range of destructive pathogens, among which, clubroot disease, caused by a biotrophic protist Plasmodiophora brassicae, has caused significant yield and economic losses worldwide, thereby threatening global food security. To counter the pathogen attack, it demands a better understanding of the complex phenomenon of Brassica-P. brassicae pathosystem at the physiological, biochemical, molecular, and cellular levels. In recent years, multiple omics technologies with high-throughput techniques have emerged as successful in elucidating the responses to biotic and abiotic stresses. In Brassica spp., omics technologies such as genomics, transcriptomics, ncRNAomics, proteomics, and metabolomics are well documented, allowing us to gain insights into the dynamic changes that transpired during host-pathogen interactions at a deeper level. So, it is critical that we must review the recent advances in omics approaches and discuss how the current knowledge in multi-omics technologies has been able to breed high-quality clubroot-resistant B. oleracea. This review highlights the recent advances made in utilizing various omics approaches to understand the host resistance mechanisms adopted by Brassica crops in response to the P. brassicae attack. Finally, we have discussed the bottlenecks and the way forward to overcome the persisting knowledge gaps in delivering solutions to breed clubroot-resistant Brassica crops in a holistic, targeted, and precise way.

Keywords:

Brassica oleracea; Plasmodiophora brassicae; omics; genomics; epigenomics; transcriptomics; ncRNAomics; proteomics; metabolomics

1. Introduction

Brassica oleracea is one of the agronomically important species of Brassicaceae family, comprising several economically important vegetables such as cabbage, cauliflower, broccoli, kale, kohlrabi, and brussels sprout. Remarkable morphological diversity is displayed by different morphotypes of B. oleracea, which are grown for their leaves, stems, inflorescence, lateral and axillary buds. B. oleracea vegetables are healthy and possess a variable amount of vitamin, fiber, minerals, and useful phytochemicals [1,2]. Additionally, B. oleracea is a good source of a major class of secondary metabolites, glucosinolates [3], possessing anti-cancer properties. B. oleracea production is greatly threatened by a range of fungi, bacteria, viruses and protist of which clubroot disease caused by a root-infecting protist Plasmodiophora brassicae Woronin is one of the most destructive diseases affecting B. oleracea worldwide. Due to P. brassicae attack, an estimated loss of 10% to 15% in both quality and yields of cruciferous crops are reported [4]. Clubroot has caused a loss of 30%, even up to a reduction of 80–91% in yield during experimental field trials in canola [5,6]. Owing to the huge economic impact caused by clubroot, various management strategies have been used to control clubroot disease. However, due to the broad host range of the pathogen and the high survival rate of the resting spores, up to 20 years [7], the management of clubroot becomes complicated. Moreover, traditional cultural practices, including soil liming or fungicides treatment are expensive and unreliable [8]. Crop rotation with non-host species [9,10] and farm machinery sanitization [11] may help in reducing the severity of clubroot to a certain extent. The concentration of resting spores of P. brassicae is highly correlated with the severity of clubroot disease [12,13]. Therefore, spore-density reduction could act as an effective strategy to manage clubroot disease. Although various management strategies have been employed to curb clubroot, host-plant resistance offers the most economical, sustainable, and environment-friendly solution to mitigate clubroot disease [14,15]. Planting improved varieties with multiple resistance genes and adopting a crop-rotation scheme would provide a better safeguard against P. brassicae growth [16,17]. Hence, an integrated approach involving conventional pest-management strategies and deployment of resistant cultivars could effectively eliminate clubroot disease [16,18,19].

In recent years, the advancement of next-generation sequencing (NGS) and mass spectrometry technologies has provided new insights into the genetic improvement of various crops for biotic and abiotic stress resistance. The omics approaches involving genomics, transcriptomics, proteomics, and metabolomics have enormous potential for understanding the mechanisms of host-pathogen interactions. In the functional genomics era, a holistic approach to using omics technologies has allowed the comprehensive examination of plants and microbes, leading to the discovery of plant defence mechanisms against pathogens. Omics technologies have broader implications in understanding the basic pathogenic mechanisms critical to disease progression. Omics approaches are increasingly applied in Brassica crops to gain insight into the complex mechanisms of host-pathogen interactions. Due to affordable NGS and spectrometry technologies, a considerable amount of data at the multi-omics levels are becoming available in Brassica crops [20], bringing the possibilities of improving disease resistance.

Clubroot, caused by Plasmodiophora brassicae Woronin, is a soil-borne and an obligate biotrophic protist and taxonomically belongs to the phylum Plasmodiophoromycota [21]. P. brassicae is one of the most devastating diseases infecting Brassica crops [22], reducing quality and yields worldwide [4]. The protist infects the plant through root hairs, which undergo abnormal cell enlargement and uncontrolled cell division, causing the formation of gall, also called ‘club’, which are irregular, nonhomogeneous, and are up to 5 to 6 inches wide (Figure 1). The deformed roots with thick and fleshy growth create a nutrient sink, nourishing the pathogen and leading to cracking and rotting of the roots. The club-shaped roots reduce the efficiency of water and nutrients uptake to the host plants, resulting in stunted growth, chlorosis, leaf abscission, wilting, reduced seed yield, and even the premature death of the infected plants [4,23]. P. brassicae has a wide host range that serves as sources of resting spores to perpetuate the infestation cycle [4,24]. Clubroot development is favored by excessive moisture, low soil pH, and soil temperature between 64 to 77 °F. Once the soil becomes infested with clubroot, the spores can survive in the soil as resting spores for up to 20 years, making it difficult to be managed by cultural practices or chemical means [4,25].

P. brassicae has a complex life cycle that consists of three stages (i) dormant resting stage, (ii) primary stage (root–hair infection stage), and (iii) secondary zoospore reinfection (cortex infection stage). Under favorable conditions, primary zoospores are released from the resting spores, germinate, and the plant root exudates enhance the germination of the resisting spores [26,27]. The attachment of zoospores to the surface of root hairs initiates primary infection, followed by penetration, and eventually grows to form the primary plasmodia. The primary plasmodia then undergo a series of cell divisions to form intracellular multinucleate secondary plasmodia. The secondary plasmodia directly infect the cortical cells, change the root hormone balance and induce cell hypertrophy (cell division) and cell hyperplasia (cell elongation), resulting in gall formation [28]. The secondary plasmodia are then divided into numerous mature resting spores scattered into the soil when the galls decompose and disintegrate [29], becoming the source of infection for the following year. Once the soil is contaminated with P. brassicae, the longevity of the resting spore makes the field unsuitable for the cultivation of Brassicaceae crops.

P. brassicae has a wide host range and could infect about 3700 species and 330 genera in the Brassicaceae family [30]. Physiological classification and virulence variation were carried out long ago in the 1930s [31]. P. brassicae pathotypes are classified based on the reactions of differential hosts. The accurate estimation of pathotypes of field isolates by host differentials is essential for resistance breeding, as accurate pathotyping assists in selecting resistant cultivars [32]. Based on the virulence pattern, several pathotype classification systems have been proposed in the past decades to study the pathogenic variability. The current differential systems used internationally are Williams’ differential set [33], European clubroot differential (ECD) [34], pathotyping according to Somé [35], Canadian clubroot differential (CCD) [36], and Sinitic clubroot differential set (SCD) [32]. The emergence of new pathotypes is a continuous process, and while testing on the additional hosts, virulence variability could be found within a pathotype [32,37,38].

In B. oleracea, significant advances were made at the multi-omics level to understand the complex resistance mechanisms of Brassica-P. brassicae pathosystem. This review summarizes the impressive contributions of emerging omics technologies to curb clubroot disease in B. oleracea by elucidating the dynamic changes transpiring at the metabolic and signaling pathways involved in defence response against P. brassicae attack. We have also focused on various aspects of clubroot disease and host-resistance mechanisms at the physiological, biochemical, and molecular levels. Finally, we have discussed the bottlenecks and how to integrate the omics technologies to deliver solutions to breed clubroot-resistant Brassica crops in a holistic, targeted, and precise way.

In the functional genomics era, ‘-omics’ are indispensable, which have been exemplified by many studies in various crops. Therefore, it is required to understand the defence mechanisms of clubroot resistance to establish the theoretical basis of genes and pathways involved in defence response to P. brassicae infection at the primary and secondary infection stages. To illuminate this, several ‘-omics’ studies, including genomics, epigenomics, transcriptomics, ncRNAomics, proteomics, and metabolomics have been conducted in Brassica species to elucidate the dynamic changes at the multi-omics levels. In the following sections, this has been discussed in detail to get a comprehensive understanding of the molecular mechanisms of Brassica-P. brassicae interaction.

2. Genomics

Dramatic innovations in NGS technologies in the last few decades have led to the publishing of whole-genome sequences, millions of molecular markers and high-density genetic maps. Numerous functional genomics studies aimed at characterizing the disease resistance genes may provide insights into the basis of disease resistance [39,40]. The molecular genetic studies in Brassica spp. have led to the identification of a large number of QTLs, candidate genes and the allelic variations associated with the resistance genes will accelerate the improvement of Brassica spp. against P. brassicae.

2.1. Pangenome to Identify Novel Resistance Gene Analogs (RGAs)

Reduced sequencing cost has facilitated an increasing amount of reference genome data in Brassica spp., including B. oleracea. Most of the B. oleracea genomes were assembled using short-read sequence technologies by Illumina [41,42]. Recently, third-generation sequencing technologies capable of generating long-read sequences such as single-molecule real-time (SMRT) sequencing (PacBio) and Nanopore sequencing technologies (Oxford Nanopore Technologies, Oxford, UK) have been used to develop high-quality chromosome-scale genome assemblies in broccoli, cabbage, and cauliflower [43,44,45]. But the reference genomes may not represent all the morphotypes of B. oleracea, such as brussels sprout (lateral leaf buds) and kohlrabi (tuberous stems) not having genome assemblies. This may result in missing out genetic diversity present within B. oleracea, overlooking novel resistance alleles by relying on a single reference genome. This limitation has triggered the development of pangenomes, which allows the identification of comprehensive genomic variations from the gene pools represented by many lines within a species [46]. The pangenome of B. oleracea revealed that many R genes are not present in all lines [47] and are dispensable indicating the highly variable nature of R genes. R genes are grouped into a large repertoire called resistance gene analogs (RGAs), including NBS-LRR (TIR-NBS-LRR and CC-NBS-LRR), pattern-recognition receptors (PRRs) comprising receptor-like protein kinases (RLKs), receptor-like proteins (RLPs) and wall-associated kinases [48,49]. Recently, a pangenome study in B. oleracea revealed that the wild relative B. macrocarpa harbors the highest number of (1495) RGA candidates [50], suggesting that wild Brassica could be a large repository of R genes. Using pangenomics, Bayer et al. [50] detected 59 RGA candidates within Sclerotinia, clubroot, and Fusarium wilt resistance QTLs in B. oleracea, and the QTLs harbored 28 RLKs. The sequence comparison of the RGAs placed within the QTL region will help candidate-gene identification for disease resistance.

2.2. Resistance Sources, Genetics of Resistance and Identification of QTLs for Clubroot Resistance in B. oleracea

Several B. oleracea germplasm collections consisting of different morphotypes have been evaluated for clubroot resistance by various research groups, and several resistance sources have been identified. Fewer resistance accessions have been reported in cauliflower [51,52,53,54] compared to other B. oleracea varieties such as cabbage, kale, broccoli, brussels sprout, etc. [51,52,55,56,57,58,59]. A large number of accessions of cabbage, cauliflower, broccoli, kale, and brussels sprout were evaluated by Crisp et al. [51] and found resistance in some cabbage and kale accessions. Peng et al. [14] reported two cabbage cultivars, ‘Kilaherb’ and ‘Tekila’, highly resistant to all the five pathotypes (2,3,5,6 and 8) found in Canada. Ramzi et al. [60] evaluated 223 accessions of B. oleracea collected from the Netherlands and Canada against different pathotypes [P1, P2, P3, P4, P5, and P1(+)], and only three accessions (CGN11150, CGB14078 and CGN15227) exhibited high resistance to all the pathotypes. Fredua-Agyema et al. [61] screened 65 B. oleracea accessions against five pathotypes (2F, 3H, 5I, 6M, and 8N) and 17 other field isolates, and four accessions were resistant, five were moderately resistant, and the remaining 56 were susceptible. In addition, broad-spectrum resistance was exhibited by seven accessions of kale and two accessions of brussels sprout. Farid et al. [62] evaluated 135 B. oleracea accessions representing all the eight morphotypes against two pathotypes [F3-14 (3A) and F-359-13 (5X L-G2)], and resistance was observed more frequently in kale. So, among different morphotypes of B. oleracea, kale, followed by cabbage, could serve as a potential donor for resistance breeding in B. oleracea.

The inheritance of clubroot resistances has been studied using either diallel cross or segregating populations in B. oleracea, and continuous resistance including both minor and major genes has been reported. The studies have indicated that recessive genes primarily govern clubroot resistance in B. oleracea [55,57,63,64,65,66,67,68,69]. Nevertheless, the dominant nature of resistance has also been reported [70]. The genetic studies also identified additive gene action [71], duplicate genes [64], recessive gene with additive gene action [66,68,69], complementary gene action [72,73] responsible for clubroot resistance in B. oleracea. However, most of the classical genetic studies indicated the prevalence of multiple loci controlling clubroot resistance in the C-genome of B. oleracea [67,70]. This was again complemented by genetic-mapping studies, suggesting the predominance of the polygenic nature of clubroot resistance in B. oleracea, discussed later in this section. In contrast, clubroot resistance is mainly controlled by race-specific, major dominant genes in B. rapa and B. napus (reviewed by Diederichsen et al. [74]).

The rapid accessibility of genomic data, genetic maps, and associated bioinformatics tools has allowed the dissection of the genetic architecture of clubroot resistance in B. oleracea. The ‘C’ genome harbors several R genes, and more than 40 QTLs with both major and minor effects have been reported by various authors (Table 1). A mapping study revealed the presence of one broad-spectrum major locus (Pb-Bo1) and several isolate-specific and minor QTLs, suggesting the role of both isolate-specific and broad-spectrum QTLs in providing continuous resistance in B. oleracea [75]. The quantitative control of resistance in B. oleracea was identified by various authors explaining limited phenotypic variance [76,77]. Several studies identified many broad-spectrum QTLs conferring resistance against different isolates of P. brassicae [76,78], broadening the spectrum of immunity in B. oleracea. The accumulation of five clubroot resistance genes (Anju1, Anju2, Anju3, Anju4, GC1) conferred broad resistance against six isolates in B. oleracea, and the genotype consisting of minor loci (Anju2, Anju3, Anju4, GC1) responded in a pathotype-specific manner [76]. This indicated the necessity of both isolate-specific and broad-spectrum resistance to carry out resistance breeding in B. oleracea.

For traits with low heritability and polygenic inheritance, especially disease resistance [79], detection of dominant QTLs could be of considerable value for breeding programs. Two dominant QTLs (CR2a and CR2b) conferring resistance to race 2 of P. brassicae in cabbage were mapped on LG 6 and LG 1, respectively [80]. Similarly, three QTLs responsible for resistance to race 7 were identified in an F2 population developed by crossing resistant broccoli with susceptible cauliflower [81]. A multiple QTL mapping approach was used to map two main QTLs (pb-3 and pb-4) in cabbage cv. Bindsachsener on LG3 and LG1 for resistance to P. brassicae [82]. Two marker loci, 4NE11a and 2NA8c were closely linked to the resistance loci pb-3 and pb-4, respectively, which would assist in marker-assisted selection for clubroot resistance.

However, the above DNA markers used in mapping were low-throughput, expensive, and time-consuming. After the advent of NGS technologies, the discovery of high-throughput SNP markers in Brassica spp. gained momentum, leading to the generation of high-density genetic maps and candidate gene detection in Brassica spp. [83,84]. A 60 K bead chip array [77,85] and NGS-enabled genotyping-by-sequencing (GBS) technique [86] have been deployed to discover and screen SNPs for high-density linkage map construction and QTL mapping for P. brassicae resistance in B. oleracea. In recent years, GBS has emerged as a robust and cost-effective method for improving the resolution of target loci [87], allowing the accurate prediction of candidate genes [88]. A high-density linkage map was constructed using SNP markers developed through GBS technique and two major QTLs (CRQTL-GN_1 and CRQTL-GN_2) for race 9 and a single major QTL (CRQTL-YC) for race 2 of P. brassicae were identified in cabbage [86]. Utilizing the 60 K Brassica SNP array, a high-density linkage map was constructed and a total of 23 QTLs were identified for disease incidence and clubroot-associated traits in B. oleracea, indicating the quantitative nature of clubroot resistance [77]. To provide better mapping resolution, GWAS was implemented and 10 QTLs and six candidate genes were reported in a ±250 Kbp QTL region of B. oleracea showing significant association with resistance against the two pathotypes (3A and 5X L-G2) [62].

Table 1. List of QTLs associated with clubroot resistance in Brassica oleracea L.

Species	Mapping Population	Pathotype/Race/Isolate	Gene Locus/QTL	Chr/LG	Reference
B. oleracea	F2	Race 2	CR2a	LG6	[80]
B. oleracea	F2	Race 2	CR2b	LG1	[80]
B. oleracea var. italica	F2	Race 7	14a	1C	[81]
			48	4C
			177b	9C
B. oleracea var. capitata	DH	Isolate CD 16/3/30	pb-3	LG3	[82]
B. oleracea var. capitata	DH	Isolate CD 16/3/30	pb-4	LG1	[82]
B. oleracea var. acephala	F2	Races 1 and 3	1 QTL	LG3	[89]
B. oleracea (Kale)	F2:3	Pathotypes P1, P2, P4, and P7	Pb-Bo1	LG1	[75]
			Pb-Bo2	LG2
			Pb-Bo3	LG3
			Pb-Bo4	LG4
			Pb-Bo5a	LG5
			Pb-Bo5b	LG5
			Pb-Bo8	LG8
			Pb-Bo9a	LG9
			Pb-Bo9b	LG9
B. oleracea	F2	Isolate Kamogawa (races 1 and 3), Anno and Yuki	QTL1	LG1	[78]
			QTL3	LG3
			QTL9	LG9
B. oleracea var. capitata	F2:3	Race 4	PbBo(Anju)1	O2	[90]
			PbBo(Anju)2	O2
			PbBo(Anju)3	O3
			PbBo(Anju)4	O7
			PbBo(GC)1	O5
B. oleracea var. capitata	F2:3	Field isolates—No. 5, No. 14, Ano-01, T-1, I-1, and M-1	Anju1	O2	[76]
			Anju2,	O2
			Anju3,	O3
			Anju4	O7
			GC1	O5
B. oleracea	F2	Race 4	23 QTLs	C1, C2, C3, C4, C6, C7, C8	[77]
B. oleracea	B. oleracea accessions	Pathotypes 3A and 5X LG-2	PbC4.1	C4	[62]
			PbC6	C6
			PbC7.1	C7
			PbC7.2	C7
			PbC8	C8
			PbC9.1	C9
			PbC3	C3
			PbC4.2	C4
			PbC7.3	C7
			PbC9.2	C9
B. oleracea var. capitata	F2:3	Races 2 and 9	CRQTL-GN_1	C2	[86]
			CRQTL-GN_2	C3
			CRQTL-YC	C3

2.3. Fine Mapping and Identification of NBS-LRR Encoding R Genes for Clubroot Resistance

Fine mapping of the resistance genes is necessary to identify candidate genes and successfully facilitate marker-assisted selection (MAS) for disease resistance. Fine mapping of clubroot resistance genes is a success story in B. rapa owing to the dominant nature of resistance genes, and several resistance genes have been fine mapped (Table 2). Fine genetic and physical mapping have led to the identification of clubroot resistance genes encoding proteins containing the NBS-LRR domain (Table 2). Most of the R genes encode proteins containing NBS-LRR (nucleotide-binding site and leucine-rich repeat) domains [91]. Based on their functional domain, the NBS-LRR protein family is subdivided into N-terminal coiled-coil-domain-containing NBS-LRR (CC-NBS-LRR) and toll/interleukin-1 receptor domain-containing NBS-LRR (TIR-NBS-LRR) subfamilies [92]. Disease resistance genes encoding NBS-LRR-related proteins are effective against hemibiotrophic and obligate pathogens [93]. The specific R genes encoding NBS–LRR proteins can recognize the effector factor secreted by pathogens activating effector-triggered immunity (ETI). Moreover, due to natural selection, pathogens produce new effectors, and host plants evolve to produce new R genes [94].

Saito et al. [95] fine mapped the locus Crr3 located on chromosome A3 of B. rapa, and synteny analysis of this region showed homology to the sequences in the top arm of ch. 3 of A. thaliana. Similarly, Kato et al. [96] fine mapped a clubroot resistance gene CRb in 24.2–24.342 Mb interval on ch. A3 of B. rapa against pathotype 3. However, the original CRb locus mapped by Piao et al. [97] was fine mapped by Zhang et al. [98] to understand the relationship of these clubroot resistance genes. The CRb locus fine mapped to a region of approximately 0.14 cM on ch. A3 of Chinese cabbage was tightly linked to two other clubroot resistance genes, CRa^kato and CRb (already fine mapped by Kato et al. [96]. In the predicted region of an 83.5-kb interval, 15 putative genes were annotated with potential involvement in clubroot resistance, and the target interval contained one TIR– NBS–LRR (TNL) and one NBS–LRR gene. A new clubroot resistance locus Rcr1 was fine mapped between 24.26–24.50 Mb on LG A3 in B. rapa ssp. Chinensis [99]. Within this interval, a cluster of four TNL and one defence-related gene was located. Functional annotation of the differential expressed genes (DEGs) showed that genes related to clubroot symptom development were significantly down-regulated in plants carrying Rcr1. Gao et al. [100] fine mapped a single dominant clubroot resistance locus to a 187-kbp physical region of ch. A3 in five hybrid Chinese cabbage cultivars and the molecular markers developed could be deployed for marker-assisted selection of clubroot resistance. Recently, fine mapping of the resistance locus PbBa8.1 within a 2.9 Mb region on ch. A8 was carried out using BSA-Seq [101]. Interestingly, another resistance gene, Crr1a was also identified in the same region, suggesting that PbBa8.1 and Crr1a might be allelic but differ in function. Very recently, fine mapping of the clubroot resistance locus CRA8.1 on chromosome A8 in B. rapa revealed the presence of two different loci CRA8.1b (395 kb fragment) and CRA8.1a (765-kb) [102]. While CRA8.1b was responsible for the resistance against PbZj and PbXm isolates, together with CRA8.1a, it can confer resistance to PbXm+ isolate of P. brassicae. Two genes encoding TNL proteins and one candidate gene encoding RLP protein were the most probable candidate genes responsible for clubroot resistance in DingWen (DW). Again, the same locus PbBa8.1 was fine mapped in the ECD04 (most valuable resources for CR breeding) genome and narrowed down into a 1428 Kb region and nine candidate genes were identified in this region [103]. Functional analysis of one candidate gene, CRA8.2.4, with NBS-LRR domain revealed that the plants with higher expression of CRA8.2.4 were not infected with clubroot. In contrast, the plants with lower or no expression showed a higher disease index.

BSR-seq, combining BSA and RNA-seq techniques, has been used in Brassica spp. to determine QTLs, fine mapping and reporting of candidate genes for clubroot resistance encoding TNL resistance proteins [104,105,106,107,108,109]. Using BSR-seq, a major gene, Rcr5 was fine mapped into the 23–31 Mb region of the A3 chromosome, and the identification of several recombinants indicated that Rcr5 was different from the previously mapped clubroot resistance genes (CRa/CRb^kato, CRb) on ch. A3 [108]. Another clubroot resistance gene, Rcr2 was identified and fine mapped on ch. A3 using BSR-Seq in Chinese cabbage cv. “Jazz” in an interval of 0.4 cM and five SNP markers co-segregating with Rcr2 were identified [105]. In the target region, four genes encoding TNL proteins were detected among which two genes with high numbers of polymorphic variants could be the most likely candidates for Rcr2. In B. oleracea, a major clubroot resistant gene, Rcr7 was mapped to a physical interval of 41–44 Mb on chromosome 7, exhibiting resistance against two pathotypes (Pathotype 3 and 5X) through the BSR-seq approach [106]. Seven clubroot resistance genes placed in the target region encoding TNL resistance proteins were identified.

In the post-genomics era, advent of NGS technologies has enabled the discovery of high-throughput SNP markers leading to high-density linkage map construction, NGS-enabled BSA-seq techniques etc. This has helped in the rapid identification of candidate clubroot genes containing the TIR-NBS-LRR domain in B. oleracea [110], B. rapa [111,112,113,114,115] and B. napus [116,117]. To rapidly identify the candidate genes for clubroot resistance, Ce et al. [110] employed a QTL-seq approach to identify four QTLs (qCRc7-1, qCRc7-2, qCRc7-3, and qCRc7-4) on ch. C7 and one on C4 (qCRc4-1) in B. oleracea. Out of 312 genes located in the three QTL regions (qCRc7-2, qCRc7-3, and qCRc7-4) on C7, six R genes encoded TNL proteins. Further, two potential candidate genes [Bol037115 (FLZ domain protein) and Bol042270 (plant intracellular Ras-group-related LRR (PIRL) protein] were identified and a functional marker “SWU-OA” was developed, exhibiting 95% accuracy in identifying clubroot-resistant lines. Though several clubroot resistance genes containing the NBS–LRR domain have been reported, the role of NBS-LRR proteins in activating ETI for disease resistance is not clearly understood in Brassica–P. brassicae pathosystem.

While the LRR domain of TIR-NBS-LRR proteins is the primary determinant of recognition specificity of the effector (Reviewed by Collier and Moffett [118]), the TIR domain is involved in cell-death induction [119]. The deletion of the TIR domain resulted in clubroot susceptibility of Crr1a^A9709 allele in B. rapa [120] and site-directed mutagenesis in the TIR domain identified loss-of-function of TNL gene [119]. To date, only three clubroot resistance genes, CRa (ch. A3) [121], Crr1a (ch. A8) [120], and CRb (ch. A3) [122] have been cloned in B. rapa. These cloned genes have been characterized as classical resistance genes, among which CRa and Crr1a encode TNL and CRb contains the NB-LRR domain. Interestingly, the DNA sequence of the functional ORF of CRb gene was found to be identical to the previously cloned CRa gene, suggesting that CRb and CRa are one and the same resistance gene [122]. However, the resistance mechanisms associated with these three genes have not been clarified yet. Recently, gain-of-function analysis using the chimeric genes revealed that 172 amino acids in the C-terminal region are essential for clubroot resistance imparted by the Crr1a gene [123]. Furthermore, very recently, one candidate gene, named CRA3.7.1, identical to CRa from B. rapa T136-8 [121] and CRb_α [122] was functionally characterized by Yang et al. [103]. B. napus lines with stable transformation with CRA3.7.1 were resistant against different Chinese isolates (pathotype 4) of clubroot. However, unlike B. rapa, the complex inheritance pattern and quantitative nature of resistance in B. oleracea [86,124] have made it difficult to fine map/clone the clubroot resistance genes restricting the deployment of R genes in resistance breeding.

Table 2. List of clubroot resistance genes with NBS-LRR domain in Brassica spp.

Species	Mapping Population	Pathotype/Race/Isolate	R Gene	Chr/LG	Fine Mapped Region/Interval	Reference
B. oleracea	BC1	Pathotype 3 and 5X	Rcr7	C7	41–44 Mb	[106]
B. oleracea	F2	Race 4	qCRc7-1	C7	38.33–44.14 Mb	[110]
			qCRc4-1	C4	16.92–18.79 Mb
			qCRc7-2	C7	38.96–39.54 Mb
			qCRc7-3	C7	41.38–42.52 Mb
			qCRc7-4	C7	43.56–44.15 Mb
B. rapa	F1	Field isolate (PbZj, PbXm, PbXm+)	CRA8.1a	A8	765 kb segment	[102]
B. rapa	F1	Field isolate (PbZj, PbXm, PbXm+)	CRA8.1b	A8	395 kb segment	[102]
B. rapa	BC1	Pathotype 3	Rcr2	A3	0.4 cM (~250 kb) segment	[105]
B. rapa	F2	Pathotype 3	Rcr5	A3	23–31Mb segment	[108]
B. rapa	BC3F2	Pathotype 4	PbBa8.1	A8	2.9 Mb segment	[101]
B. rapa	F2	Race 2	CRa	A3		[121]
B. rapa	F2	Isolate Ano-01 (Pathotype 4)	Crr1a	A8	8 kb segment	[120]
B. rapa	F2	Pathotype 3	CRb^kato	A3	24.2–24.342 Mb	[96]
B. rapa	F2	Pathotype 4	CRb	A3	0.14 cM segment	[98]
B. rapa ssp. chinensis	BC1	Pathotype 3	Rcr1	A3	24.26–24.50 Mb	[99]
B. rapa	F2:3	Isolate Ano-01	Crr3	A3	0.35 cM segment	[95]
B. rapa	F2	Pathotypes 2, 5 and 6	Rcr1	A3		[104]
B. rapa	BC1	Pathotypes 3H and 5X	Rcr3	A8	10.00–10.23 Mb	[109]
B. rapa	BC1	Pathotypes 3H and 5X	Rcr9^wa	A8	10.85–11.17 Mb	[109]
B. nigra	F2	Pathotype 3	Rcr6	B3	6.1–6.6 Mb	[107]
B. rapa	F2, BC	Pathotype 3	Rcr6	A8	14.8–15.4 Mb	[107]
B. rapa	BC1	Pathotypes 2, 3, 5, 6, 8	Rcr4	A3	2.96 Mb segment	[111]
		Pathotype 5x	Rcr8	A2	3.59 Mb segment
		Pathotype 5x	Rcr9	A8	6.48 Mb segment
B. rapa	DH	Pathotype “Banglim”	PbBrA08^Banglim	A8	~1 Mb segment	[114]
B. rapa	F2	Pathotype 4	CRs	A8	0.8 Mb segment	[113]
B. rapa ssp. Pekinensis	F2	Race 4	CRd	A3	60 Kb segment	[112]
B. napus	DH	Field isolate (Lower Silesian Province, Poland)	Crr3^Tsc	A3	0.4 cM segment	[116]
B. napus	DH	Pathotypes 3A, 3D, 3H	Rcr10^ECD01	A3	3.7 Mb segment	[117]
B. napus	DH	Pathotypes 3A, 3D, 3H, and 5X	Rcr9^ECD01	A8	2.2 Mb segment	[117]

2.4. Pyramiding of Resistance Genes

Resistance conferred by single genes is not durable and prone to break down. Pyramiding clubroot resistance genes with different resistance mechanisms could be a good strategy for accumulating multiple resistance genes into a single cultivar. Pyramiding multiple R genes or combining genes with minor effects have improved the durability of resistance [125,126]. The accumulated genes may impart resistance to either multiple pathotypes [127,128] or higher resistance to a single pathotype [76] of P. brassicae. Previously, the breakdown of clubroot resistance has been reported in single-gene homozygous lines of Chinese cabbage [127] and B. napus [129]. A resistant canola cultivar reportedly showed increased clubroot severity to pathotype 3 of P. brassicae under controlled conditions [130]. Matsumoto et al. [127] pyramided three major clubroot genes (CRa, CRk, and CRc) and developed a homozygous Chinese cabbage line conferring higher resistance to all the six isolates of P. brassicae. Similarly, Shah et al. [128] pyramided clubroot resistance genes, CRb (resistant to race 2, 4, and 8) and PbBa8.1 (resistant to pathotype 4) in B. napus, and developed homozygous and heterozygous lines through MAS. Comparatively, homozygous lines exhibited better resistance than the heterozygous lines, suggesting that the accumulation of multiple resistance genes into a single line in a homozygous state could lead to durable resistance. However, in B. oleracea few attempts have been made to pyramid the clubroot resistance genes for broad spectrum and durable resistance [76,78]. Tomita et al. [76] illustrated the single and cumulative effects of clubroot resistance gene(s) by evaluating the resistant lines carrying multiple combinations of clubroot resistance genes against different isolates of P. brassicae. Incidentally, a single involvement of the major resistance gene located in PbBo (Anju)1 or accumulation of minor QTLs did not provide sufficient resistance. However, the genotype with a combination of a major resistance gene with all the four minor QTLs imparted the highest resistance against the six isolates of P. brassicae. Hence, for successful resistance breeding, the accumulation of both major and minor clubroot resistance genes is necessary for durable resistance against multiple pathotypes of P. brassicae in B. oleracea.

2.5. Comparative Mapping Studies

During evolution, diploid Brassica species have evolved from a common hexaploid ancestor [131,132,133,134] through whole-genome triplication of the ancestral genome, leading to reshuffling and changes in the genome number [134,135,136]. Comparative linkage mapping has elucidated the degree of genomic conservation through micro and macro synteny studies, and conserved genomic regions have been identified in Brassica species [137,138,139,140]. Gene conservation and microsynteny analysis of B. napus with B. rapa and B. oleracea reported high conserved collinearity with their orthologues across the genome, suggesting little or no changes in the microstructure of specific segments during hybridization events [141]. B. oleracea genome (CC) shares a high ancestral synteny with the genome (AA) of B. rapa with a high level of conserved gene content and order [41,142]. Both the genomes share a set of 24 conserved chromosomal blocks [143].

Comparative mapping may exploit the conserved synteny between B. rapa and B. oleracea genome to reveal the relative positions of the clubroot-resistant QTLs in B. oleracea [77,86,90]. Synteny analysis of B. oleracea with previously reported QTLs of B. rapa [95,96,144,145,146,147] revealed strong collinearity of CRQTL-GN_1 located on ch. C2 with ch. A2 of B. rapa harboring CRc gene where its linked marker ‘m6R’ was mapped [86]. Comparative analysis by Nagaoka et al. [90] also showed that a minor (pb-Bo (Anju)2) and major QTL (pb-Bo (Anju)1) located on C2 of B. oleracea are collinear with the genomic region of A2 of B. rapa carrying CRc gene. These results indicated that pb-Bo (Anju)2 and pb-Bo (Anju)4 loci were homologous to CRc and CRb genes of B. rapa, respectively. A QTL interval overlapped by NFR.II-3 and PCR.II-2 on C3 (6.28–6.32 Mb) was partially syntenic to A2 chromosome (0.59–6.22 Mb) of B. rapa where the marker, m6R linked to CRc [147] and Pb (Anju)2 [90] was located [77]. Another QTL (NFR.II-7) on C7 was syntenic to a region overlapped with fine-mapped clubroot resistance loci, Crr1 on A8 of B. rapa. Two expressed and unexpressed TNL genes located in QTL Rcr7 on ch. C7 were homoeologous to four B. rapa genes residing in a 25 Mb region of ch. A3, which were different from the previously mapped resistance genes (Rcr1/Rcr2/Rcr4/CRa/CRb) of B. rapa [106]. Hence, Rcr7 mapped in B. oleracea, could have originated from a gene in ch. A3 of B. rapa, which is different from Rcr1/Rcr2/Rcr4.

Brassica spp. and Arabidopsis thaliana have originated from a common ancestor, so certain chromosomal segments are expected to be conserved. Microsynteny analysis has suggested that each genomic segment of A. thaliana corresponds to three syntenic copies of B. rapa [148]. Clubroot resistance genes have originated from major resistance clusters (MRCs) of a common ancestral genome and distributed to different regions during the evolutionary process [146,149]. The regions harboring clubroot resistance genes in B. oleracea correspond to MRCs of A. thaliana genome. The regions of clubroot resistance QTLs, pb-Bo (Anju)1 and pb-Bo (Anju)3 corresponded to the top of ch. 5, pb-Bo (Anju)2 and pb-Bo (Anju)4 corresponded to the middle of ch. 4 and pb-Bo (Anju)4 corresponded to the distal end of ch. 1 of A. thaliana [90]. In B. rapa, clubroot resistance genes, Crr1, Crr2, and CRb were in synteny with the central region of ch. 4 of A. thaliana [124,146]. The regions of Crr3 of B. rapa corresponded to the ch. 3 of A. thaliana [95]. The comparative analysis of clubroot resistance genes among various species of Brassicaceae indicated that clubroot resistance genes originated from a common ancestor and are highly conserved across all the lineages of Brassicaceae family.

Over the past 20 years, good progress has been made in mapping many promising clubroot-resistant genes/QTLs in the A-genome in B. rapa (Supplementary Table S1). Two resistance loci, CRa and CRb^kato are allelic since they are localized in the same position [122], while Rcr1, Rcr2, and Rcr4 were found co-localized with CRa/CRb^kato [104,105,111] on A3 chromosome of B. rapa. Additionally, three clubroot resistance hotspots corresponding to Crr3/CRk/CRd and CRa/CRb/CRb^kato regions on A3 and Crr1 region on the ch. A8 in B. rapa were identified [150]. In B. napus, more than 30 clubroot resistance loci have been mapped in the AC genome against several P. brassicae strains (Supplementary Table S1). Most of the loci (19 QTLs) mapped by Werner et al. [151] are race-specific and spread across eight chromosomes. In B. napus, the major resistance gene of the A genome [74,152,153] have been used to develop clubroot-resistant Brassica oilseeds. Hence, for sustainable production of B. napus, it is essential to broaden the genetic base of clubroot resistance by identifying novel resistance in the C genome of B. oleracea.

3. Epigenomics

Due to the rapid evolution of plant pathogens, mere exploitation of the resistance (R) genes through classical breeding approaches may be less effective [154]. Moreover, there is a gradual erosion of the diversity of R genes owing to intense artificial selection in conventional breeding practices. In recent years, the breeders have been exploiting the epigenetic variation through epi-breeding, which has provided a new avenue for crop improvement [155,156,157]. Epigenetic variations through natural diversity or artificially induced variation (by chemical treatments, induced gene-specific DNA methylation, and epigenome editing) have shown great potential in regulating crop-disease resistance. The epigenetic processes are highly interconnected and orchestrate defence-related transcriptional programming for generational and transgenerational defence priming and respond to pathogen infections [158]. The merger of epigenetics with genomics, known as epigenomics, has developed as a new omics technique to understand the epigenomic molecular mechanisms underlying plant-disease resistance. There is increasing evidence of epigenetic processes governing transcriptional regulation of plant defence responses against a wide range of phytopathogens [159,160,161]. So, as an alternative approach, epigenetics, including DNA (de)methylation, post-translational modification (PTM) of histones, chromatin assembly and remodeling, and RNA methylation, could broaden the phenotypic diversity, essential for crop improvement for disease resistance. DNA methylation usually refers to the addition of a methyl at the C5 position of cytosine base to form 5-methylcytosine (5 mC) and is considered an important epigenetic modification in regulating gene expression and transposon silencing [162,163]. With the rapid development of high-throughput sequencing, several advanced DNA methylation profiling techniques such as whole-genome bisulfite sequencing (WGBS), shotgun bisulfite sequencing, methylation-sensitive amplified fragment length polymorphism (MSAP), methylated DNA immunoprecipitation sequencing (MeDIPseq), methyl-CpG binding domain protein capture sequencing (MBDCap-seq), etc., have been used in DNA methylome analysis in model crop plants [164,165,166,167]. Using the MSAP technique in 30 B. oleracea populations and lines, Salmon et al. [168] reported high DNA methylation levels and polymorphism related to high structural genome plasticity. As a part of plant defence response, pathogen-infection-induced, DNA hypomethylation in many plant species, including A. thaliana, resulted in elevated pathogen resistance [169]. DNA methylation studies have been carried out in Brassica spp. to reveal the plant’s immunity against pathogens. A recent study by Tirnaz et al. [170] has shown that DNA methylation regulates the promoters of defence genes, causing variation in resistance response against black leg infection at the seedling stage of B. napus. The resistant cultivar exhibited a higher number of differentially methylated defence-gene promoters than the susceptible cultivar. Very recently, whole-genome DNA methylation analysis in B. rapa revealed the potential regulatory role of DNA methylation modification in the defence mechanism against white rust [171]. The heritable differences in DNA methylation, called transgenerational epigenetic variants, also contribute to quantitative disease resistance. This can be achieved by developing epigenetic recombinant inbred line (epiRIL) populations with the similar genotypic constitution but different DNA methylation levels at specific chromatin regions. An epiRIL population was constructed in A. thaliana to decipher the epigenetic architecture of clubroot resistance. A total of 16 epiQTLs were detected, and six epiQTLs were co-localized with previously identified clubroot resistance QTLs, indicating that quantitative resistance to clubroot is mediated by a combination of both allelic and epiallelic variations [172]. Generally, methylation levels vary according to the genomic location and transposon-enriched regions possess a comparatively higher methylated level than the genetic regions [164]. Hence, transposon elements associated with DNA methylation could contribute to pathogen resistance and susceptibility [163]. Another important epigenetic mechanism, post-translational modification (PTM) of histones, such as acetylation, methylation, and ubiquitylation, usually occur at the N-terminal tails of histone, thereby regulating the chromatin structure and function [159,161,173]. The involvement of histone (de)acetylation, methylation and ubiquitylation in regulating plant-pathogen interactions in different crops have been reviewed extensively by Zhi and Chang [158]. Chromatin assembly and remodeling also regulate plant disease resistance. Chromatin structure modulates DNA accessibility to transcription machinery and plays a very important role in gene transcription regulation [174]. Several studies have revealed the involvement of chromatin structure in regulating plant defence responses [173,175,176,177]. Hence, the breeders need to go beyond the conventional breeding strategy of depending on genetic variation and instead, they look towards a wider perspective on how epigenetic modification might regulate plant immunity against pathogens in Brassica. Though the study of plant epigenetics has a long and rich history, only recently, an epigenetic map was constructed for the first time in B. napus [178]. Based on MSAP, retrotransposon- and centromeric-specific markers, QTLs associated with important agronomic traits in the centromeric regions of five linkage groups were identified. Thus, in Brassica spp., limited epigenetic studies have been published and warrant further investigation to decipher the role of epigenomics in understanding the mechanism of Brassica-pathogen interaction. This will fill the critical knowledge gap and can be a solution to the existing limitations to minimize yield loss due to plant disease.

4. Transcriptomics

4.1. Hormone Signal Transduction during Brassica-P. brassicae Interaction

P. brassicae is a biotroph and is required to be co-cultured with its host, making it difficult to decipher the molecular mechanisms of Brassica-P. brassicae interactions. Nevertheless, in recent years, several RNA-seq studies were framed in B. oleracea to reveal the mechanisms of clubroot resistance by uncovering the genes involved in host defence responses (Table 3). P. brassicae infection can modify plant hormone homeostasis, leading to clubroot formation [179,180,181,182]. Comparative transcriptome analysis between clubroot-susceptible broccoli inbred line and resistant wild cabbage revealed the down-regulation of DEGs associated with plant hormone signal transduction at the secondary infection stage, suggesting that the defence responses are induced in the primary stage, and are repressed at the secondary infection stage [183]. Similarly, through transcriptome analysis, Wang et al. [184] identified resistance-related genes involved in plant hormone signaling playing important roles at early stage of P. brassicae infection, also reported by Chen et al. [185].

The hormonal homeostasis of auxin and cytokinin play pivotal roles during host–P. brassicae interactions, triggering hypertrophy and hyperplasia, resulting in clubroot formation [22,186,187,188,189]. The hypertrophies of clubroot infected plants go hand in hand with the changes in homeostasis of auxin and cytokinin, which are host and time-dependent [22,188]. Microarray analysis and laser microdissection [190] have confirmed the role of auxin and cytokinin metabolism and signaling in clubroot formation in Arabidopsis. The ability of the plants to maintain auxin and cytokinin homeostasis may help control clubroot formation in the infected root tissue [191]. During clubroot development, auxins accumulate and increase in the infected tissue in a sink-like manner [22]. Xu et al. [192] suggested that activation of IAA signaling stimulates the root hair infection at the early stage of P. brassicae infection in B. napus. The auxin biosynthesis gene “nitrilase” mutants delayed gall formation and reduced gall size in A. thaliana [193,194]. The up-regulation of genes involved in auxin homeostasis such as nitrilases (NIT1 and NIT2), auxin-induced GH3 homologs, and putative auxin transport proteins were exhibited in A. thaliana during clubroot development. In contrast, genes involved in cytokinin homeostasis were down-regulated at an early stage of infection [179]. However, Zhao et al. [195] reported the up-regulation of auxin and cytokinin biosynthesis-related genes at a very early phase of infection (24 hai), demonstrating early regulation of both growth hormones during clubroot development. On the contrary, down-regulation of host auxin biosynthesis and transport-related genes at the later stage of infection was consistent with reduced gall formation in resistant wild cabbage line [183]. GH3 and SAUR are important in decreasing IAA content, thereby relieving the expansion of root cells. Auxin-induced GH3 family conjugates IAA to several amino acids and reduces IAA concentrations [196]. SAUR genes negatively regulate auxin synthesis and transport [197] and the expansion of root cells. Ning et al. [198] reported the up-regulation of six GH3 (encodes indole-3-acetic acid amido synthetase) and one SAUR gene in clubroot-resistant cabbage cultivar (XG). Similar results of up-regulation of most of the auxin-related genes (ARFs, IAAs, GH3, SAUR) in symptomless roots (SL) of kohlrabi were also reported by Ciaghi et al. [189].

Cytokinins play a vital role in gall development by regulating cell division and increasing the availability of nutrients by interfering in the sugar metabolism and invertase production [22,179,180]. The root-protein profile of a susceptible canola genotype revealed the crucial role of cytokinin in the early phases of clubroot infection [199]. Though cytokinin increases in the early response to P. brassicae infection [181,200], it was reportedly down-regulated at later stages of gall development [180,181]. However, Laila et al. [201] reported the induction of several cytokinin biosynthetic and signaling genes at early and late stages of infection in both root and leaf tissues of Chinese cabbage. Most of the cytokinin genes, including cytokinin dehydrogenase/oxidase family genes (CKX5), CK receptors, CK-regulated UDPglucosyl transferase, and cytokinin synthesis genes except CKX6, were up-regulated in symptomless roots of kohlrabi [189]. This could be possible as, in A. thaliana, overexpression of CKX has reduced gall formation [179], indicating that more active CK metabolism in the SL root tissue might interfere with clubroot. Similar results were also obtained by Zhu et al. [202], who reported significant up-and down-regulation of three CKX genes (Bol020547, Bol028392, and Bol045724) in resistant and susceptible cabbage, respectively. Cytokinin response factor 4 gene (CRF4) is a component of cytokinin signaling pathway positioned close to clubroot resistance loci Crr1a and CRa was reported to mediate resistance against clubroot in B. napus [203].

A pathogen attack during active growth triggers the plants to execute efficient and systemic defence mechanisms by recognizing particular signals from the damaged cells to initiate defence response [204,205]. Through different kinds of local, constitutive, and inducible mechanisms, plants protect themselves against invading pathogens [206]. Multiple signal-transduction pathways such as SA, ET, and JA pathways stimulate the defence responses and induce several forms of systemic resistance, such as systemic acquired resistance (SAR) and induced systemic resistance (ISR) [207,208]. In plants, phytohormones salicylic acid (SA) and jasmonic acid (JA) are the crucial central defence signaling molecules playing vital roles against biotrophic and hemibiotrophic pathogens. SA is involved in plant defence against biotrophic pathogens, whereas JA and ethylene (ET) act against necrotrophic pathogens [209]. Abscisic acid (ABA) and ethylene have been reported to antagonize or synergize the SA and JA signaling pathways [210,211,212], indicating hormonal cross-talk playing crucial roles to optimize the immune response. A proteomic study at the initial infection stage in B. rapa revealed the involvement of proteins in SA-mediated SAR, JA/ET-mediated ISR against P. brassicae [213]. Exogenous application of SA and JA has significantly reduced root gall formation in B. oleracea and Arabidopsis during P. brassicae attack [214,215]. In B. rapa, higher expression of effectors receptors and PR genes involved in SA signaling in the resistant plant indicated a robust ETI response as part of an early defence mechanism [185]. SA is involved in activating SAR in plants [216]. This was evident as sid2 (salicylic acid induction-deficient 2) Arabidopsis mutants with SAR-deficient npr1-1 and SA-deficient isochorismate synthase 1 (ICS1) showed increased susceptibility to P. brassicae compared to the resistant bik-1 mutant with elevated SA levels [217]. NPR1 (nonexpressor of PR gene 1) genes and ICS1 are the key regulators of SA signaling and biosynthesis in plants [93]. Upon P. brassicae inoculation, two NPR1 homologs were up-regulated in clubroot-resistant B. oleracea, leading to downstream SA signaling activation [183]. One TGA factor (responsible for SA-dependent interaction), TGA4 was up-regulated, and TGA1 was weakly down-regulated in the resistant genotype, suggesting that TGA4-NPR1 interaction induces SA-dependent pathway in the resistant genotype. Similar results were obtained by Ning et al. [198], who reported the up-regulation of NPR1 transcript and TGA4 (interact with NPR1 to induce SAR) in the resistant line (XG) of B. oleracea. However, NPR1 and ICS1 were not up-regulated significantly in cabbage at the early stage of infection, suggesting that SA signaling pathway-related genes might be involved in resistance at the later stage of infection [184]. Up-regulation of genes related to SA signal transduction has been reported at the secondary infection stage in B. oleracea [198]. Nevertheless, SA alone is not sufficient to instigate the defence response against P. brassicae [218]. With an increase in SA levels in clubroot tissue, a SABATH-type methyltransferase (PbBSMT) secreted by P. brassicae [211,219] methylates SA (MeSA) leading to its removal from local infected tissue, thereby disrupting the SA-induced host defence pathway, also reported by Ludwig-Müller et al. [220] and Ciaghi et al. [189].

In general, a higher accumulation of JA is shown in clubroot susceptible hosts and reduced in resistant genotypes [182,221]. Accumulation of JA happens in the developing root galls [222], and several JA-responsive genes were induced in the infected root tissues of clubroot susceptible A. thaliana [179,222]. Jasmonate resistant 1 (jar1) mutant lines of Arabidopsis with impaired JA-Ile accumulation showed higher susceptibility to P. brassicae [222]. Enhanced expression of the BnMYB28.1 gene (regulate clubroot development by modulating aliphatic GSL metabolism) was observed by the exogenous treatment of JA during P. brassicae infection in B. napus [223]. JA also induces the enzymes involved in indole GSLs and auxin biosynthesis, which generally increases during clubroot infection [224]. Enzymes involved in indole GSLs biosynthesis (TrpOxE) and catabolism (myrosinase, nitrilase) were enhanced after treatment with JA and methyl jasmonate, suggesting that increased JA level during clubroot development may up-regulate these three enzymes, thereby enhancing indole GSLs and auxin biosynthesis [225]. Ciaghi et al. [189] reported the down-regulation of JA synthesis in symptomless roots of B. oleracea. JAZs (Jasmonate ZIM domain-containing protein) act as the key transcriptional repressors in JA signaling pathway [226]. Several JAZs were up-regulated in the resistant genotype of B. oleracea, though significantly down-regulated in the susceptible genotype [198,227]. This proves that repression of the JA signaling pathway happens in the resistant genotype during P. brassicae infection. However, several exceptions have been reported where JA signaling mediates resistance against P. brassicae in B. rapa [99,228]. In summary, auxin and cytokinin signaling play a significant role in the development of clubroot disease and root gall. Both the hormones stimulate division and elongation of the host cell of the infected- roots during clubroot formation. Similarly, JA signaling primarily enhance clubroot susceptibility with the induction of JA-responsive genes in the clubroot-infected roots. In contrast, SA plays a central role in regulating immune response against P. brassicae infection by reducing root gall formation significantly.

Table 3. Published transcriptomic and differential gene expression studies in Brassica spp. on clubroot resistance.

Species	Pathotype/Race/Isolate	Target Tissue	Time Point (Tissue Collection)	Inference	Reference
B. oleracea var. italica and B. macrocarpa	Pathotype 4	Roots	0, 7, and 14 dai	Genes related to NBS-LRR proteins, SA signal transduction, cell wall and phytoalexins biosynthesis, chitinase, Ca²⁺ signaling and RBOH were up-regulated in the resistant genotype	[183]
B. oleracea var. capitata	-	Roots	7 and 28 dai	Six BoSWEET genes were up-regulated in the susceptible cultivar	[229]
B. oleracea var. capitata	-	Roots	7 and 28 dai	22 BoSTP genes harbouring the conserved sugar transporter domain were identified. BoSTP4b and BoSTP12 were involved in monosaccharide unloading and carbon partitioning associated with P. brassicae colonization	[230]
B. oleracea var. capitata	16/4/0 (ECD)	Roots	3 dai	Clubroot resistance genes were involved in pathogen recognition, cell wall modification, plant hormone signaling, generation of ROS, transcriptional regulation	[184]
B.oleracea var. gongylodes	Field isolate (Ranggen, Austria)	Roots	-	Genes involved in host cell wall synthesis and reinforcement, cytokinin metabolism and signaling, SA- mediated defence response were up-regulated and jasmonic acid synthesis was down-regulated in symptomless roots	[189]
B. oleracea var. capitata	Pathotype 4	Roots	7 and 28 dai	Genes associated with cell-wall modification, PRRs, disease resistance proteins, SA signal transduction, calcium influx, RBOH, MAPK cascades, transcription factors and chitinase were up-regulated in the clubroot-resistant line	[198]
B. oleracea var. capitata	Pathotype 4	Roots	28 dai	Most of the JAZs (Jasmonate ZIM) were activated in the resistant line	[227]
B. oleracea var. capitata	Race 4	Roots and leaves	0, 7, 14, 21, 35, 42, 52 and 60 dai	MES genes are important to control clubroot disease. SA biosynthesis is suppressed in resistant plants	[231]
B. oleracea	Race 4	Roots	7 and 28 dai	36 CKX genes were identified and three genes were down- and up-regulated significantly in the susceptible and resistant materials, respectively	[202]
B. oleracea	Isolate yeoncheon	Leaves and roots	0, 3, 6, 12, 24, 72 hai and 15 and 40 dai	Two BolMyro and 12 BolMBP genes were highly expressed in the susceptible line, whereas only one BolMyro and five BolMBP genes were highly induced in the resistant line	[232]
B. rapa ssp. pekinensis	Pathotype 4	Total root tissue	0, 2, 5, 8, 13, and 22 dai	Genes associated with auxin, PR, disease resistance proteins, oxidative stress, and WRKY and MYB transcription factors were involved regulating clubroot resistance	[233]
B. rapa	Pathotype 4	Roots	10 dai	Brassica-specific genes (BSGs), which are expressed in various tissues can be induced by P. brassicae	[234]
B. rapa	Pathotype 3	Total root tissue	15 dpi	In the resistant plant carrying Rcr1, genes related to jasmonate and ethylene metabolism, signaling and biosynthesis of callose and indole-containing compounds were up-regulated	[99]
B. rapa	Pathotype 4	Roots	0, 12, 72, and 96 hai	Genes associated with effector receptors and PR genes involved in SA signaling pathway were induced in clubroot-resistant NIL conferring CRb-mediated clubroot resistance	[185]
B. rapa ssp. pekinesis	Pathotype 4	Roots	30 dpi	DEGs related to metabolic process, biological regulation, calcium ion influx, glucosinolate biosynthesis, response to stimulus, plant-pathogen interaction, plant hormone signal transduction, cell wall thickening, SA homeostasis, chitin metabolism, pathogenesis-related pathways showed significant upregulation in the resistant line	[188]
B. rapa	Pathotype 4	Roots	0 h and 4 and 8 dpi	Resistant line carrying the CRd gene revealed that plant hormone signal transduction (SA, JA, ET, and BR) played key roles in the late stages of P. brassicae infection	[228]
B. rapa var. pekinensis	Pathotype 4	Roots and leaves	1, 3, 14, 28, and 35 dai	BrGH3.3 and BrNIT1 (auxin signaling), BrPIN1 (auxin transporter), BrDCK1 (auxin receptor) and BrLAX1 (root hair development) were involved in auxin signaling	[235]
B. rapa ssp. chinensis	Pathotype 3	Roots	15 dpi	Increased biosynthesis of lignin and phenolics play a major role in defence responses	[236]
B. rapa var. pekinensis	Pathotype 4	Roots and leaves	1, 3, 14, 28 and 35 dai	cytokinin related genes (BrIPT1, BrRR1, BrRR3 and 4) up-regulated during gall enlargement	[201]
B. rapa ssp. pekinensis	Isolate Ibaraki-1	Roots	10, 20, 25, 30, 35 and 40 dpi	Expression analysis of nitrilase genes (BrNIT2) suggested that 1.1 kb transcripts might be involved in auxin overproduction during clubroot development	[237]
B. rapa ssp. Pekinensis	Isolate Ibaraki-1	Roots	10, 15, 20, 30, 35 and 40 dpi	Expression of AO gene, BrAO1 increased with clubroot development	[238]
B. rapa ssp. pekinensis	Isolate Ibaraki-1	Roots	10, 15, 20, 23, 27, 30, 35, 40 and 60 dpi	P. Brassicae infection transiently stimulates the transcription of BrIPT1, 3, 5, and 7 (cytokinin synthase genes) before club formation	[239]
B. rapa	Race 4	Roots	0, 3, 9 and 20 dai	Plant hormone signal transduction, plant-pathogen interaction, and fifteen hub genes (RIN4 and IAA16) were involved in immune response	[240]
B. napus	Pathotype 4	Total root tissue	20 dai	The pyramided line (618R) strongly triggers multiple resistance pathways	[241]
B. napus subsp. rapifera Metzg	Pathotype 3A	Total root tissue	7, 14, and 21 dai	In the resistant cultivar, genes related to calcium signaling and genes encoding LRR receptor kinases, RBOH, WRKYs, erfs, and basic leucine zippers were up-regulated	[242]
B. napus	Pathotype 4	Roots	12, 24, 60, and 96 hpi	Genes associated with plant hormone signal transduction, fatty acid metabolism, and glucosinolate biosynthesis were involved in regulation of clubroot resistance	[243]
B. napus	Pathotype 3	Roots	10 dai	The gene CRF4, a component of cytokinin signaling pathway play a fundamental role in clubroot resistance.	[203]
B. napus	Field isolates (Fuling, China) and pathotype 4	Total root tissue	0, 3, 6, 9, and 12 dai	Host intercellular G proteins got activated together with the enhanced Ca²⁺ signaling, promoted ROS production and PCD in the host plant.	[191]
B. napus	Field isolate (Kunming, China)	Roots	20 dai	High clubroot resistance was due to the induced expression of broad-spectrum and clubroot specific (Crr1 and Cra) resistance genes	[244]
B. napus	Pathotype 5X	Roots	7, 14 and 21 (dai)	Immune related genes are associated with SA-mediated responses. JA-mediated responses were inhibited in the resistant genotype.	[245]
B. napus	Pathotypes 5I (P5I) and 5X (P5X)	Total root tissue	7, 14, and 21 dai	13 genes encoded high cysteine content proteins and three genes encoded proteins with an RXLR motif	[246]
B. napus	Pathotype 3	Roots and leaves	5, 7, 10, 14 dpi	Up-regulation of phenylpropanoid pathway genes were involved in lignin and flavonoid biosynthesis	[247]
B. napus	Pathotype 4	Roots and leaves	3, 7, and 10 dai	BnAAO4 might be directly responsible for overproduction of IAA during early infection	[192]
B. napus subs. napus	Pathotype 6	Roots, leaves, galls	2, 5, 7, 10, 15, 22, 35, 42, and 49 dai	In the resistant roots, higher basal level of SA was stimulated via ICS1 expression earlier than the susceptible cultivar	[181]
B. napus	Pathotype 4	Roots	3, 7, 14, and 28 dai	Expression of BnMYB28.1 was significantly enhanced following treatment with exogenous JA	[223]
B. napus	17/31/31 (ECD)	Roots	-	21 genes and 82 candidate genes potentially involved in clubroot resistance were identified	[248]
B. juncea var. tumida Tsen	Field isolate (Chongqing, China)	Total root tissue	15dai	Resistance related genes were involved in PRRs, PTI and ETI signaling pathways, calcium influx, salicylic acid pathway, reactive oxygen intermediates, MAPK-cascades, and cell wall modification	[249]
B. juncea var. tumida Tsen	Field isolate (Fuling, China)	Roots	10, 15, 20, 25, 30 and 40 dpi	Six resistance-related genes encoding ethylene responsive TF, abscisic acid receptor, CDPK-5, quinone reductase gene, MYB family TF and a heat shock TF were up-regulated	[250]
B. campestris ssp. chinensis Makino	Race 7	Roots and leaves	40 DAG	Expression levels of genes encoding SOD, APX, CAT, and GR were enhanced	[251]

dai, days after inoculation; dpi, days post inoculation; hpi, hours post inoculation; DAG, days after germination.

4.2. Cell Wall Modification and Lignification

Plant cell walls are very dynamic, act as a physical barrier against pathogen invasion, and can be remodelled by the plants or pathogens [252]. Plant-microbe interactions can cause drastic changes in the chemical composition of the cell wall, including cellulose, hemicellulose, pectin, lignin, callose etc., as a consequence of infection. During P. brassicae infection, a series of physiological changes occur, including the formation of characteristics root gall, leading to cell wall modification and reorganisation, which differs significantly from the symptomless roots. While pectin plays an important role in cell expansion, adhesion, strength, and porosity, lignification protects cell wall polysaccharides from degradation [253]. Down-regulation of genes involved in the biosynthesis of cellulose, hemicellulose, pectin, callose, and lignin decreased root cell wall rigidity and stability of the clubroot infected cells of Brassica plants [254]. On the contrary, enzymes responsible for degrading these elements were up-regulated in clubroots. Enzymes such as polygalacturonases, pectate lyases, pectin methylesterases (PMEs), and pectin acetylesterases degrade pectin, whereas glycosyl hydrolases family 9 degrades cell wall. Xyloglucan endotransglucosylases/hydrolases or expansins and expansin-like genes are involved in cell wall loosening and elongation processes. PMEs, which regulate the permeability and stability of cell walls, were up-regulated in B. oleracea during P. brassicae invasion [184]. Most of the cell division and expansion-related genes were down-regulated in the clubroot-resistant NIL of B. rapa [185]. However, to protect the plant cells from excessive degradation from pectinase, host plants produce enzyme-inhibiting enzymes, such as PMEIs (PME-inhibitor) and PGIPs (PG-inhibiting protein). In the clubroots of Brassica plants, the genes coding these inhibitors were down-regulated [254]. Plant cell-wall-degrading enzymes (CWDEs) play an important role in loosening and the breakdown of cell wall components [255] and establishment of pathogens [256]. In a study, genes involved in cellulose [cellulose synthase and cellulose synthase-like D], hemicellulose [fucosyltransferase and cellulose synthase-like A], and pectin (GAUT) biosynthesis were activated in the resistant genotype at early and secondary infection stage in B. oleracea [198]. GAUT is a key enzyme involved in the biosynthesis of pectic polysaccharide homogalacturonan, which is essential for cell wall formation [257]. Several GAUT genes were up-regulated in the clubroot-resistant wild cabbage in response to P. brassicae infection [183]. At the same time, genes related to β-glucosidase (involved in cellulose hydrolysis) were up-regulated in the susceptible genotype. Lignin synthesized through phenylpropanoid metabolism can be induced as a physical barrier against pathogens [258]. In clubroot-susceptible Arabidopsis, three genes, 4-coumarate-CoA ligase (4CL1), cinnamyl-coenzyme A reductase (CCR1), and cinnamyl alcohol dehydrogenase (CAD5), involved in lignin biosynthesis were reported to be down-regulated [259,260]. In contrast, these lignin biosynthesis genes were activated at the early infection stage in A. thaliana, causing accumulation of lignin except CAD5 [195]. Similarly, in B. oleracea, genes encoding caffeoyl-CoA-O-methyltransferase (CCoAOMT), CCR1, and peroxidase were up-regulated in the resistant genotype, suggesting a vital role played by lignin in host defence against P. brassicae [198]. PAL (L-phenylalanine ammonia-lyase) is the entry point enzyme of the phenylpropanoid pathway induced by the pathogens [261]. In B. rapa, up-regulation of the BrPAL1 gene has indicated that basal defence response induction by clubroot resistance gene Rcr1 was activated via the phenylpropanoid pathway [236]. Conversely, PAL and other genes involved in lignin biosynthesis (C4H, 4CL, COMT, CCR1, F5H) were down-regulated in clubroot infected tissue of B. oleracea [254]. Guaiacyl and syringyl are the vital components of the cell wall of angiosperms [262], and six genes associated with peroxidase are involved in the biosynthesis of guaiacyl, and syringyl lignin were up-regulated in clubroot-resistant wild cabbage [183]. Hence, it is obvious that P. brassicae infection reduces the rigidity of the root cell wall of the host plant by down-regulating the composition of cell wall and up-regulating CWDEs (Figure 2). In contrast, pectin deposition and lignification processes could play critical roles in host defence against P. brassicae infection.

4.3. Role of Sugars and SWEET Genes in Clubroot Disease Response

P. brassicae is dependent on the host cell for its nutrient during gall formation. During disease progression, the development of galls on the root system is a consequence of the translocation of carbohydrates from shoots to roots, constituting a metabolic sink. Sugars are the primary energy sources of hosts and pathogens and are transported via monosaccharide transporters, sucrose transporters, and sugars will eventually be exported transporters (SWEETs) [264,265,266,267] (Figure 2). The biotrophic pathogens extract sugars from the host cells [268,269] for their growth and development. In P. brassicae, 2% of sucrose solution promotes resting spore germination [270], and in the galls of P. brassicae-infected A. thaliana and Brassica plants [271,272], soluble sugars are accumulated [273,274]. In addition, trehalose also gets accumulated in the galls during clubroot development [274]. Hence, galls could act as a carbon sink in clubroot development. Transcriptome studies in A. thaliana revealed the up-regulation of several genes involved in sugar transport and metabolism during gall formation [179,275]. Apart from sucrose, glucose and fructose transport is regulated via sugar transporter proteins (STPs) and hexose transporters (HTs) [276,277]. Recently, 22 BoSTP genes with a conserved sugar transporter domain have been identified in B. oleracea [230]. The expression of two STP genes, BoSTP4b and BoSTP12, were induced in clubroot-susceptible cabbage indicating its involvement in monosaccharide unloading and carbon partitioning during galls development. Irani et al. [278] reported the differential expression of genes involved in sucrose and starch biosynthesis upon P. brassicae attack in A. thaliana. A significant increase in glucose and fructose in the roots of clubroot-susceptible plants was observed compared to the resistant plants of A. thaliana [279]. Pathogens compete with the host plants in utilizing the sugars secreted by the host plants for growth and development to sustain their life cycle [280,281]. The competition for sugars is controlled by the sugar transporters stated above [266,280], and regulation of these transporters will throw light on the disease control mechanisms in Brassica spp. The SWEET genes are responsible for sugar transport across cell membranes and are involved in diverse physiological processes in different plant species [282]. SWEET genes act as susceptible genes, and the recessive alleles of SWEET genes provide resistance [283]. SWEET proteins play a critical role in host-pathogen interactions and are often targets of extracellular pathogens [282,284,285], regulating carbon transport during parasitism and pathogen interaction. Pathogen infection modulates the expression profiles of SWEET genes in obtaining sugar during host-pathogen interaction. In B. rapa, several BrSWEETs homologs were up-regulated significantly in clubroot susceptible -NILs compared to the control plant [282]. In addition, slower gall formation in the sweet11 mutant of Arabidopsis compared to the wild-type plants confirmed the SWEET gene’s role in clubroot disease development. Hence, it is apparent that P. brassicae colonization may trigger active translocation and sugar partitioning between the source and the clubbed root tissues, thereby activating the genes involved in sugar transport and metabolism.

5. ncRNAomics

Non-coding RNAs (ncRNAs) have housekeeping or regulatory roles [286]. ncRNAs, such as long non-coding RNAs (lnc RNAs) and micro RNAs (miRNAs), play essential roles in response to biotic and abiotic stresses in plants [287,288]. miRNAs are small non-coding RNAs, highly conserved, and regulate the gene expression by post-transcriptional repression [289,290]. miRNAs bind to the target mRNA’s 3′ untranslated region (UTR) to control their expression [291]. Plant miRNAs provide resistance against invading pathogens by interacting with several regions of R genes. Although, plant miRNAs have demonstrated their role in immune response against viruses, bacteria, and fungi [291,292], relatively few studies have exhibited their functions in host defence response against P. brassicae infection in Brassica spp. (Table 4). Verma et al. [293] characterized the changes in miRNA expression profiles of canola roots and identified P. brassicae-responsive putative miRNAs regulating the genes involved in clubroot disease initiation and progression, elucidating post-transcriptional regulation of the target genes during pathogenesis. Genome-wide identification of miRNAs and their targets in B. rapa reported that miR164a decreased with P. brassicae stress [294]. miR164, reportedly involved in auxin homeostasis [295], was hypothesized to be related to clubroot development. Paul et al. [296] revealed the role of a mi-RNA (Bra-miR1885b) in cleaving the resistance gene Bra019412, confirming that miR1885 is critical in regulating the TIR-NBS gene expression during host defence against P. brassicae infection. In a comprehensive study, Li et al. [297] identified six antagonistic miRNA-target pairs involved in root development, hypersensitive cell death, and chloroplast metabolic synthesis pathways. The elucidation of cross-talk between miRNAs and their targets may throw new light on understanding the molecular mechanisms of resistance against P. brassicae.

Long noncoding RNAs (lncRNAs) are important regulatory molecules mediating gene modulation in response to various biotic and environmental stresses in plants and are poorly conserved. lncRNAs exert their regulatory effect through DNA methylation, acetylation, architectural modifications of DNA, and RNA-RNA interactions [298,299]. lncRNAs also regulate the protein-coding genes through cis- or trans-acting processes [300]. A lncRNA-mRNA regulatory network identified the genes regulated by lncRNAs, and 2344 interactions were detected between 1725 mRNAs and 103 lncRNAs [301]. A comparative analysis of the lncRNAs with the clubroot resistance QTL intervals revealed eight lncRNAs localized near the clubroot-resistant QTLs (Anju1, Rcr8, CRd, CRs, qBrCR38-1, and qBrCR38-2). Through the strand-specific lncRNA-Seq approach, 530 differentially expressed (DE) lncRNAs were identified, with 24 in ch. A8 [302] known to carry QTLs introgressed from the rutabaga which confer resistance against five pathotypes of P. brassicae [303]. Out of 24, eight lncRNAs were expressed in the resistant plants, and the genes targeted by these lncRNAs were involved in the plant-pathogen interactions, including defensin, pathogen-related protein, and disease resistance protein (NBS-LRR). The same research group identified 464 DE lncRNAs associated with clubroot resistance in B. napus carrying resistance against pathotype 3 on ch. A3 [304]. A comparative analysis of these lncRNAs with the previously reported DE lncRNAs [302] found 10 lncRNAs regulating defence-related genes. Hence, lncRNAs might play a fundamental role in conferring clubroot resistance through their involvement in transcriptional and post-transcriptional regulation of the defence responsive genes. However, understanding the biological functions of these ncRNAs and their target genes need further research.

Table 4. Published ncRNA studies in Brassica spp. on clubroot resistance.

Species	Target Tissue	Pathotype /Race/Isolate	Time Point (Tissue Collection)	Inference	Reference
B. napus	Total roots	Pathotype 4/Pb1	20 dpi	Six antagonistic miRNA-target pairs associated with root development, hypersensitive cell death, and chloroplast metabolic synthesis were identified in the clubroot resistant line	[297]
B. rapa ssp. pekinensis	Roots	Race 4	15 dai	The putative target genes of the miRNAs were involved in seleno compound metabolism and plant hormone signal transduction	[294]
B. napus	Roots	Pathotype SACAN03-1	10 and 20 dpi	Several target genes TF, hormone-related genes, genes associated with cytokinin, auxin/ethylene response elements were identified	[293]
B. rapa	Leaves and roots	Race 4, Uiryeong, and Banglim	1.5, 3, 6, 12, 24, 48, 72, 96 hpi, and 15 dpi	Cleavage of Bra019412 by Bra-miR1885b suggested that miR1885a negatively regulate the TIR-NBS gene expression during clubroot infection in B. rapa	[296]
B. napus	Roots	Pathotype 3	6, 10, 14, 18 and 22 dpi	24 DE lncRNAs were identified on chromosome A8 known to carrying QTLs conferring resistance against five pathotypes of P. brassicae	[302]
B. napus	Roots	Pathotype 3	0 hpi and 10, 14, and 22 dpi	Target genes regulated by DE lncRNAs belong to plant-pathogen interaction, hormone signalling and primary and secondary metabolic pathways	[304]
Brassica campestris ssp. chinensis Makino	Roots	Race 7	6 wpi	15 mRNAs involved in lncRNA-mRNA co-expression network belong to defense response proteins, protein phosphorylation, root-hair cell differentiation, SA biosynthetic regulation process	[301]

dai, days after inoculation; dpi, days post inoculation; wpi, weeks post inoculation.

6. Proteomics

Proteomics deals with the high-throughput analysis of protein’s structure, function, localization, protein-protein interactions, and role in stress response [305]. Proteins are regarded as an essential tool in functional genomics to analyze major signaling and biochemical pathways involved in plants’ responses to environmental stimuli. Unlike the genome, the proteome is highly dynamic and tends to change based on temporal or environmental factors. Proteomic studies focusing on post-translational modifications, subcellular localization and compartmentalization, signaling pathways, and protein-protein interactions can open up new methods for crop improvement [306], which is discussed later. Protein translates the genomic information into functional information and plays a key role in understanding the molecular mechanisms of plant-pathogen interactions [307,308].

Several techniques have been used to study proteomics. The most widely used methods for identifying and characterizing the separated proteins are gel-base two-dimensional polyacrylamide gel electrophoresis (2DPAGE or 2-DE) and the gel-free shotgun proteomics approach [309,310]. 2-DE was the most popular technique for protein separation, which resolves the proteins based on isoelectric point and molecular mass [311]. Later, technological advances have allowed the targeted mass spectrometry (MS) based quantitative approach to be a powerful technique for proteome analysis. The fourth-generation MS techniques, including selective reaction monitoring (SRM), multiple reaction monitoring (MRM), and parallel monitoring reaction (PRM) [312,313], do allow a comprehensive understanding of differentially expressed proteins contributing to abiotic and biotic stress responses. Among several modern proteomics techniques, iTRAQ-based quantitative proteomics has gained popularity for the high-throughput profiling of proteins. Recently, X-ray crystallography and NMR spectroscopy have been developed to determine the three-dimensional structure of proteins, which would help decipher the biological functions of proteins [314]. In past decades, several proteomic studies were framed to elucidate the dynamic changes in protein composition related to metabolic and signaling pathways involved in host defence against P. brassicae (Table 5).

A proteomic analysis suggested that P. brassicae infection metabolizes the fatty acids from the host causing fatty-acid degradation as the infection progresses, indicating the participation of fatty-acid signaling in P. brassicae infection [315]. Differentially expressed proteins (DEPs) analysis revealed that proteins involved in the glutathione transferase activity pathway could reduce the damage caused by P. brassicae by catalyzing glutathione and electrophilic compound [316]. A label-free shotgun proteomics was followed to gain further insights into clubroot regulations at the post-transcriptional level in B. rapa. Based on functional annotations of differentially accumulated proteins (DAPs), a novel signaling pathway acting in a calcium-independent manner via a cascade of MAPK contributing to clubroot resistance (mediated by the resistance gene Rcr1) was hypothesized [317]. Another proteomic study in Chinese cabbage demonstrated the up-regulation of cycloartenol synthase (CAS1) and cytochrome P450 51G1 proteins involved in the synthesis of brassinosteroid (BR) at the secondary stage of P. brassicae infection [315]. The role of CAS1 in clubroot development was confirmed by treating the clubroot-infected plants with an inhibitor of CAS1, resulting in reduced root gall size. Based on the proteomic studies, it became apparent that in addition to auxin, cytokinin, and JA, brassinosteroids and fatty-acid signaling pathway also regulate clubroot disease development.

Table 5. Published proteomic analyses in Brassica spp. during interaction with clubroot.

Species	Target Tissue	Pathotype/Race/Isolate	Time Point (Tissue Collection)	Methodology	Inference	Reference
B. oleracea	Leaves	Field isolate (Gangneung, Korea)	5 dai	2-DGE, MALDI-TOF/TOF MS	The resistant plants showed an increased abundance of ABA-responsive protein, fructose-bisphosphate aldolase and glucose sensor interaction protein, mediating basal defence against P. brassicae	[318]
B. oleracea	Roots	-	4 wai	2-DE	cytokinin may not cause the tumorous growth and the protist was inhibiting host gene expression causing host protein degradation leading to gall formation	[319]
B. rapa ssp. pekinensis	Roots	Race 4	70 dai	2-DE, MALDI-TOF	10 DEPs responded to stimulation of which two were involved in SA signaling pathway.	[320]
B. rapa	Roots	Pathotype 3	15 dpi	UHPLC-MS/MS	Functional annotation of 527 DAPs suggested a novel signaling pathway acting in a calcium-independent manner through an unique MAPK cascade	[317]
B. rapa ssp. Pekinensis	Roots	Field isolate (SAU, China)	5 dai	2-DE, MALDI-TOF/TOF MS	Proteins related to SA-mediated SAR and JA/ET-mediated ISR were identified showing some degree of cross-talk	[213]
B. rapa	Roots	Race 4	3 dai	2-DE, LC/MS/MS	Resistant line produced more ATP-binding protein for the ABC transporter whereas the susceptible line exhibited increased levels of PR1 production	[321]
B. rapa	Roots	Field isolate (Songming, Kunming, China)	14, 21, 28, 35, and 42 dai	iTRAQ, HPLC-MS/MS	DEPs were associated with the glutathione transferase activity pathway and significantly enriched cytokinin signaling or arginine biosynthesis pathways, both of which were related to stimuli and plant defense reaction	[316]
B. rapa subsp. pekinensis	Roots	Isolate Pb2	0, 10 and 20 dai	2-DE, iTRAQ, LC-ESI-MS/MS	Proteins involved in brassinosteroids metabolism (CAS1, CYP51G1) were up-regulated after inoculation	[315]
B. napus	Roots	Pathotype 3	12, 24, 48, and 72 hai	2-DE, LC/MS/MS	Reduction of adenosine kinase indicated the role of cytokinin in clubroot infection and decreased intensity of CCoAOMT abundance suggested a reduction in host lignin biosynthesis upon pathogen attack	[199]
B. napus	Roots	Pathotype 3	7, 14, and 21-DPI	LC-MS/MS	73 putative proteins orthologous to clubroot-resistant proteins and QTL associated with eight CR loci in different chromosomes including A3 and A8 were identified	[322]

dai, days after inoculation; dpi, days post inoculation; wai, weeks after infection; hai, hours after inoculation.

7. Metabolomics

Metabolomics refers to the comprehensive study of metabolites participating in various cellular events in a biological system [323]. Metabolomics is placed at the phenotypic end of the -omics spectrum capturing the information starting with the genome and progressing through transcriptome and proteome [324]. Qualitative and quantitative metabolites profiling of different tissues, cells, and organs can help identify and quantify primary and secondary/specialized metabolites of plants used in critical biological processes. Metabolomics helps analyze the changes in host plant metabolism in response to pathogen attack, thereby providing a better understanding of host-pathogen interactions. The activation/deactivation of metabolites associated with different signaling pathways determines the resistance or susceptible outcome of a plant-disease interaction [325]. In recent years, multiple separation and analytical techniques such as MS, liquid, and gas chromatography-MS (LC-MS, GC-MS), Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR-MS), capillary electrophoresis liquid-chromatography mass spectrometry (CE-MS), and NMR have been developed to analyze the plant metabolites (reviewed by Raza et al. [326]). In plants, metabolomic analyses can be accomplished by both non-targeted [327] and targeted [328] approaches. While untargeted metabolomics deals with both secondary and primary metabolites, the targeted approach identifies glucosinolates (GSLs). Over the years, several metabolomic studies in different Brassica crops evaluated the effects of phytohormones, secondary metabolites and GSLs to evaluate conferring resistance to P. brassicae (Table 6).

During gall formation, a plethora of changes occurs in the primary and secondary metabolism (Reviewed by Ludwig-Müller et al. [22]). Primary metabolism is involved in a plant’s growth, development, and reproduction and revolves around critical physiological compounds such as sugars and amino acids. In the previous section, we have discussed about the role of carbohydrates in constituting a metabolic sink during the development of galls in the root system. In contrast to carbohydrate metabolism, little information about nitrogen metabolism during clubroot disease development is available, except for a few studies [329]. A study on cabbage has shown that total nitrogen, protein, and amino-acid levels increased in the galls of cabbage during clubroot development [271]. A study has suggested that clubroot susceptibility was positively correlated with the accumulation of several amino acids at the early infection stage in B. napus [330]. In clubroot infected Arabidopsis, a large amount of proline accumulates, which could be attributed to the response to water limitation caused by the loss of functional roots [182]. The induction of arginine constitutes the basal defence mechanism by reducing hormone-triggered cellular proliferation during gall development [222]. A difference in arginine metabolism signature was reported in susceptible and partially resistant Arabidopsis plants. Specifically, in susceptible plants, a massive induction of arginine was found in the later stage of infection [182].

During gall formation, pathogen alters the levels of plant growth hormones, especially auxins and cytokinins, important for hypertrophy of the infected roots. In B. rapa, compared to resistant genotype, the susceptible genotype showed higher auxin and cytokinin levels after P. brassicae infection except trans-zeatin and 3-indolebutyric acid [331]. In A. thaliana and B. rapa, IAA levels increased at different phases of clubroot infection [225,332,333,334]. IAA biosynthesis in Brassicaceae proceeds via indole GSLs through the formation of indole-3-acetaldoxime (IAOX), indole-3-methyl glucosinolate (IMG), and indole-3-acetonitrile (IAN). During the invasion of the pathogen, IMG converts to IAN by myrosinase, thereby increasing the levels of auxin precursor. Studies have shown that in clubroot-infected B. rapa roots, IAN is specifically converted to IAA from indole GSLs [335]. The enzyme nitrilase may regulate IAA biosynthesis in Brassicaceae by converting IAN to IAA, and nitrilase activity with increased IAA content during root gall development has been reported in Chinese cabbage [336,337]. Grsic et al. [225] reported an enhanced activity of nitrilase and myrosinase at the late stage of clubroot development in Chinese cabbage. Hydrolysis of free IAA from inactive auxin conjugates could be another pathway for IAA biosynthesis. A study in B. rapa reported hydrolysis of several IAA-amino acid conjugates during clubroot infection [333].

In addition to auxin, increased concentrations of free and bound cytokinins have been reported during clubroot disease development. P. brassicae can form cytokinins in a limited amount by converting trans-zeatin and its riboside [338]. Devos et al. [339] reported a greater amount of active cytokinins such as zeatin early in the infected B. rapa plants. Though P. brassicae requires cytokinin for its development, it can synthesize only small amounts of cytokinin [180], prompting it to take cytokinins from its host. In the host, cytokinins help develop vascular cambium essential for normal plant growth and act as a route for P. brassicae to hijack host development for gall formation. Malinowski et al. [180] reported that gall formation is associated with a decline in cytokinin content, and other phytohormones may be involved in the hypertrophy of clubbed roots. The down-regulation of cytokinin can be a part of the plant-defence mechanism against P. brassicae. It reduces the signals involved in cell division and the cell cycle progression in the root cortex [200]. Disturbing the balance of cytokinin synthesis and degradation may impact clubroot disease progression.

The key hormone involved in the defence response against biotrophic pathogens is SA, and the application of exogenous SA was reported to curb clubroot disease in Arabidopsis [259]. SA level was enhanced in the partially resistant Bur-0 ecotype of A. thaliana after P. brassicae infection with mild elevation of JA [215], indicating that both SA- and JA-triggered defences result in P. brassicae resistance. But SA appears to be more efficient than JA in conferring resistance. Exogenous SA decreased the clubroot symptoms in two accessions of Arabidopsis [215] and pakchoi [251]. Upon P. brassicae infection, SA content was increased at later stages of infection in the susceptible cultivar of B. napus but at an earlier time point in the resistant cultivar [181]. However, mechanisms governing SA to repress clubroot resistance are not very clear. In Arabidopsis, SA and its analogs treatment have reduced auxin level and signaling, essential for gall formation [340]. Xi et al. [251] hypothesized that exogenous SA treatment might influence auxin biosynthesis and signaling, thereby reducing the infection abilities of P. brassicae and enhancing resistance. Double SA application (before infection and 15 dai) diminished gall formation in the resistant cultivar (Alister) of B. napus [181]. Interestingly, the latest study has demonstrated a lower accumulation of SA in the resistant line of B. rapa than that of the control [240]. This could have happened due to the down-regulation of NPR1 homologs (the key regulators of SA-mediated resistance) in the resistant line leading to a significant decrease in SA content.

In contrast to SA, JA plays a vital role in clubroot disease development (Figure 2 and Figure 3) at the secondary infection stage/cortex infection stage. Xu et al. [223] reported a greater accumulation of JA at 14–28 dai in susceptible B. napus during clubroot infection. Two to three-fold higher JA and its expression level was reported in susceptible Col-0 at the secondary infection stage in Arabidopsis [215]. In a recent study, JA precursor (cis-OPDA), JA-bound (jasmonoyl-L-isoleucine, JA-Ile), and free JA content decreased at 9 and 20 dai in the resistant line of B. rapa (BrT24), though increased significantly in the susceptible line [240]. Elevation of JA in the susceptible cultivars raises a question of whether this is a part of pathogen strategy to overcome plant defence by suppressing the SA pathway [181,240]. Interestingly, JA also mediates resistance against clubroot at the secondary infection stage, although it is weak. Exogenous JA treatment reduced clubroot symptoms only in the susceptible Arabidopsis (Col-0), indicating its participation in the weak defence against P. brassicae [215]. Apart from SA and JA, the role of ethylene mediating resistance to clubroot has been demonstrated in A. thaliana [341,342]. Wei et al. [240] opined that ethylene signaling is required to restrict gall growth. Knaust and Ludwig-Müller [341] have shown that ET response 1 (etr1) and ET insensitive2 (ein2) mutants were more susceptible than the wild-type Arabidopsis. This was in agreement with Siemens et al. [179], who reported the down-regulation of ethylene biosynthesis genes in clubroot-infected A. thaliana. Devos et al. [339] reported an increase in the content of 1-Aminocyclopropane 1-carboxylic acid (ACC) (direct precursor of ethylene) in the unaffected roots of B. rapa compared to the infected plants at 14 dpi. But Lan et al. [331] could not observe any change in the levels of ACC which could be attributed to different genetic backgrounds of the genotypes. Another phytohormone, brassinosteroids (BR), reportedly mediated clubroot resistance by its inhibition in the resistant line of B. rapa but was induced in the susceptible line (Figure 3).

Glucosinolates (GSLs) are one of the largest known groups of secondary metabolites in the family Brassicaceae [343]. Based on their amino acid precursors, GSLs can be divided into three groups, aliphatic, aromatic, and indolic GSL [344]. The GSLs have long been associated with clubroot disease, and their role in clubroot disease development has been reviewed extensively by Ludwig- Müller [345]. While aromatic GSLs act as a plant defence against pests, aliphatic GSLs are considered defence compounds against plant pathogens [345,346]. Compared to aromatic and aliphatic GSLs, most studies have focused on indolic GSLs in clubroot disease development. Indolic GSLs are thought to be the precursors of IAA/auxin biosynthesis in Brassicaceae, and high IAA levels are involved in gall formation. The earlier induction of indole GSLs may be responsible for the overproduction of IAA during clubroot disease development. Several studies in the Brassicaceae family proved that indole GSLs content is correlated with clubroot disease development and severity, directly or indirectly [224,332,334,345]. Nonetheless, indolic GSLs were involved in innate immunity response in A. thaliana [347]. Correlations between low indole GSLs content and clubroot resistance have been observed in the members of Brassicaceae [223,348,349,350]. The elevation of indolic GSLs happened largely due to the accumulation of 4-methoxyglucobrassicin [223,232] and neoglucobrassicin, glucobrassicin [232]. Zamani-Noor et al. [351] reported higher mean contents of 4-methoxyglucobrassicin in P. brassicae-infected resistant and susceptible plants than non-inoculated plants irrespective of the pathotypes used. So, further study on the function of 4-methoxyglucobrassicin will throw light on the role of indolic GSLs in clubroot disease development. In contrast to indole GSLs, knowledge of aliphatic and aromatic GSLs in clubroot disease is limited. Though aliphatic GSLs are supposed to be involved in defence response, several studies showed the opposite results. Ludwig- Müller et al. [224] reported increased aliphatic GSLs in two susceptible Chinese cabbage varieties but observed no change in the resistant varieties. Xu et al. [223] also reported that aliphatic GSLs were involved in clubroot development in B. napus. Various components of aliphatic GSLs (such as glucoalyssin) were increased together with the decreased glucoraphanin content in the resistant plants. This summarizes that instead of total components of GSLs, particular components of GSLs are responsible for clubroot resistance or susceptibility. The role of aromatic GSLs in clubroot disease is not very clear, though few authors have reported its enhanced content both in resistant and susceptible plants. Two resistant varieties of Chinese cabbage showed an increase in aromatic GSLs, indicating their role in host resistance [224]. Zamani-Noor et al. [351] observed lower levels of gluconasturtiin (aromatic GSL) in the roots of susceptible varieties of B. napus compared to resistant varieties. Xu et al. [223] demonstrated enhanced content of aromatic GSLs in both the resistant and susceptible plants at the secondary infection stage, though its component was completely different.

In summary, GSL metabolites, specifically indole GSLs, are more likely to play an important role in disease development than defence response against P. brassicae. However, a recent study has raised the possibility of GSL breakdown products acting against P. brassicae. A recent report has shown that the resistant cultivar could maintain water balance through breakdown products of aromatic GSL in the stomatal aperture during P. brassicae infection [351]. Nevertheless, it requires further research to understand the role of GSL metabolism in clubroot-disease development and defence in the Brassicaceae family.

Table 6. Published metabolomic analyses in Brassica spp. involved in resistance against clubroot.

Species	Target Tissue	Pathotype/Race/Isolate	Time Point (Tissue Collection)	Methodology	Inference	Reference
B. oleracea	Leaves and roots	Isolate yeoncheon	0, 3, 6, 12, 24, 72 hai and 15 and 40 dai	HPLC	Plants with higher levels of neoglucobrassicin, glucobrassicin and methoxyglucobrassicin exhibited disease symptoms with gall formation	[232]
B. napus	Roots	Pathotype 1	14, 21, 28, 35, and 42 dpi	UPLC-MS/MS, GC-MS	Clubroot susceptibility was positively correlated with clubroot-induced amino acids accumulation	[330]
B. napus	Leaves and roots	Pathotype 4	3, 7, and 10 dai	RP-HPLC/ESI–MS/MS	IAA acts as a signalling molecule to induce root hair infection during early stage of infection whereas NPA treatment reduced the disease index	[192]
B. napus subs. napus	Leaves, roots, galls	Pathotype 6	2, 5, 7, 10, 15, 22, 35, 42, and 49 dai	HPLC	JA promoted gall formation in both the cultivars, whereas SA suppressed gall formation in the resistant cultivar	[181]
B. napus	Roots	Pathotype 4	3, 7, 14, and 28 dai	HPLC	JA-induced aromatic GSLs were involved in defence response and JA-induced aliphatic GSLs may be involved in clubroot disease development	[223]
B. napus	Leaves and roots	Isolate P1 and P1 (+) (pathotype 1)	35 dpi	LC-MS	Single and total aliphatic and indolic GSL contents were significantly lower in the leaves and roots of susceptible cultivars compared to the resistant ones	[351]
Brassica napus cv. Westar	Roots	Pathotype 3	3, 4, 5 and 6 wpi	HPLC-DAD, HPLC-ESI-MS	Plants produced a complex blend of phytoalexins and other antimicrobial metabolites as a defence response	[352]
B. campestris ssp. chinensis Makino	Leaves and Roots	Race 7	40 DAG	-	Clubroot incidence rate and disease index were decreased after treatment with 0.6 mM exogenous SA	[251]
B. campestris ssp. pekinensis	Roots	-	5, 10, 14, 20, 24, 28, 32 and 40 dai	HPLC	Indole and aliphatic was higher in the roots of susceptible varieties whereas aromatic glucosinolates was higher in the roots of resistant varieties	[224]
Brassica campestris L. ssp. pekinensis cv. Granat	Leaves and Roots	-	14, 21, 28, 35, 42 dai	HPLC	JA level was enhanced during club development and may be involved in the up-regulation of three enzymes required for IAA synthesis	[225]
B. campestris	Roots	-	5, 10, 12, 13 and 14 dai	GC-MS	Mean of IAA content in the infected plant was 66.5% higher than the non-infected plants	[332]
B. rapa ssp. pekinensis	Roots	Field isolate (Songming, Kunming, Yunnan, China)	14, 21, 28, 35, 42 dpi	LC-ESI-MS/MS,	Metabolites related to amino-acid biosynthesis, fatty-acid biosynthesis and elongation, glutathione and glucosinolate metabolism were highly accumulated in the resistant genotype	[331]
B, rapa	Roots	Race 4	0, 3, 9, and 20 dai	UHPLC-MS	Inhibition of IAA, cytokinin, JA, and SA contents may play important roles in regulation of clubroot resistance	[240]

dai, days after inoculation; dpi, days post inoculation; wpi, weeks after inoculation; DAG, days after germination.

8. Multi-Omics Opened Up New Avenues for Crop Improvement

The traditional breeding techniques mainly based on phenotypic selection are unable to achieve the needs of food security and sustainability crop productivity [353], as several desirable traits are complex in nature. Engineering these complex traits could help crop improvement by a proper understanding of the flow of information from the gene, RNA, protein and metabolite to these traits. To achieve genetic gains for the desirable traits, several molecular breeding approaches, including MAS, MABC, marker-assisted recurrent selection (MARS), GWAS, genomic selection (GS), NGS-enabled QTL-seq, BSR-seq, and GBS techniques, have been used to speed up the breeding process. Combining all these genomic tools with the conventional breeding techniques, called ‘genomics-assisted breeding’ [354], is harnessed by the breeders to practice precision breeding. Furthermore, the sequencing cost has been reduced several folds with the development of NGS technologies and platforms. As a result, genome-sequence assemblies of hundreds of plants became available to understand the relationship of genomic segments with the phenotype. In addition, genomic techniques are widely used for germplasm enhancement by deciphering the genome architecture and genome variations, thereby improving the genetic stocks. Mutagenomics tools such as Targeted Induced Local Lesions IN Genomes (TILLING) has emerged, which is a modern omics technique that causes high-throughput mutations leading to gene modification in the target traits. All these genomic tools could be applied to enhance clubroot resistance of the germplasm/breeding lines in Brassica spp. Specifically, combining genomic selection with the multi-omics analysis could improve the prediction accuracy of the trait performance. The advancement of NGS technologies facilitates scRNA (single-cell RNA) sequencing, which provides the information about unique mutations in the cell [355]. Recently, another transcriptomics approach known as alternative splicing (AS) has been used to produce multiple transcripts in response to abiotic stress conditions [356]. Several powerful quantitative proteomics approaches (discussed earlier) are aiding in the identification of proteins involved in the causative function of important traits, including clubroot resistance. The differentially expressed protein can help identify novel protein markers for crop improvement. Several high-throughput metabolomics techniques have been widely used in different crops in response to biotic/abiotic stresses and to unravel the phenotypic plasticity. Metabolomics integrated with other omics approaches such as genomics, transcriptomics, and proteomics could provide a list of various functions ranging from genome to metabolome, including phenotypic characteristics [357]. In recent years, metabolites have been increasingly used to predict phenotyping properties. In the second decade of the 21st century, CRISPR/Cas mediated genome editing technology is extensively used to edit plant genomes. Genome-editing technique integrated with speed breeding will facilitate the rapid validation of the incorporated gene without in vitro manipulations [306]. Multi-omics platforms integrated with genome-editing tools will help develop precision breeding. Finally, the high-throughput phenomics platforms for rapid and precise phenotypic assessment will maximize productivity and promote sustainable crop production. Hence, full automatization of clubroot disease indexing by digital root imaging systems is a long overdue task which needs to be adopted for rapid pathotyping [358]. Often, the digitalization of root architecture and morphology is carried out by analysing the digital root images using different software, which is extremely necessary in the near future for disease indexing of clubroot disease. The multi-omics technologies are generating huge data, known as ‘big data’, whose integration has been a challenging task. So, deep learning (DL) has emerged as a powerful approach to integrate multi-omics data [359], which can encode and model many forms of complex data. Different omics tools have led to the emergence of different technology platforms, methods and computational tools, and the combination of these tools will provide sufficient power to enhance clubroot resistance in Brassica spp.

9. Concluding Remarks and Perspectives

In recent years, the application of omics technologies has provided insights into the molecular mechanism of disease resistance at the genomic, epigenomic, transcriptomic, proteomic, and metabolomic levels. If these technologies are integrated at the right scale, they may decipher the multi-dimensional properties of plant diseases [360]. In this review, we have discussed the recent advances made in various omics techniques to understand the mechanism of clubroot resistance in Brassica crops. Still, several challenges (Figure 4) remain to realize the full potential of omics techniques in managing clubroot disease.

Effective deployment of R genes in clubroot resistance breeding demands detailed knowledge of the ecology and life history of the host, pathogen, and their interactions, allowing the host resistance prediction at different stages of infection. While B. rapa remains a good source of many race-specific, dominant R genes, B. oleracea has a complex inheritance pattern and a more continuous resistance involving major and minor genes. This pointed towards different physiological resistance mechanisms imparted by B. rapa and B. oleracea, resulting in complete resistance in B. rapa, which is lacking in B. oleracea [30,361]. Hence, it becomes difficult to fine map or clone resistance genes, restricting R genes’ utilization in resistance breeding in B. oleracea. Combining both race-specific and race-nonspecific genes may be an effective and durable strategy to potentially increase resistance against P. brassicae. In the Brassica-P. brassicae pathosystem, several R genes have been mapped, but only three have been cloned. Moreover, the molecular mechanism of resistance of these cloned genes has yet to be clarified. Historically, cloning of R genes has been accomplished by map-based cloning. However, in the post-genomics era, significant accomplishments have been made in cloning R genes in several crops including, Brassica that have complex genomes.

To date, in Brassica spp. different research groups have identified many clubroot-resistant QTLs. Nevertheless, comparing these QTLs is impossible due to the lack of common molecular markers, use of different clubroot resistant sources, and P. brassicae pathotypes/isolates. Besides, various researchers have named QTLs/genes independently. However, many of these belong to the same genomic region leading to naming some of these loci by other names. Accurate and unambiguous naming of these loci would help in efficient deployment these genes in breeding of clubroot resistance. Different isolates could be functionally different in their pathogenesis; therefore, it is important to develop isolate/pathotype-specific clubroot-resistant lines, and molecular markers need to be developed to detect isolate-specific resistant lines.

In Brassica spp., R gene identification for clubroot disease has focused mainly on NBS-LRR genes. Hence, future studies should analyze the contribution of other classes of R genes, such as RLKs, RLPs, and wall-associated kinases in clubroot resistance, which may facilitate the cloning of novel R genes. In this regard, pangenome study will help identify a large R gene repertoire (RGAs) in Brassica spp. Pangenomics is a promising approach for studying the structural variation in the genes and has been proved useful in deciphering the structure, function, and evolutionary origin of R genes. Furthermore, super-pangenome representing the genomes of wild relatives and different species [362] may facilitate the identification of many more novel candidate resistance genes, improving the speed and accuracy of crop breeding by broadening the Brassica gene pool. In addition to the host resistance genes, the investigation of pathogenesis-related genes, effector candidates, transcriptome, miRNA, proteome and metabolome data of P. brassicae-inoculated tissue is essential to understand the interaction of host-pathogen to formulate the strategy to develop clubroot-resistant Brassica crops (For a comprehensive review, see Jutta Ludwig-Müller [363]).

The genome complexity of Brassica spp. has contributed to the complicated gene rearrangement, duplication, and loss [364], narrowing the scope of utilization of R genes in the breeding programs. This has also resulted in the loss of genetic diversity in B. napus compared to its progenitors, B. rapa and B. oleracea [365]. Clustering of R genes is prevalent in clubroot disease, further providing evidence of genome complexity. Clustering of R genes may help recognize diverse pathotypes carrying different Avr genes; however, clustering and duplication may be problematic in R gene identification as these genes may collapse in genome sequence assemblies [366]. At times, R-genes from the parents get masked in the resynthesized genomes of the progenies, as occurred in the clubroot R gene [151]. This can be overcome by genome editing techniques such as CRISPR-Cas9, which has been successfully used for the functional gene studies in the Brassica-pathogen system though not performed in the Brassica-P. brassicae pathosystem.

A huge number of data collected through multi-omics technologies has enabled the construction of network biology, wherein computational and mathematical analysis and modelling predict the pathogenicity and mechanisms of virulence in host-pathogen interactions. While analyzing certain biological processes, integrated multi-omics approaches could complement each other. In this context, systems biology has provided an excellent platform to integrate different -omics technologies to have a holistic understanding of the adaptation and development of an organism [367]. Integration of multi-omics technologies can enhance our understanding of the complete biological systems by predicting the behavior and interactions among genes, proteins, and metabolites with respect to external stimuli [368]. Previously, a comprehensive analysis of multi-omics approaches has increased our understanding of systems biology associated with abiotic stress response in plants [369,370]. However, a model needs to be developed to identify the molecular regulator network involved in clubroot resistance by combining systems biology with multi-omics approaches. With the advancement of computational tools, discoveries involving Brassica-P. brassicae pathosystem will be made in near future to increase our understanding of the molecular regulator network involved in clubroot resistance in Brassica crops.

Supplementary Materials

The following are available online at https://www.mdpi.com/article/10.3390/ijms23169280/s1. References [371,372,373,374,375,376,377,378,379,380,381,382,383,384,385,386,387,388,389,390,391] are cited in the supplementary materials.

Author Contributions

H.G. conceived the idea and revised the manuscript. R.K.S. wrote the manuscript. H.G., Y.S., H.Y., X.S., J.W. reviewed and edited the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

Funding was provided by the Natural Science Foundation of Zhejiang Province (LD22C150002, LQ20C150001), the Science and Technology Department of Zhejiang Province (2021C02065-4, 2022C02051, 2021C02042), Zhejiang Province Public Welfare Project (LGN20C150005).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

The authors wish to thank Jisuan Chen from Haitong Food Technology Co., Ltd., Nimbo, for his input during the preparation of the manuscript. We also thank BioRender (BioRender.com, accessed on 16 June 2022) for using open access template to draw Figure 2, Figure 3 and Figure 4.

Conflicts of Interest

The authors declare no conflict of interest.

References

Cartea, M.E.; Lema, M.; Francisco, M.; Velasco, P. Basic information on vegetable Brassica crops. In Genetics, Genomics and Breeding of Vegetable Brassicas, 1st ed.; Sadowsky, J., Kole, C., Eds.; Science Publishers: Enfield, NH, USA, 2011; pp. 1–34. [Google Scholar]
Gupta, U.S. Brassica Vegetables, What’s New About Crop Plants, 1st ed.; Science Publishers: Enfield, NH, USA, 2011; pp. 378–402. [Google Scholar]
Kapusta-Duch, J.; Kopeć, A.; Piatkowska, E.; Borczak, B.; Leszczyńska, T. The beneficial effects of Brassica vegetables on human health. Rocz. Panstw. Zakl. Hig. 2012, 63, 389–395. [Google Scholar] [PubMed]
Dixon, G.R. The Occurrence and Economic Impact of Plasmodiophora brassicae and Clubroot Disease. J. Plant Growth Regul. 2009, 28, 194–202. [Google Scholar] [CrossRef]
Tewari, J.P.; Strelkov, S.E.; Orchard, D.; Hartman, M.; Lange, R.M.; Turkington, T.K. Identification of clubroot of crucifers on canola (Brassica napus) in Alberta. Can. J. Plant Pathol. 2005, 27, 143–144. [Google Scholar] [CrossRef]
Pageau, D.; Lajeunesse, J.; Lafond, J. Impact de l’hernie des crucifères [Plasmodiophora brassicae] sur la productivité et la qualité du canola. Can. J. Plant Pathol. 2006, 28, 137–143. [Google Scholar] [CrossRef]
Wallenhammar, A.-C. Prevalence of Plasmodiophora brassicae in a spring oilseed rape growing area in Central Sweden and factors influencing soil infestation levels. Plant Pathol. 1996, 45, 710–719. [Google Scholar] [CrossRef]
Hwang, S.F.; Howard, R.J.; Strelkov, S.E.; Gossen, B.D.; Peng, G. Management of clubroot (Plasmodiophora brassicae) on canola (Brassica napus) in western Canada. Can. J. Plant Pathol. 2014, 36, 49–65. [Google Scholar] [CrossRef]
Hwang, S.F.; Ahmed, H.U.; Zhou, Q.; Turnbull, G.D.; Strelkov, S.E.; Gossen, B.D.; Peng, G. Effect of host and non-host crops on Plasmodiophora brassicae resting spore concentrations and clubroot of canola. Plant Pathol. 2015, 64, 1198–1206. [Google Scholar] [CrossRef]
Peng, G.; Lahlali, R.; Hwang, S.F.; Pageau, D.; Hynes, R.K.; McDonald, M.R.; Gossen, B.D.; Strelkov, S.E. Crop rotation, cultivar resistance, and fungicides/biofungicides for managing clubroot (Plasmodiophora brassicae) on canola. Can. J. Plant Pathol. 2014, 36, 99–112. [Google Scholar] [CrossRef]
Strelkov, S.E.; Hwang, S.-F.; Howard, R.J.; Hartman, M.; Turkington, T.K. Progress towards the sustainable risk management of clubroot (Plasmodiophora brassicae) of canola on the Canadian prairies. Prairie Soils Crops J. 2011, 4, 114–121. [Google Scholar]
Wallenhammar, A.C.; Johnsson, L.; Gerhardson, B. Clubroot Resistance and Yield Loss in Spring Oilseed Turnip Rape and Spring Oilseed Rape. In Proceedings of the 10th International Rapeseed Congress, Canberra, Australia, 26–29 September 1999. [Google Scholar]
Hwang, S.F. Seedling age and inoculum density affect clubroot severity and seed yield in canola. Can. J. Plant Sci. 2011, 91, 183–190. [Google Scholar] [CrossRef]
Peng, G.; Falk, K.C.; Gugel, R.K.; Franke, C.; Yu, F.; James, B.; Strelkov, S.E.; Hwang, S.-F.; McGregor, L. Sources of resistance to Plasmodiophora brassicae (clubroot) pathotypes virulent on canola. Can. J. Plant Pathol. 2014, 36, 89–99. [Google Scholar] [CrossRef]
Liu, Y.; Xu, A.; Liang, F.; Yao, X.; Wang, Y.; Liu, X.; Zhang, Y.; Dalelhan, J.; Zhang, B.; Qin, M. Screening of clubroot-resistant varieties and transfer of clubroot resistance genes to Brassica napus using distant hybridization. Breed. Sci. 2018, 68, 258–267. [Google Scholar] [CrossRef] [PubMed]
Donald, C.; Porter, I. Integrated Control of Clubroot. J. Plant Growth Regul. 2009, 28, 289. [Google Scholar] [CrossRef]
Peng, G.; Pageau, D.; Strelkov, S.; Gossen, B.; Hwang, S.; Lahlali, R. A >2-year crop rotation reduces resting spores of Plasmodiophora brassicae in soil and the impact of clubroot on canola. Eur. J. Agron 2015, 70, 78–84. [Google Scholar] [CrossRef]
Faggian, R.; Strelkov, S.E. Detection and Measurement of Plasmodiophora brassicae. J. Plant Growth Regul. 2009, 28, 282–288. [Google Scholar] [CrossRef]
Hwang, S.-F.; Ahmed, H.U.; Zhou, Q.; Fu, H.; Turnbull, G.D.; Fredua-Agyeman, R.; Fredua-Agyeman, R.; Strelkov, S.E.; Gossen, B.D.; Peng, G. Influence of resistant cultivars and crop intervals on clubroot of canola. Can. J. Plant Sci. 2019, 99, 862–872. [Google Scholar] [CrossRef]
Francisco, M.; Soengas, P.; Velasco, P.; Bhadauria, V.; Cartea, M.E.; Rodríguez, V.M. Omics approach to identify factors involved in Brassica disease resistance. Curr. Issues Mol. Biol. 2016, 19, 31–42. [Google Scholar]
Barr, D.J.S. Evolution and kingdoms of organisms from the perspective of a mycologist. Mycologia 1992, 84, 1–11. [Google Scholar] [CrossRef]
Ludwig-Müller, J.; Prinsen, E.; Rolfe, S.A.; Scholes, J.D. Metabolism and plant hormone action during clubroot disease. J. Plant Growth Regul. 2009, 28, 229–244. [Google Scholar] [CrossRef]
Kageyama, K.; Asano, T. Life Cycle of Plasmodiophora brassicae. J. Plant Growth Regul. 2009, 28, 203–211. [Google Scholar] [CrossRef]
Howard, R.J.; Strelkov, S.E.; Harding, M.W. Clubroot of cruciferous crops—New perspectives on an old disease. Can. J. Plant Pathol. 2010, 32, 43–57. [Google Scholar] [CrossRef]
Voorrips, R.E. Plasmodiophora brassicae: Aspects of pathogenesis and resistance in Brassica oleracea. Euphytica 1995, 83, 139–146. [Google Scholar] [CrossRef]
Friberg, H.; Lagerlöf, J.; Rämert, B. Germination of Plasmodiophora brassicae resting spores stimulated by a non-host plant. Eur. J. Plant Pathol. 2005, 113, 275–281. [Google Scholar] [CrossRef]
Rashid, A.; Ahmed, H.U.; Xiao, Q.; Hwang, S.F.; Strelkov, S.E. Effects of root exudates and pH on Plasmodiophora brassicae resting spore germination and infection of canola (Brassica napus L.) root hairs. Crop Protect. 2013, 48, 16–23. [Google Scholar] [CrossRef]
Ingram, D.S.; Tommerup, I.C. The life history of Plasmodiophora brassicae Woron. Proc. R. Soc. London. Ser. B. Biol. Sci. 1972, 180, 103–112. [Google Scholar]
Rolfe, S.A.; Strelkov, S.E.; Links, M.G.; Clarke, W.E.; Robinson, S.J.; Djavaheri, M.; Malinowski, R.; Haddadi, P.; Kagale, S.; Parkin, I.A.P.; et al. The compact genome of the plant pathogen Plasmodiophora brassicae is adapted to intracellular interactions with host Brassica spp. BMC Genom. 2016, 17, 272. [Google Scholar] [CrossRef]
Hwang, S.F.; Strelkov, S.E.; Feng, J.; Gossen, B.D.; Howard, R.J. Plasmodiophora brassicae: A review of an emerging pathogen of the Canadian canola (Brassica napus) crop. Mol. Plant Pathol. 2012, 13, 105–113. [Google Scholar] [CrossRef]
Honig, F. Der Kohlkropferreger (Plasmodiophora brassicae Wor.): Eine Monographie; Verlag nicht ermittelbar: Leipzig, Germany, 1931. [Google Scholar]
Pang, W.; Liang, Y.; Zhan, Z.; Li, X.; Piao, Z. Development of a Sinitic clubroot differential set for the pathotype classification of Plasmodiophora brassicae. Front. Plant Sci. 2020, 11, 568771. [Google Scholar] [CrossRef]
Williams, P.H. A system for the determination of races of Plasmodiophora brassicae that infect cabbage and rutabaga. Phytopathology 1966, 56, 624–626. [Google Scholar]
Buczacki, S.T.; Toxopeus, H.; Mattusch, P.; Johnston, T.D.; Dixon, G.R.; Hobolth, L.A. Study of physiologic specialization in Plasmodiophora brassicae: Proposals for attempted rationalization through an international approach. Trans. Br. Mycol. Soc. 1975, 65, 295–303. [Google Scholar] [CrossRef]
Somé, A.; Manzanares, M.J.; Laurens, F.; Baron, F.; Thomas, G.; Rouxel, F. Variation for virulence on Brassica napus L. amongst Plasmodiophora brassicae collections from France and derived single-spore isolates. Plant Pathol. 1996, 45, 432–439. [Google Scholar] [CrossRef]
Strelkov, S.E.; Hwang, S.-F.; Manolii, V.P.; Cao, T.; Fredua-Agyeman, R.; Harding, M.W.; Peng, G.; Gossen, B.D.; Mcdonald, M.R.; Feindel, D. Virulence and pathotype classification of Plasmodiophora brassicae populations collected from clubroot resistant canola (Brassica napus) in Canada. Can. J. Plant Pathol. 2018, 40, 284–298. [Google Scholar] [CrossRef]
Strelkov, S.; Hwang, S.; Manolii, V.; Cao, T.; Feindel, D. Emergence of new virulence phenotypes of Plasmodiophora brassicae on canola (Brassica napus) in Alberta, Canada. Eur. J. Plant Pathol. 2016, 145, 517–529. [Google Scholar] [CrossRef]
Strelkov, S.E.; Manolii, V.P.; Harding, M.W.; Daniels, G.C.; Nuffer, P.; Aigu, Y.; Hwang, S.F. The Occurrence and Spread of Clubroot on Canola in Alberta in 2019. Canadian Plant Disease Survey 2020 Vol. 100: Disease Highlights 2019. Can. J. Plant Pathol. 2020, 42, 117–120. [Google Scholar] [CrossRef]
Hulbert, S.; Pumphrey, M. A time for more booms and fewer busts? Unraveling cereal-rust interactions. Mol. Plant Microbe. Interact. 2014, 27, 207–214. [Google Scholar] [CrossRef] [PubMed]
Mellor, K.E.; Hoffman, A.M.; Timko, M.P. Use of ex vitro composite plants to study the interaction of cowpea (Vigna unguiculata L.) with the root parasitic angiosperm Striga gesnerioides. Plant Methods 2012, 8, 22. [Google Scholar] [CrossRef]
Liu, S.; Liu, Y.; Yang, X.; Tong, C.; Edwards, D.; Parkin, I.A.P.; Zhao, M.; Ma, J.; Yu, J.; Huang, S.; et al. The Brassica oleracea genome reveals the asymmetrical evolution of polyploid genomes. Nat. Commun. 2014, 5, 3930. [Google Scholar] [CrossRef]
Parkin, I.; Koh, C.; Tang, H.; Robinson, S.J.; Kagale, S.; E Clarke, W.; Town, C.D.; Nixon, J.; Krishnakumar, V.; Bidwell, S.L.; et al. Transcriptome and methylome profiling reveals relics of genome dominance in the mesopolyploid Brassica oleracea. Genome Biol. 2014, 15, R77. [Google Scholar] [CrossRef]
Belser, C.; Istace, B.; Denis, E.; Dubarry, M.; Baurens, F.-C.; Falentin, C.; Genete, M.; Berrabah, W.; Chèvre, A.-M.; Delourme, R.; et al. Chromosome-scale assemblies of plant genomes using nanopore long reads and optical maps. Nat. Plants 2018, 4, 879–887. [Google Scholar] [CrossRef]
Sun, D.; Wang, C.; Zhang, X.; Zhang, W.; Jiang, H.; Yao, X.; Liu, L.; Wen, Z.; Niu, G.; Shan, X. Draft genome sequence of cauliflower (Brassica oleracea L. var. botrytis) provides new insights into the C genome in Brassica species. Hortic. Res. 2019, 6, 82. [Google Scholar] [CrossRef]
Guo, N.; Wang, S.; Gao, L.; Liu, Y.; Wang, X.; Lai, E.; Duan, M.; Wang, G.; Li, J.; Yang, M.; et al. Genome sequencing sheds light on the contribution of structural variants to Brassica oleracea diversification. BMC Biol. 2021, 19, 93. [Google Scholar] [CrossRef] [PubMed]
Bayer, P.E.; Golicz, A.A.; Scheben, A.; Batley, J.; Edwards, D. Plant pan-genomes are the new reference. Nat. Plants 2020, 6, 914–920. [Google Scholar] [CrossRef]
Golicz, A.A.; Bayer, P.E.; Barker, G.C.; Edger, P.P.; Kim, H.; Martinez, P.A.; Chan, C.K.K.; Severn-Ellis, A.; McCombie, W.R.; Parkin, I.A.P.; et al. The pangenome of an agronomically important crop plant Brassica oleracea. Nat. Commun. 2016, 7, 13390. [Google Scholar] [CrossRef] [PubMed]
Amsbury, S. Sensing Attack: The role of wall-associated kinases in plant pathogen responses. Plant Physiol. 2020, 183, 1420–1421. [Google Scholar] [CrossRef]
Tirnaz, S.; Bayer, P.; Inturrisi, F.; Neik, T.; Yang, H.; Dolatabadian, A.; Zhang, F.; Severn-Ellis, A.; Patel, D.; Pradhan, A.; et al. Resistance gene analogs in the Brassicaceae: Identification, Characterization, Distribution, and Evolution. Plant Physiol. 2020, 184, 909–922. [Google Scholar] [CrossRef] [PubMed]
Bayer, P.E.; Golicz, A.A.; Tirnaz, S.; Chan, C.K.; Edwards, D.; Batley, J. Variation in abundance of predicted resistance genes in the Brassica oleracea pangenome. Plant Biotechnol. J. 2019, 17, 789–800. [Google Scholar] [CrossRef] [PubMed]
Crisp, P.; Crute, I.R.; Sutherland, R.A.; Angell, S.M.; Bloor, K.; Burgess, H.; Gordon, P.L. The exploitation of genetic resources of Brassica oleracea in breeding for resistance to clubroot (Plasmodiophora brassicae). Euphytica 1989, 42, 215–226. [Google Scholar] [CrossRef]
Manzanares-Dauleux, M.J.; Divaret, I.; Baron, F.; Thomas, G. Evaluation of French Brassica oleracea landraces for resistance to Plasmodiophora brassicae. Euphytica 2000, 113, 211–218. [Google Scholar] [CrossRef]
KoPecKý, P.; Doležalová, I.; Duchoslav, M.; DušeK, K. Variability in resistance to clubroot in European cauliflower cultivars. Plant Prot. Sci. 2012, 48, 156–161. [Google Scholar] [CrossRef]
Heinrich, A.; Kawai, S.; Myers, J. Screening Brassica cultivars for resistance to western Oregon clubroot pathotypes. Hort Technol. 2017, 27, 510–516. [Google Scholar] [CrossRef]
Voorrips, R.E.; Visser, D.L. Examination of resistance to clubroot in accessions of Brassica oleracea using a glasshouse seedling test. Neth. J. Plant Pathol. 1993, 99, 269–276. [Google Scholar] [CrossRef]
Dias, J.S.; Ferreira, M.E.; Williams, P.H. Screening of Portuguese cole landraces (Brassica oleracea L.) with Peronospora parasitica and Plasmodiophora brassicae. Euphytica 1993, 67, 135–141. [Google Scholar] [CrossRef]
Carlsson, M.; Bothmer, R.V.; Merker, A. Screening and evaluation of resistance to downy mildew (Peronospora parasitica) and clubroot (Plasmodiophora brassicae) in genetic resources of Brassica oleracea. Hereditas 2004, 141, 293–300. [Google Scholar] [CrossRef] [PubMed]
Jakir Hasan, M.; Strelkov, S.E.; Howard, R.J.; Rahman, H. Screening of Brassica germplasm for resistance to Plasmodiophora brassicae pathotypes prevalent in Canada for broadening diversity in clubroot resistance. Can. J. Plant Sci. 2012, 92, 501–515. [Google Scholar] [CrossRef]
Nieuwhof, M.; Wiering, D. Clubroot resistance in Brassica oleracea L. Euphytica 1962, 11, 233–239. [Google Scholar] [CrossRef]
Ramzi, N.; Kaczmarek, J.; Jędryczka, M. Identification of clubroot resistance sources from world gene bank accessions. In Proceedings of the IOBC-WPRS Bulletin, Integrated Control in Oilseed Crops, Zagreb, Croatia, 18–20 September 2018; Volume 136, pp. 144–147. [Google Scholar]
Fredua-Agyeman, R.; Hwang, S.-F.; Strelkov, S.E.; Zhou, Q.; Manolii, V.P.; Feindel, D. Identification of Brassica accessions resistant to ‘old’and ‘new’pathotypes of Plasmodiophora brassicae from Canada. Plant Pathol. 2019, 68, 708–718. [Google Scholar] [CrossRef]
Farid, M.; Yang, R.-C.; Kebede, B.; Rahman, H. Evaluation of Brassica oleracea accessions for resistance to Plasmodiophora brassicae and identification of genomic regions associated with resistance. Genome 2020, 63, 91–101. [Google Scholar] [CrossRef]
Walker, J.C.; Larson, R.H. Progress in the development of clubroot-resistant cabbage. Phytopathology 1951, 41, 37. [Google Scholar]
Chiang, M.S.; Crête, R. Inheritance of clubroot resistance in cabbage (Brassica oleracea L. var. capitata L.). Can. J. Genet. Cytol. 1970, 12, 253–256. [Google Scholar] [CrossRef]
Vriesenga, J.D.; Honma, S. Inheritance of seedling resistance to clubroot in Brassica oleracea L. HortScience 1971, 6, 395–396. [Google Scholar]
Chiang, M.S.; Crête, R. Diallel analysis of the inheritance of resistance to race 6 of Plasmodiophora brassicae in cabbage. Can. J. Plant Sci. 1976, 56, 865–868. [Google Scholar] [CrossRef]
Yoshikawa, H. Breeding for clubroot resistance of crucifer crops in Japan. JARQ 1983, 17, 6–11. [Google Scholar]
Crute, I.R.; Pink, D.A.C. The characteristics and inheritance of resistance to clubroot in Brassica oleracea. Aspects Appl. Biol. 1989, 23, 57–60. [Google Scholar]
Hansen, M. Genetic variation and inheritance of tolerance to clubroot (Plasmodiophora brassicae Wor.) and other quantitative characters in cabbage (Brassica oleracea L.). Hereditas 1989, 110, 13–22. [Google Scholar] [CrossRef]
Laurens, F.; Thomas, G. Inheritance of resistance to clubroot (Plasmodiophora brassicae Wor.) in kale (Brassica oleracea ssp. acephala). Hereditas 1993, 119, 253–262. [Google Scholar] [CrossRef]
Grandclement, C.; Laurens, F.; Thomas, G. Genetic analysis of resistance to clubroot (Plasmodiophora brassicae Woron) in two Brassica oleracea groups (ssp. acephala and ssp. botrytis) through diallel analysis. Plant Breed. 1996, 115, 152–156. [Google Scholar] [CrossRef]
Voorrips, R.E.; Kanne, H.J. Genetic analysis of resistance to clubroot (Plasmodiophora brassicae) in Brassica oleracea. I. Analysis of symptom grades. Euphytica 1997, 93, 31–39. [Google Scholar] [CrossRef]
Voorrips, R.E.; Kanne, H.J. Genetic analysis of resistance to clubroot (Plasmodiophora brassicae) in Brassica oleracea. II. Quantitative analysis of root symptom measurements. Euphytica 1997, 93, 41–48. [Google Scholar] [CrossRef]
Diederichsen, E.; Frauen, M.; Linders, E.G.A.; Hatakeyama, K.; Hirai, M. Status and perspectives of clubroot resistance breeding in Crucifer crops. J. Plant Growth Regul. 2009, 28, 265–281. [Google Scholar] [CrossRef]
Rocherieux, J.; Glory, P.; Giboulot, A.; Boury, S.; Barbeyron, G.; Thomas, G.; Manzanares-Dauleux, M.J. Isolate-specific and broad-spectrum QTLs are involved in the control of clubroot in Brassica oleracea. Theor. Appl. Genet. 2004, 108, 1555–1563. [Google Scholar] [CrossRef]
Tomita, H.; Shimizu, M.; Asad-ud Doullah, M.; Fujimoto, R.; Okazaki, K. Accumulation of quantitative trait loci conferring broad-spectrum clubroot resistance in Brassica oleracea. Mol. Breed. 2013, 32, 889–900. [Google Scholar] [CrossRef]
Peng, L.; Zhou, L.; Li, Q.; Wei, D.; Ren, X.; Song, H.; Mei, J.; Si, J.; Qian, W. Identification of quantitative trait loci for clubroot resistance in Brassica oleracea with the use of Brassica SNP microarray. Front. Plant Sci. 2018, 9, 822. [Google Scholar] [CrossRef] [PubMed]
Nomura, K.; Minegishi, Y.; Kimizuka-Takagi, C.; Fujioka, T.; Moriguchi, K.; Shishido, R.; Ikehashi, H. Evaluation of F2 and F3 plants introgressed with QTLs for clubroot resistance in cabbage developed by using SCAR markers. Plant Breed. 2005, 124, 371–375. [Google Scholar] [CrossRef]
Michelmore, R.W. Isolation of disease resistance genes from crop plants. Curr. Opin. Biotechnol. 1995, 6, 145–152. [Google Scholar] [CrossRef]
Landry, B.S.; Hubert, N.; Crete, R.; Chang, M.S.; Lincoln, S.E.; Etoh, T. A genetic map for Brassica oleracea based on RFLP markers detected with expressed DNA sequences and mapping of resistance genes to race 2 of Plasmodiophora brassicae (Woronin). Genome 1992, 35, 409–420. [Google Scholar] [CrossRef]
Figdore, S.S.; Ferreira, M.E.; Slocum, M.K.; Williams, P.H. Association of RFLP markers with trait loci affecting clubroot resistance and morphological characters in Brassica oleracea L. Euphytica 1993, 69, 33–44. [Google Scholar] [CrossRef]
Voorrips, R.E.; Jongerius, M.C.; Kanne, H.J. Mapping of two genes for resistance to clubroot (Plasmodiophora brassicae) in a population of doubled haploid lines of Brassica oleracea by means of RFLP and AFLP markers. Theor. Appl. Genet. 1997, 94, 75–82. [Google Scholar] [CrossRef]
Malmberg, M.M.; Shi, F.; Spangenberg, G.C.; Daetwyler, H.D.; Cogan, N.O.I. Diversity and genome analysis of Australian and global oilseed Brassica napus L. germplasm using transcriptomics and whole genome re-sequencing. Front. Plant Sci. 2018, 9, 508. [Google Scholar] [CrossRef]
Qu, C.; Jia, L.; Fu, F.; Zhao, H.; Lu, K.; Wei, L.; Xu, X.; Liang, Y.; Li, S.; Wang, R.; et al. Genome-wide association mapping and identification of candidate genes for fatty acid composition in Brassica napus L. using SNP markers. BMC Genom. 2017, 18, 232. [Google Scholar] [CrossRef]
Clarke, W.E.; Higgins, E.E.; Plieske, J.; Wieseke, R.; Sidebottom, C.; Khedikar, Y.; Batley, J.; Edwards, D.; Meng, J.; Li, R.; et al. A high-density SNP genotyping array for Brassica napus and its ancestral diploid species based on optimised selection of single-locus markers in the allotetraploid genome. Theor. Appl. Genet. 2016, 129, 1887–1899. [Google Scholar] [CrossRef]
Lee, J.; Izzah, N.K.; Choi, B.-S.; Joh, H.J.; Lee, S.-C.; Perumal, S.; Seo, J.; Ahn, K.; Jo, E.J.; Choi, G.J.; et al. Genotyping-by-sequencing map permits identification of clubroot resistance QTLs and revision of the reference genome assembly in cabbage (Brassica oleracea L.). DNA Res. 2016, 23, 29–41. [Google Scholar] [CrossRef]
Mammadov, J.; Aggarwal, R.; Buyyarapu, R.; Kumpatla, S. SNP markers and their impact on plant breeding. Int. J. Plant Genom. 2012, 2012, 728398. [Google Scholar] [CrossRef] [PubMed]
Afzal, M.; Alghamdi, S.S.; Rahman, M.H.U.; Ahmad, A.; Farooq, T.; Alam, M.; Khan, I.A.; Ullah, H.; Nasim, W.; Fahad, S. Current status and future possibilities of molecular genetics techniques in Brassica napus. Biotechnol. Lett. 2018, 40, 479–492. [Google Scholar] [CrossRef] [PubMed]
Moriguchi, K.; Kimizuka-Takagi, C.; Ishii, K.; Nomura, K. A Genetic map based on RAPD, RFLP, isozyme, morphological markers and QTL analysis for clubroot resistance in Brassica oleracea. Breed. Sci. 1999, 49, 257–265. [Google Scholar] [CrossRef]
Nagaoka, T.; Doullah, M.A.; Matsumoto, S.; Kawasaki, S.; Ishikawa, T.; Hori, H.; Okazaki, K. Identification of QTLs that control clubroot resistance in Brassica oleracea and comparative analysis of clubroot resistance genes between B. rapa and B. oleracea. Theor. Appl. Genet. 2010, 120, 1335–1346. [Google Scholar] [CrossRef]
Dangl, J.L.; Jones, J.D. Plant pathogens and integrated defence responses to infection. Nature 2001, 411, 826–833. [Google Scholar] [CrossRef]
McHale, L.; Tan, X.; Koehl, P.; Michelmore, R.W. Plant NBS-LRR proteins: Adaptable guards. Genome Biol. 2006, 7, 212. [Google Scholar] [CrossRef]
Glazebrook, J. Contrasting mechanisms of defense against biotrophic and necrotrophic pathogens. Annu. Rev. Phytopathol. 2005, 43, 205–227. [Google Scholar] [CrossRef]
Bent, A.F.; Mackey, D. Elicitors, effectors, and R genes: The new paradigm and a lifetime supply of questions. Annu. Rev. Phytopathol. 2007, 45, 399–436. [Google Scholar] [CrossRef]
Saito, M.; Kubo, N.; Matsumoto, S.; Suwabe, K.; Tsukada, M.; Hirai, M. Fine mapping of the clubroot resistance gene, Crr3, in Brassica rapa. Theor. Appl. Genet. 2006, 114, 81–91. [Google Scholar] [CrossRef]
Kato, T.; Hatakeyama, K.; Fukino, N.; Matsumoto, S. Fine mapping of the clubroot resistance gene CRb and development of a useful selectable marker in Brassica rapa. Breed Sci. 2013, 63, 116–124. [Google Scholar] [CrossRef] [PubMed]
Piao, Z.Y.; Deng, Y.Q.; Choi, S.R.; Park, Y.J.; Lim, Y.P. SCAR and CAPS mapping of CRb, a gene conferring resistance to Plasmodiophora brassicae in Chinese cabbage (Brassica rapa ssp. pekinensis). Theor. Appl. Genet. 2004, 108, 1458–1465. [Google Scholar] [CrossRef] [PubMed]
Zhang, T.; Zhao, Z.; Zhang, C.; Pang, W.; Choi, S.R.; Lim, Y.P.; Piao, Z. Fine genetic and physical mapping of the CRb gene conferring resistance to clubroot disease in Brassica rapa. Mol. Breed. 2014, 34, 1173–1183. [Google Scholar] [CrossRef]
Chu, M.; Song, T.; Falk, K.C.; Zhang, X.; Liu, X.; Chang, A.; Lahlali, R.; McGregor, L.; Gossen, B.D.; Yu, F.; et al. Fine mapping of Rcr1 and analyses of its effect on transcriptome patterns during infection by Plasmodiophora brassicae. BMC Genom. 2014, 15, 1166. [Google Scholar] [CrossRef]
Gao, F.; Hirani, A.H.; Liu, J.; Liu, Z.; Fu, G.; Wu, C.; McVetty, P.B.E.; Li, G. Fine mapping a clubroot resistance locus in Chinese cabbage. J. Am. Soc. Hort. Sci. 2014, 139, 247–252. [Google Scholar] [CrossRef]
Zhan, Z.; Jiang, Y.; Shah, N.; Hou, Z.; Zhou, Y.; Dun, B.; Li, S.; Zhu, L.; Li, Z.; Piao, Z.; et al. Association of clubroot resistance locus PbBa8.1 with a linkage drag of high erucic acid content in the seed of the European turnip. Front. Plant Sci. 2020, 11, 810. [Google Scholar] [CrossRef]
Wang, Y.; Xiang, X.; Huang, F.; Yu, W.; Zhou, X.; Li, B.; Zhang, Y.; Chen, P.; Zhang, C. Fine mapping of clubroot resistance loci CRA8.1 and candidate gene analysis in Chinese cabbage (Brassica rapa L.). Front. Plant Sci. 2022, 13, 898108. [Google Scholar] [CrossRef]
Yang, Z.; Jiang, Y.; Gong, J.; Li, Q.; Dun, B.; Liu, D.; Yin, F.; Yuan, L.; Zhou, X.; Wang, H.; et al. R gene triplication confers European fodder turnip with improved clubroot resistance. Plant Biotechnol. J. 2022, 20, 1502–1517. [Google Scholar] [CrossRef]
Yu, F.; Zhang, X.; Huang, Z.; Chu, M.; Song, T.; Falk, K.C.; Deora, A.; Chen, Q.; Zhang, Y.; McGregor, L.; et al. Identification of genome-wide variants and discovery of variants associated with Brassica rapa clubroot resistance gene Rcr1 through bulked segregant RNA sequencing. PLoS ONE 2016, 11, e0153218. [Google Scholar] [CrossRef]
Huang, Z.; Peng, G.; Liu, X.; Deora, A.; Falk, K.C.; Gossen, B.D.; McDonald, M.R.; Yu, F. Fine mapping of a clubroot resistance gene in Chinese cabbage using SNP markers identified from bulked segregant RNA sequencing. Front. Plant Sci. 2017, 8, 1448. [Google Scholar] [CrossRef]
Dakouri, A.; Zhang, X.; Peng, G.; Falk, K.C.; Gossen, B.D.; Strelkov, S.E.; Yu, F. Analysis of genome-wide variants through bulked segregant RNA sequencing reveals a major gene for resistance to Plasmodiophora brassicae in Brassica oleracea. Sci. Rep. 2018, 8, 17657. [Google Scholar] [CrossRef] [PubMed]
Chang, A.; Lamara, M.; Wei, Y.; Hu, H.; Parkin, I.A.P.; Gossen, B.D.; Peng, G.; Yu, F. Clubroot resistance gene Rcr6 in Brassica nigra resides in a genomic region homologous to chromosome A08 in B. rapa. BMC Plant Biol. 2019, 19, 224. [Google Scholar] [CrossRef] [PubMed]
Huang, Z.; Peng, G.; Gossen, B.D.; Yu, F. Fine mapping of a clubroot resistance gene from turnip using SNP markers identified from bulked segregant RNA-Seq. Mol. Breed. 2019, 39, 131. [Google Scholar] [CrossRef]
Karim, M.M.; Dakouri, A.; Zhang, Y.; Chen, Q.; Peng, G.; Strelkov, S.E.; Gossen, B.D.; Yu, F. Two clubroot-resistance genes, Rcr3 and Rcr9(wa), mapped in Brassica rapa using bulk segregant RNA sequencing. Int. J. Mol. Sci. 2020, 21, 5033. [Google Scholar] [CrossRef]
Ce, F.; Mei, J.; He, H.; Zhao, Y.; Hu, W.; Yu, F.; Li, Q.; Ren, X.; Si, J.; Song, H.; et al. Identification of candidate genes for clubroot-resistance in Brassica oleracea using quantitative trait loci-sequencing. Front. Plant Sci. 2021, 12, 703520. [Google Scholar] [CrossRef]
Yu, F.; Zhang, X.; Peng, G.; Falk, K.C.; Strelkov, S.E.; Gossen, B.D. Genotyping-by-sequencing reveals three QTL for clubroot resistance to six pathotypes of Plasmodiophora brassicae in Brassica rapa. Sci. Rep. 2017, 7, 4516. [Google Scholar] [CrossRef] [PubMed]
Pang, W.; Fu, P.; Li, X.; Zhan, Z.; Yu, S.; Piao, Z. Identification and mapping of the clubroot resistance gene CRd in Chinese cabbage (Brassica rapa ssp. pekinensis). Front. Plant Sci. 2018, 9, 653. [Google Scholar] [CrossRef]
Laila, R.; Park, J.-I.; Robin, A.H.K.; Natarajan, S.; Vijayakumar, H.; Shirasawa, K.; Isobe, S.; Kim, H.-T.; Nou, I.-S. Mapping of a novel clubroot resistance QTL using ddRAD-seq in Chinese cabbage (Brassica rapa L.). BMC Plant Biol. 2019, 19, 13. [Google Scholar] [CrossRef]
Choi, S.R.; Oh, S.H.; Chhapekar, S.S.; Dhandapani, V.; Lee, C.Y.; Rameneni, J.J.; Ma, Y.; Choi, G.J.; Lee, S.-S.; Lim, Y.P. Quantitative trait locus mapping of clubroot resistance and Plasmodiophora brassicae pathotype Banglim-specific marker development in Brassica rapa. Int. J. Mol. Sci. 2020, 21, 4157. [Google Scholar] [CrossRef]
Hasan, M.J.; Shaikh, R.; Basu, U.; Rahman, H. Mapping clubroot resistance of Brassica rapa introgressed into Brassica napus and development of molecular markers for the resistance. Crop Sci. 2021, 61, 4112–4127. [Google Scholar] [CrossRef]
Kopec, P.M.; Mikolajczyk, K.; Jajor, E.; Perek, A.; Nowakowska, J.; Obermeier, C.; Chawla, H.S.; Korbas, M.; Bartkowiak-Broda, I.; Karlowski, W.M. Local duplication of TIR-NBS-LRR gene marks clubroot resistance in Brassica napus cv. Tosca. Front. Plant Sci. 2021, 12, 639631. [Google Scholar] [CrossRef] [PubMed]
Yu, F.; Zhang, Y.; Wang, J.; Chen, Q.; Karim, M.M.; Gossen, B.D.; Peng, G. Identification of two major QTLs in Brassica napus lines with introgressed clubroot resistance from turnip cultivar ECD01. Front. Plant Sci. 2022, 12, 785989. [Google Scholar] [CrossRef] [PubMed]
Collier, S.M.; Moffett, P. NB-LRRs work a "bait and switch" on pathogens. Trends Plant Sci. 2009, 14, 521–529. [Google Scholar] [CrossRef] [PubMed]
Swiderski, M.R.; Birker, D.; Jones, J.D. The TIR domain of TIR-NB-LRR resistance proteins is a signaling domain involved in cell death induction. Mol. Plant Microbe. Interact. 2009, 22, 157–165. [Google Scholar] [CrossRef] [PubMed]
Hatakeyama, K.; Suwabe, K.; Tomita, R.N.; Kato, T.; Nunome, T.; Fukuoka, H.; Matsumoto, S. Identification and characterization of Crr1a, a gene for resistance to clubroot disease (Plasmodiophora brassicae Woronin) in Brassica rapa L. PLoS ONE 2013, 8, e54745. [Google Scholar] [CrossRef]
Ueno, H.; Matsumoto, E.; Aruga, D.; Kitagawa, S.; Matsumura, H.; Hayashida, N. Molecular characterization of the CRa gene conferring clubroot resistance in Brassica rapa. Plant Mol. Biol. 2012, 80, 621–629. [Google Scholar] [CrossRef]
Hatakeyama, K.; Niwa, T.; Kato, T.; Ohara, T.; Kakizaki, T.; Matsumoto, S. The tandem repeated organization of NB-LRR genes in the clubroot-resistant CRb locus in Brassica rapa L. Mol. Genet. Genom. 2017, 292, 397–405. [Google Scholar] [CrossRef]
Hatakeyama, K.; Yuzawa, S.; Tonosaki, K.; Takahata, Y.; Matsumoto, S. Allelic variation of a clubroot resistance gene (Crr1a) in Japanese cultivars of Chinese cabbage (Brassica rapa L.). Breed. Sci. 2022, 72, 115–123. [Google Scholar] [CrossRef]
Piao, Z.; Ramchiary, N.; Lim, Y.P. Genetics of clubroot resistance in Brassica Species. J. Plant Growth Regul. 2009, 28, 252–264. [Google Scholar] [CrossRef]
Mundt, C. Probability of mutation to multiple virulence and durability of resistance gene pyramids. Phytopathology 1990, 80, 221–223. [Google Scholar] [CrossRef]
Pilet-Nayel, M.L.; Moury, B.; Caffier, V.; Montarry, J.; Kerlan, M.C.; Fournet, S.; Durel, C.E.; Delourme, R. Quantitative resistance to plant pathogens in pyramiding strategies for durable crop protection. Front. Plant Sci. 2017, 8, 1838. [Google Scholar] [CrossRef] [PubMed]
Matsumoto, E.; Ueno, H.; Aruga, D.; Sakamoto, K.; Hayashida, N. Accumulation of three clubroot resistance genes through marker-assisted selection in Chinese cabbage (Brassica rapa ssp. pekinensis). J. Jpn. Soc. Hortic. Sci. 2012, 81, 184–190. [Google Scholar] [CrossRef]
Shah, N.; Sun, J.; Yu, S.; Yang, Z.; Wang, Z.; Huang, F.; Dun, B.; Gong, J.; Liu, Y.; Li, Y.; et al. Genetic variation analysis of field isolates of clubroot and their responses to Brassica napus lines containing resistant genes CRb and PbBa8.1 and their combination in homozygous and heterozygous state. Mol. Breed. 2019, 39, 153. [Google Scholar] [CrossRef]
Diederichsen, E.; Frauen, M.; Ludwig-Müller, J. Clubroot disease management challenges from a German perspective. Can. J. Plant Pathol. 2014, 36, 85–98. [Google Scholar] [CrossRef]
LeBoldus, J.M.; Manolii, V.P.; Turkington, T.K.; Strelkov, S.E. Adaptation to Brassica host genotypes by a single-spore isolate and population of Plasmodiophora brassicae (clubroot). Plant Dis. 2012, 96, 833–838. [Google Scholar] [CrossRef] [PubMed]
Lagercrantz, U.; Lydiate, D.J. Comparative genome mapping in Brassica. Genetics 1996, 144, 1903–1910. [Google Scholar] [CrossRef]
Lysak, M.A.; Koch, M.A.; Pecinka, A.; Schubert, I. Chromosome triplication found across the tribe Brassiceae. Genome Res. 2005, 15, 516–525. [Google Scholar] [CrossRef]
Lysak, M.A.; Cheung, K.; Kitschke, M.; Bures, P. Ancestral chromosomal blocks are triplicated in Brassiceae species with varying chromosome number and genome size. Plant Physiol. 2007, 145, 402–410. [Google Scholar] [CrossRef]
Cheng, F.; Mandáková, T.; Wu, J.; Xie, Q.; Lysak, M.A.; Wang, X. Deciphering the diploid ancestral genome of the Mesohexaploid Brassica rapa. Plant Cell 2013, 25, 1541–1554. [Google Scholar] [CrossRef]
Blanc, G.; Barakat, A.; Guyot, R.; Cooke, R.; Delseny, M. Extensive duplication and reshuffling in the Arabidopsis genome. Plant Cell 2000, 12, 1093–1101. [Google Scholar] [CrossRef]
Vision Todd, J.; Brown Daniel, G.; Tanksley Steven, D. The Origins of genomic duplications in Arabidopsis. Science 2000, 290, 2114–2117. [Google Scholar] [CrossRef] [PubMed]
Cavell, A.C.; Lydiate, D.J.; Parkin, I.A.P.; Dean, C.; Trick, M. Collinearity between a 30-centimorgan segment of Arabidopsis thaliana chromosome 4 and duplicated regions within the Brassica napus genome. Genome 1998, 41, 62–69. [Google Scholar] [CrossRef] [PubMed]
Lagercrantz, U. Comparative mapping between Arabidopsis thaliana and Brassica nigra indicates that Brassica genomes have evolved through extensive genome replication accompanied by chromosome fusions and frequent rearrangements. Genetics 1998, 150, 1217–1228. [Google Scholar] [CrossRef] [PubMed]
O’Neill, C.M.; Bancroft, I. Comparative physical mapping of segments of the genome of Brassica oleracea var. alboglabra that are homoeologous to sequenced regions of chromosomes 4 and 5 of Arabidopsis thaliana. Plant J. 2000, 23, 233–243. [Google Scholar] [CrossRef]
Ryder, C.D.; Smith, L.B.; Teakle, G.R.; King, G.J. Contrasting genome organisation: Two regions of the Brassica oleracea genome compared with collinear regions of the Arabidopsis thaliana genome. Genome 2001, 44, 808–817. [Google Scholar] [CrossRef]
Rana, D.; Boogaart, T.V.D.; O’Neill, C.M.; Hynes, L.; Bent, E.; Macpherson, L.; Park, J.Y.; Lim, Y.P.; Bancroft, I. Conservation of the microstructure of genome segments in Brassica napus and its diploid relatives. Plant J. 2004, 40, 725–733. [Google Scholar] [CrossRef]
Chalhoub, B.; Denoeud, F.; Liu, S.; Parkin, I.A.P.; Tang, H.; Wang, X.; Chiquet, J.; Belcram, H.; Tong, C.; Samans, B.; et al. Early allopolyploid evolution in the post-Neolithic Brassica napus oilseed genome. Science 2014, 345, 950–953. [Google Scholar] [CrossRef]
Schranz, M.E.; Lysak, M.A.; Mitchell-Olds, T. The ABC’s of comparative genomics in the Brassicaceae: Building blocks of crucifer genomes. Trends Plant Sci. 2006, 11, 535–542. [Google Scholar] [CrossRef]
Matsumoto, E.; Yasui, C.; Ohi, M.; Tsukada, M. Linkage analysis of RFLP markers for clubroot resistance and pigmentation in Chinese cabbage (Brassica rapa ssp. pekinensis). Euphytica 1998, 104, 79–86. [Google Scholar] [CrossRef]
Suwabe, K.; Tsukazaki, H.; Iketani, H.; Hatakeyama, K.; Fujimura, M.; Nunome, T.; Fukuoka, H.; Matsumoto, S.; Hirai, M. Identification of two loci for resistance to clubroot (Plasmodiophora brassicae Woronin) in Brassica rapa L. Theor. Appl. Genet. 2003, 107, 997–1002. [Google Scholar] [CrossRef]
Suwabe, K.; Tsukazaki, H.; Iketani, H.; Hatakeyama, K.; Kondo, M.; Fujimura, M.; Nunome, T.; Fukuoka, H.; Hirai, M.; Matsumoto, S. Simple sequence repeat-based comparative genomics between Brassica rapa and Arabidopsis thaliana: The genetic origin of clubroot resistance. Genetics 2006, 173, 309–319. [Google Scholar] [CrossRef] [PubMed]
Sakamoto, K.; Saito, A.; Hayashida, N.; Taguchi, G.; Matsumoto, E. Matsumoto, E. Mapping of isolate-specific QTLs for clubroot resistance in Chinese cabbage (Brassica rapa L. ssp. pekinensis). Theor. Appl. Genet. 2008, 117, 759–767. [Google Scholar] [CrossRef] [PubMed]
The Brassica rapa Genome Sequencing Project Consortium; Wang, X.; Wang, H.; Wang, J.; Sun, R.; Wu, J.; Liu, S.; Bai, Y.; Mun, J.-H.; Bancroft, I.; et al. The genome of the mesopolyploid crop species Brassica rapa. Nat. Genet. 2011, 43, 1035–1039. [Google Scholar] [CrossRef] [PubMed]
Suwabe, K.; Suzuki, G.; Nunome, T.; Hatakeyama, K.; Mukai, Y.; Fukuoka, H.; Matsumoto, S. Microstructure of a Brassica rapa genome segment homoeologous to the resistance gene cluster on Arabidopsis chromosome 4. Breed Sci. 2012, 62, 170–177. [Google Scholar] [CrossRef] [PubMed]
Fredua-Agyeman, R.; Jiang, J.; Hwang, S.-F.; Strelkov, S.E. QTL Mapping and inheritance of clubroot resistance genes derived from Brassica rapa subsp. rapifera (ECD 02) reveals resistance loci and distorted segregation ratios in two F2 populations of different crosses. Front. Plant Sci. 2020, 11, 899. [Google Scholar] [CrossRef]
Werner, S.; Diederichsen, E.; Frauen, M.; Schondelmaier, J.; Jung, C. Genetic mapping of clubroot resistance genes in oilseed rape. Theor. Appl. Genet. 2008, 116, 363–372. [Google Scholar] [CrossRef]
Rahman, H.; Shakir, A.; Jakir Hasan, M. Breeding for clubroot resistant spring canola (Brassica napus L.) for the Canadian prairies: Can the European winter canola cv. Mendel be used as a source of resistance? Can. J. Plant Sci. 2011, 91, 447–458. [Google Scholar] [CrossRef]
Rahman, H.; Franke, C. Association of fusarium wilt susceptibility with clubroot resistance derived from winter Brassica napus L. ‘Mendel’. Can. J. Plant Pathol. 2019, 41, 60–64. [Google Scholar] [CrossRef]
Rodriguez-Moreno, L.; Song, Y.; Thomma, B.P. Transfer and engineering of immune receptors to improve recognition capacities in crops. Curr. Opin. Plant Biol. 2017, 38, 42–49. [Google Scholar] [CrossRef]
Gallusci, P.; Dai, Z.; Génard, M.; Gauffretau, A.; Leblanc-Fournier, N.; Richard-Molard, C.; Vile, D.; Brunel-Muguet, S. Epigenetics for plant improvement: Current knowledge and modeling avenues. Trends Plant Sci. 2017, 22, 610–623. [Google Scholar] [CrossRef]
Tirnaz, S.; Batley, J. Epigenetics: Potentials and challenges in crop breeding. Mol. Plant 2019, 12, 1309–1311. [Google Scholar] [CrossRef] [PubMed]
Varotto, S.; Tani, E.; Abraham, E.; Krugman, T.; Kapazoglou, A.; Melzer, R.; Radanović, A.; Miladinović, D. Epigenetics: Possible applications in climate-smart crop breeding. J. Exp. Bot. 2020, 71, 5223–5236. [Google Scholar] [CrossRef] [PubMed]
Zhi, P.; Chang, C. Exploiting epigenetic variations for crop disease resistance improvement. Front. Plant Sci. 2021, 12, 692328. [Google Scholar] [CrossRef] [PubMed]
Ramirez-Prado, J.S.; Abulfaraj, A.A.; Rayapuram, N.; Benhamed, M.; Hirt, H. Plant immunity: From signaling to epigenetic control of defense. Trends Plant Sci. 2018, 23, 833–844. [Google Scholar] [CrossRef]
Wang, C.; Wang, C.; Xu, W.; Zou, J.; Qiu, Y.; Kong, J.; Yang, Y.; Zhang, B.; Zhu, S. Epigenetic changes in the regulation of Nicotiana tabacum response to cucumber mosaic virus infection and symptom recovery through single-base resolution methylomes. Viruses 2018, 10, 402. [Google Scholar] [CrossRef]
Alonso, C.; Ramos-Cruz, D.; Becker, C. The role of plant epigenetics in biotic interactions. New Phytol. 2019, 221, 731–737. [Google Scholar] [CrossRef]
Henderson, I.R.; Jacobsen, S.E. Epigenetic inheritance in plants. Nature 2007, 447, 418–424. [Google Scholar] [CrossRef]
Tirnaz, S.; Batley, J. DNA methylation: Toward crop disease resistance improvement. Trends Plant Sci. 2019, 24, 1137–1150. [Google Scholar] [CrossRef]
Cokus, S.J.; Feng, S.; Zhang, X.; Chen, Z.; Merriman, B.; Haudenschild, C.D.; Pradhan, S.; Nelson, S.F.; Pellegrini, M.; Jacobsen, S.E. Shotgun bisulphite sequencing of the Arabidopsis genome reveals DNA methylation patterning. Nature 2008, 452, 215–219. [Google Scholar] [CrossRef]
Guevara, M.; de María, N.; Sáez-Laguna, E.; Vélez, M.D.; Cervera, M.T.; Cabezas, J.A. Analysis of DNA cytosine methylation patterns using methylation-sensitive amplification polymorphism (MSAP). Methods Mol. Biol. 2017, 1456, 99–112. [Google Scholar] [CrossRef]
Li, Q.; Hermanson, P.J.; Springer, N.M. Detection of DNA methylation by whole-genome bisulfite sequencing. Methods Mol. Biol. 2018, 1676, 185–196. [Google Scholar] [CrossRef] [PubMed]
Hsu, H.K.; Weng, Y.I.; Hsu, P.Y.; Huang, T.H.; Huang, Y.W. Detection of DNA methylation by MeDIP and MBDCap assays: An overview of techniques. Methods Mol. Biol. 2020, 2102, 225–234. [Google Scholar] [CrossRef] [PubMed]
Salmon, A.; Clotault, J.; Jenczewski, E.; Chable, V.; Manzanares-Dauleux, M.J. Brassica oleracea displays a high level of DNA methylation polymorphism. Plant Sci. 2008, 174, 61–70. [Google Scholar] [CrossRef]
Yu, A.; Lepère, G.; Jay, F.; Wang, J.; Bapaume, L.; Wang, Y.; Abraham, A.L.; Penterman, J.; Fischer, R.L.; Voinnet, O.; et al. Dynamics and biological relevance of DNA demethylation in Arabidopsis antibacterial defense. Proc. Natl. Acad. Sci. USA 2013, 110, 2389–2394. [Google Scholar] [CrossRef]
Tirnaz, S.; Merce, C.; Bayer, P.E.; Severn-Ellis, A.A.; Edwards, D.; Batley, J. Effect of Leptosphaeria maculans infection on promoter DNA methylation of defence genes in Brassica napus. Agronomy 2020, 10, 1072. [Google Scholar] [CrossRef]
Tirnaz, S.; Miyaji, N.; Takuno, S.; Bayer, P.E.; Shimizu, M.; Akter, M.A.; Edwards, D.; Batley, J.; Fujimoto, R. Whole-genome DNA methylation analysis in Brassica rapa subsp. perviridis in response to Albugo candida infection. Front. Plant Sci. 2022, 13, 849358. [Google Scholar] [CrossRef]
Liégard, B.; Baillet, V.; Etcheverry, M.; Joseph, E.; Lariagon, C.; Lemoine, J.; Evrard, A.; Colot, V.; Gravot, A.; Manzanares-Dauleux, M.J.; et al. Quantitative resistance to clubroot infection mediated by transgenerational epigenetic variation in Arabidopsis. New Phytol. 2019, 222, 468–479. [Google Scholar] [CrossRef]
Wang, C.; Wang, C.; Zou, J.; Yang, Y.; Li, Z.; Zhu, S. Epigenetics in the plant-virus interaction. Plant Cell Rep. 2019, 38, 1031–1038. [Google Scholar] [CrossRef]
Li, B.; Carey, M.; Workman, J.L. The role of chromatin during transcription. Cell 2007, 128, 707–719. [Google Scholar] [CrossRef]
Yang, X.; Lu, Y.; Zhao, X.; Jiang, L.; Xu, S.; Peng, J.; Zheng, H.; Lin, L.; Wu, Y.; MacFarlane, S.; et al. Downregulation of nuclear protein H2B induces salicylic acid mediated defense against PVX infection in Nicotiana benthamiana. Front. Microbiol. 2019, 10, 1000. [Google Scholar] [CrossRef]
Mozgová, I.; Wildhaber, T.; Liu, Q.; Abou-Mansour, E.; L’Haridon, F.; Métraux, J.P.; Gruissem, W.; Hofius, D.; Hennig, L. Chromatin assembly factor CAF-1 represses priming of plant defence response genes. Nat. Plants 2015, 1, 15127. [Google Scholar] [CrossRef] [PubMed]
Muñoz-Viana, R.; Wildhaber, T.; Trejo-Arellano, M.S.; Mozgová, I.; Hennig, L. Arabidopsis chromatin assembly factor 1 is required for occupancy and position of a subset of nucleosomes. Plant J. 2017, 92, 363–374. [Google Scholar] [CrossRef] [PubMed]
Long, Y.; Xia, W.; Li, R.; Wang, J.; Shao, M.; Feng, J.; King, G.J.; Meng, J. Epigenetic QTL mapping in Brassica napus. Genetics 2011, 189, 1093–1102. [Google Scholar] [CrossRef] [PubMed]
Siemens, J.; Keller, I.; Sarx, J.; Kunz, S.; Schuller, A.; Nagel, W.; Schmülling, T.; Parniske, M.; Ludwig-Müller, J. Transcriptome analysis of Arabidopsis clubroots indicate a key role for cytokinins in disease development. Mol. Plant Microbe. Interact. 2006, 19, 480–494. [Google Scholar] [CrossRef]
Malinowski, R.; Novák, O.; Borhan, M.H.; Spíchal, L.; Strnad, M.; Rolfe, S.A. The role of cytokinins in clubroot disease. Eur. J. Plant Pathol. 2016, 145, 543–557. [Google Scholar] [CrossRef]
Prerostova, S.; Dobrev, P.I.; Konradyova, V.; Knirsch, V.; Gaudinova, A.; Kramna, B.; Kazda, J.; Ludwig-Müller, J.; Vankova, R. Hormonal responses to Plasmodiophora brassicae infection in Brassica napus cultivars differing in their pathogen resistance. Int. J. Mol. Sci. 2018, 19, 4024. [Google Scholar] [CrossRef]
Jubault, M.; Hamon, C.; Gravot, A.; Lariagon, C.; Delourme, R.; Bouchereau, A.; Manzanares-Dauleux, M.J. Differential regulation of root arginine catabolism and polyamine metabolism in clubroot-susceptible and partially resistant Arabidopsis genotypes. Plant Physiol. 2008, 146, 2008–2019. [Google Scholar] [CrossRef]
Zhang, X.; Liu, Y.; Fang, Z.; Li, Z.; Yang, L.; Zhuang, M.; Zhang, Y.; Lv, H. Comparative transcriptome analysis between Broccoli (Brassica oleracea var. italica) and wild cabbage (Brassica macrocarpa Guss.) in response to Plasmodiophora brassicae during different infection stages. Front. Plant Sci. 2016, 7, 1929. [Google Scholar] [CrossRef]
Wang, S.; Yu, F.; Zhang, W.; Tang, J.; Li, J.; Yu, L.; Wang, H.; Jiang, J. Comparative transcriptomic analysis reveals gene expression changes during early stages of Plasmodiophora brassicae infection in cabbage (Brassica oleracea var. capitata L.). Can. J. Plant Pathol. 2019, 41, 188–199. [Google Scholar] [CrossRef]
Chen, J.; Pang, W.; Chen, B.; Zhang, C.; Piao, Z. Transcriptome analysis of Brassica rapa near-isogenic lines carrying clubroot-resistant and -susceptible alleles in response to Plasmodiophora brassicae during early infection. Front. Plant Sci. 2016, 6, 1183. [Google Scholar] [CrossRef]
Ludwig-Müller, J.; Schuller, A. What can we learn from clubroots: Alterations in host roots and hormone homeostasis caused by Plasmodiophora brassicae. Eur. J. Plant Pathol. 2008, 121, 291–302. [Google Scholar] [CrossRef]
Ludwig-Müller, J.; Auer, S.; Jülke, S.; Marschollek, S. Manipulation of Auxin and Cytokinin Balance During the Plasmodiophora brassicae–Arabidopsis thaliana Interaction. In Auxins and Cytokinins in Plant Biology; Dandekar, T., Naseem, M., Eds.; Humana Press: New York, NY, USA, 2017; Volume 1569, pp. 41–60. [Google Scholar] [CrossRef]
Jia, H.; Wei, X.; Yang, Y.; Yuan, Y.; Wei, F.; Zhao, Y.; Yang, S.; Yao, Q.; Wang, Z.; Tian, B.; et al. Root RNA-seq analysis reveals a distinct transcriptome landscape between clubroot-susceptible and clubroot-resistant Chinese cabbage lines after Plasmodiophora brassicae infection. Plant Soil 2017, 421, 1–13. [Google Scholar] [CrossRef]
Ciaghi, S.; Schwelm, A.; Neuhauser, S. Transcriptomic response in symptomless roots of clubroot infected kohlrabi (Brassica oleracea var. gongylodes) mirrors resistant plants. BMC Plant Biol. 2019, 19, 288. [Google Scholar] [CrossRef]
Schuller, A.; Kehr, J.; Ludwig-Müller, J. Laser Microdissection coupled to transcriptional profiling of Arabidopsis roots inoculated by Plasmodiophora brassicae indicates a role for Brassinosteroids in clubroot formation. Plant Cell Physiol. 2014, 55, 392–411. [Google Scholar] [CrossRef] [PubMed]
Mei, J.; Guo, Z.; Wang, J.; Feng, Y.; Ma, G.; Zhang, C.; Qian, W.; Chen, G. Understanding the resistance mechanism in Brassica napus to clubroot caused by Plasmodiophora brassicae. Phytopathology 2019, 109, 810–818. [Google Scholar] [CrossRef] [PubMed]
Xu, L.; Ren, L.; Chen, K.; Liu, F.; Fang, X. Putative role of IAA during the early response of Brassica napus L. to Plasmodiophora brassicae. Eur. J. Plant Pathol. 2016, 145, 601–613. [Google Scholar] [CrossRef]
Neuhaus, K.; Grsic-Rausch, S.; Sauerteig, S.; Ludwig-Müller, J. Arabidopsis plants transformed with nitrilase 1 or 2 in antisense direction are delayed in clubroot development. J. Plant Physiol. 2000, 156, 756–761. [Google Scholar] [CrossRef]
Grsic-Rausch, S.; Kobelt, P.; Siemens, J.M.; Bischoff, M.; Ludwig-Müller, J. Expression and localization of nitrilase during symptom development of the clubroot disease in Arabidopsis. Plant Physiol. 2000, 122, 369–378. [Google Scholar] [CrossRef] [PubMed]
Zhao, Y.; Bi, K.; Gao, Z.; Chen, T.; Liu, H.; Xie, J.; Cheng, J.; Fu, Y.; Jiang, D. Transcriptome analysis of Arabidopsis thaliana in response to Plasmodiophora brassicae during early infection. Front. Microbiol. 2017, 8, 673. [Google Scholar] [CrossRef]
Ludwig-Müller, J. Auxin homeostasis, signaling, and interaction with other growth hormones during the clubroot disease of Brassicaceae. Plant Signal. Behav. 2014, 9, e28593. [Google Scholar] [CrossRef]
Kant, S.; Bi, Y.M.; Zhu, T.; Rothstein, S.J. SAUR39, a small auxin-up RNA gene, acts as a negative regulator of auxin synthesis and transport in rice. Plant Physiol. 2009, 151, 691–701. [Google Scholar] [CrossRef] [PubMed]
Ning, Y.; Wang, Y.; Fang, Z.; Zhuang, M.; Zhang, Y.; Lv, H.; Liu, Y.; Li, Z.; Yang, L. Comparative transcriptome analysis of cabbage (Brassica oleracea var. capitata) infected by Plasmodiophora brassicae reveals drastic defense response at secondary infection stage. Plant Soil 2019, 443, 167–183. [Google Scholar] [CrossRef]
Cao, T.; Srivastava, S.; Rahman, M.H.; Kav, N.N.V.; Hotte, N.; Deyholos, M.K.; Strelkov, S.E. Proteome-level changes in the roots of Brassica napus as a result of Plasmodiophora brassicae infection. Plant Sci. 2008, 174, 97–115. [Google Scholar] [CrossRef]
Devos, S.; Laukens, K.; Deckers, P.; Van Der Straeten, D.; Beeckman, T.; Inzé, D.; Van Onckelen, H.; Witters, E.; Prinsen, E. A hormone and proteome approach to picturing the initial metabolic events during Plasmodiophora brassicae infection on Arabidopsis. Mol. Plant Microbe. Interact. 2006, 19, 1431–1443. [Google Scholar] [CrossRef]
Laila, R.; Robin, A.H.K.; Park, J.I.; Saha, G.; Kim, H.T.; Kayum, M.A.; Nou, I.S. Expression and role of response regulating, biosynthetic and degrading genes for cytokinin signaling during clubroot disease development. Int. J. Mol. Sci. 2020, 21, 3896. [Google Scholar] [CrossRef]
Zhu, M.; Wang, Y.; Lu, S.; Yang, L.; Zhuang, M.; Zhang, Y.; Lv, H.; Fang, Z.; Hou, X. Genome-wide identification and analysis of cytokinin dehydrogenase/oxidase (CKX) family genes in Brassica oleracea L. reveals their involvement in response to Plasmodiophora brassicae infections. Hortic. Plant J. 2022, 8, 68–80. [Google Scholar] [CrossRef]
Summanwar, A.; Farid, M.; Basu, U.; Kav, N.; Rahman, H. Comparative transcriptome analysis of canola carrying clubroot resistance from ’Mendel’ or Rutabaga and the development of molecular markers. Physiol. Mol. Plant Pathol. 2021, 114, 101640. [Google Scholar] [CrossRef]
Jones, J.D.; Dangl, J.L. The plant immune system. Nature 2006, 444, 323–329. [Google Scholar] [CrossRef]
Howe, G.A.; Jander, G. Plant Immunity to Insect Herbivores. Annu. Rev. Plant Biol. 2008, 59, 41–66. [Google Scholar] [CrossRef]
Wielkopolan, B.; Obrępalska-Stęplowska, A. Three-way interaction among plants, bacteria, and coleopteran insects. Planta 2016, 244, 313–332. [Google Scholar] [CrossRef]
Ryals, J.A.; Neuenschwander, U.H.; Willits, M.G.; Molina, A.; Steiner, H.Y.; Hunt, M.D. Systemic acquired resistance. Plant Cell 1996, 8, 1809–1819. [Google Scholar] [CrossRef] [PubMed]
Nie, P.; Li, X.; Wang, S.; Guo, J.; Zhao, H.; Niu, D. Induced systemic resistance against Botrytis cinerea by Bacillus cereus AR156 through a JA/ET- and NPR1-dependent signaling pathway and activates PAMP-triggered immunity in Arabidopsis. Front. Plant Sci. 2017, 8, 238. [Google Scholar] [CrossRef] [PubMed]
Tortosa, M.; Cartea, M.E.; Velasco, P.; Soengas, P.; Rodriguez, V.M. Calcium-signaling proteins mediate the plant transcriptomic response during a well-established Xanthomonas campestris pv. campestris infection. Hortic. Res. 2019, 6, 103. [Google Scholar] [CrossRef] [PubMed]
Robert-Seilaniantz, A.; Grant, M.; Jones, J.D. Hormone crosstalk in plant disease and defense: More than just jasmonate-salicylate antagonism. Annu. Rev. Phytopathol. 2011, 49, 317–343. [Google Scholar] [CrossRef] [PubMed]
Pieterse, C.M.; Van der Does, D.; Zamioudis, C.; Leon-Reyes, A.; Van Wees, S.C. Hormonal modulation of plant immunity. Annu. Rev. Cell. Dev. Biol. 2012, 28, 489–521. [Google Scholar] [CrossRef]
Thaler, J.S.; Humphrey, P.T.; Whiteman, N.K. Evolution of jasmonate and salicylate signal crosstalk. Trends Plant Sci. 2012, 17, 260–270. [Google Scholar] [CrossRef]
Ji, R.; Wang, Y.; Wang, X.; Liu, Y.; Shen, X.; Feng, H. Proteomic analysis of the interaction between Plasmodiophora brassicae and Chinese cabbage (Brassica rapa L. ssp. Pekinensis) at the initial infection stage. Sci. Hortic. 2018, 233, 386–393. [Google Scholar] [CrossRef]
Lovelock, D.A.; Donald, C.E.; Conlan, X.A.; Cahill, D.M. Salicylic acid suppression of clubroot in broccoli (Brassicae oleracea var. italica) caused by the obligate biotroph Plasmodiophora brassicae. Australas. Plant Pathol. 2013, 42, 141–153. [Google Scholar] [CrossRef]
Lemarié, S.; Robert-Seilaniantz, A.; Lariagon, C.; Lemoine, J.; Marnet, N.; Jubault, M.; Manzanares-Dauleux, M.J.; Gravot, A. Both the jasmonic acid and the salicylic acid pathways contribute to resistance to the biotrophic clubroot agent Plasmodiophora brassicae in Arabidopsis. Plant Cell Physiol. 2015, 56, 2158–2168. [Google Scholar] [CrossRef]
Durrant, W.E.; Dong, X. Systemic acquired resistance. Annu. Rev. Phytopathol. 2004, 42, 185–209. [Google Scholar] [CrossRef]
Chen, T.; Bi, K.; He, Z.; Gao, Z.; Zhao, Y.; Fu, Y.; Cheng, J.; Xie, J.; Jiang, D. Arabidopsis mutant bik1 exhibits strong resistance to Plasmodiophora brassicae. Front. Physiol 2016, 7, 402. [Google Scholar] [CrossRef]
Lovelock, D.A.; Šola, I.; Marschollek, S.; Donald, C.E.; Rusak, G.; van Pée, K.H.; Ludwig-Müller, J.; Cahill, D.M. Analysis of salicylic acid-dependent pathways in Arabidopsis thaliana following infection with Plasmodiophora brassicae and the influence of salicylic acid on disease. Mol. Plant Pathol. 2016, 17, 1237–1251. [Google Scholar] [CrossRef] [PubMed]
Bulman, S.; Richter, F.; Marschollek, S.; Benade, F.; Jülke, S.; Ludwig-Müller, J. Arabidopsis thaliana expressing PbBSMT, a gene encoding a SABATH-type methyltransferase from the plant pathogenic protist Plasmodiophora brassicae, show leaf chlorosis and altered host susceptibility. Plant Biol. 2019, 21 (Suppl. 1), 120–130. [Google Scholar] [CrossRef] [PubMed]
Ludwig-Müller, J.; Jülke, S.; Geiß, K.; Richter, F.; Mithöfer, A.; Šola, I.; Rusak, G.; Keenan, S.; Bulman, S. A novel methyltransferase from the intracellular pathogen Plasmodiophora brassicae methylates salicylic acid. Mol. Plant Pathol. 2015, 16, 349–364. [Google Scholar] [CrossRef] [PubMed]
Bi, K.; He, Z.; Gao, Z.; Zhao, Y.; Fu, Y.; Cheng, J.; Xie, J.; Jiang, D.; Chen, T. Integrated omics study of lipid droplets from Plasmodiophora brassicae. Sci. Rep. 2016, 6, 36965. [Google Scholar] [CrossRef]
Gravot, A.; Deleu, C.; Wagner, G.; Lariagon, C.; Lugan, R.; Todd, C.; Wendehenne, D.; Delourme, R.; Bouchereau, A.; Manzanares-Dauleux, M.J. Arginase induction represses gall development during clubroot infection in Arabidopsis. Plant Cell Physiol. 2012, 53, 901–911. [Google Scholar] [CrossRef]
Xu, L.; Yang, H.; Ren, L.; Chen, W.; Liu, L.; Liu, F.; Zeng, L.; Yan, R.; Chen, K.; Fang, X. Jasmonic acid-mediated aliphatic glucosinolate metabolism is involved in clubroot disease development in Brassica napus L. Front. Plant Sci. 2018, 9, 750. [Google Scholar] [CrossRef]
Ludwig-Müller, J.; Schubert, B.; Pieper, K.; Ihmig, S.; Hilgenberg, W. Glucosinolate content in susceptible and resistant Chinese cabbage varieties during development of clubroot disease. Phytochemistry 1997, 44, 407–414. [Google Scholar] [CrossRef]
Grsic, S.; Kirchheim, B.; Pieper, K.; Fritsch, M.; Hilgenberg, W.; Ludwig-Müller, J. Auxin biosynthesis in clubroot diseased Chinese cabbage plants and induction by jasmonic acid. Physiol. Plant 1999, 105, 521–531. [Google Scholar] [CrossRef]
Kazan, K.; Manners, J.M. JAZ repressors and the orchestration of phytohormone crosstalk. Trends Plant Sci. 2012, 17, 22–31. [Google Scholar] [CrossRef]
Liu, X.; Zhao, C.; Yang, L.; Zhang, Y.; Wang, Y.; Fang, Z.; Lv, H. Genome-wide identification, expression profile of the TIFY gene family in Brassica oleracea var. capitata, and their divergent response to various pathogen infections and phytohormone treatments. Genes 2020, 11, 127. [Google Scholar] [CrossRef] [PubMed]
Fu, P.; Piao, Y.; Zhan, Z.; Zhao, Y.; Pang, W.; Li, X.; Piao, Z. Transcriptome arofile of Brassica rapa L. reveals the involvement of jasmonic acid, ethylene, and brassinosteroid signaling pathways in clubroot resistance. Agronomy 2019, 9, 589. [Google Scholar] [CrossRef]
Zhang, W.; Wang, S.; Yu, F.; Tang, J.; Shan, X.; Bao, K.; Yu, L.; Wang, H.; Fei, Z.; Li, J. Genome-wide characterization and expression profiling of SWEET genes in cabbage (Brassica oleracea var. capitata L.) reveal their roles in chilling and clubroot disease responses. BMC Genom. 2019, 20, 93. [Google Scholar] [CrossRef] [PubMed]
Zhang, W.; Wang, S.; Yu, F.; Tang, J.; Yu, L.; Wang, H.; Li, J. Genome-wide identification and expression profiling of sugar transporter protein (STP) family genes in cabbage (Brassica oleracea var. capitata L.) reveals their involvement in clubroot disease responses. Genes 2019, 10, 71. [Google Scholar] [CrossRef]
Manoharan, R.K.; Shanmugam, A.; Hwang, I.; Park, J.-I.; Nou, I.-S. Expression of salicylic acid-related genes in Brassica oleracea var. capitata during Plasmodiophora brassicae infection. Genome 2016, 59, 379–391. [Google Scholar] [CrossRef]
Kayum, M.A.; Nath, U.K.; Park, J.-I.; Hossain, M.R.; Kim, H.-T.; Kim, H.-R.; Nou, I.-S. Glucosinolate profile and Myrosinase gene expression are modulated upon Plasmodiophora brassicae infection in cabbage. Funct. Plant Biol. 2020, 48, 103–118. [Google Scholar] [CrossRef]
Yuan, Y.; Qin, L.; Su, H.; Yang, S.; Wei, X.; Wang, Z.; Zhao, Y.; Li, L.; Liu, H.; Tian, B.; et al. Transcriptome and coexpression network analyses reveal Hub genes in Chinese cabbage (Brassica rapa L. ssp. pekinensis) during different Stages of Plasmodiophora brassicae infection. Front. Plant Sci. 2021, 12, 650252. [Google Scholar] [CrossRef]
Jiang, M.; Dong, X.; Lang, H.; Pang, W.; Zhan, Z.; Li, X.; Piao, Z. Mining of Brassica-specific genes (BSGs) and their induction in different developmental stages and under Plasmodiophora brassicae stress in Brassica rapa. Int. J. Mol. Sci. 2018, 19, 2064. [Google Scholar] [CrossRef]
Robin, A.H.K.; Saha, G.; Laila, R.; Park, J.-I.; Kim, H.-T.; Nou, I.-S. Expression and role of biosynthetic, transporter, receptor, and responsive genes for auxin signaling during clubroot disease development. Int. J. Mol. Sci. 2020, 21, 5554. [Google Scholar] [CrossRef]
Lahlali, R.; Song, T.; Chu, M.; Yu, F.; Kumar, S.; Karunakaran, C.; Peng, G. Evaluating changes in cell-wall components associated with Clubroot resistance using Fourier Transform Infrared spectroscopy and RT-PCR. Int. J. Mol. Sci. 2017, 18, 2058. [Google Scholar] [CrossRef]
Ando, S.; Tsushima, S.; Kamachi, S.; Konagaya, K.-i.; Tabei, Y. Alternative transcription initiation of the nitrilase gene (BrNIT2) caused by infection with Plasmodiophora brassicae Woron. in Chinese cabbage (Brassica rapa L.). Plant Mol. Biol. 2008, 68, 557–569. [Google Scholar] [CrossRef] [PubMed]
Ando, S.; Tsushima, S.; Tagiri, A.; Kamachi, S.; Konagaya, K.I.; Hagio, T.; Tabei, Y. Increase in BrAO1 gene expression and aldehyde oxidase activity during clubroot development in Chinese cabbage (Brassica rapa L.). Mol. Plant Pathol. 2006, 7, 223–234. [Google Scholar] [CrossRef] [PubMed]
Ando, S.; Asano, T.; Tsushima, S.; Kamachi, S.; Hagio, T.; Tabei, Y. Changes in gene expression of putative isopentenyltransferase during clubroot development in Chinese cabbage (Brassica rapa L.). Physiol. Mol. Plant Pathol. 2005, 67, 59–67. [Google Scholar] [CrossRef]
Wei, X.; Zhang, Y.; Zhao, Y.; Xie, Z.; Hossain, M.R.; Yang, S.; Shi, G.; Lv, Y.; Wang, Z.; Tian, B.; et al. Root transcriptome and metabolome profiling reveal key phytohormone-related genes and pathways involved clubroot resistance in Brassica rapa L. Front. Plant Sci. 2021, 12, 759623. [Google Scholar] [CrossRef]
Shah, N.; Li, Q.; Xu, Q.; Liu, J.; Huang, F.; Zhan, Z.; Qin, P.; Zhou, X.; Yu, W.; Zhu, L.; et al. CRb and PbBa8.1 synergically increases resistant genes expression upon infection of Plasmodiophora brassicae in Brassica napus. Genes 2020, 11, 202. [Google Scholar] [CrossRef]
Zhou, Q.; Galindo-González, L.; Manolii, V.; Hwang, S.-F.; Strelkov, S.E. Comparative transcriptome analysis of Rutabaga (Brassica napus) cultivars indicates activation of salicylic acid and ethylene-mediated defenses in response to Plasmodiophora brassicae. Int. J. Mol. Sci. 2020, 21, 8381. [Google Scholar] [CrossRef]
Li, L.; Long, Y.; Li, H.; Wu, X. Comparative transcriptome analysis reveals key pathways and Hub genes in rapeseed during the early stage of Plasmodiophora brassicae infection. Front. Genet. 2020, 10, 1275. [Google Scholar] [CrossRef]
Chen, S.W.; Liu, T.; Gao, Y.; Zhang, C.; Peng, S.D.; Bai, M.B.; Li, S.J.; Xu, L.; Zhou, X.Y.; Lin, L.B. Discovery of clubroot-resistant genes in Brassica napus by transcriptome sequencing. Genet. Mol. Res. 2016, 15, gmr8243. [Google Scholar] [CrossRef]
Galindo Gonzalez, L.; Manolii, V.; Hwang, S.; Strelkov, S. Response of Brassica napus to Plasmodiophora brassicae involves salicylic acid-mediated immunity: An RNA-Seq-Based Study. Front. Plant Sci. 2020, 11, 1025. [Google Scholar] [CrossRef]
Jiang, J.; Fredua-Agyeman, R.; Hwang, S.F.; Strelkov, S.E. Differentially expressed genes in canola (Brassica napus) during infection by virulent and avirulent Plasmodiophora brassicae pathotypes. Plant Pathol. 2021, 70, 50–60. [Google Scholar] [CrossRef]
Irani, S.; Todd, C.D.; Wei, Y.; Bonham-Smith, P.C. Changes in phenylpropanoid pathway gene expression in roots and leaves of susceptible and resistant Brassica napus lines in response to Plasmodiophora brassicae inoculation. Physiol. Mol. Plant Pathol. 2019, 106, 196–203. [Google Scholar] [CrossRef]
Hejna, O.; Havlickova, L.; He, Z.; Bancroft, I.; Curn, V. Analysing the genetic architecture of clubroot resistance variation in Brassica napus by associative transcriptomics. Mol. Breed. 2019, 39, 112. [Google Scholar] [CrossRef] [PubMed]
Luo, Y.; Dong, D.; Su, Y.; Wang, X.; Peng, Y.; Peng, J.; Zhou, C. Transcriptome analysis of Brassica juncea var. tumida Tsen responses to Plasmodiophora brassicae primed by the biocontrol strain Zhihengliuella aestuarii. Funct. Integr. 2018, 18, 301–314. [Google Scholar] [CrossRef] [PubMed]
Luo, Y.; Yin, Y.; Liu, Y.; Pei, X.; Wang, Z.; Fan, Y.; Wang, X.; Leng, R. Identification of differentially expressed genes in Brassica juncea var. tumida Tsen following infection by Plasmodiophora brassicae. Eur. J. Plant Pathol. 2013, 137, 43–53. [Google Scholar] [CrossRef]
Xi, D.; Li, X.; Gao, L.; Zhang, Z.; Zhu, Y.; Zhu, H. Application of exogenous salicylic acid reduces disease severity of Plasmodiophora brassicae in pakchoi (Brassica campestris ssp. chinensis Makino). PLoS ONE 2021, 16, e0248648. [Google Scholar] [CrossRef] [PubMed]
Underwood, W. The plant cell wall: A dynamic barrier against pathogen invasion. Front. Plant Sci. 2012, 3, 85. [Google Scholar] [CrossRef]
Ferrari, S.; Savatin, D.V.; Sicilia, F.; Gramegna, G.; Cervone, F.; Lorenzo, G.D. Oligogalacturonides: Plant damage-associated molecular patterns and regulators of growth and development. Front. Plant Sci. 2013, 4, 49. [Google Scholar] [CrossRef]
Badstöber, J.; Ciaghi, S.; Neuhauser, S. Dynamic cell wall modifications in brassicas during clubroot disease. bioRxiv 2020. [Google Scholar] [CrossRef]
Marín-Rodríguez, M.C.; Orchard, J.; Seymour, G.B. Pectate lyases, cell wall degradation and fruit softening. J. Exp. Bot. 2002, 53, 2115–2119. [Google Scholar] [CrossRef]
Kämper, J.; Kahmann, R.; Bölker, M.; Ma, L.-J.; Brefort, T.; Saville, B.J.; Banuett, F.; Kronstad, J.W.; Gold, S.E.; Müller, O.; et al. Insights from the genome of the biotrophic fungal plant pathogen Ustilago maydis. Nature 2006, 444, 97–101. [Google Scholar] [CrossRef]
Sterling, J.D.; Quigley, H.F.; Orellana, A.; Mohnen, D. The catalytic site of the pectin biosynthetic enzyme alpha-1,4-galacturonosyltransferase is located in the lumen of the Golgi. Plant Physiol. 2001, 127, 360–371. [Google Scholar] [CrossRef]
Mitchell, H.J.; Hall, S.A.; Stratford, R.; Hall, J.L.; Barber, M.S. Differential induction of cinnamyl alcohol dehydrogenase during defensive lignification in wheat (Triticum aestivum L.): Characterisation of the major inducible form. Planta 1999, 208, 31–37. [Google Scholar] [CrossRef]
Agarwal, A.; Kaul, V.; Faggian, R.; Rookes, J.E.; Ludwig, M.L.J.; Cahill, D.M. Analysis of global host gene expression during the primary phase of the Arabidopsis thaliana-Plasmodiophora brassicae interaction. Funct. Plant Biol. 2011, 38, 462–478. [Google Scholar] [CrossRef] [PubMed]
Jubault, M.; Lariagon, C.; Taconnat, L.; Renou, J.-P.; Gravot, A.; Delourme, R.; Manzanares-Dauleux, M.J. Partial resistance to clubroot in Arabidopsis is based on changes in the host primary metabolism and targeted cell division and expansion capacity. Funct. Integr. 2013, 13, 191–205. [Google Scholar] [CrossRef]
Cozzolino, D. Use of infrared spectroscopy for in-field measurement and phenotyping of plant properties: Instrumentation, data Analysis, and examples. Appl. Spectrosc. Rev. 2014, 49, 564–584. [Google Scholar] [CrossRef]
Obst, J.R. Guaiacyl and syringyl lignin composition in hardwood cell components. Holzforschung 1982, 36, 143–152. [Google Scholar] [CrossRef]
Hasan, J.; Megha, S.; Rahman, H. Clubroot in Brassica: Recent advances in genomics, breeding, and disease management. Genome 2021, 64, 735–760. [Google Scholar] [CrossRef]
Reinders, A.; Sivitz, A.B.; Starker, C.G.; Gantt, J.S.; Ward, J.M. Functional analysis of LjSUT4, a vacuolar sucrose transporter from Lotus japonicus. Plant Mol. Biol. 2008, 68, 289–299. [Google Scholar] [CrossRef]
Reinders, A.; Sivitz, A.B.; Ward, J.M. Evolution of plant sucrose uptake transporters. Front. Plant Sci. 2012, 3, 22. [Google Scholar] [CrossRef]
Toyofuku, K.; Kasahara, M.; Yamaguchi, J. Characterization and expression of monosaccharide transporters (osMSTs) in rice. Plant Cell Physiol. 2000, 41, 940–947. [Google Scholar] [CrossRef]
Chen, L.Q.; Qu, X.Q.; Hou, B.H.; Sosso, D.; Osorio, S.; Fernie, A.R.; Frommer, W.B. Sucrose efflux mediated by SWEET proteins as a key step for phloem transport. Science 2012, 335, 207–211. [Google Scholar] [CrossRef] [PubMed]
Manck-Götzenberger, J.; Requena, N. Arbuscular mycorrhiza symbiosis induces a major transcriptional reprogramming of the potato SWEET sugar transporter family. Front. Plant Sci. 2016, 7, 487. [Google Scholar] [CrossRef] [PubMed]
Roman-Reyna, V.; Rathjen, J.P. Apoplastic sugar extraction and quantification from wheat leaves infected with biotrophic fungi. Methods Mol. Biol. 2017, 1659, 125–134. [Google Scholar] [CrossRef]
Guo, X.H. Biological Characteristics and Pathogenesis of Plasmodiophora brassicae. Master’s Thesis, Southwest Agriculture University, Chongqing, China, 2001. [Google Scholar]
Williams, P.H. Metabolic synthesis and degradation during clubroot development in cabbage hypocotyls. Phytopathology 1968, 58, 921–928. [Google Scholar]
Keen, N.T.; Williams, P.H. Translocation of sugars into infected cabbage tissues during clubroot development. Plant Physiol. 1969, 44, 748–754. [Google Scholar] [CrossRef]
Evans, J.L.; Scholes, J.D. How does clubroot alter the regulation of carbon metabolism in its host? Asp. Appl. Biol. 1995, 42, 125–132. [Google Scholar]
Brodmann, A.; Schuller, A.; Ludwig-Müller, J.; Aeschbacher, R.A.; Wiemken, A.; Boller, T.; Wingler, A. Induction of trehalase in Arabidopsis plants infected with the trehalose-producing pathogen Plasmodiophora brassicae. Mol. Plant Microbe. Interact. 2002, 15, 693–700. [Google Scholar] [CrossRef]
Malinowski, R.; Smith, J.A.; Fleming, A.J.; Scholes, J.D.; Rolfe, S.A. Gall formation in clubroot-infected Arabidopsis results from an increase in existing meristematic activities of the host but is not essential for the completion of the pathogen life cycle. Plant J. 2012, 71, 226–238. [Google Scholar] [CrossRef]
Ludewig, F.; Flügge, U.I. Role of metabolite transporters in source-sink carbon allocation. Front. Plant Sci. 2013, 4, 231. [Google Scholar] [CrossRef]
Sherson, S.M.; Alford, H.L.; Forbes, S.M.; Wallace, G.; Smith, S.M. Roles of cell-wall invertases and monosaccharide transporters in the growth and development of Arabidopsis. J. Exp. Bot. 2003, 54, 525–531. [Google Scholar] [CrossRef]
Irani, S.; Trost, B.; Waldner, M.; Nayidu, N.; Tu, J.; Kusalik, A.J.; Todd, C.D.; Wei, Y.; Bonham-Smith, P.C. Transcriptome analysis of response to Plasmodiophora brassicae infection in the Arabidopsis shoot and root. BMC Genom. 2018, 19, 23. [Google Scholar] [CrossRef] [PubMed]
Walerowski, P.; Gündel, A.; Yahaya, N.; Truman, W.; Sobczak, M.; Olszak, M.; Rolfe, S.; Borisjuk, L.; Malinowski, R. Clubroot disease stimulates early steps of phloem differentiation and recruits SWEET sucrose transporters within developing galls. Plant Cell 2018, 30, 3058–3073. [Google Scholar] [CrossRef] [PubMed]
Doidy, J.; Grace, E.; Kühn, C.; Simon-Plas, F.; Casieri, L.; Wipf, D. Sugar transporters in plants and in their interactions with fungi. Trends Plant Sci. 2012, 17, 413–422. [Google Scholar] [CrossRef] [PubMed]
Lemoine, R.; La Camera, S.; Atanassova, R.; Dédaldéchamp, F.; Allario, T.; Pourtau, N.; Bonnemain, J.L.; Laloi, M.; Coutos-Thévenot, P.; Maurousset, L.; et al. Source-to-sink transport of sugar and regulation by environmental factors. Front. Plant Sci. 2013, 4, 272. [Google Scholar] [CrossRef]
Li, H.; Li, X.; Xuan, Y.; Jiang, J.; Wei, Y.; Piao, Z. Genome wide identification and expression profiling of SWEET genes family reveals its role during Plasmodiophora brassicae-induced formation of clubroot in Brassica rapa. Front. Plant Sci. 2018, 9, 207. [Google Scholar] [CrossRef]
Gupta, P.K.; Balyan, H.S.; Gautam, T. SWEET genes and TAL effectors for disease resistance in plants: Present status and future prospects. Mol. Plant Pathol. 2021, 22, 1014–1026. [Google Scholar] [CrossRef]
Chen, L.-Q.; Hou, B.-H.; Lalonde, S.; Takanaga, H.; Hartung, M.L.; Qu, X.-Q.; Guo, W.-J.; Kim, J.-G.; Underwood, W.; Chaudhuri, B.; et al. Sugar transporters for intercellular exchange and nutrition of pathogens. Nature 2010, 468, 527–532. [Google Scholar] [CrossRef]
Chong, J.; Piron, M.C.; Meyer, S.; Merdinoglu, D.; Bertsch, C.; Mestre, P. The SWEET family of sugar transporters in grapevine: VvSWEET4 is involved in the interaction with Botrytis cinerea. J. Exp. Bot. 2014, 65, 6589–6601. [Google Scholar] [CrossRef]
Summanwar, A.; Basu, U.; Rahman, H.; Kav, N.N.V. Non-coding RNAs as emerging targets for crop improvement. Plant Sci. 2020, 297, 110521. [Google Scholar] [CrossRef]
Nejat, N.; Mantri, N. Emerging roles of long non-coding RNAs in plant response to biotic and abiotic stresses. Crit. Rev. Biotechnol. 2018, 38, 93–105. [Google Scholar] [CrossRef]
Shriram, V.; Kumar, V.; Devarumath, R.M.; Khare, T.S.; Wani, S.H. MicroRNAs as potential targets for abiotic stress tolerance in plants. Front. Plant Sci. 2016, 7, 817. [Google Scholar] [CrossRef] [PubMed]
Carrington, J.C.; Ambros, V. Role of microRNAs in plant and animal development. Science 2003, 301, 336–338. [Google Scholar] [CrossRef] [PubMed]
Bartel, D.P. MicroRNAs: Genomics, biogenesis, mechanism, and function. Cell 2004, 116, 281–297. [Google Scholar] [CrossRef]
Kulshrestha, C.; Pathak, H.; Kumar, D.; Dave, S.; Sudan, J. Elucidating micro RNAs role in different plant-pathogen interactions. Mol. Biol. Rep. 2020, 47, 8219–8227. [Google Scholar] [CrossRef] [PubMed]
Song, X.; Li, Y.; Cao, X.; Qi, Y. MicroRNAs and their regulatory roles in plant-environment interactions. Annu. Rev. Plant Biol. 2019, 70, 489–525. [Google Scholar] [CrossRef]
Verma, S.S.; Rahman, M.H.; Deyholos, M.K.; Basu, U.; Kav, N.N. Differential expression of miRNAs in Brassica napus root following infection with Plasmodiophora brassicae. PLoS ONE 2014, 9, e86648. [Google Scholar] [CrossRef]
Wei, X.; Xu, W.; Yuan, Y.; Yao, Q.; Zhao, Y.; Wang, Z.; Jiang, W.; Zhang, X. Genome-wide investigation of microRNAs and their targets in Brassica rapa ssp. pekinensis root with Plasmodiophora brassicae infection. Hortic. Plant J. 2016, 2, 209–216. [Google Scholar] [CrossRef]
Guo, H.S.; Xie, Q.; Fei, J.F.; Chua, N.H. MicroRNA directs mRNA cleavage of the transcription factor NAC1 to downregulate auxin signals for Arabidopsis lateral root development. Plant Cell 2005, 17, 1376–1386. [Google Scholar] [CrossRef]
Paul, P.; Chhapekar, S.S.; Rameneni, J.J.; Oh, S.H.; Dhandapani, V.; Subburaj, S.; Shin, S.-Y.; Ramchiary, N.; Shin, C.; Choi, S.R.; et al. MiR1885 regulates disease tolerance genes in Brassica rapa during early infection with Plasmodiophora brassicae. Int. J. Mol. Sci. 2021, 22, 9433. [Google Scholar] [CrossRef]
Li, Q.; Shah, N.; Zhou, X.; Wang, H.; Yu, W.; Luo, J.; Liu, Y.; Li, G.; Liu, C.; Zhang, C.; et al. Identification of icro Ribonucleic Acids and their targets in response to Plasmodiophora brassicae infection in Brassica napus. Front. Plant Sci. 2021, 12, 734419. [Google Scholar] [CrossRef]
Wilusz, J.E.; Sunwoo, H.; Spector, D.L. Long noncoding RNAs: Functional surprises from the RNA world. Genes Dev. 2009, 23, 1494–1504. [Google Scholar] [CrossRef] [PubMed]
Matsui, A.; Seki, M. The involvement of long noncoding RNAs in response to plant stress. Methods Mol. Biol. 2019, 1933, 151–171. [Google Scholar] [CrossRef] [PubMed]
Kornienko, A.E.; Guenzl, P.M.; Barlow, D.P.; Pauler, F.M. Gene regulation by the act of long non-coding RNA transcription. BMC Biol. 2013, 11, 59. [Google Scholar] [CrossRef] [PubMed]
Zhu, H.; Li, X.; Xi, D.; Zhai, W.; Zhang, Z.; Zhu, Y. Integrating long noncoding RNAs and mRNAs expression profiles of response to Plasmodiophora brassicae infection in Pakchoi (Brassica campestris ssp. chinensis Makino). PLoS ONE 2019, 14, e0224927. [Google Scholar] [CrossRef] [PubMed]
Summanwar, A.; Basu, U.; Rahman, H.; Kav, N. Identification of lncRNAs responsive to infection by Plasmodiophora brassicae in clubroot-susceptible and -resistant Brassica napus lines carrying resistance introgressed from Rutabaga. Mol. Plant Microbe. Interact. 2019, 32, 1360–1377. [Google Scholar] [CrossRef]
Hasan, M.J.; Rahman, H. Genetics and molecular mapping of resistance to Plasmodiophora brassicae pathotypes 2, 3, 5, 6, and 8 in rutabaga (Brassica napus var. napobrassica). Genome 2016, 59, 805–815. [Google Scholar] [CrossRef]
Summanwar, A.; Basu, U.; Kav, N.N.V.; Rahman, H. Identification of lncRNAs in response to infection by Plasmodiophora brassicae in Brassica napus and development of lncRNA-based SSR markers. Genome 2021, 64, 547–566. [Google Scholar] [CrossRef]
Raza, A.; Tabassum, J.; Kudapa, H.; Varshney, R.K. Can omics deliver temperature resilient ready-to-grow crops? Crit. Rev. Biotechnol. 2021, 41, 1209–1232. [Google Scholar] [CrossRef]
Weckwerth, W.; Ghatak, A.; Bellaire, A.; Chaturvedi, P.; Varshney, R.K. PANOMICS meets germplasm. Plant Biotechnol. J. 2020, 18, 1507–1525. [Google Scholar] [CrossRef]
Quirino, B.F.; Candido, E.S.; Campos, P.F.; Franco, O.L.; Krüger, R.H. Proteomic approaches to study plant–pathogen interactions. Phytochemistry 2010, 71, 351–362. [Google Scholar] [CrossRef]
Lodha, T.D.; Hembram, P.; Nitile Tep, J.B. Proteomics: A successful approach to understand the molecular mechanism of plant-pathogen interaction. Am. J. Plant Sci 2013, 4, 1212–1226. [Google Scholar] [CrossRef]
Eldakak, M.; Milad, S.I.M.; Nawar, A.I.; Rohila, J.S. Proteomics: A biotechnology tool for crop improvement. Front. Plant Sci. 2013, 4, 35. [Google Scholar] [CrossRef] [PubMed]
Chaturvedi, P.; Doerfler, H.; Jegadeesan, S.; Ghatak, A.; Pressman, E.; Castillejo, M.A.; Wienkoop, S.; Egelhofer, V.; Firon, N.; Weckwerth, W. Heat-treatment-responsive proteins in different developmental stages of tomato pollen detected by targeted Mass Accuracy Precursor Alignment (tMAPA). J. Proteome. Res. 2015, 14, 4463–4471. [Google Scholar] [CrossRef] [PubMed]
Pomastowski, P.; Buszewski, B. Two-dimensional gel electrophoresis in the light of new developments. TrAC Trends Anal. Chem. 2014, 53, 167–177. [Google Scholar] [CrossRef]
Boersema, P.J.; Kahraman, A.; Picotti, P. Proteomics beyond large-scale protein expression analysis. Curr. Opin. Biotechnol. 2015, 34, 162–170. [Google Scholar] [CrossRef]
Borràs, E.; Sabidó, E. What is targeted proteomics? A concise revision of targeted acquisition and targeted data analysis in mass spectrometry. Proteomics 2017, 17, 1700180. [Google Scholar] [CrossRef]
Aslam, B.; Basit, M.; Nisar, M.A.; Khurshid, M.; Rasool, M.H. Proteomics: Technologies and their applications. J. Chromatogr. Sci. 2017, 55, 182–196. [Google Scholar] [CrossRef]
Su, T.; Yu, S.; Wang, W.; Li, P.; Zhang, F.; Yu, Y.; Zhang, D.; Zhao, X. iTRAQ analysis of protein profile during the secondary stage of infection of Plasmodiophora brassicae in Chinese cabbage (Brassica rapa subsp. pekinensis). J. Plant Pathol. 2018, 100, 533–542. [Google Scholar] [CrossRef]
Lan, M.; Li, G.; Hu, J.; Yang, H.; Zhang, L.; Xu, X.; Liu, J.; He, J.; Sun, R. iTRAQ-based quantitative analysis reveals proteomic changes in Chinese cabbage (Brassica rapa L.) in response to Plasmodiophora brassicae infection. Sci. Rep. 2019, 9, 12058. [Google Scholar] [CrossRef]
Song, T.; Chu, M.; Lahlali, R.; Yu, F.; Peng, G. Shotgun label-free proteomic analysis of clubroot (Plasmodiophora brassicae) resistance conferred by the gene Rcr1 in Brassica rapa. Front. Plant Sci. 2016, 7, 1013. [Google Scholar] [CrossRef]
Moon, J.; Kim, S.; Choi, G.; Kwon, S.-Y.; Cho, H.S.; Kim, H.-S.; Moon, J.S.; Park, J.M. Comparative proteomic analysis of host responses to Plasmodiophora brassicae infection in susceptible and resistant Brassica oleracea. Plant Biotechnol. Rep. 2020, 14, 263–274. [Google Scholar] [CrossRef]
Hansen, C.E.; Flengsrud, R.; Kopperud, C. Two-dimensional gel electrophoresis of proteins in healthy roots and clubroots of Brassica oleracea. Acta Agric. Scand.-B Soil Plant Sci. 1994, 44, 123–128. [Google Scholar] [CrossRef]
Ji, R.; Gao, S.; Bi, Q.; Wang, Y.; Lv, M.; Ge, W.; Feng, H. The salicylic acid signaling pathway plays an important role in the resistant process of Brassica rapa L. ssp. pekinensis to Plasmodiophora brassicae Woronin. J. Plant Growth Regul. 2021, 40, 405–422. [Google Scholar] [CrossRef]
Jeung, J.Y.; Lim, Y.P.; Hwang, C.H. Root proteome analysis of Chinese cabbage in response to Plasmodipohora brassicae Woron. J. Plant Biotechnol. 2015, 42, 350–355. [Google Scholar] [CrossRef]
Adhikary, D.; Mehta, D.; Uhrig, R.G.; Rahman, H.; Kav, N.N.V. A Proteome-level investigation into Plasmodiophora brassicae resistance in Brassica napus canola. Front. Plant Sci. 2022, 13, 860393. [Google Scholar] [CrossRef]
Yang, Y.; Saand, M.A.; Huang, L.; Abdelaal, W.B.; Zhang, J.; Wu, Y.; Li, J.; Sirohi, M.H.; Wang, F. Applications of multi-omics technologies for crop improvement. Front. Plant Sci. 2021, 12, 563953. [Google Scholar] [CrossRef]
Liu, X.; Locasale, J.W. Metabolomics: A Primer. Trends Biochem. Sci. 2017, 42, 274–284. [Google Scholar] [CrossRef]
Castro-Moretti, F.R.; Gentzel, I.N.; Mackey, D.; Alonso, A.P. Metabolomics as an emerging tool for the study of plant-pathogen interactions. Metabolites 2020, 10, 52. [Google Scholar] [CrossRef]
Raza, A. Metabolomics: A systems biology approach for enhancing heat stress tolerance in plants. Plant. Cell. Rep. 2020, 41, 741–763. [Google Scholar] [CrossRef]
Hall, R.D. Plant metabolomics: From holistic hope, to hype, to hot topic. New Phytol. 2006, 169, 453–468. [Google Scholar] [CrossRef]
Griffiths, W.J.; Koal, T.; Wang, Y.; Kohl, M.; Enot, D.P.; Deigner, H.P. Targeted metabolomics for biomarker discovery. Angew. Chem. Int. Ed. Engl. 2010, 49, 5426–5445. [Google Scholar] [CrossRef] [PubMed]
Aigu, Y.; Daval, S.; Gazengel, K.; Marnet, N.; Lariagon, C.; Laperche, A.; Legeai, F.; Manzanares-Dauleux, M.J.; Gravot, A. Multi-Omic investigation of low-nitrogen conditional resistance to clubroot reveals Brassica napus genes involved in nitrate assimilation. Front. Plant Sci. 2022, 13, 790563. [Google Scholar] [CrossRef] [PubMed]
Wagner, G.; Charton, S.; Lariagon, C.; Laperche, A.; Lugan, R.; Hopkins, J.; Frendo, P.; Bouchereau, A.; Delourme, R.; Gravot, A.; et al. Metabotyping: A new approach to investigate rapeseed (Brassica napus L.) genetic diversity in the metabolic response to clubroot infection. Mol. Plant Microbe. Interact. 2012, 25, 1478–1491. [Google Scholar] [CrossRef] [PubMed]
Lan, M.E.I.; Hu, J.; Yang, H.; Zhang, L.; Xu, X.; He, J. Phytohormonal and metabolism analysis of Brassica rapa L. ssp. pekinensis with different resistance during Plasmodiophora brassicae infection. BIOCELL 2020, 44, 751–767. [Google Scholar] [CrossRef]
Ludwig-Müller, J.; Bendel, U.; Thermann, P.; Ruppel, M.; Epstein, E.; Hilgenberg, W. Concentrations of indole-3-acetic acid in plants of tolerant and susceptible varieties of Chinese cabbage infected with Plasmodiophora brassicae Woron. New Phytol. 1993, 125, 763–769. [Google Scholar] [CrossRef]
Ludwig-Müller, J.; Epstein, E.; Hilgenberg, W. Auxin-conjugate hydrolysis in Chinese cabbage: Characterization of an amidohydrolase and its role during infection with clubroot disease. Physiol. Plant. 1996, 97, 627–634. [Google Scholar] [CrossRef]
Ludwig-Müller, J.; Pieper, K.; Ruppel, M.; Cohen, J.D.; Epstein, E.; Kiddle, G.; Bennett, R. Indole glucosinolate and auxin biosynthesis in Arabidopsis thaliana (L.) Heynh. glucosinolate mutants and the development of clubroot disease. Planta 1999, 208, 409–419. [Google Scholar] [CrossRef]
Rausch, T.; Butcher, D.N.; Hilgenberg, W. Indole-3-methylglucosinolate biosynthesis and metabolism in clubroot diseased plants. Physiol. Plant. 1983, 58, 93–100. [Google Scholar] [CrossRef]
Ugajin, T.; Takita, K.; Takahashi, H.; Muraoka, S.; Tada, T.; Mitsui, T.; Hayakawa, T.; Ohyama, T.; Hori, H. Increase in indole-3-acetic acid (IAA) level and nitrilase activity in turnips induced by Plasmodiophora brassicae infection. Plant Biotechnol. 2003, 20, 215–220. [Google Scholar] [CrossRef]
Ishikawa, T.; Okazaki, K.; Kuroda, H.; Itoh, K.; Mitsui, T.; Hori, H. Molecular cloning of Brassica rapa nitrilases and their expression during clubroot development. Mol. Plant Pathol. 2007, 8, 623–637. [Google Scholar] [CrossRef]
Müller, P.; Hilgenberg, W. Isomers of zeatin and zeatin riboside in clubroot tissue: Evidence for trans-zeatin biosynthesis by Plasmodiophora brassicae. Physiol. Plant. 2006, 66, 245–250. [Google Scholar] [CrossRef]
Devos, S.; Vissenberg, K.; Verbelen, J.P.; Prinsen, E. Infection of Chinese cabbage by Plasmodiophora brassicae leads to a stimulation of plant growth: Impacts on cell wall metabolism and hormone balance. New Phytol. 2005, 166, 241–250. [Google Scholar] [CrossRef] [PubMed]
Wang, D.; Pajerowska-Mukhtar, K.; Culler, A.H.; Dong, X. Salicylic acid inhibits pathogen growth in plants through repression of the auxin signaling pathway. Curr. Biol. 2007, 17, 1784–1790. [Google Scholar] [CrossRef]
Knaust, A.; Ludwig-Müller, J. The Ethylene signaling pathway is needed to restrict root gall growth in Arabidopsis after infection with the obligate biotrophic protist Plasmodiophora brassicae. J. Plant Growth Regul. 2013, 32, 9–21. [Google Scholar] [CrossRef]
Lahlali, R.; McGregor, L.; Song, T.; Gossen, B.D.; Narisawa, K.; Peng, G. Heteroconium chaetospira induces resistance to clubroot via upregulation of host genes involved in jasmonic acid, ethylene, and auxin biosynthesis. PLoS ONE 2014, 9, e94144. [Google Scholar] [CrossRef]
Ishida, M.; Hara, M.; Fukino, N.; Kakizaki, T.; Morimitsu, Y. Glucosinolate metabolism, functionality and breeding for the improvement of Brassicaceae vegetables. Breed Sci. 2014, 64, 48–59. [Google Scholar] [CrossRef]
Wittstock, U.; Halkier, B.A. Glucosinolate research in the Arabidopsis era. Trends Plant Sci. 2002, 7, 263–270. [Google Scholar] [CrossRef]
Ludwig-Müller, J. Glucosinolates and the clubroot disease: Defense compounds or auxin precursors? Phytochem. Rev. 2009, 8, 135–148. [Google Scholar] [CrossRef]
Eliu, T.; Ezhang, X.; Eyang, H.; Agerbirk, N.; Eqiu, Y.; Ewang, H.; Eshen, D.; Esong, J.; Eli, X. Aromatic glucosinolate biosynthesis pathway in Barbarea vulgaris and its response to Plutella xylostella Infestation. Front. Plant Sci. 2016, 7, 83. [Google Scholar] [CrossRef]
Clay, N.K.; Adio, A.M.; Denoux, C.; Jander, G.; Ausubel, F.M. Glucosinolate metabolites required for an Arabidopsis innate immune response. Science 2009, 323, 95–101. [Google Scholar] [CrossRef]
Butcher, D.N.; El-Tigani, S.; Ingram, D.S. The role of indole glucosinolates in the club root disease of the Cruciferae. Physiol. Plant Pathol. 1974, 4, 127–140. [Google Scholar] [CrossRef]
Ockendon, J.G.; Buczacki, S.T. Indole glucosinolate incidence and clubroot susceptibility of three cruciferous weeds [asparagus]. Trans. Br. Mycol. Soc. 1979, 72, 156–157. [Google Scholar] [CrossRef]
Chong, C.; Chiang, M.S.; Crete, R. Thiocyanate ion content in relation to clubroot disease severity in cabbages [by Plasmodiophora brassicae]. HortScience 1981, 16, 663–664. [Google Scholar]
Zamani-Noor, N.; Hornbacher, J.; Comel, C.J.; Papenbrock, J. Variation of glucosinolate contents in clubroot-resistant and -susceptible Brassica napus cultivars in response to virulence of Plasmodiophora brassicae. Pathogens 2021, 10, 563. [Google Scholar] [CrossRef] [PubMed]
Pedras, M.S.C.; Zheng, Q.-A.; Strelkov, S. Metabolic changes in roots of the oilseed canola infected with the biotroph Plasmodiophora brassicae: Phytoalexins and phytoanticipins. J. Agric. Food Chem. 2008, 56, 9949–9961. [Google Scholar] [CrossRef] [PubMed]
Langridge, P.; Fleury, D. Making the most of ’omics’ for crop breeding. Trends Biotechnol. 2011, 29, 33–40. [Google Scholar] [CrossRef] [PubMed]
Varshney, R.K.; Graner, A.; Sorrells, M.E. Genomics-assisted breeding for crop improvement. Trends Plant Sci. 2005, 10, 621–630. [Google Scholar] [CrossRef]
Shapiro, E.; Biezuner, T.; Linnarsson, S. Single-cell sequencing-based technologies will revolutionize whole-organism science. Nat. Rev. Genet. 2013, 14, 618–630. [Google Scholar] [CrossRef]
Laloum, T.; Martín, G.; Duque, P. Alternative splicing control of abiotic stress responses. Trends Plant Sci. 2018, 23, 140–150. [Google Scholar] [CrossRef]
Weckwerth, W. Green systems biology—From single genomes, proteomes and metabolomes to ecosystems research and biotechnology. J Proteom. 2011, 75, 284–305. [Google Scholar] [CrossRef]
Salih, R.; Pérez-López, E. Digitalization of clubroot disease index, a long overdue task. Horticulturae 2021, 7, 241. [Google Scholar] [CrossRef]
LeCun, Y.; Bengio, Y.; Hinton, G. Deep learning. Nature 2015, 521, 436–444. [Google Scholar] [CrossRef] [PubMed]
Crandall, S.G.; Gold, K.M.; Jiménez-Gasco, M.D.M.; Filgueiras, C.C.; Willett, D.S. A multi-omics approach to solving problems in plant disease ecology. PLoS ONE 2020, 15, e0237975. [Google Scholar] [CrossRef] [PubMed]
Donald, E.C.; Jaudzems, G.; Porter, I.J. Pathology of cortical invasion by Plasmodiophora brassicae in clubroot resistant and susceptible Brassica oleracea hosts. Plant Pathol. 2008, 57, 201–209. [Google Scholar] [CrossRef]
Khan, A.W.; Garg, V.; Roorkiwal, M.; Golicz, A.A.; Edwards, D.; Varshney, R.K. Super-Pangenome by integrating the wild side of a species for accelerated crop improvement. Trends Plant Sci. 2020, 25, 148–158. [Google Scholar] [CrossRef]
Ludwig-Müller, J. What can we learn from -Omics approaches to understand clubroot disease? Int. J. Mol. Sci. 2022, 23, 6293. [Google Scholar] [CrossRef]
Town, C.D.; Cheung, F.; Maiti, R.; Crabtree, J.; Haas, B.J.; Wortman, J.R.; Hine, E.E.; Althoff, R.; Arbogast, T.S.; Tallon, L.J.; et al. Comparative genomics of Brassica oleracea and Arabidopsis thaliana reveal gene loss, fragmentation, and dispersal after polyploidy. Plant Cell 2006, 18, 1348–1359. [Google Scholar] [CrossRef]
Cheung, F.; Trick, M.; Drou, N.; Lim, Y.P.; Park, J.-Y.; Kwon, S.-J.; Kim, J.-A.; Scott, R.; Pires, J.C.; Paterson, A.H.; et al. Comparative analysis between homoeologous genome segments of Brassica napus and its progenitor species reveals extensive sequence-level divergence. Plant Cell 2009, 21, 1912–1928. [Google Scholar] [CrossRef]
Neik, T.X.; Barbetti, M.J.; Batley, J. Current status and challenges in identifying disease resistance genes in Brassica napus. Front. Plant Sci. 2017, 8, 1788. [Google Scholar] [CrossRef]
Pinu, F.R.; Beale, D.J.; Paten, A.M.; Kouremenos, K.; Swarup, S.; Schirra, H.J.; Wishart, D. Systems biology and multi-omics integration: Viewpoints from the metabolomics research community. Metabolites 2019, 9, 76. [Google Scholar] [CrossRef]
Kumar, A.; Pathak, R.K.; Gupta, S.M.; Gaur, V.S.; Pandey, D. Systems biology for smart crops and agricultural innovation: Filling the gaps between genotype and phenotype for complex traits linked with robust agricultural productivity and sustainability. Omics 2015, 19, 581–601. [Google Scholar] [CrossRef] [PubMed]
Cramer, G.R.; Urano, K.; Delrot, S.; Pezzotti, M.; Shinozaki, K. Effects of abiotic stress on plants: A systems biology perspective. BMC Plant Biol. 2011, 11, 163. [Google Scholar] [CrossRef] [PubMed]
Daldoul, S.; Ben Amar, A.; Guillaumie, S.; Mliki, A. Integration of omics and system biology approaches to study grapevine (Vitis vinifera L.) response to salt stress: A perspective for functional genomics—A review. J. Int. Sci. Vigne Vin 2014, 48, 189–200. [Google Scholar] [CrossRef]
Lee, G.; Baek, N.; Park, K. Genetic Mapping of Resistant Genes in Brassica pekinensis Against Plasmodiophora brassicae Race 6. Plant Pathol. J. 2002, 18, 266–270. [Google Scholar] [CrossRef]
Hirai, M.; Harada, T.; Kubo, N.; Tsukada, M.; Suwabe, K.; Matsumoto, S. A novel locus for clubroot resistance in Brassica rapa and its linkage markers. Theor. Appl. Genet. 2004, 108, 639–643. [Google Scholar] [CrossRef]
Hayashida, N.; Takabatake, Y.; Nakazawa, N.; Aruga, D.; Nakanishi, H.; Taguchi, G.; Sakamoto, K.; Matsumoto, E. Construction of a practical SCAR marker linked to clubroot resistance in Chinese cabbage, with intensive analysis of HC352b genes. J. Jpn. Soc. Hortic. Sci. 2008, 77, 150–154. [Google Scholar] [CrossRef]
Cho, K.H.; Park, S.H.; Kim, K.T.; Kim, S.; Kim, J.S.; Park, B.S.; Woo, J.G.; Lee, H.J. Mapping quantitative trait loci (QTL) for clubroot resistance in Brassica rapa L. J. Hortic. Sci. Biotechnol. 2012, 87, 325–333. [Google Scholar] [CrossRef]
Kato, T.; Hatakeyama, K.; Fukino, N.; Matsumoto, S. Identificaiton of a clubroot resistance locus conferring resistance to a Plasmodiophora brassicae classified into pathotype group 3 in Chinese cabbage (Brassica rapa L.). Breed. Sci. 2012, 62, 282–287. [Google Scholar] [CrossRef]
Chu, M.; Yu, F.; Falk, K.C.; Liu, X.; Zhang, X.; Chang, A.; Peng, G. Identification of the clubroot resistance gene RPB1 and introgression of the resistance into canola breeding lines using a marker-assisted approach. Acta Horticulturae 2013, 1005, 599–605. [Google Scholar] [CrossRef]
Chen, J.; Jing, J.; Zhan, Z.; Zhang, T.; Zhang, C.; Piao, Z. Identification of novel QTLs for isolate-specific partial resistance to Plasmodiophora brassicae in Brassica rapa. PLoS ONE 2013, 8, e85307. [Google Scholar] [CrossRef]
Pang, W.; Liang, S.; Li, X.; Li, P.; Yu, S.; Lim, Y.P.; Piao, Z. Genetic detection of clubroot resistance loci in a new population of Brassica rapa. Hortic Environ Biotechnol. 2015, 55, 540–547. [Google Scholar] [CrossRef]
Nguyen, M.L.; Monakhos, G.F.; Komakhin, R.A.; Monakhos, S.G. The new clubroot resistance locus is located on chromosome A05 in Chinese cabbage (Brassica rapa L.). Russ. J. Genet. 2018, 54, 296–304. [Google Scholar] [CrossRef]
Hirani, A.H.; Gao, F.; Liu, J.; Fu, G.; Wu, C.; McVetty, P.B.E.; Duncan, R.W.; Li, G. Combinations of independent dominant loci conferring clubroot resistance in all four turnip accessions (Brassica rapa) from the European clubroot differential set. Front. Plant Sci. 2018, 9, 1628. [Google Scholar] [CrossRef] [PubMed]
Zhu, H.; Zhai, W.; Li, X.; Zhu, Y. Two QTLs controlling clubroot resistance identified from Bulked Segregant Sequencing in Pakchoi (Brassica campestris ssp. chinensis Makino). Sci. Rep. 2019, 9, 9228. [Google Scholar] [CrossRef]
Manzanares-Dauleux, M.J.; Delourme, R.; Baron, F.; Thomas, G. Mapping of one major gene and of QTLs involved in resistance to clubroot in Brassica napus. Theor. Appl. Genet. 2000, 101, 885–891. [Google Scholar] [CrossRef]
Fredua-Agyeman, R.; Rahman, H. Mapping of the clubroot disease resistance in spring Brassica napus canola introgressed from European winter canola cv. ‘Mendel’. Euphytica 2016, 211, 201–213. [Google Scholar] [CrossRef]
Zhang, H.; Feng, J.; Hwang, S.F.; Strelkov, S.E.; Falak, I.; Huang, X.; Sun, R. Mapping of clubroot (Plasmodiophora brassicae) resistance in canola (Brassica napus). Plant Pathol. 2016, 65, 435–440. [Google Scholar] [CrossRef]
Li, L.; Luo, Y.; Chen, B.; Xu, K.; Zhang, F.; Li, H.; Huang, Q.; Xiao, X.; Zhang, T.; Hu, J.; et al. A genome-wide association study reveals new loci for resistance to clubroot disease in Brassica napus. Front Plant Sci 2016, 7, 1483. [Google Scholar] [CrossRef]
Laperche, A.; Aigu, Y.; Jubault, M.; Ollier, M.; Guichard, S.; Glory, P.; Strelkov, S.E.; Gravot, A.; Manzanares-Dauleux, M.J. Clubroot resistance QTL are modulated by nitrogen input in Brassica napus. Theor. Appl. Genet. 2017, 130, 669–684. [Google Scholar] [CrossRef]
Aigu, Y.; Laperche, A.; Mendes, J.; Lariagon, C.; Guichard, S.; Gravot, A.; Manzanares-Dauleux, M.J. Nitrogen supply exerts a major/minor switch between two QTL s controlling Plasmodiophora brassicae spore content in rapeseed. Plant Pathol. 2018, 67, 1574–1581. [Google Scholar] [CrossRef]
Wagner, G.; Laperche, A.; Lariagon, C.; Marnet, N.; Renault, D.; Guitton, Y.; Bouchereau, A.; Delourme, R.; Manzanares-Dauleux, M.J.; Gravot, A. Resolution of quantitative resistance to clubroot into QTL-specific metabolic modules. J. Exp. Bot. 2019, 70, 5375–5390. [Google Scholar] [CrossRef] [PubMed]
Fredua-Agyeman, R.; Yu, Z.; Hwang, S.-F.; Strelkov, S.E. Genome-wide mapping of loci associated with resistance to clubroot in Brassica napus ssp. napobrassica (Rutabaga) accessions from Nordic countries. Front. Plant Sci. 2020, 11, 742. [Google Scholar] [CrossRef] [PubMed]
Botero-Ramírez, A.; Laperche, A.; Guichard, S.; Jubault, M.; Gravot, A.; Strelkov, S.E.; Manzanares-Dauleux, M.J. Clubroot symptoms and resting spore production in a doubled haploid population of oilseed rape (Brassica napus) Are Controlled by Four Main QTLs. Front. Plant Sci. 2020, 11, 604527. [Google Scholar] [CrossRef] [PubMed]
Dakouri, A.; Lamara, M.; Karim, M.M.; Wang, J.; Chen, Q.; Gossen, B.D.; Strelkov, S.E.; Hwang, S.-F.; Peng, G.; Yu, F. Identification of resistance loci against new pathotypes of Plasmodiophora brassicae in Brassica napus based on genome-wide association mapping. Sci. Rep. 2021, 11, 6599. [Google Scholar] [CrossRef] [PubMed]

Figure 1. Cauliflower infected with clubroot [(A) Cauliflower field heavily infested with clubroot disease, (B) Clubroot-infected cauliflower plant with characteristic root gall].

Figure 2. Schematic view of a model depicting metabolic and transcriptional changes happening in susceptible host after P. brassicae infection adopted and modified from Hasan et al. [263] with copy right permission (License Number—1236246-1) from Canadian Science Publishing and Copyright Clearance Center (www.copyright.com, Accessed on 16 June 2022).

Figure 3. Proposed mechanism of clubroot resistance in Brassica crops.

Figure 4. Existing bottlenecks in the utilization of multi-omics approaches to develop clubroot-resistant Brassica crops.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

Share and Cite

MDPI and ACS Style

Shaw, R.K.; Shen, Y.; Yu, H.; Sheng, X.; Wang, J.; Gu, H. Multi-Omics Approaches to Improve Clubroot Resistance in Brassica with a Special Focus on Brassica oleracea L. Int. J. Mol. Sci. 2022, 23, 9280. https://doi.org/10.3390/ijms23169280

AMA Style

Shaw RK, Shen Y, Yu H, Sheng X, Wang J, Gu H. Multi-Omics Approaches to Improve Clubroot Resistance in Brassica with a Special Focus on Brassica oleracea L. International Journal of Molecular Sciences. 2022; 23(16):9280. https://doi.org/10.3390/ijms23169280

Chicago/Turabian Style

Shaw, Ranjan K., Yusen Shen, Huifang Yu, Xiaoguang Sheng, Jiansheng Wang, and Honghui Gu. 2022. "Multi-Omics Approaches to Improve Clubroot Resistance in Brassica with a Special Focus on Brassica oleracea L." International Journal of Molecular Sciences 23, no. 16: 9280. https://doi.org/10.3390/ijms23169280

APA Style

Shaw, R. K., Shen, Y., Yu, H., Sheng, X., Wang, J., & Gu, H. (2022). Multi-Omics Approaches to Improve Clubroot Resistance in Brassica with a Special Focus on Brassica oleracea L. International Journal of Molecular Sciences, 23(16), 9280. https://doi.org/10.3390/ijms23169280

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Menu

Multi-Omics Approaches to Improve Clubroot Resistance in Brassica with a Special Focus on Brassica oleracea L.

Abstract

1. Introduction

2. Genomics

2.1. Pangenome to Identify Novel Resistance Gene Analogs (RGAs)

2.2. Resistance Sources, Genetics of Resistance and Identification of QTLs for Clubroot Resistance in B. oleracea

2.3. Fine Mapping and Identification of NBS-LRR Encoding R Genes for Clubroot Resistance

2.4. Pyramiding of Resistance Genes

2.5. Comparative Mapping Studies

3. Epigenomics

4. Transcriptomics

4.1. Hormone Signal Transduction during Brassica-P. brassicae Interaction

4.2. Cell Wall Modification and Lignification

4.3. Role of Sugars and SWEET Genes in Clubroot Disease Response

5. ncRNAomics

6. Proteomics

7. Metabolomics

8. Multi-Omics Opened Up New Avenues for Crop Improvement

9. Concluding Remarks and Perspectives

Supplementary Materials

Author Contributions

Funding

Institutional Review Board Statement

Informed Consent Statement

Data Availability Statement

Acknowledgments

Conflicts of Interest

References

Share and Cite

Article Metrics

Article Access Statistics

Further Information

Guidelines

MDPI Initiatives

Follow MDPI