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Article

Exploring the Genetic Potential for Multi-Resistance to Rust and Other Coffee Phytopathogens in Breeding Programs

by
Bruna Lopes Mariz
1,
Eveline Teixeira Caixeta
1,2,*,
Marcos Deon Vilela de Resende
2,
Antônio Carlos Baião de Oliveira
2,
Dênia Pires de Almeida
1 and
Danúbia Rodrigues Alves
1
1
Instituto de Biotecnologia Aplicada à Agropecuária (BIOAGRO), Universidade Federal de Viçosa, Avenida Peter Henry Rolfs, s/n, Viçosa 36570-900, MG, Brazil
2
Embrapa Café, Parque Estação Biológica, Av. W3 Norte, Brasília 70770-901, DF, Brazil
*
Author to whom correspondence should be addressed.
Plants 2025, 14(3), 391; https://doi.org/10.3390/plants14030391
Submission received: 21 December 2024 / Revised: 18 January 2025 / Accepted: 23 January 2025 / Published: 28 January 2025
(This article belongs to the Special Issue Molecular Approaches for Plant Resistance to Rust Diseases)
Browse Figures
Versions Notes

Abstract

:
The application of marker-assisted selection in coffee breeding programs accelerates the identification and concentration of target alleles, being essential for developing cultivars resistant to multiple diseases. In this study, a population was developed from artificial crossings between Timor Hybrid and Tupi Amarelo, with the aim of promoting the pyramiding of resistance genes to the main diseases and pests of Coffea arabica: coffee leaf rust (CLR), coffee berry disease (CBD), cercospora, and leaf miner. Resistance was confirmed by nine molecular markers at loci associated with CLR (genes SH3, CC-NBS-LRR, RLK, QTL-GL2, and GL5) and with CBD (gene Ck-1). The resistance to CLR, cercospora, and leaf miner was evaluated using phenotypic diagrammatic scales. Mixed models estimated population superiority in 16 morphoagronomic traits over four agricultural years. The introgression of resistance alleles to CLR and CBD was identified in 98.6% of the population, with 29% showing pyramiding of five resistance genes. These pyramiding genotypes showed 100% resistance to the leaf miner and 90% to cercospora. The traits were grouped into univariate, bivariate, and trivariate repeatability models, with 11 significant ones. These results are indicative of genetic variability to be explored in the development of cultivars with multiple resistances and high agronomic potential.

1. Introduction

The development and use of resistant cultivars have proven to be the most suitable methods for sanitary control in crops, due to the cost–benefit ratio, efficacy, easy adoption by producers, as well as the low environmental impact. In coffee improvement programs, interspecific and intraspecific crossings have been carried out to introgress resistance genes into cultivars with agronomic characteristics of commercial interest [1,2,3,4]. Therefore, the importance of gene stacking is to obtain cultivars with durable multiple resistance to different pathogens as well as optimal beverage quality, high productivity, and morphoagronomic characteristics that facilitate phytotechnical management [5,6,7].
Among the most aggressive and pandemic diseases is coffee leaf rust (CRL), the causal agent is the fungus Hemileia vastatrix Berk. et Br., the coffee berry disease (CBD) caused by Colletotrichum kahawae, and cercosporiosis (CER) caused by Cercospora coffeicola. The most prevalent pest in the crops is the coffee leaf miner (CLM) caused by Leucoptera coffeella. These pathogenic agents specialized in coffee have competitive advantages due to being hemibiotrophic with easy dispersion, capable of attacking at any phenological stage and exhibiting a high adaptability to different microclimates [8,9,10,11,12,13,14].
The CLR can cause productivity losses of over 50% due to the premature dropping of leaves and drying out of productive branches, which creates energy deficits for the development of flower buds [15]. More than 120 cultivars of arabica coffee are registered, most of which have had their resistance surpassed by the fungus H. vastatrix [16]. This scenario reinforces the importance of ongoing research in identifying new sources of resistance and in pyramiding resistance genes [17,18,19].
Currently, it is known that at least nine dominant resistance genes to CLR are present in coffee plants of different species, which can act together or individually. The SH1 to SH5 genes have been identified in C. arabica, but they have already been replaced by CLR in several coffee cultivation areas. The SH6 to SH9 genes were detected in C. canephora, and the SH3 gene was identified in C. liberica [5,20,21].
Some sources of resistance to CLR are known and used in coffee breeding programs; they are derived from Timor Hybrid (HdT), Icatu, BA series, and other Indian selections. The HdT is the only natural cross between C. arabica and C. canephora, and it possesses the SH5 gene, derived from arabica, and the SH6, SH7, SH8, and SH9 genes, derived from canephora [6,11,22,23]. Studies suggest the existence of two additional main resistance genes that have not yet been characterized, along with several others of lesser effect, which may or may not be associated with the genes SH1–SH9. These genes theoretically confer resistance to more than 50 races of H. vastatrix [17,24,25].
CBD has devastated many coffee plantations, especially on the African continent [26,27]. Productivity losses can reach 80% if no control measures are applied [28] and 100% in areas with heavy rainfall and high altitude [29]. So far, there are no reports of the disease in Latin America and Asia. However, CBD poses an imminent risk to coffee cultivation worldwide. There are various governmental efforts in preventive management to prevent its establishment in producing countries, as well as the development of resistant cultivars through preventive genetic improvement [10,26,30,31].
The CBD resistance in C. arabica is governed by three genes [32]. These genes are the R gene in the variety Rume Sudan, T gene in HdT, and a recessive k-gene found in both K7 and Rume Sudan. The T and R genes are dominant while the k-gene is recessive and only confers partial resistance to CBD in a homozygous state. The R locus has been reported to have multiple alleles (R1R1) in C. arabica variety Rume Sudan [31,32,33].
In addition to the main coffee diseases, CLR and CBD, plantations also face productive losses of up to 30% due to CER [13] and 50% due to CLR [9]. In advanced infections, there is leaf and lateral branch drop, accelerated maturation, and an increase in the incidence of defective grain formation [34,35]. So far, no resistance gene has been identified for CER and CLR, with resistance observed only through morphological markers and visual field analyses.
Molecular marker-assisted selection has been used in the genetic improvement of coffee plants to identify genes associated with resistance to CLR and CBD [36]. This approach is fundamental for characterizing resistance to the pathogen, even in the absence of its occurrence in the cultivation areas. Furthermore, it enables the understanding of inheritance dynamics and the genetic variability of populations intended for improvement [19,37].
In addition to molecular analysis, statistical methodologies applied to the agronomic traits of plants have been used to enhance the efficiency of selection in genetic improvement [38,39]. Mixed models allow for high accuracy in estimating variance components and genetic parameters, predicting gains from selection, and studying repeatability in perennial coffee plants [40]. These models enable the comparison of individuals over time and space, embedded in a complex data structure of morphoagronomic traits [41,42].
Despite advances in coffee breeding programs, the development of cultivars with multiple disease resistances is still a major challenge, especially due to the reliance on visual selection, which predominantly considers the phenotype of the plants [7,43]. This process is slow and often limited by the low efficiency in incorporating multiple genes for lasting resistance. Furthermore, there is a persistent lack of studies addressing the pyramiding of specific genes for simultaneous resistance to CLR, CBD, CER, and CLM in coffee cultivars, considering the complexity of the co-evolution of the pathosystem.
In this context, the present research is justified by the need to accelerate and improve genetic enhancement programs through the application of marker-assisted selection and robust data analysis using mixed models. These integrated approaches allow for the efficient identification and concentration of target alleles, optimizing time and resources for the development of superior cultivars. This study aims to develop and evaluate a population obtained through artificial hybridizations between cultivars of arabica coffee with sources of genetic resistance to CLR, CBD, CER, and the CLM. The main focus is the pyramiding of resistance genes and the identification of agronomically promising genotypes, contributing to overcoming current limitations and innovation in coffee genetic breeding.

2. Results

2.1. Assisted Selection by Molecular Markers for CLR and CBD

Molecular markers for CLR and CBD were developed for the analysis of results in agarose and polyacrylamide gels. These markers were integrated with fluorescent probes compatible with Sanger genotyping. All electropherograms detected in the marker region are presented in Figure 1, including the nonspecific ones.
The parents HdT MG 0357 and Tupi Amarelo IAC 5162 presented, respectively, the genotypes aaBBC-D-eeFF and aaBbccddE-Ff (Table 1). For the markers associated with locus B, 57.04% of the F2 individuals showed the dominant homozygous resistance allele, 33.80% were heterozygotes, and only 9.15% were recessive homozygotes (without the resistance allele). At locus C, the presence of the resistance allele (C_) was identified in 59.15% of the segregating progeny. In 74.65% genotypes of the population F2 was observed the presence of locus D. In 71.13% genotypes was observed the presence of locus E. No coffee plant in the F2 population presented the SH3 gene.
Based on the amplification by SAT 235 and SAT 207 markers (locus F), it was observed that 56.34% individuals of the analyzed coffee plants have the Ck-1 gene in homozygosity, 35.21% individuals in heterozygosity, and only 8.45% plants do not have the resistance gene for C. kahawae.
Only two individuals were homozygous recessive for all analyzed loci, representing 1.4% of the F2 population. This susceptibility can only be derived from the F1 hybrid C12P-8-B20-E5 (aaBbC_D_E_Ff), which is likely heterozygous for all loci. It is observed that in the genotype of F1 hybrid C12P-22-B20-E5 (aaBBC_D_eeFF), there is no possibility of double recessive mendelian segregation at loci B and F.
In the joint analysis for the four rust resistance loci (B, C, D, and E), 56 individuals had at least one resistance allele at each locus (B-C-D-E-), which represents 39.44% of the F2 population. Loci B and F were identified 45.07% as homozygous dominant for both loci (BBFF). Considering all loci/genes, 29% genotypes have dominant and double dominant alleles, with genotype BBC_D_E_FF.
The segregation test was significant only for loci D and E, with probabilities of 92% and 28%, respectively. For the other loci (A, B, C and F), the results were null, which may be attributed to the limited sample size, as the segregation test based on the chi-squared statistic is sensitive to the number of samples evaluated (Table 2).

2.2. Morphoagronomic Analyses

The variables that met the cut-off points and were useful in the analysis were 10 in 2018, 9 in 2020, 6 in 2021, and 11 in 2022 (Table 3). All evaluated traits showed significant genotypic variation in at least one year, indicating genetic variability in the population, except CF, which was null because it does not vary over the years. Based on h2a, 36% were in the range of 0.15 to 0.50, which are classified as moderate but are considered high in the scientific community for the evaluated quantitative traits. The estimated selective accuracy was higher than 0.60 in 53% of the traits and higher than 0.80 in 20% of the traits throughout all years, reflecting an overall average of 0.56.
Considering Y, in year 2018, it was significant with a low average (0.74 L/plant); in 2020, its h2a was null, with low accuracy, not significant, but with production four times higher than in 2018 (3.10 L/plant); in 2021, it was significant, with a low average and a marked discrepancy in performance between the best and worst genotypes; and in 2022, it was not significant and had a low average. The average VIG during the four evaluated years remained higher than six, which corresponds to coffee plants with adequate leafiness and homogeneous distribution of plagiotropic branches along the orthotropic branch. There was an increase in PH of coffee plants of about 39%, 6%, and 11% throughout the 2020, 2021, and 2022 harvests, respectively.
In the four evaluated years, the plants behaved resistant to coffee rust infection, with average scores on the diagrammatic scale below two. The CLR had high heritability in 2018 (0.39) and 2022 (0.50) and close to nullity in 2020 and 2021. In 2022, it was the year with the lowest incidences of CLR, CER, and CLM, with the highest h2a and Ac reported for these traits.
In the repeatability analyses (r), the cut-off point h2a > 0.03 was maintained, and non-significant character–year combinations were eliminated. Therefore, CF and SD characters could not be analyzed because they were not significant in any evaluated year. It is observed that the years 2018, 2020, 2021, and 2022 contributed with viable data for 10, 8, 4, and 7 traits, respectively (Table 4). Thus, it was possible to adopt triple repeatability models (3 years), double repeatability models (2 years), and univariate models (1 year).
The coefficients of r ranged from 0 to 0.59, with the majority of accuracies above 80%, and 11 significant traits/models. The heritability values of CD, QPB, LPB, and NNR were similar in h2g (~0.11) and h2ad (~0.06). For CLR and CLM, the genetic parameters were identical in r (0.15), h2g (0.14), and h2ad (0.08), and contradicting this pattern, CER had low and non-significant parameters by LRT.

2.3. Selection of Genotypes with Five-Gene Pyramiding for Resistance to CLR and CBD

In the F2 population, 29% of the genotypes exhibited pyramiding of five resistance genes, with loci B and F in homozygous dominant and loci C, D, and E containing at least one resistance allele (BBC_D_E_FF) for CLR and CBD (Table 5). The resistance alleles for H. vastatrix contributed to the phenotypic scores, using a diagrammatic scale, indicating resistance of all genotypes to coffee rust (average 1.58). These genotypes with double dominant genes for CLR and CBD were less affected by CER (score~2) and CLM (score~1.74), which may be an indication of cross-resistance. In general, all the genotypes with multiple resistance genes had high agronomic performance averages, considering the characteristics related to production (VIG = score 7, TF = score 3, PNR = 48, PCR = 0.64 metros, NNR = 20). The highest productive averages were from individuals 114 and 128, with 3.88 and 2.90 L per plant, respectively. These coffee plants had production up to three times higher when compared to the overall population average of 1.23 L per plant.

3. Discussion

In genetic breeding of coffee for disease resistance, genic pyramiding is the best way to obtain multiple loci that offer combined vertical resistance, thus limiting the infection of various pathogen races simultaneously [5,7]. The theory that “for every dominant resistance gene in the host, there is a dominant avirulence gene in the pathogen” was proposed by Flor in 1942 and is still accepted today to explain resistance in plants. Based on this theory, for a pathogen to overcome the resistance of genotypes, such as those identified in this work, that contain up to five resistance genes, it is necessary for mutations in five avirulence genes of the fungus to occur [44].
From the crossings between HdT MG0357 and Tupi Amarelo IAC 5162, genes for resistance to CLR and CBD were introduced (Table 1). According to the adoption of assisted selection, more than 60% of the genotypes of the segregating population had introgression of resistance to races I and II, identified at loci B and C. The combination of these loci (B and C) for these breeds allows for greater selection pressure exerted on the pathogen, making its infection with the genotype more difficult. In the Americas, 18 races of H. vastatrix have been reported, with race II being the most prevalent in the susceptible cultivars planted, which demonstrates the importance of the results obtained from this study [8,15]. The absence of the SH3 resistance allele (locus A) in the F1 and F2 genotypes was predictable, as the population does not result from crosses with C. liberica, the source of this resistance [18]. Future backcrosses with this progeny may be carried out for the introgression of the SH3 gene.
In 70% of the population, introgression of resistance was identified in loci D and E, corresponding to genes belonging to the CC-NBS-LRR and LRR-RLK families. These gene families correspond to the first line of defense of the plant against infection, as they are a diverse group of transmembrane receptors that can recognize molecular patterns associated with pathogens and activate an immune response [25,45]. The Coffea-H. vastatrix pathosystem is complex due to the constant co-evolution of races against the distinct defense mechanisms of plants [11,19,21]. Transcriptome and interactome studies of HdT identified target genes involved in a pre-haustorial defense response, associated with resistance to H. vastatrix [17].
Due to the crossings with the resistance source HdT, 90% of the F2 population exhibited resistance to CBD. CBD is a very aggressive disease with the potential to cause collapse in productive systems that have susceptible cultivars [27]. Research worldwide is conducted to monitor its migration and variations in virulence [29,30,46]. Even without reports of C. kahawae in South America [10,26], the introgression of the Ck-1 gene into improved varieties is an important control measure in case the pathogen becomes established in the territory. This preventive improvement is only possible with the implementation of a molecular marker, to characterize and select resistance to CBD, without the presence of the pathogen [7,31].
Based on the genotypic results obtained, the individuals of the F2 population that exhibited pyramiding of five resistance genes (BBC_D_E_FF) were identified as the most promising for resistance to the diseases CLR and CBD (Table 5). These genotypes represent 29% of the population and exhibit a genetic combination with high potential for multiple resistance, making them priority candidates for advancement in subsequent generations.
With the exception of locus E, all other loci were genotyped using two molecular markers. The use of two or more markers at the same locus reinforces the reliability of the results, avoiding the selection of plants that have the marker but lost the resistance allele due to recombination [30,47,48]. Furthermore, studies that validated and applied these molecular markers confirmed their consistency, evidencing that their results are not impacted by sample size, as observed in the segregation test (Table 2) [24,25,30,47,49,50,51,52,53].
The REML/BLUP modeling used for the 16 morphoagronomic traits demonstrated effectiveness by providing statistical significance and high selective precision for the studies of genetic parameters and repeatability (Table 3 and Table 4). The LRT proved that most of the traits were significant with the combinations of crops, which justifies the repeatability models being the best to describe the behavior of time on perennial species. In general, the use of repeatability leads to higher accuracy, especially in situations of low heritability and repeatability simultaneously, as observed in Table 3 and Table 4.
For the traits FUC (0.19) and FMC (0.13), repeatability was high, considering that they are governed by many genes and highly influenced by environmental conditions from fruit formation to harvest. The low magnitudes of r in some traits show the lack of regularity in the repetition of behavior in the following evaluation years, consequently causing difficulties in the process of selecting superior genotypes based on few years of evaluation.
The number of measurements required for high accuracies generally requires several years of evaluations, which burdens the costs and time of coffee genetic improvement. It is estimated that to obtain 90% of the maximum accuracy, 17 measurements with heritability of 0.20 are required, which according to the literature is common for the traits of yield, stem diameter, plant height, crown diameter, and rust resistance. For traits with high heritability, for example, 0.50, the recommended number of replications is four to achieve 90% accuracy [38].
Another contributing factor to the low genetic parameters is the degree of relatedness between the parents since both are cultivars derived from HdT accessions. Previous studies on genetic diversity confirm that HdT MG 0357 and Tupi Amarelo IAC 5162 belong to divergent genetic groups but with a considered moderate genetic distance [54]. The genus Coffea has low genetic diversity, attributed to domestication and the perennial nature of the crop, being even more limited in C. arabica due to autogamy and the multiple genetic bottlenecks that occurred during polyploidization [1,2,3,4]. It also reports low genetic parameters in coffee arabica breeding programs for resistance to CLR, using artificial crossings between HdT and arabicas, and emphasizes the importance of morphoagronomic characterization combined with MAS to achieve better selective gains.
Although it may seem contradictory for the traits related to productivity to have more expressive genotypic variances than the actual production, this scenario is common due to the need for a greater number of evaluations, as reported in this and other studies [50,51]. Even so, there is an intrinsic genetic correlation among the characteristics related to productivity, such as Y, VIG, PH, CD, SD, QPB, LPB, and NNR.
The low severity of CER (scores~2) may be related to resistance genes that have not yet been characterized in these genotypes and also the good fertility of plants, which is a decisive factor for the low incidence of this disease [34,35].
Tolerance to CLM is observed in cultivars derived from the Sarchimor group, such as Tupi IAC 1669-33, which is an ancestral parent that contributed to the formation of the studied population [9]. Studies found that despite the high percentage of leaves damaged by CLM, the cultivar Tupi IAC 1669-33 demonstrated the ability to retain its leaves for a longer time, showing a better response to the attack [55]. Cultivars of C. arabica from HdT and resistant to rust may compromise the performance of the coffee leaf miner by prolonging the duration of the pupal development stage and reducing the size of the adults. The hypothesis is that crossings with the HdT could have modified the profile of nutrients and secondary metabolites in the leaf tissues, unfavorably for the development of the CLM [56].
Using the phenotypic averages obtained via the diagrammatic scale, it is possible to infer that the population is resistant to CLR throughout the years evaluated. These averages (close to 2) are related to hypersensitivity reactions in the leaf, which occur as an immune response to parasitic infection through encapsulation of haustoria in the intercellular spaces by lignification of cell walls and hypertrophy of plant cells, and/or increased activity of oxidative enzymes [43]. Therefore, the H. vastatrix fungus can penetrate the tissues, but it usually stops developing after the first haustoria formed, which is called post-haustorial resistance. Plants without any symptoms (score 1) can exhibit pre-haustorial resistance, which prevents the development of hyphae and the formation of haustoria in the tissues [15,20,21].
Despite the expected segregation in F2, the population behaving resistant to CLR is a strong indication that there was introgression of genes for this, corroborating with the molecular data that showed the pyramiding of resistance genes for H. vastatrix. No correlations were identified between the incidences of CLR, CER, and CLM among themselves and with Y, a fact that corroborates with [53]. However, [57] obtained positive and high correlations between CLR and CLM with heritability close to 90% and also did not obtain significant correlations between Y, CLR, and CLM.
A selection of 29% of the population with five pyramids of resistance genes to CLR and CBD, combined with field resistance to CER (average score of 2) and CLM (average score of 1.7), characterizes these genotypes as carriers of multiple resistances (Table 5). The FMC in this selection presented genotypes with variations in precocity, ranging from early to late (grades 2–5). This diversity enables the staggering of planting plots, optimizing the harvest due to maturation in stages. In addition, these genotypes contained a plant architecture for field distribution typical for arabica coffees, with averages of 1.30 m for PH, 0.35 m for SD, and 1.43 m for CD. These genotypes show promise for the advancement of generation, with selection gains aimed at increasing productivity, improving beverage quality, and monitoring multiple resistances.
The process of this genetic improvement program has already been ongoing for 15 years due to the hybridizations between the parent strains HdT MG 0357 and Tupi Amarelo IAC 5162. Considering the crossings made with their ancestors, it is estimated that the program has more than 35 years of history. Through robust statistics, morphoagronomic characterizations, and the adoption of marker-assisted selection in the upcoming generations, it is expected to accelerate the selection process. Thus, within a period of 10 years, it will be feasible to launch competitive cultivars that are highly resistant to H. vastatrix and other pathogens.

4. Materials and Methods

4.1. Prospecting for the Improvement Program

Artificial crosses were made between access of the HdT MG 0357, belonging to the Germplasm Bank of the Agricultural Research Corporation of Minas Gerais (EPAMIG, Minas Gerais, Brazil) and the lineage called Tupi Amarelo IAC 5162, originating from the Breeding Program of the Intituto Agronomico de Campinas (IAC, Campinas, Brazil).
The HdT MG 0357 is derived from the access HdT UFV 441-04, which was introduced in Brazil from the Center for Research into Coffee Rusts (CIFC), located in Oeiras, Portugal. These hybrids have good beverage quality, tall statures, medium maturation cycles, and high resistance to diseases and pests.
The Tupi Amarelo IAC 5162 line is a yellow-fruited Sarchimor, selected by the IAC. This line was developed from the identification of a plant with yellow fruits in a crop of the Tupi IAC 1669-33 cultivar. This cultivar originated from the hybrid CIFC H361-4, which is derived from the cross between Villa Sarchi CIFC 971/10 and HdT CIFC 832/2. Therefore, the line Tupi Amarelo IAC 5162 is probably derived from a natural cross between a plant of Tupi IAC 1669-33 and a coffee plant of the Catuaí Amarelo cultivar (Caturra × Mundo Novo). The Tupi IAC 1669-33 has red fruits, a high percentage of grains classified in sieve 16 and above, drink quality similar to Bourbon Vemelho, and moderately early and uniform maturation. It also has resistance to H. vastatrix, low stature, large fruits, and high productive potential.
The crossing was carried out with the main objective of pyramiding resistance genes to H. vastatrix, aiming for longer-lasting resistance to CLR and incorporating resistance to other diseases such as CBD. Other purposes of the cross were plant height reduction and taking advantage of the superior beverage quality potential of the HdT MG0357 accession, which was previously verified in various sensory analysis tests.
Previous studies were conducted on the genetic potential and combining ability of the cross HdT MG0357 × Tupi Amarelo IAC 5162 and the two F1 plants generated (C12P-8-B20-E5 and C12P-22-B20-E5) [54]. Subsequently, the F1 generation plants were self-pollinated to generate an F2 population composed of 142 genotypes, cultivated in Viçosa, MG, Brazil (20°44′28.4″ S, 42°50′53.9″ W).
The design was in augmented blocks with a 3.0 × 0.80 m spacing. The cultivars Paraíso MG H419-1 and Catuaí Vermelho IAC 144 were used as controls, with three plants of each control per block. The control plant Paraíso MGH419-1 (Catuaí Amarelo IAC 30 × HdT UFV 445-46) was used for its high resistance to rust, short stature, medium maturation, high productivity, and cup quality. The Catuaí Vermelho IAC 144 (Caturra Amarelo IAC 476-11 × Mundo Novo IAC 374-19) was chosen for its high cultivation in Brazil (Figure 2).

4.2. Molecular Marker-Assisted Selection for CLR and CBD

The genetic material was extracted from the population according to the methodology described in [58]. The DNA concentration was quantified using Nanodrop (NanoDrop Technologies, Wilmington, EUA), and the quality was verified by 1% agarose gel electrophoresis.
For molecular marker-assisted selection, specific loci markers were used, previously identified as associated with genes that confer resistance to CLR and CBD. In the analysis of data for resistance to H. vastatrix, locus A, which corresponds to the SH3 gene, was considered. We identified two markers SAT 244 and BA 124-12K, segregating at 0 cM with the SH3 gene in the genetic mapping study of an F2 population (Matari × S.288) [47]. The S.288 line carried the SH3 gene for resistance to CLR introgressed from C. liberica. Loci B and C corresponded to gene/QTL regions for resistance to races I, II, and pathotype 001 of H. vastatrix. Molecular markers associated with two groups of the genetic linkage map were identified. Markers SSR 16 and CaRHv8 were associated with Gene/QTL-GL2 at an approximate distance of 3 cM, and marker CaRHv9 was associated with 2.3 cm from Gene/QTL-GL5. These identified loci/QTL came from HdT (accession HdT-UFV 443-03), one of the main sources of resistance to coffee rust [36,59]. The D locus corresponds to the CC-NBS-LRR gene that confers resistance to H. vastatrix. In silico analysis, based on information generated by the Brazilian Coffee Genome Project [52], identified DNA sequences potentially involved in coffee disease resistance, for which they developed and validated the CARF 005 marker in the accession (HdT CIFC 832/2). The region amplified by the CARF 005 marker was confirmed as belonging to the HdT 832/2 accession by sequencing a BAC clone [25]. Furthermore, the authors [25], based on the availability of differential coffee clones, stated that it could be one of the unidentified SH genes that have not yet been supplanted (at least in Brazil) in HDT. The E locus corresponded to the Leucine-rich repeat receptor-like protein kinases (LRR-RLKs) gene family. This gene was identified by [24] through the sequencing of a BAC clone from accession 832/2. From the nucleotide sequence of the gene, the authors [24] developed the marker LRR-RLK2 and confirmed by evaluating differential coffee clones that it could also be one of the unidentified SH genes. Regarding the F locus, it corresponded to the resistance gene to another important coffee disease, CBD. This gene was named Ck-1, originating from the resistance source HdT, and was characterized using a genetic mapping approach. In this work, two SSR markers were identified as associated with the Ck-1 gene [30]. The marker SAT 207 was mapped at 17.2 cM from the gene, while SAT 235 segregated at 0 cM with the Ck-1 gene. These two markers were validated for use in assisted selection by [49] (Table 6).
All genotyping was conducted by capillary electrophoresis on an ABI 3130xl Genetic Analyzer—AppliedBiosystems.
  • Assisted selection for the SH3 gene—Locus A
For assisted selection, the molecular markers SAT 244 and BA 124-12K were used. The SAT 244 is codominant, and the BA 124-12K-f is dominant; so, when analyzed together, they can identify heterozygotes, dominant homozygotes, and recessive homozygotes.
The accesses CIFC H147/1, CIFC H153/2, and S.288/23 were used as controls carrying the resistance gene, and the cultivars Caturra Vermelho CIFC 19/1 and Catuaí Amarelo IAC 64 (UFV 2148/57) were used as non-carrying controls of the resistance gene to CBD.
In the amplification reaction of the fragments, 2 µL of genomic DNA at a concentration of 25 ng·µL−1 (50 ng) was used, 2.5 µL of PCR reaction buffer 1×, 1 µL of MgCl2 (2 mM), 0.25 µL of dNTP (0.1 mM), 5 µL of forward primer (0.4 μM), 5 µL of reverse primer (0.4 μM), 0.2 µL of Taq DNA polymerase enzyme (0.5 units), completing the volume to 25 µL with ultrapure water [47].
The amplification of the fragments consisted of denaturation at 95 °C for 5 min, 35 cycles of 94 °C for 45 s for denaturation, annealing at 52 °C for SAT 244 and 56 °C for BA 124-12K-f for 45 s, extension at 72 °C for 45 s, and final extension at 72 °C for 10 min.
  • Assisted selection for QTL LG2—Locus B
For assisted selection, the molecular markers CaRHv8 and SSR 16 were used. The CaRHv8 is a dominant marker that identifies only the recessive allele, that is, the presence of allele amplification indicates being (b_) or being able to be homozygous recessive (bb) or heterozygous (Bb), and the absence of allele amplification indicates being homozygous dominant (BB). The SSR 16 marker presents a codominant pattern, which identifies homozygous and heterozygous individuals (BB, Bb, and bb).
As control, the HdT UFV 443-03 genitors were used as resistant and Catuaí Amarelo IAC 64 (UFV 2148/57) as susceptible, as they originated the F2 population of the genetic map where the loci/QTL associated with resistance to races I, II, and pathotype 001 were identified.
The reaction for CaRHv8 was performed with 2 µL of genomic DNA at a concentration of 25 ng·µL-1 (50 ng), 2 µL of PCR reaction buffer (1×), 0.8 µL of MgCl2 (2 mM), 0.3 µL of dNTP (0.15 mM), 1 µM of each primer, and 0.2 µL of Taq DNA polymerase enzyme (0.5 units), with a final volume of 20 µL. A program with denaturation at 95 °C for 5 min, 35 cycles of 94 °C for 30 s, annealing at 65 °C for 30 s, extension at 72 °C for 1 min, and final extension at 72 °C for 10 min was used.
The reaction for the SSR 16 marker was similar to CaRHv8; it only differs from the conditions of the CaRHv8 marker by using 0.4 µL of MgCl2 (0.6 mM). The cycling program had an initial denaturation phase at 94 °C for 2 min; 10 touchdown cycles at 94 °C for 30 s, with annealing temperature decreasing by 1 °C per cycle (66–57 °C) for 30 s, and extension at 72 °C for 30 s; followed by 30 cycles of denaturation at 94 °C, annealing at 57 °C, and extension at 72 °C, each step lasting 30 s. The final extension was performed at 72 °C for 10 min.
  • Assisted selection for gene/QTL of LG5—Locus C
For assisted selection, the molecular marker CaRHv9 was used. It is a dominant marker that only identifies the dominant allele, that is, the presence of allele amplification indicates being (C_), which means it can be homozygous dominant (CC) or heterozygous (Cc), and the absence of allele amplification indicates being homozygous recessive (cc). We used the same controls, concentration of reagents, and amplification conditions as CaRHv8.
  • Assisted selection for CC-NBS-LRR—Locus D
For assisted selection, the molecular marker CARF 005 was used. The CARF 005 is a dominant marker that allows the identification of genotypes D_ and dd. The controls used were HdT CIFC 832/2 and Caturra Vermelho CIFC 19/1, as resistant and susceptible, respectively.
The reaction conditions were 2 µL of genomic DNA at a concentration of 25 ng·µL−1 (50 ng), 2 µL of PCR reaction buffer (1×), 0.4 µL of MgCl2 (2 mM), 0.3 µL of dNTP (0.15 mM), 1 µM of each primer, 0.2 µL of Taq DNA polymerase enzyme (0.5 units), and water up to a final volume of 20 µL. The cycling program was 95 °C for 5 min for denaturation, 35 cycles of 94 °C for 30 s, 60 °C for 35 s for annealing, 72 °C for 1 min for extension, and finally strand closure at 72 °C for 10 min.
  • Assisted selection for HdT_LRR_RLK2—Locus E
For assisted selection, the molecular marker LRR_RLK2 was used. The LRR_RLK2 is a dominant marker capable of identifying genotypes E_ and ee. The controls used were the HdT CIFC 832/2 as resistant and Caturra Vermelho CIFC 19/1 as susceptible. The marker was amplified under the same reaction conditions and cycling program as the CARF 005 marker, except for the annealing temperature, which occurred at 66 °C for 30 s.
  • Assisted selection for Ck-1—Locus F
For assisted selection, the molecular markers SAT 235 and SAT 207 were used. In the analysis of the population with these markers, the HdT UFV 377-15, UFV 440-10, and cultivar MGS Catiguá 3 were used as controls carrying the Ck-1 gene. The susceptible controls used were Caturra Vermelho CIFC 19/1 and Catuaí Amarelo IAC 64 (UFV 2148-57).
In the amplification reaction of the fragments, 2 µL of genomic DNA at a concentration of 25 ng·µL−1 (50 ng), 2.5 µL of PCR reaction buffer 1×, 1 µL of MgCl2 (2 mM), 0.25 µL of dNTP (0.1 mM), 5 µL of forward primer (0.4 μM), 5 µL of reverse primer (0.4 μM), and 0.2 µL of Taq DNA polymerase enzyme (0.5 units) were used, completing the final volume of 25 µL. The amplification conditions consisted of a denaturation phase at 95 °C for 5 min; 35 cycles at 94 °C for 45 s; annealing at 50 °C for 45 s; extension at 72 °C for 45 s; and the final extension at 72 °C for 10 min.
The segregation of the markers was determined using the chi-squared test.

4.3. Evaluating Morphoagronomic Traits

In the fruit ripening stage, 16 phenotypic traits related to production, disease/pest resistance, and beverage quality were measured in the crops from 2018 to 2022 (Table 7).
Statistical analyses were performed using the Restricted Maximum Likelihood (REML) methodology to estimate the variance components by maximum likelihood. These components provide the basis for the Best Linear Unbiased Prediction (BLUP), used for predicting genetic values.
In the individual analyses, the model used was y = Xr + Za + Wp + e, where y is the data vector, r is the vector of repeat effects (assumed to be fixed) added to the overall mean, a is the vector of individual additive genetic effects (assumed to be random), p is the vector of plot effects, and e is the vector of errors or residuals (random). The uppercase letters represent the incidence matrices for the referred effects.
In the repeatability analysis, the model used was y = Xm + Zg + Wb + Tp + e, where y is the data vector, m is the vector of the effects of the measurement–repetition combinations (assumed to be fixed) added to the overall mean, g is the vector of genotypic effects (assumed to be random), b is the vector of block effects (assumed to be random), p is the vector of permanent environmental effects (in the case of plots) (random), and e is the vector of errors or residuals (random).
To adjust the model to more rigorous criteria and determine the significance of the characteristic, the following parameters were considered: individual accuracy greater than 0.5, p-value less than 0.25, and additive heritability greater than 0.03 [40]. All analyses were performed using Selegen REML/BLUP software version 2020 [60].

Author Contributions

Conceptualization, E.T.C., M.D.V.d.R. and A.C.B.d.O.; methodology, B.L.M. and A.C.B.d.O.; validation, B.L.M., D.P.d.A., D.R.A. and M.D.V.d.R.; formal analysis, B.L.M., M.D.V.d.R., D.P.d.A. and D.R.A.; resources, E.T.C. and A.C.B.d.O., writing—original draft preparation, B.L.M., D.P.d.A. and D.R.A.; writing—review and editing, B.L.M., E.T.C., M.D.V.d.R., A.C.B.d.O., D.P.d.A. and D.R.A.; supervision, E.T.C.; project administration, E.T.C.; funding acquisition, E.T.C. and A.C.B.d.O. All authors have read and agreed to the published version of the manuscript.

Funding

This work was financially supported by the Brazilian Coffee Research and Development Consortium (Consórcio Pesquisa Café, CBP&D/Café), the Foundation for Research Support of the State of Minas Gerais (FAPEMIG), the National Council of Scientific and Technological Development (CNPq), the National Institutes of Science and Technology of Coffee (INCT/Café), and Coordination for the Improvement of Higher Education Personnel (CAPES).

Data Availability Statement

In this manuscript, the molecular markers used in the analysis are previously available in the literature and referenced in the manuscript. The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

Acknowledgments

We are grateful the funding support received from the Brazilian Coffee Research and Development Consortium (Consórcio Pesquisa Café, CBP&D/Café), the Foundation for Research Support of the State of Minas Gerais (FAPEMIG), the National Council of Scientific and Technological Development (CNPq), the National Institutes of Science and Technology of Coffee (INCT/Café), and Coordination for the Improvement of Higher Education Personnel (CAPES).

Conflicts of Interest

The authors declare no conflicts of interest.

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Plants 14 00391 g001
Figure 1. Description of the molecular markers for Hemileia vastatrix and Colletotrichum kahawae, covering the locus, the length of the generated electropherogram, and the identified alleles. * Electropherograms relevant for analysis are highlighted in blue, with dark blue representing dominant alleles and light blue representing recessive ones.
Figure 1. Description of the molecular markers for Hemileia vastatrix and Colletotrichum kahawae, covering the locus, the length of the generated electropherogram, and the identified alleles. * Electropherograms relevant for analysis are highlighted in blue, with dark blue representing dominant alleles and light blue representing recessive ones.
Plants 14 00391 g001
Plants 14 00391 g002
Figure 2. Prospecting of the coffee improvement program for durable multiple resistance to diseases and pests, resulting from the integration of genotypes for resistance to Hemileia vastatrix.
Figure 2. Prospecting of the coffee improvement program for durable multiple resistance to diseases and pests, resulting from the integration of genotypes for resistance to Hemileia vastatrix.
Plants 14 00391 g002
Table 1. Molecular marker-assisted selection associated with coffee rust resistance: SH3 gene (locus A); locus/QTL for resistance to races I, II, and pathotype 001 (loci B and C); CC-NBS-LRR (locus D); HdT_LRR_RLK2 (locus E); and resistance to CBD, gene Ck-1 (locus F).
Table 1. Molecular marker-assisted selection associated with coffee rust resistance: SH3 gene (locus A); locus/QTL for resistance to races I, II, and pathotype 001 (loci B and C); CC-NBS-LRR (locus D); HdT_LRR_RLK2 (locus E); and resistance to CBD, gene Ck-1 (locus F).
N°Individual *GenotypeN°IndividualGenotypeN°IndividualGenotype
1HdT MG 0357aaBBC-D-eeFF50T22 B20 P20aaBBccD-E-Ff99T23 B21 P33aaBBC-D-E-FF
2Tupi IAC 5162aaBbccddE-Ff51T22 B20 P21aaBbccD-eeFf100T23 B21 P36aaBBC-D-E-Ff
3C12-P8-B20-E5aaBbC_D_E_Ff52T22 B20 P25aabbccD-E-Ff101T23 B21 P37aaBBC-ddE-FF
4C12-P22-B20-E6aaBBC_D_eeFF53T22 B20 P26aabbccD-eeFf102T23 B21 P39aaBbC-ddE-FF
5T22 B19 P1aaBBC-D-E-ff54T22 B20 P27aaBBccddE-Ff103T23 B21 P40aaBBC-ddE-FF
6T22 B19 P3aaBBC-ddE-Ff55T22 B20 P29aabbccddeeff104T23 B21 P41aaBBC-ddE-FF
7T22 B19 P4aaBbccddeeFf56T22 B20 P30aaBbccD-eeFF105T23 B21 P42aaBBC-ddE-FF
8T22 B19 P5aaBbccddeeff57T22 B20 P31aaBbccD-E-Ff106T23 B21 P44aaBBC-ddE-FF
9T22 B19 P6aaBbC-D-eeFf58T22 B20 P32aaBBccD-E-FF107T23 B21 P45aaBbC-ddE-FF
10T22 B19 P7aaBbC-D-eeFf59T22 B20 P34aabbccD-eeFf108T23 B21 P46aaBBC-ddE-FF
11T22 B19 P9aaBbC-D-eeFf60T22 B20 P35aaBBccddeeff109T23 B21 P47aaBBC-D-E-FF
12T22 B19 P10aaBbC-D-eeFF61T22 B20 P36aaBbccD-E-Ff110T23 B21 P48aaBBC-D-E-FF
13T22 B19 P11aaBbC-D-E-FF62T22 B20 P37aaBBccddeeFf111T23 B21 P50aaBBC-ddE-FF
14T22 B19 P12aaBbC-D-eeFF63T22 B20 P38aaBbccD-E-Ff112T23 B22 P1aaBBC-D-E-Ff
15T22 B19 P13aaBBC-D-E-Ff64T22 B20 P40aaBBccD-E-FF113T23 B22 P3aaBBC-D-E-FF
16T22 B19 P15aaBbC-D-eeFF65T22 B20 P42aaBbccD-eeFf114T23 B22 P4aaBbC-D-E-FF
17T22 B19 P16aaBbC-D-E-Ff66T22 B20 P43aaBbccD-E-Ff115T23 B22 P5aaBBC-ddE-FF
18T22 B19 P17aaBbC-D-eeFf67T22 B20 P44aabbccD-E-Ff116T23 B22 P6aaBBC-D-E-FF
19T22 B19 P19aaBBC-D-eeFf68T22 B20 P46aaBbccddeeff117T23 B22 P7aaBBC-D-E-FF
20T22 B19 P20aabbccddeeFf69T22 B20 P48aabbccD-E-Ff118T23 B22 P8aaBBC-D-E-Ff
21T22 B19 P21aabbccD-E-Ff70T22 B20 P49aaBbccddE-FF119T23 B22 P9aaBBC-D-E-FF
22T22 B19 P22aaBbccD-eeFf71T22 B20 P50aaBBccD-E-FF120T23 B22 P11aaBbC-D-E-Ff
23T22 B19 P26aaBBccddeeFf72T23 B21 P1aaBBccD-E-FF121T23 B22 P12aaBbC-D-E-FF
24T22 B19 P35aaBbccD-E-Ff73T23 B21 P2aaBbccD-E-FF122T23 B22 P14aaBBC-ddE-FF
25T22 B19 P36aaBBccD-eeFf74T23 B21 P3aaBBccD-E-FF123T23 B22 P15aaBbC-ddE-FF
26T22 B19 P39aaBbccD-E-FF75T23 B21 P4aaBBC-D-E-FF124T23 B22 P17aaBBC-D-E-FF
27T22 B19 P40aaBbccD-E-FF76T23 B21 P5aaBBC-D-E-FF125T23 B22 P18aaBBC-D-E-FF
28T22 B19 P41aaBbccddeeFf77T23 B21 P6aaBBC-ddE-FF126T23 B22 P19aaBBC-D-E-FF
29T22 B19 P42aaBbccddeeFf78T23 B21 P7aaBbC-D-E-Ff127T23 B22 P20aaBBC-D-E-FF
30T22 B19 P43aaBbccD-E-Ff79T23 B21 P9aaBBC-D-E-FF128T23 B22 P21aaBBC-D-E-FF
31T22 B19 P44aaBBccD-eeFf80T23 B21 P10aaBbC-D-E-FF129T23 B22 P23aaBBC-D-E-FF
32T22 B19 P46aaBBccddeeFF81T23 B21 P13aaBbC-D-E-FF130T23 B22 P25aaBBC-D-E-FF
33T22 B19 P47aaBbccD-E-Ff82T23 B21 P15aaBBC-D-E-FF131T23 B22 P28aaBBC-ddeeFF
34T22 B19 P48aaBBccD-E-Ff83T23 B21 P16aaBBC-D-E-FF132T23 B22 P30aaBBC-D-E-FF
35T22 B19 P49aaBbccD-eeFf84T23 B21 P17aaBBC-D-E-FF133T23 B22 P34aaBBccD-E-FF
36T22 B19 P50aaBbccddeeff85T23 B21 P18aaBBC-ddE-FF134T23 B22 P35aabbC-D-E-Ff
37T22 B20 P3aabbccD-eeFf86T23 B21 P19aaBBC-ddE-FF135T23 B22 P37aaBBC-D-E-FF
38T22 B20 P4aaBbccddeeff87T23 B21 P20aaBBC-ddE-Ff136T23 B22 P38aaBBC-D-E-FF
39T22 B20 P5aaBbccD-eeFf88T23 B21 P21aaBBC-D_E-FF137T23 B22 P39aaBBC-D-E-FF
40T22 B20 P6aaBBccD-eeFF89T23 B21 P22aaBBC-D-E-FF138T23 B22 P40aaBBC-D-E-FF
41T22 B20 P7aaBbccD-eeff90T23 B21 P24aaBBC-D-E-FF139T23 B22 P41aaBBC-D-E-FF
42T22 B20 P8aaBbccD-eeFf91T23 B21 P25aaBBC-ddE-FF140T23 B22 P42aaBbC-D-E-FF
43T22 B20 P10aaBbccddeeff92T23 B21 P26aaBBC-D-E-FF141T23 B22 P43aaBBC-D-E-FF
44T22 B20 P11aaBbccD-eeFf93T23 B21 P27aaBBC-D-E-FF142T23 B22 P44aaBBC-D-E-FF
45T22 B20 P12aabbccddeeff94T23 B21 P28aaBBC-D-E-FF143T23 B22 P45aaBBC-D-E-FF
46T22 B20 P13aabbccD-E-Ff95T23 B21 P29aaBBC-D-E-FF144T23 B22 P46aaBBC-D-E-FF
47T22 B20 P15aaBBccD-E-Ff96T23 B21 P30aaBBC-D-E-FF145T23 B22 P49aaBBC-D-E-FF
48T22 B20 P17aabbccD-eeff97T23 B21 P31aaBBC-D-E-FF146T23 B22 P50aaBbC-D-E-ff
49T22 B20 P18aaBBccD-eeFf98T23 B21 P32aaBBC-D-E-FF147Paraíso H419-1aaBBccddeeff
148Catuaí VermelhoaabbccddeeFf
* Treatment 22, Block 19, Plant 1.
Table 2. Chi-squared segregation test for loci related to resistance to coffee rust: SH3 gene (locus A), locus/QTL for resistance to races I, II, and pathotype 001 (loci B and C); CC-NBS-LRR (locus D); HdT_LRR_RLK2 (locus E); and resistance to CBD, gene Ck-1 (locus F).
Table 2. Chi-squared segregation test for loci related to resistance to coffee rust: SH3 gene (locus A), locus/QTL for resistance to races I, II, and pathotype 001 (loci B and C); CC-NBS-LRR (locus D); HdT_LRR_RLK2 (locus E); and resistance to CBD, gene Ck-1 (locus F).
Genetic LociExpected SegregationDegrees of FreedomChi-Squared Probability
A1:2:124260
B1:2:1280.030
C3:1119.010
D3:110.0192.28
E3:111.1428.65
F1:2:1277.550
Table 3. Estimated genetic parameters for the evaluated morphoagronomic traits.
Table 3. Estimated genetic parameters for the evaluated morphoagronomic traits.
Year2018202020212022
Genetic Parameterh2aAcμh2aAcμh2aAcμh2aAcμ
Y0.25 *0.800.74-0.143.100.04 *0.560.96-0.140.52
VIG0.09 *0.766.330.04 *0.676.66-0.276.400.03 *0.556.63
PH0.05 *0.6985.320.04 *0.68139.680.07 *0.73148.05-0.56166.92
FS0.05 *0.672.970.08 *0.743.08-0.102.81-0.112.82
SD-0.133.01-0.615.12-0.5660.460.04 *0.6672.51
CD0.18 *0.81106.150.16 *0.80138.12-0.44144.730.04 *0.65153.01
QPB-0.2334.89-0.1652.94-0.5241.830.11 *0.7660.91
LPB0.12 *0.7846.330.25 *0.8363.16-0.1571.80-0.5562.37
NNR-0.1012.90-0.4123.69-0.1724.850.11 *0.7719.31
CLR0.39 *0.831.610.07 *0.671.98-0.261.910.50 *0.841.58
CER-0.121.840.09 *0.752.410.09 *0.762.150.13 *0.731.80
CLM0.07 *0.711.58-0.272.400.19 *0.801.660.39 *0.831.40
CS0.44 *0.851.900.44 *0.851.900.44 *0.851.900.44 *0.851902.00
CF-0.481.44-0.481.44-0.481.44-0.481436.00
FMC-0.202.690.12 *0.783.12-0.332.830.13 *0.742.79
FUC0.07 *0.632.16-0.322.720.03 *0.592.630.29 *0.832.83
h2a: Individual additive heritability; Ac: accuracy; µ: average; *: significant 5%; Y: yield; VIG: vegetative vigor; PH: plant height; FS: fruit size; SD: stem diameter; CD: canopy diameter; QPB: quantity of productive branch; LPB: length of productive branch; NNR: number of nodes in the reproductive branch; CLR: coffee leaf rust severity; CER: cercosporiosis severity; CLM: coffee leaf miner infestation; CS: color of the sprout; CF: color of ripe fruit; FMC: fruit maturation cycle; and FUC: fruit uniformity cycle.
Table 4. Repeatability and its estimated genetic parameters for the morphoagronomic traits.
Table 4. Repeatability and its estimated genetic parameters for the morphoagronomic traits.
Genetic ParameterYearsrh2gVgVeh2adAc-famAcc-IndLRT
Y2018-0.250.200.560.180.800.916.51 **
VIG2018.20200.230.070.091.000.040.760.780 **
PH2018.20210.010.0010.841325.850.000.540.540.46 ns
FS2018.20200.060.020.000.190.010.610.620.48 ns
CD2018.20200.130.1183.74673.110.060.810.853.72 *
QPB2022-0.11--0.060.770.812.36 *
LPB2018.20200.120.1230.72226.660.070.820.865.45 **
NNR2022-0.11--0.060.770.812.36 *
CLR2018.2020.20220.150.140.050.310.080.840.8913.08 **
CER2020.2021.20220.080.020.010.410.010.620.630.27 ns
CLM2018.2021.20220.150.140.040.270.080.830.8811.68 **
CS2018.2020.20210.590.370.070.070.450.841.0713.93 **
FMC2020.20220.130.090.070.630.050.780.813.65 *
FUC2018.20220.190.190.120.510.120.830.9013.17 **
r: Repeatability of individual installments; h2g: genotypic heritability; Vg: genotypic variance; Ve: residual variance; h2ad: additive heritability; Ac-Fam: accuracy by PEV; Ac-Indiv: individual accuracy; LRT: Likelihood Ratio Test; * significance at 1%, ** significance at 5%, and ns not significant; Y: yield; VIG: vegetative vigor; PH: plant height; FS: fruit size; SD: stem diameter; CD: canopy diameter; QPB: quantity of productive branch; LPB: length of productive branch; NNR: number of nodes in the reproductive branch; CLR: coffee leaf rust severity; CER: cercosporiosis severity; CLM: coffee leaf miner infestation; CS: color of the sprout; CF: color of ripe fruit; FMC: fruit maturation cycle; and FUC: fruit uniformity cycle.
Table 5. Genotypes with high agronomic performance and gene pyramiding for resistance to CLR and CBD (BBC_D_E_FF).
Table 5. Genotypes with high agronomic performance and gene pyramiding for resistance to CLR and CBD (BBC_D_E_FF).
NºYVIGPHFSSDCD QPBLPBNNRCLRCERLMCSCFFMCFUC
732.5081413441645666192222133
741.80811734604860171222133
770.8571303391404760152222132
801.6881353361595166222222333
811.7871383351535673242222133
821.0571283351345662202222133
861.4371493351445756212222233
872.6581333481775064192222133
881.7871223401395064212222333
902.3371323391424865222222133
911.4361303341365356182222233
922.0581453471835582242222143
931.5071363361634869212222133
940.7861232331344358212322133
952.8881413411645573252222233
961.3071353351494669212223133
972.3371293361475465232222132
1070.0871342461474966202222133
1081.4871213311445266252222133
1111.587923281332757202222143
1143.8881723391886177242222143
1151.7581463351646477242222132
1170.7571333371515460192222233
1221.9071463371474463221222133
1230.1051033261162648112312133
1240.1081563401695570212322243
1251.2871083281313961192222132
1261.0561173451194346142312133
1270.3061073411063850182222122
1282.9071153311384372222222133
1301.1571203391314553182222132
1330.0761283321474866222212144
1341.2071433301575366242222133
1350.2381563421726078231222154
1361.2071333341494666192222133
1371.0061373441545471212222233
1090.7571293301253665202222143
1400.10678331003040111212132
1410.8071463361414568232222132
1420.9061393331434372221222143
1430.5861013261223062192222233
μ1.356.81129.742.8834.72143.3347.5164.020.231.581.991.742.021.273.072.76
Y: Yield; VIG: vegetative vigor; PH: plant height; FS: fruit size; SD: stem diameter; CD: canopy diameter; QPB: quantity of productive branch; LPB: length of productive branch; NNR: number of nodes in the reproductive branch; CLR: coffee leaf rust severity; CER: cercosporiosis severity; CLM: coffee leaf miner infestation; CS: color of the sprout; CF: color of ripe fruit; FMC: fruit maturation cycle; FUC: fruit uniformity cycle; and µ: average.
Table 6. Description of the molecular markers are associated with genes that confer resistance to Hemileia vastatrix and Colletotrichum kahawae.
Table 6. Description of the molecular markers are associated with genes that confer resistance to Hemileia vastatrix and Colletotrichum kahawae.
ResistanceLocusGeneMarkerTypeDistance (cM)TagPrimersT (°C)Reference
Hemileia
vastatrix		ASH3SAT 244 SSR0CodominantF:GCATGTGCTTTTTGATGTCGT
R:GCATACTAAGGAATTATCTGACTGCT		52[47,49]
BA-124 -12K-fSCAR0DominantF:TGATTTCGCTTGTTGTCGAG
R: TGCAGATTGATGGCACGTTA 		56
BGene/QTL-GL2CaRHv8 SCAR3DominantF:CCTTCTAGTGTTACCGAGGA
R: CTTAGCGCCATGAATAGCCA		65[59]
SSR 016SSR3.7CodominantR:CCACACAACTCTCCTCATTC
F:ACCCGAAAGAAAGAACCAAG 		65[48]
CGene/QTL-GL5CaRHv9 SCAR2.3DominantF:TGATGAAGAAGAGCGCATAGC
R:GTCTAAGACCAGAATCAGATGG 		65[59]
DNB-ARC e LRR CARF 005 Functional.DominantF:GGACATCAACACCAACCTC
R:ATCCCTACCATCCACTTCAAC		60[25,52]
EHdT_LRR_RLK2RLK2Functional.DominantF:GCTCACAGGTCCGATTCCTCTG
R:TTTGGGAATAGGCCCGGAAAGA		60[24]
Colletotrichum kahawaeFCk-1SAT 235SSR0CodominantF:TCGTTCTGTCATTAAATCGTCAA
R: GCAAATCATGAAAATAGTTGGTG		50[30,49]
SAT 207SSR17.2CodominantF:GAAGCCGTTTCAAGCC
R: CAATCTCTTTCCGATGCTCT 		50
QTL: Quantitative Trait Locus; SSR: simple sequence repeat; SCAR: sequence characterized amplified region; and CAPS: cleaved amplified polymorphic sequence.
Table 7. Methodology for evaluating the main morphoagronomic traits of coffee.
Table 7. Methodology for evaluating the main morphoagronomic traits of coffee.
TRAITS
YYield
Estimated in liters per plant
VIGVegetative vigor
Evaluated on a scoring scale ranging from 1 (minimum vigor) to 10 (maximum vigor)
PHPlant height
Measured in the main orthotropic branch, from the soil surface to the final point of branch growth
FSFruit size
1 = tiny, 2 = small, 3 = medium, 4 = big, and 5 = large
SDStem diameter
Measured with the aid of a digital caliper, in the region of the plant’s stem (+ or −5 cm from the surface of the soil)
CDCanopy diameter
Measured in the transverse direction to the planting line, measuring the largest projection of the coffee tree canopy
QPBQuantity of productive branch
Number on the main stem
LPBLength of productive branch
Measurement in the middle third of a representative plagiotropic branch of the plant
NNRNumber of nodes in the reproductive branch
Number of nodes of the representative plagiotropic branch of the plant measured in LPB
CLRCoffee leaf rust severity
1—Absence of pustules and hypersensitivity reactions
2—Few leaves with pustules without spores and hypersensitivity reactions
3—Few pustules with high spore production and poorly distributed
4—Medium content of pustules per leaf, with high spore production and well distributed throughout the plant
5—High quantity of pustules, spore production, and plant defoliation
Note: Plants with a score of 1 or 2 = resistant and 3 to 5 = susceptible
CERCercosporiosis severity
1—Leaf without cercospora symptoms
2—Low incidence of cercospora lesions on the leaves
3—Medium incidence of small-diameter cercospora lesions on the leaves
4—High incidence of large-diameter cercospora lesions on the leaves
5—Severity of cercospora on leaves with presence of necrosis
Note: Plants with a score of 1 or 2 = resistant and 3 to 5 = susceptible
CLMCoffee leaf miner infestation
1—Immune leaves, without any injury
2—Leaves with few sharply shaped lesions
3—Leaves with few and small lesions
4—Leaves with moderate infestation and typical lesions with live larvae
5—Leaves with severe infestation and typical lesions with live larvae
CSColor of the sprout
1—Green; 2—light bronze; 3—bronze; and 4—dark bronze
CFColor of ripe fruit
1—Green; 2—yellow; and 3—orange
FMCFruit maturation cycle
1—Early; 2—medium to early; 3—medium; 4—medium to late; and 5—late
FUCFruit uniformity cycle
1—Uniform; 2—moderately uniform; 3—moderately non-uniform; and 4—non-uniform
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Mariz, B.L.; Caixeta, E.T.; Resende, M.D.V.d.; Oliveira, A.C.B.d.; Almeida, D.P.d.; Alves, D.R. Exploring the Genetic Potential for Multi-Resistance to Rust and Other Coffee Phytopathogens in Breeding Programs. Plants 2025, 14, 391. https://doi.org/10.3390/plants14030391

AMA Style

Mariz BL, Caixeta ET, Resende MDVd, Oliveira ACBd, Almeida DPd, Alves DR. Exploring the Genetic Potential for Multi-Resistance to Rust and Other Coffee Phytopathogens in Breeding Programs. Plants. 2025; 14(3):391. https://doi.org/10.3390/plants14030391

Chicago/Turabian Style

Mariz, Bruna Lopes, Eveline Teixeira Caixeta, Marcos Deon Vilela de Resende, Antônio Carlos Baião de Oliveira, Dênia Pires de Almeida, and Danúbia Rodrigues Alves. 2025. "Exploring the Genetic Potential for Multi-Resistance to Rust and Other Coffee Phytopathogens in Breeding Programs" Plants 14, no. 3: 391. https://doi.org/10.3390/plants14030391

APA Style

Mariz, B. L., Caixeta, E. T., Resende, M. D. V. d., Oliveira, A. C. B. d., Almeida, D. P. d., & Alves, D. R. (2025). Exploring the Genetic Potential for Multi-Resistance to Rust and Other Coffee Phytopathogens in Breeding Programs. Plants, 14(3), 391. https://doi.org/10.3390/plants14030391

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