Next Article in Journal
Isogenic Japonica Rice Koshihikari Integrated with Late Flowering Gene Hd16 and Semidwarfing Gene sd1 to Prevent High Temperature Maturation and Lodging by Typhoon
Next Article in Special Issue
iTRAQ-Based Quantitative Proteomics Unveils Protein Dynamics in the Root of Solanum melongena L. under Waterlogging Stress Conditions
Previous Article in Journal
A Study on the Phenotypic Variation of 103 Cucumber (Cucumis sativus L.) Landraces for the Development of Desirable Cultivars Suitable for the Changing Climate
Previous Article in Special Issue
LSAP: A Machine Learning Method for Leaf-Senescence-Associated Genes Prediction
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Genome-Wide Analysis of the NAC Family Associated with Two Paleohexaploidization Events in the Tomato

1
Center for Genomics and Computational Biology, School of Life Sciences, North China University of Science and Technology, Tangshan 063000, China
2
University of Chinese Academy of Sciences, Beijing 100049, China
*
Authors to whom correspondence should be addressed.
These authors contributed equally to this work.
Life 2022, 12(8), 1236; https://doi.org/10.3390/life12081236
Submission received: 11 July 2022 / Revised: 6 August 2022 / Accepted: 10 August 2022 / Published: 15 August 2022
(This article belongs to the Special Issue Genome Evolution Mechanism of Plant Polyploids)

Abstract

:
NAC transcription factors play an important regulatory role in tomato fruit ripening. We chose a novel perspective to explore the traces left by two paleopolyploidizations in the NAC family using a bioinformatics approach. We found that 85 (S. lycopersicum) and 88 (S. pennellii) members of the NAC family were present in two tomatoes, and most of them were amplified from two paleohexaploidizations. We differentiated NAC family members from the different paleohexaploidizations and found that the SWGT-derived NAC genes had more rearrangement events, so it was different from the DWGT-derived NAC genes in terms of physicochemical properties, phylogeny, and gene location. The results of selection pressure show that DWGT-derived NAC genes tended to be positively selected in S. lycopersicum and negatively selected in S. pennellii. A comprehensive analysis of paleopolyploidization and expression reveals that DWGT-derived NAC genes tend to promote fruit ripening, and are expressed at the early and middle stages, whereas SWGT-derived NAC genes tend to terminate fruit growth and are expressed at the late stages of fruit ripening. This study obtained NAC genes from different sources that can be used as materials for tomato fruit development, and the method in the study can be extended to the study of other plants.

1. Introduction

The tomato (Solanum lycopersicum, abbreviated S. lycopersicum) is a diploid (2n = 24) crop of the Solanaceae family whose fruits are rich in organic nutrients such as sugars, amino acids, lycopene, β -carotene, and vitamin C (ascorbic acid), and is one of the important economic vegetable crops in the world [1,2]. The tomato is a model organism for agronomic, nutritional, and genetic studies due to its small genome (~900 Mb) [3], short growth cycle, high self-fertility, and homozygosity [4,5,6].
Various factors such as plant hormones, environmental signals, and transcription factors influence fruit ripening in tomato, of which the NAC transcription factor is one of the major ones [7,8]. The NAC family, named after NAM, ATAF1/2, and CUC2, is one of the largest families of TFs that play important roles in different stages of plant growth, development, and maturation [8,9]. An increasing number of studies revealed that NAC proteins play important roles in various metabolic pathways, and resistance to biotic and abiotic stresses in tomatoes, such as flower border formation [10], leaf senescence [11], fruit ripening [12,13,14,15], phytohormones [16], salt [17], drought [17,18], and heavy metals [19].
Paleopolyploidization, also known as whole-genome duplication (WGD), is an important driver of plant evolution through the numerical multiplication and functional diversification of genes [20,21,22,23,24]. The tomato genome has undergone two paleohexaploidizations in its evolutionary history, also known as whole genome triploidization (WGT) events. The first was a γ event [3] (~120 mya) that occurred in the common ancestor of dicotyledons, referred to here as DWGT. The second was a paleohexaploidization (~67 mya) that occurred in the common ancestor of Solanaceae [3,25,26], referred to here as SWGT. Paleopolyploidization produces more gene family members that may affect the regulatory functions of the gene family, and influence the growth and development of the crop. For example, the effects of paleopolyploidization on gene function were identified in the studies of several gene families such as PHYB1/PHYB2 [3], U-box E3 gene [27], XTH and DOF [28], but few studies have associated tomato paleohexaploidization with its NAC family characteristics.
Given the importance of the NAC family in the physiological activity of tomatoes, this study presents a novel comparative analysis of the NAC family and paleohexaploidizations in two tomato genomes (S. lycopersicum and its wild-type S. pennellii). This study uses Coffea canephora [29] as an out-group that did not undergo SWGT to distinguish NAC genes generated by different paleohexaploidizations. Furthermore, the study explores the associative features of two paleohexaploidizations with the NAC family in terms of chromosomal localization, physicochemical properties, phylogeny, selection pressure, differential expression, and functional enrichment. This study helps in applying the characteristics of the NAC family to the improvement of tomato fruits.

2. Materials and Methods

2.1. Species Selection and the Generation of NAC Members

Two tomato genomic data were downloaded from Sol Genomics Network (https://solgenomics.net/, accessed on 8 July 2022) [30], with ITAG version 4.0 for cultivar S. lycopersicum [31] and Spenn-v2.0 for the wild species S. pennellii [32]. Genomic data for out-group C. canephora [29] were downloaded from the Coffee Genome Hub (https://coffee-genome-hub.southgreen.fr/, accessed on 8 July 2022). Hidden Markov model (HMM) seeds for the NAC domain (PF02365) were downloaded from Pfam [33]. Bioperl [34] was used to manipulate sequences, Muscle [35] to perform multiple sequence alignment, and HMMER 3 [36] to perform Pfam Hmm seed-based sequence alignment. The threshold for specific NAC library construction was 1 × 10 20 , and the threshold for NAC identification was 1 × 10 10 .

2.2. Physical Localization, Physicochemical Properties, and Phylogenetic Analysis

The distribution of NAC members on chromosomes was demonstrated using MG2C [37] on the basis of the location of genes in genomic assembly data. The primary structure of NAC proteins was analyzed using Protparam in Expasy [38]. The subcellular localization of NAC proteins was analyzed using CELLO [39]. The secondary structure of NAC proteins was predicted using SOPMA [40]. The multiple sequence alignment of the identified NAC families was performed using Muscle software, and the construction of evolutionary trees using the maximal likelihood method (ML) in FastTree [41] software setting Bootstrap = 1000. The evolutionary tree was trimmed and embellished using the Chiplot tool (https://www.chiplot.online/, accessed on 8 July 2022).

2.3. Genomic Collinearity Search and Selection Pressure Analysis

The search for collinear fragments was performed in C. canephora and two tomato genomes using MCScanX [42] with default parameters to obtain genes of different origins, such as tandem repeats and paleopolyploidization. The origin of the NAC genes was obtained by querying the identified NAC family members in the above results. On the basis of the above results, the downstream analysis of MCScanX (detect_collinearity_within_gene_families.pl) was executed to obtain the collinearity of NAC family members. The multiple sequence alignment of collinear NAC genes using Clustalw [43] software, followed by calculation of Ka (nonsynonymous substitutions) and Ks (synonymous substitutions) values for each collinear NAC gene pair using Bioperl. The selection pressure on NAC genes of different species was analyzed on the basis of the ratio of Ka to Ks, with Ka/Ks > 1 being positive selection, Ka/Ks = 1 being neutral selection, and Ka/Ks < 1 being purifying selection. Genomic collinearity and NAC genes were visualized using Circos [44].

2.4. Fruit-Ripening-Specific Expression Analysis and Enrichment Analysis

For the analysis of differential expression and enrichment in the NAC family, we selected the expression microarray data of tomato (cv., Money Maker) at three fruit-ripening stages. The three stages were mature green (MG), breaker (Br), and breaker + 10 days (Br10), and each stage had three biological replicates. These data were downloaded from the NCBI Gene Expression Omnibus [45] and stored in accession number GSE108415 [46]. Limma [47] software screens for specific differentially expressed genes in fruit ripening. AnnotationHub [48], DOSE [49], and clusterProfiler [50] were used for the enrichment analysis of differentially expressed genes and the NAC family. ggplot2 [51] and enrichplot [52] were used to visualize differential expression volcano maps and enrichment analysis results. pheatmap (https://github.com/raivokolde/pheatmap, accessed on 8 July 2022) was used for clustering and drawing heat maps. Linear fit models for differentially expressed genes were estimated using the least-squares method. The p-value and adj. p-Value for each group comparison were calculated using the modified t-statistic and BH method [53], respectively. The screening threshold for differential genes was |logFoldChange| > 2 and p-value < 0.05. The screening threshold for both GO and KEGG enrichment was adj. p-value < 0.05. The FoldEnrichment value in Go enrichment analysis is equal to the ratio of the GeneRatio to BgRatio; RichFactor in KEGG enrichment analysis is equal to the ratio of molecules of GeneRatio (i.e., Count) to molecules of BgRatio.

3. Results

3.1. Identification and Localization of NAC Family

C. canephora has undergone only one paleohexaploidization (DWGT) event and has a relatively conservative evolutionary rate, thus serving as an out-group species. The NAC genes in C. canephora, S. lycopersicum, and S. pennellii were identified on the basis of a hidden Markov model of the NAC domain. The number of NAC genes in each species was recorded (Table 1). The results show that S. lycopersicum and S. pennellii had similar numbers of NAC genes (85 vs. 88). The number of NAC genes was significantly higher in both tomatoes when compared to C. canephora. This suggests that the second paleohexaploidization may have resulted in the expansion of the NAC family members in the tomato genome.
The physical localization of NAC genes in S. lycopersicum and S. pennellii shows that NAC genes were distributed very similarly on the same chromosomes in different tomatoes (Figure 1A). For example, NAC genes had the same arrangement on chromosome 1 in both tomatoes. On chromosome 7, the difference was that S. pennellii had one more gene located in the middle of the chromosome, Sopen07g012150.1. The results for different chromosomes show that NAC genes are unevenly arranged on different chromosomes (Figure 1B). For example, the number of NAC genes on chromosomes 2 and 6 was more than that on chromosomes 9 and 12. At the overall level, NAC genes often form some gene clusters at the ends of the chromosomes (Figure S1). For example, the average distance of NAC genes on chromosome 2 of S. lycopersicum was 0.0578 Mb (Solyc02g061780.3.1, Solyc02g061900.1.1, Solyc02g062060.1.1, Solyc02g061870.1.1 and Solyc02g061910.1.1), which is very close (Figure S1A). Similarly, NAC genes also form clusters on chromosome 4 of S. pennellii, with an average distance of 0.0586 Mb (Figure S1B).

3.2. Physicochemical Characteristics of NAC Proteins

In total, 173 NAC genes were identified in two tomatoes (Table 1), and the primary structure and physicochemical properties of their proteins were analyzed using the Protparam tool (Figure 2 and Figure S2, and Table S1). The results of amino acid numbers show that the majority of NAC proteins had amino acid numbers between 100 and 700, with Solyc03g062750.1.1 having the lowest number of amino acids (122) in S. lycopersicum. In addition, two NAC proteins in S. pennellii had amino acid numbers greater than 700 (Table S1), Sopen10g022760.1 (853), and Sopen02g025910.1 (1014). The molecular mass of NAC proteins showed a positive correlation with the number of amino acids. In detail, the majority of NAC proteins had molecular masses less than 80,000 (Figure 2B). The NAC protein with the smallest molecular mass was Solyc03g062750.1.1 (14,427.78), which also had the lowest number of amino acids. The NAC protein with the largest molecular mass was Sopen02g025910.1 (115,206.37), which also had the highest number of amino acids (Figure S2 and Table S1).
The results of isoelectric points show that the range of isoelectric points of NAC proteins in S. lycopersicum was between 4.58 and 9.90. Among these NAC proteins, (PI < 6.5) 47 were acidic, (PI > 7.5) 26 were alkaline, and the remaining 12 were between 6.5 and 7.5 (Figure 2C and Table S1). Correspondingly, the isoelectric points of NAC proteins in S. pennellii ranged from 4.21 to 9.82. Among them, the numbers of acidic and basic proteins were 51 and 26, respectively, and the remaining 11 were neutral proteins (Figure S2 and Table S1). The instability index results show that most of the proteins in two tomatoes (111) had instability coefficients greater than 40, i.e., unstable proteins, and a small number of proteins (62) were less than 40, i.e., stable proteins (Figure 2D and Figure S2 and Table S1). The results of the fat coefficients show that most of the NAC proteins had fat coefficients between 40 and 80 in two tomatoes (Figure 2E and Figure S2, and Table S1).
The results of subcellular localization analysis of 173 NAC proteins show that all proteins were present in the nucleus except Solyc04g078670.3.1 and Sopen10g022760.1, which may also be present in chloroplasts (Figure 2F, Table S1). On the basis of the results of secondary structure prediction for 173 NAC proteins, we counted the frequency of secondary structures (e.g., α -helix, β -turn, random coil, and extended chain) for each protein (Figure 3, Table S2). The results show that the random coil had the highest frequency in the NAC proteins and was the dominant structure in the secondary structure. In addition, the frequency of β -turn was the lowest, and the frequency of the α -helix and extended strand was moderate.

3.3. Phylogeny of the NAC Family

Phylogenetic trees were constructed in C. canephora, S. lycopersicum, and S. pennellii using Fastree on the basis of the results of the multiple sequence alignment of NAC proteins (Figure 4, Figures S3 and S4). In the case of S. lycopersicum, a phylogenetic tree of 85 NAC family members was constructed (Figure 4). According to the topology of the phylogenetic tree, the NAC family can be divided into three subgroups, SL_NAC1 (47 genes), SL_NAC2 (21 genes), and SL_NAC3 (17 genes). Topological results show that SL_NAC2 and SL_NAC1 had the highest and lowest overall evolutionary rates, respectively, with the branching SL_NAC3 having the middle evolutionary rate. This may indicate that more than half of NACs in S. lycopersicum are relatively conserved. In addition, Solyc08g007015.1 in SL_NAC3 is noteworthy for its rate of evolution, which was much higher than that of other proteins in the group. Similar to S. lycopersicum, the phylogenetic tree of NAC protein can be divided into three subgroups in S. pennellii, while the phylogenetic tree of C. canephora had no distinct grouping characteristics (Figures S3 and S4).

3.4. Association of Two Paleohexaploidizations with NAC Family Amplification

The tomato has undergone two paleohexaploidizations in its evolutionary history, which may have resulted in the expansion of the gene families [54]. The results of whole-genome collinearity analysis show (Table 2) that the genes derived from DWGT accounted for 35.61% of the total genes in C. canephora, while those derived from tandem were only 2.58%. This indicates that DWGT is the main driving force of coffee gene amplification. In the genomes of S. lycopersicum and S. pennellii, genes derived from two paleohexaploidizations contributed 51.79% and 71.31%, which means that DWGT and SWGT are the main amplification methods in the two tomato genomes (Table 2). In contrast, the number of SWGT amplified genes in S. pennellii was significantly higher than that in S. lycopersicum. In addition, tandem partially contributed to the genomic amplification of two tomato species, adding 11.77% and 15.44% genes. The amplification of the NAC family showed a similar pattern (Table 3). In the case of S. lycopersicum, the number of NAC genes generated by DWGT, SWGT, and tandem was 61 (71.76%), 10 (11.76%), and 3 (3.53%), respectively. Similarly, paleohexaploidization was the primary mode of NAC family amplification in C. canephora and S. pennellii, and tandem produced relatively few NAC family members, which is consistent with genomic amplification (Figure 5, Figures S5 and S6).

3.5. Selection Pressure on NAC Genes

To a certain extent, the ratio of Ka to Ks can reflect the direction of the selection pressure on the genes of the species [55]. According to the collinear relationship between genes within a species, the Ka and Ks between genes in each species were calculated; then, the selection pressure (Ka/Ks) was analyzed and counted (Table 4, Tables S3 and S4). The results show that the number of Ks > 1 (1546) between DWGT gene pairs in S. lycopersicum was greater than that of Ks < 1 (778), and the number of Ks > 1 (10) between NAC gene pairs produced by DWGT was also greater than that of Ks < 1 (4). This indicates that the positive selection pressure was greater than the negative selection pressure on the genes generated by DWGT, and the NAC genes are in the same direction. The number of gene pairs Ks > 1 (363) produced by SWGT was very close to Ks < 1 (339), which indicates that the positive and negative selections of genes produced by SWGT were relatively balanced, and the direction of its selection pressure could not be accurately determined. In the S. pennellii genome, genes generated by SWGT were under more pressure from negative selection than from positive selection. Genes generated by DWGT (including NAC genes) were under more negative selection pressure than positive selection pressure, which was opposite to S. lycopersicum.

3.6. Developmental-Stage-Specific Expression Analysis

On the basis of expression data of three maturation stages in S. lycopersicum, pairwise comparisons were performed (MG vs. BR, BR vs. BR10, MG vs. BR10), and the statistics of differentially expressed genes were screened (Figure 6, Tables S5 and S6). The results show that the number of upregulated genes shared by the three stages was 69, which was higher than the number of downregulated genes (18), but they had a similar overall proportion (3.1% and 2.7%). Another commonality is that there were no genes in common in either up- or downregulated gene comparisons in the MG vs. BR combination and the BR vs. BR10 combination (Figure 6). The results of differential expression analysis at different maturation stages show (Figure 7) that some differentially expressed genes were highly significant (see Section 2). For example, in the MG and BR combination (Figure 7A), there were 25 highly significantly differentially expressed genes, of which 7 were upregulated and 18 were downregulated. In the BR and BR10 combination, there were only 5 highly significantly differentially expressed genes and all of them were upregulated (Figure 7B). There were 35 highly significantly differentially expressed genes in the MG vs. BR10 combination, of which 16 were upregulated and 19 were downregulated (Figure 7C).
The differential expression analysis of NAC genes at different maturation stages found that 7 NAC genes were differentially expressed (6 upregulated and 5 downregulated) in the MG vs. BR combination (Figure 7D). In the BR and BR10 combination (Figure 7E), this number was 5 (2 upregulated, 3 downregulated). In the MG vs. BR10 combination (Figure 7F), this number was 6 (3 up-regulated, 3 down-regulated). Although the number of differentially expressed NAC genes was low, their −Log10 (p-value) was relatively high (greater than 5) except for Solyc05g055480. To understand the expression patterns of NAC genes at different maturation stages, the expression levels of all NAC genes were clustered and displayed (Figure 8). For example, in the MG stage, Solyc08g077110, Solyc06g063380, Solyc12g036480, Solyc04g025760, Solyc02g069960, Solyc07g066330, Solyc10g005010, Solyc09g010160 and Solyc0 6g061080 are more active. In the Br stage, the expression of Solyc11g068620, Solyc03g097650, Solyc03g1 15850 and Solyc03g062750 was more active. In the BR10 stage, the expression of Solyc03g083880, Solyc06g063430, Solyc07g062240, Solyc07g053680 and Solyc10g079220 was more active. The expression results indicate that the NAC gene played a role in different maturation stages.

3.7. GO and KEGG Enrichment Analysis

Gene ontology (GO) can classify genes from three levels (MF: molecular function, BP: biological process, CC: cellular components), and predict the pathway of their function [56,57]. The differentially expressed genes of the three comparative combinations were extracted and subjected to GO enrichment analysis (Tables S7 and S8). Among the upregulated genes, genes in the combination of MG and BR were fully enriched in biological process and had lower fold enrichment, while the genes in the combinations of BR and BR10, and MG and BR10 were scattered into the three GO-enriched classes and had higher fold enrichment (Figure S7). Among the downregulated genes, genes of the BR and BR10 combination were enriched into two GO classes (BP and MF), while genes of the MG and BR, and MG and BR10 combinations were scattered into three GO classes (Figure S8). Taking the differentially expressed genes of the MG and BR10 combination as an example (Figures S7 and S8), the upregulated genes were highly enriched in several growth-essential pathways such as photorespiration, carbon fixation, glycogen metabolic process, and energy reserve metabolic process. The downregulated genes were highly enriched in structurally related pathways such as fruit ripening, oxidoreductase activity, and response to unfolded protein. The Kyoto Encyclopedia of Genes and Genomes (KEGG) can analyze the pathway enrichment of candidate genes in 7 categories to observe their interactions in different biochemical processes. Taking the MG and BR combination as an example, the upregulated genes were highly enriched in three pathways, the biosynthesis of nucleotide sugars, carbon fixation in photosynthetic organisms, and glyoxylate and dicarboxylate metabolism (Figure 9A, Table S9), which is similar to the results of GO. Downregulated genes were highly enriched in three additional pathways: protein processing in the endoplasmic reticulum, cysteine and methionine metabolism, and flavonoid biosynthesis (Figure 9B, Table S10). The results of differential expression show that upregulated genes were highly enriched in multiple active pathways such as maintaining organism survival and growth, while downregulated genes tended to be highly enriched in fruit ripening and protein structure maintenance.
The same GO and KEGG enrichment operations were performed on the NAC genes of S. lycopersicum. Due to the small number of NAC genes, only GO enrichment results were obtained (Figure S10, Table S11). The results show that 6 NAC genes were enriched in 7 BPs involved in growth and development, of which Solyc05g007770.3.1 was present on all 7 BPs.

4. Discussion

In this study, 85 and 88 NAC genes were identified in S. lycopersicum and S. pennellii, respectively, which differed from the number identified in PlantTFDB v5.0 (101 and 105 NAC genes) [19]. There may be two reasons for this difference. First, in the process of identifying NAC genes, this study set two strict search thresholds, which resulted in fewer matches (see Section 2). Second, the tomato genome version used in PlantTFDB v5.0 is ITAG 2.3, and the latest ITAG 4.0 version was used in this study [31]. The difference in the number of NAC genes in S. lycopersicum may have been influenced by all two reasons, and this difference in S. pennellii may have mainly been due the first reason. Chromosomal mapping reveals that the NAC family appeared to be unevenly distributed across the two tomato genomes, and this uneven distribution is also seen in Pyrus bretschneideri (white pear) [58], Betula pendula (white birch) [59] and Zea mays L. (maize) [60] and other plant genomes.
On the basis of gene collinearity analysis, the origin of the NAC family since two paleohexaploidizations was analyzed. Our study reveals that most of the NAC genes in tomatoes originated from DWGT, and a small proportion of NAC genes originated from SWGT (Table 3). By linking paleohexaploidization to some basic features of the NAC family, we found many interesting results. The NAC genes of DWGT origin were unevenly distributed on all 12 chromosomes, while the NAC genes of SWGT origin were distributed centrally on chromosomes 2, 3, 5, 6, and 8 in the tomato (Figure 1 and Figure S1). This may have been because each paleohexaploidization was accompanied by genomic rearrangement, so the NAC genes of DWGT origin underwent two rearrangements and showed uneven distribution. Comparing the physicochemical properties of NAC proteins from different sources, the NAC proteins derived from SWGT were smaller than those produced by DWGT in terms of amino acid number, relative molecular mass, isoelectric point, and instability coefficient, and only the fat coefficient was slightly higher than the latter (Figure 2 and Table S1). This may have also been the result of two rearrangements, such as the distribution of NAC genes on chromosomes. This indicates that the two paleohexaploidization had different effects on the physicochemical properties of NAC proteins.
The phylogenetic trees of the NAC family in S. lycopersicum and S. pennellii share two striking similarities. One is that the evolutionary trees of both tomato NAC families can be divided into three subgroups, and the other is that each evolutionary tree had a subgroup with a high evolution rate. (Figure 4 and Figure S3). Combining the origin of NAC genes with their phylogenetic trees revealed that NAC genes of SWGT origin were most abundant in the subgroup with the fastest evolutionary rate, For example, 50% (5/10) of the NAC genes of SWGT origin were in the fastest evolving subgroup in S. lycopersicum. Similarly, nearly half (9/19) of the NAC genes in S. pennellii showed this phenomenon. Another phenomenon is that SWGT-derived NAC genes on other subgroups also tend to be close to the branches with faster evolutionary rates. This suggests that recent paleopolyploidization events can significantly increase the evolutionary rate of the NAC family.
The analytical results of the genomic collinearity method and topological method also revealed interesting phenomena. After species divergence and paleohexaploidization, the offspring gene ratio of an ancestral gene should be C. canephora:S. pennellii:S. lycopersicum = 1:3:3 (Figure 10B), which was confirmed in the phylogenetic tree of all NAC genes in the three species (Figure 10C). However, gene clusters that fit the complete model are rare, and more gene clusters fit the residual model (Figure 10D). It is possible that the rearrangements following paleopolyploidization were also accompanied by substantial gene loss, resulting in a large reduction in family genes. This also explains why the number of NAC genes in S. pennellii and S. lycopersicum was less than three times the number of NACs in C. canephora (Table 1).
Several studies have shown that NAC transcription factors play a key role in the tomato fruit-ripening regulatory network. During fruit ripening, NAC transcription factors can act as positive regulators to promote the synthesis of hormones, such as ethylene and abscisic acid [12,15,16]. However, the expression of NAC genes can also accelerate leaf senescence and reduce photosynthesis time, thus reducing fruit quality [11]. The results of expression analysis in S. lycopersicum show that NAC genes are significantly up or down regulated at least once during fruit ripening (Figure 8). Most of the NAC genes showed significantly high expression at the MG and BR stages, i.e., promoting fruit ripening [16]. A small number of NAC genes showed significant expression at the BR10 stage, i.e., when tomatoes have ripened into soft fruits. The NAC gene remains highly expressed at the Br10 stage, probably to accelerate leaf senescence and terminate continued fruit growth [11]. This confirmed that the NAC gene can be expressed at different stages to promote and terminate fruit ripening in tomatoes [11,16]. Associating the origin of NAC genes with the results of enrichment analysis also revealed new phenomena. In the GO enrichment analysis of NAC genes in S. lycopersicum, a total of six genes were enriched in five pathways, five of which originated from DWGT and were more preferred to be enriched on processes related to plant development (e.g., leaf, system, phyllome, etc.) (Table S11), which was consistent with the results of the differential expression analysis. Expression analysis based on gene origin revealed that NAC genes of DWGT origin were more preferred to be expressed in the early and middle stages of fruit ripening, while NAC genes of SWGT origin were more preferred to be expressed in the early and late stages. That is, NAC genes of different origins perform functions at different stages. These results indicate that the DWGT-derived NAC gene was mainly expressed at the early stage of fruit ripening and promoted fruit ripening. However, SWGT-derived NAC genes were mainly expressed in late fruit ripening, terminating fruit ripening.

5. Conclusions

NAC transcription factors are among the important regulators of tomato fruit ripening. In this study, a novel analysis associating paleopolyploidization with the NAC family was performed in the tomato and its wild relatives. Genomewide collinearity analysis revealed that DWGT and SWGT were the main causes of NAC family amplification. We found that the two types of NAC family members derived from DWGT and SWGT exhibited different characteristics in terms of physicochemical properties, gene location, and phylogeny. We speculate that this difference is due to the fact that NAC family members derived from SWGT experienced more rearrangement events. For example, NAC genes derived from SWGT exhibit more concentration on chromosomes, smaller mean values in physicochemical properties, and faster evolutionary rates. Analysis of paleohexaploidization and gene expression showed that NAC genes derived from DWGT tend to be expressed at early and mid-fruit ripening and promote fruit ripening. In contrast, SWGT-derived NAC genes tended to be expressed at late fruit ripening, promoting leaf senescence and terminating fruit growth. Our study links paleohexaploidization to the NAC family and provides a scheme to explore the link between the origin of the NAC family and its function. This study also provides guidance for the developmental control of tomato fruits. We hope to continue to apply our research ideas and methods to more plant genes. Meanwhile, the linkage between paleopolyploidization and gene families needs more studies to be confirmed.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/life12081236/s1, Figure S1: physical and chemical properties of two tomato NAC proteins. Figure S2: statistical chart of physicochemical properties of Solanum pennellii NAC protein. Figure S3: Solanum pennellii NAC protein phylogenetic tree. Figure S4: Coffea canephora NAC protein phylogenetic tree. Figure S5: collinear map of Solanum pennellii NAC gene. Figure S6: collinear map of Coffea canephora NAC gene. Figure S7: GO enrichment dot plot of Solanum lycopersicum upregulated genes in different periods. Figure S8: GO enrichment map of Solanum lycopersicum downregulated genes in different periods. Figure S9: KEGG enrichment map of Solanum lycopersicum upregulated genes in different periods. Figure S10: GO enrichment map of NAC genes in Solanum lycopersicum in different periods. Table S1: physicochemical properties of two tomato NAC proteins. Table S2: secondary structure prediction table of two tomato NAC proteins. Table S3: selection pressure gauge among different WGT-producing genes. Table S4: selection pressure gauge among NAC genes produced by different WGT. Table S5: differential expression results of Solanum lycopersicum gene in different periods. Table S6: differential expression results of Solanum lycopersicum NAC gene in different periods. Table S7: GO enrichment results of downregulated genes in Solanum lycopersicum in different periods. Table S8: GO enrichment results of upregulated genes in Solanum lycopersicum in different periods. Table S9: KEGG enrichment results of downregulated genes in Solanum lycopersicum in different periods. Table S10: KEGG enrichment results of upregulated genes in Solanum lycopersicum in different periods. Table S11: GO enrichment results of Solanum lycopersicum NAC gene in different periods.

Author Contributions

Conceptualization, Y.L. (Yuxian Li); data curation, J.W.; formal analysis, Y.H., L.Z. and M.Y.; project administration, J.W. and Y.L. (Yuxian Li); software, Z.W. and T.L.; visualization, Z.W. and T.L.; writing—original draft, J.Y. and Y.L. (Ying Liu); writing—review and editing, J.Y. and Y.L. (Yuxian Li). All authors have read and agreed to the published version of the manuscript.

Funding

This research study was funded by the China National Science Foundation (32170236 and 31501333 to Jinpeng Wang), the Natural Science Foundation of Hebei Province (C2020209064 to Jinpeng Wang and C2020209020 to Min Yuan), the Tangshan Science and Technology Program Project (21130217C to Yuxian Li), and the North China University of Technology Student Innovation Project (X2020088 to Jiale Yuan).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data are contained within the article or available upon reasonable request from the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.

Abbreviations

The following abbreviations are used in this manuscript:
TFsTranscription factors
WGDWhole-genome duplication
WGTWhole-genome triplication
myaMillion years ago
DWGTWhole-genome triplication event shared by dicots
SWGTWhole-genome triplication event shared by Solanaceae
MGMature green
BrBreaker
Br10Breaker + 10 days

References

  1. Bergougnoux, V. The history of tomato: From domestication to biopharming. Biotechnol. Adv. 2014, 32, 170–189. [Google Scholar] [CrossRef] [PubMed]
  2. Perveen, R.; Suleria, H.A.R.; Anjum, F.M.; Butt, M.S.; Pasha, I.; Ahmad, S. Tomato (Solanum lycopersicum) Carotenoids and Lycopenes Chemistry; Metabolism, Absorption, Nutrition, and Allied Health Claims—A Comprehensive Review. Crit. Rev. Food Sci. Nutr. 2015, 55, 919–929. [Google Scholar] [CrossRef] [PubMed]
  3. The Tomato Genome Consortium. The tomato genome sequence provides insights into fleshy fruit evolution. Nature 2012, 485, 635. [Google Scholar] [CrossRef] [PubMed]
  4. Uluisik, S.; Chapman, N.H.; Smith, R.; Poole, M.; Adams, G.; Gillis, R.B.; Besong, T.; Sheldon, J.; Stiegelmeyer, S.; Perez, L.; et al. Genetic improvement of tomato by targeted control of fruit softening. Nat. Biotechnol. 2016, 34, 950–952. [Google Scholar] [CrossRef]
  5. Gao, L.; Gonda, I.; Sun, H.; Ma, Q.; Bao, K.; Tieman, D.M.; Burzynski-Chang, E.A.; Fish, T.L.; Stromberg, K.A.; Sacks, G.L.; et al. The tomato pan-genome uncovers new genes and a rare allele regulating fruit flavor. Nat. Genet. 2019, 51, 1044–1051. [Google Scholar] [CrossRef]
  6. Klee, H.J.; Giovannoni, J.J. Genetics and control of tomato fruit ripening and quality attributes. Annu. Rev. Genet. 2011, 45, 41–59. [Google Scholar] [CrossRef] [PubMed]
  7. Wang, R.; Angenent, G.C.; Seymour, G.; de Maagd, R.A. Revisiting the Role of Master Regulators in Tomato Ripening. Trends Plant Sci. 2020, 25, 291–301. [Google Scholar] [CrossRef] [PubMed]
  8. Li, C.; Hou, X.; Qi, N.; Liu, H.; Li, Y.; Huang, D.; Wang, C.; Liao, W. Insight into ripening-associated transcription factors in tomato: A review. Sci. Hortic. 2021, 288, 110363. [Google Scholar] [CrossRef]
  9. Kou, X.; Zhou, J.; Wu, C.E.; Yang, S.; Liu, Y.; Chai, L.; Xue, Z. The interplay between ABA/ethylene and NAC TFs in tomato fruit ripening: A review. Plant Mol. Biol. 2021, 106, 223–238. [Google Scholar] [CrossRef]
  10. Hendelman, A.; Stav, R.; Zemach, H.; Arazi, T. The tomato NAC transcription factor SlNAM2 is involved in flower-boundary morphogenesis. J. Exp. Bot. 2013, 64, 5497–5507. [Google Scholar] [CrossRef] [PubMed]
  11. Ma, X.; Zhang, Y.; Turečková, V.; Xue, G.P.; Fernie, A.R.; Mueller-Roeber, B.; Balazadeh, S. The NAC Transcription Factor SlNAP2 Regulates Leaf Senescence and Fruit Yield in Tomato. Plant Physiol. 2018, 177, 1286–1302. [Google Scholar] [CrossRef] [PubMed]
  12. Gao, Y.; Wei, W.; Zhao, X.; Tan, X.; Fan, Z.; Zhang, Y.; Jing, Y.; Meng, L.; Zhu, B.; Zhu, H.; et al. A NAC transcription factor, NOR-like1, is a new positive regulator of tomato fruit ripening. Hortic. Res. 2018, 5, 75. [Google Scholar] [CrossRef] [PubMed]
  13. Gao, Y.; Wei, W.; Fan, Z.; Zhao, X.; Zhang, Y.; Jing, Y.; Zhu, B.; Zhu, H.; Shan, W.; Chen, J.; et al. Re-evaluation of the nor mutation and the role of the NAC-NOR transcription factor in tomato fruit ripening. J. Exp. Bot. 2020, 71, 3560–3574. [Google Scholar] [CrossRef] [PubMed]
  14. Meng, C.; Yang, D.; Ma, X.; Zhao, W.; Liang, X.; Ma, N.; Meng, Q. Suppression of tomato SlNAC1 transcription factor delays fruit ripening. J. Plant Physiol. 2016, 193, 88–96. [Google Scholar] [CrossRef] [PubMed]
  15. Zhu, M.; Chen, G.; Zhou, S.; Tu, Y.; Wang, Y.; Dong, T.; Hu, Z. A new tomato NAC (NAM/ATAF1/2/CUC2) transcription factor, SlNAC4, functions as a positive regulator of fruit ripening and carotenoid accumulation. Plant Cell Physiol. 2014, 55, 119–135. [Google Scholar] [CrossRef] [PubMed]
  16. Yang, S.; Zhou, J.; Watkins, C.B.; Wu, C.; Feng, Y.; Zhao, X.; Xue, Z.; Kou, X. NAC transcription factors SNAC4 and SNAC9 synergistically regulate tomato fruit ripening by affecting expression of genes involved in ethylene and abscisic acid metabolism and signal transduction. Postharvest Biol. Technol. 2021, 178, 111555. [Google Scholar] [CrossRef]
  17. Wang, G.; Zhang, S.; Ma, X.; Wang, Y.; Kong, F.; Meng, Q. A stress-associated NAC transcription factor (SlNAC35) from tomato plays a positive role in biotic and abiotic stresses. Physiol. Plant 2016, 158, 45–64. [Google Scholar] [CrossRef] [PubMed]
  18. Thirumalaikumar, V.P.; Devkar, V.; Mehterov, N.; Ali, S.; Ozgur, R.; Turkan, I.; Mueller-Roeber, B.; Balazadeh, S. NAC transcription factor JUNGBRUNNEN 1 enhances drought tolerance in tomato. Plant Biotechnol. J. 2018, 16, 354–366. [Google Scholar] [CrossRef] [PubMed]
  19. Jin, J.F.; Wang, Z.Q.; He, Q.Y.; Wang, J.Y.; Li, P.F.; Xu, J.M.; Zheng, S.J.; Fan, W.; Yang, J.L. Genome-wide identification and expression analysis of the NAC transcription factor family in tomato (Solanum lycopersicum) during aluminum stress. BMC Genom. 2020, 21, 1–14. [Google Scholar] [CrossRef] [PubMed]
  20. Wu, S.; Han, B.; Jiao, Y. Genetic Contribution of Paleopolyploidy to Adaptive Evolution in Angiosperms. Mol. Plant 2020, 13, 59–71. [Google Scholar] [CrossRef] [PubMed]
  21. Zhang, K.; Wang, X.; Cheng, F. Plant Polyploidy: Origin, Evolution, and Its Influence on Crop Domestication. Hortic. Plant J. 2019, 5, 231–239. [Google Scholar] [CrossRef]
  22. Ruprecht, C.; Lohaus, R.; Vanneste, K.; Mutwil, M.; Nikoloski, Z.; Van de Peer, Y.; Persson, S. Revisiting ancestral polyploidy in plants. Sci. Adv. 2017, 3, e1603195. [Google Scholar] [CrossRef]
  23. Tang, H.; Bowers, J.E.; Wang, X.; Ming, R.; Alam, M.; Paterson, A.H. Synteny and collinearity in plant genomes. Science 2008, 320, 486–488. [Google Scholar] [CrossRef] [PubMed]
  24. Weiss-Schneeweiss, H.; Emadzade, K.; Jang, T.S.; Schneeweiss, G.M. Evolutionary consequences, constraints and potential of polyploidy in plants. Cytogenet. Genome Res. 2013, 140, 137–150. [Google Scholar] [CrossRef] [PubMed]
  25. Diambra, L.A. Genome sequence and analysis of the tuber crop potato. Nature 2011, 475, 189–195. [Google Scholar]
  26. The French–Italian Public Consortium for Grapevine Genome Characterization. The grapevine genome sequence suggests ancestral hexaploidization in major angiosperm phyla. Nature 2007, 449, 463–467. [Google Scholar] [CrossRef] [PubMed]
  27. Sharma, B.; Taganna, J. Genome-wide analysis of the U-box E3 ubiquitin ligase enzyme gene family in tomato. Sci. Rep. 2020, 10, 9581. [Google Scholar] [CrossRef] [PubMed]
  28. Cai, X.; Zhang, Y.; Zhang, C.; Zhang, T.; Hu, T.; Ye, J.; Zhang, J.; Wang, T.; Li, H.; Ye, Z. Genome-wide analysis of plant-specific Dof transcription factor family in tomato. J. Integr. Plant Biol. 2013, 55, 552–566. [Google Scholar] [CrossRef]
  29. Denoeud, F.; Carretero-Paulet, L.; Dereeper, A.; Droc, G.; Guyot, R.; Pietrella, M.; Zheng, C.; Alberti, A.; Anthony, F.; Aprea, G.; et al. The coffee genome provides insight into the convergent evolution of caffeine biosynthesis. Science 2014, 345, 1181–1184. [Google Scholar] [CrossRef]
  30. Fernandez-Pozo, N.; Menda, N.; Edwards, J.D.; Saha, S.; Tecle, I.Y.; Strickler, S.R.; Bombarely, A.; Fisher-York, T.; Pujar, A.; Foerster, H.; et al. The Sol Genomics Network (SGN)—From genotype to phenotype to breeding. Nucleic Acids Res. 2015, 43, D1036–D1041. [Google Scholar] [CrossRef]
  31. Hosmani, P.S.; Flores-Gonzalez, M.; van de Geest, H.; Maumus, F.; Bakker, L.V.; Schijlen, E.; van Haarst, J.; Cordewener, J.; Sanchez-Perez, G.; Peters, S.; et al. An improved de novo assembly and annotation of the tomato reference genome using single-molecule sequencing, Hi-C proximity ligation and optical maps. bioRxiv 2019, 2019, 767764. [Google Scholar] [CrossRef]
  32. Bolger, A.; Scossa, F.; Bolger, M.E.; Lanz, C.; Maumus, F.; Tohge, T.; Quesneville, H.; Alseekh, S.; Sørensen, I.; Lichtenstein, G.; et al. The genome of the stress-tolerant wild tomato species Solanum pennellii. Nat. Genet. 2014, 46, 1034–1038. [Google Scholar] [CrossRef] [PubMed]
  33. Mistry, J.; Chuguransky, S.; Williams, L.; Qureshi, M.; Salazar, G.A.; Sonnhammer, E.L.; Tosatto, S.C.; Paladin, L.; Raj, S.; Richardson, L.J.; et al. Pfam: The protein families database in 2021. Nucleic Acids Res. 2021, 49, D412–D419. [Google Scholar] [CrossRef] [PubMed]
  34. Stajich, J.E.; Block, D.; Boulez, K.; Brenner, S.E.; Chervitz, S.A.; Dagdigian, C.; Fuellen, G.; Gilbert, J.G.; Korf, I.; Lapp, H.; et al. The Bioperl toolkit: Perl modules for the life sciences. Genome Res. 2002, 12, 1611–1618. [Google Scholar] [CrossRef] [PubMed]
  35. Edgar, R.C. MUSCLE: Multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 2004, 32, 1792–1797. [Google Scholar] [CrossRef] [PubMed]
  36. Mistry, J.; Finn, R.D.; Eddy, S.R.; Bateman, A.; Punta, M. Challenges in homology search: HMMER3 and convergent evolution of coiled-coil regions. Nucleic Acids Res. 2013, 41, e121. [Google Scholar] [CrossRef] [PubMed]
  37. Chao, J.; Li, Z.; Sun, Y.; Aluko, O.O.; Wu, X.; Wang, Q.; Liu, G. MG2C: A user-friendly online tool for drawing genetic maps. Mol. Hortic. 2021, 1, 1–4. [Google Scholar] [CrossRef]
  38. Duvaud, S.; Gabella, C.; Lisacek, F.; Stockinger, H.; Ioannidis, V.; Durinx, C. Expasy, the Swiss Bioinformatics Resource Portal, as designed by its users. Nucleic Acids Res. 2021, 49, W216–W227. [Google Scholar] [CrossRef]
  39. Yu, C.S.; Chen, Y.C.; Lu, C.H.; Hwang, J.K. Prediction of protein subcellular localization. Proteins Struct. Funct. Bioinf. 2006, 64, 643–651. [Google Scholar] [CrossRef]
  40. Geourjon, C.; Deleage, G. SOPMA: Significant improvements in protein secondary structure prediction by consensus prediction from multiple alignments. Bioinformatics 1995, 11, 681–684. [Google Scholar] [CrossRef]
  41. Price, M.N.; Dehal, P.S.; Arkin, A.P. FastTree 2—Approximately maximum-likelihood trees for large alignments. PLoS ONE 2010, 5, e9490. [Google Scholar] [CrossRef] [PubMed]
  42. Wang, Y.; Tang, H.; De Barry, J.D.; Tan, X.; Li, J.; Wang, X.; Lee, T.; Jin, H.; Marler, B.; Guo, H.; et al. MCScanX: A toolkit for detection and evolutionary analysis of gene synteny and collinearity. Nucleic Acids Res. 2012, 40, e49. [Google Scholar] [CrossRef] [PubMed]
  43. Thompson, J.D.; Gibson, T.J.; Higgins, D.G. Multiple sequence alignment using ClustalW and ClustalX. Curr. Protoc. Bioinf. 2003, 2.3.1–2.3.22. [Google Scholar] [CrossRef] [PubMed]
  44. Krzywinski, M.; Schein, J.; Birol, I.; Connors, J.; Gascoyne, R.; Horsman, D.; Jones, S.J.; Marra, M.A. Circos: An information aesthetic for comparative genomics. Genome Res. 2009, 19, 1639–1645. [Google Scholar] [CrossRef]
  45. Barrett, T.; Wilhite, S.E.; Ledoux, P.; Evangelista, C.; Kim, I.F.; Tomashevsky, M.; Marshall, K.A.; Phillippy, K.H.; Sherman, P.M.; Holko, M.; et al. NCBI GEO: Archive for functional genomics data sets—Update. Nucleic Acids Res. 2012, 41, D991–D995. [Google Scholar] [CrossRef]
  46. Diretto, G.; Frusciante, S.; Fabbri, C.; Schauer, N.; Busta, L.; Wang, Z.; Matas, A.J.; Fiore, A.; KC Rose, J.; Fernie, A.R.; et al. Manipulation of β-carotene levels in tomato fruits results in increased ABA content and extended shelf life. Plant Biotechnol. J. 2020, 18, 1185–1199. [Google Scholar] [CrossRef]
  47. Ritchie, M.E.; Phipson, B.; Wu, D.; Hu, Y.; Law, C.W.; Shi, W.; Smyth, G.K. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 2015, 43, e47. [Google Scholar] [CrossRef]
  48. Morgan, M.S.L. AnnotationHub: Client to Access AnnotationHub Resources. R Package Version 340. 2022. Available online: https://annotationhub.bioconductor.org/ (accessed on 8 July 2022).
  49. Yu, G.; Wang, L.G.; Yan, G.R.; He, Q.Y. DOSE: An R/Bioconductor package for disease ontology semantic and enrichment analysis. Bioinformatics 2015, 31, 608–609. [Google Scholar] [CrossRef]
  50. Wu, T.; Hu, E.; Xu, S.; Chen, M.; Guo, P.; Dai, Z.; Feng, T.; Zhou, L.; Tang, W.; Zhan, L.; et al. clusterProfiler 4.0: A universal enrichment tool for interpreting omics data. Innovation 2021, 2, 100141. [Google Scholar] [CrossRef]
  51. Wickham, H. Data Analysis. In ggplot2: Elegant Graphics for Data Analysis; Springer International Publishing: Cham, Switzerland, 2016; pp. 198–210. [Google Scholar]
  52. Yu, G. Enrichplot: Visualization of Functional Enrichment Result. R Package Version 1.16.1. 2022. Available online: http://bioconductor.org/packages/release/bioc/html/enrichplot.html (accessed on 8 July 2022).
  53. Benjamini, Y.; Hochberg, Y. Controlling the False Discovery Rate—A Practical and Powerful Approach to Multiple Testing. J. R. Stat. Soc. Ser. B Methodol. 1995, 57, 289–300. [Google Scholar] [CrossRef]
  54. He, X.; Zhang, J. Rapid Subfunctionalization Accompanied by Prolonged and Substantial Neofunctionalization in Duplicate Gene Evolution. Genetics 2005, 169, 1157–1164. [Google Scholar] [CrossRef] [PubMed]
  55. Yang, Z. PAML 4: Phylogenetic Analysis by Maximum Likelihood. Mol. Biol. Evol. 2007, 24, 1586–1591. [Google Scholar] [CrossRef] [PubMed]
  56. Gene Ontology Consortium. The Gene Ontology resource: Enriching a GOld mine. Nucleic Acids Res. 2021, 49, D325–D334. [Google Scholar] [CrossRef]
  57. Ashburner, M.; Ball, C.A.; Blake, J.A.; Botstein, D.; Butler, H.; Cherry, J.M.; Davis, A.P.; Dolinski, K.; Dwight, S.S.; Eppig, J.T.; et al. Gene ontology: Tool for the unification of biology. Nat. Genet. 2000, 25, 25–29. [Google Scholar] [CrossRef] [PubMed]
  58. Gong, X.; Zhao, L.; Song, X.; Lin, Z.; Gu, B.; Yan, J.; Zhang, S.; Tao, S.; Huang, X. Genome-wide analyses and expression patterns under abiotic stress of NAC transcription factors in white pear (Pyrus bretschneideri). BMC Plant Biol. 2019, 19, 161. [Google Scholar] [CrossRef] [PubMed]
  59. Chen, S.; Lin, X.; Zhang, D.; Li, Q.; Zhao, X.; Chen, S. Genome-Wide Analysis of NAC Gene Family in Betula pendula. Forests 2019, 10, 741. [Google Scholar] [CrossRef]
  60. Shiriga, K.; Sharma, R.; Kumar, K.; Yadav, S.K.; Hossain, F.; Thirunavukkarasu, N. Genome-wide identification and expression pattern of drought-responsive members of the NAC family in maize. Meta Gene 2014, 2, 407–417. [Google Scholar] [CrossRef] [PubMed]
Figure 1. Distribution of NAC genes on two tomato chromosomes. (A) NAC on chromosomes 1 and 7 of S. lycopersicum and S. pennellii with a similar positional distribution. (B) NAC on different chromosomes of S. lycopersicum with chromosome end distribution. Each NAC gene is labeled with its possible origin: DWGT, SWGT, and unknown.
Figure 1. Distribution of NAC genes on two tomato chromosomes. (A) NAC on chromosomes 1 and 7 of S. lycopersicum and S. pennellii with a similar positional distribution. (B) NAC on different chromosomes of S. lycopersicum with chromosome end distribution. Each NAC gene is labeled with its possible origin: DWGT, SWGT, and unknown.
Life 12 01236 g001
Figure 2. Primary structural and physicochemical properties of NAC proteins. (A) The number of amino acids of NAC protein in S. lycopersicum ranged from 122 to 687. (B) The relative molecular mass of NAC protein in S. lycopersicum ranged from 14,427.78 to 76,250.64, a similar to the distribution of amino acid numbers. (C) The isoelectric points of NAC proteins in S. lycopersicum ranged from 4.58 to 9.90, and they were mostly acidic. (D) The instability coefficients of NAC proteins in S. lycopersicum ranged from 24.28 to 61.13, and most of them belonged to instability coefficients (>40). (E) The fatty coefficients of NAC proteins in S. lycopersicum ranged from 40.45 to 82.39. (F) The subcellular localization of NAC proteins in S. lycopersicum was mainly in the nucleus. Each NAC protein is labeled with its possible origin: DWGT, SWGT, and unknown.
Figure 2. Primary structural and physicochemical properties of NAC proteins. (A) The number of amino acids of NAC protein in S. lycopersicum ranged from 122 to 687. (B) The relative molecular mass of NAC protein in S. lycopersicum ranged from 14,427.78 to 76,250.64, a similar to the distribution of amino acid numbers. (C) The isoelectric points of NAC proteins in S. lycopersicum ranged from 4.58 to 9.90, and they were mostly acidic. (D) The instability coefficients of NAC proteins in S. lycopersicum ranged from 24.28 to 61.13, and most of them belonged to instability coefficients (>40). (E) The fatty coefficients of NAC proteins in S. lycopersicum ranged from 40.45 to 82.39. (F) The subcellular localization of NAC proteins in S. lycopersicum was mainly in the nucleus. Each NAC protein is labeled with its possible origin: DWGT, SWGT, and unknown.
Life 12 01236 g002
Figure 3. Predicted secondary structures of two tomato NAC proteins. Horizontal coordinates are the sequentially arranged NAC proteins, and vertical coordinates are the proportion of the four secondary structures of each NAC protein. (A) Secondary structure of the NAC protein in S. lycopersicum has a higher frequency of random curl. (B) Secondary structures of NAC proteins in S. pennellii are similar in distribution to those of S. lycopersicum.
Figure 3. Predicted secondary structures of two tomato NAC proteins. Horizontal coordinates are the sequentially arranged NAC proteins, and vertical coordinates are the proportion of the four secondary structures of each NAC protein. (A) Secondary structure of the NAC protein in S. lycopersicum has a higher frequency of random curl. (B) Secondary structures of NAC proteins in S. pennellii are similar in distribution to those of S. lycopersicum.
Life 12 01236 g003
Figure 4. Phylogenetic tree of S. lycopersicum NAC proteins, the evolutionary rate of each protein is distributed in blocks. type represents different subgroups; Source represents different sources of NAC genes; Bootstrap values are the confidence level of the evolutionary tree; Tree scale represents the unit of branch length.
Figure 4. Phylogenetic tree of S. lycopersicum NAC proteins, the evolutionary rate of each protein is distributed in blocks. type represents different subgroups; Source represents different sources of NAC genes; Bootstrap values are the confidence level of the evolutionary tree; Tree scale represents the unit of branch length.
Life 12 01236 g004
Figure 5. Collinear mapping of S. lycopersicum NAC genes. (a) S. lycopersicum chromosomes and NAC genes. (b) Distribution of genes on chromosomes (per 100 Kb). (c) Distribution of GC content on chromosomes (per 100 Kb). (d) Linkages between all collinear gene pairs of S. lycopersicum (gray), and collinear linkages of NAC genes from different sources (DWGT, red; SWGT, green).
Figure 5. Collinear mapping of S. lycopersicum NAC genes. (a) S. lycopersicum chromosomes and NAC genes. (b) Distribution of genes on chromosomes (per 100 Kb). (c) Distribution of GC content on chromosomes (per 100 Kb). (d) Linkages between all collinear gene pairs of S. lycopersicum (gray), and collinear linkages of NAC genes from different sources (DWGT, red; SWGT, green).
Life 12 01236 g005
Figure 6. Venn diagram of differentially expressed genes at different maturation stages of S. lycopersicum. (A) Comparison of the intersection of upregulated genes in the three maturation stages of S. lycopersicum. (B) Comparison of the intersection of downregulated genes in the three maturation stages of S. lycopersicum.
Figure 6. Venn diagram of differentially expressed genes at different maturation stages of S. lycopersicum. (A) Comparison of the intersection of upregulated genes in the three maturation stages of S. lycopersicum. (B) Comparison of the intersection of downregulated genes in the three maturation stages of S. lycopersicum.
Life 12 01236 g006
Figure 7. Volcano plot of differential expression at different ripening stages of S. lycopersicum. The horizontal coordinate is the log2 value of Fold Change and the vertical coordinate is the −Log10 value of p-value, highly significant differentially expressed genes (Log2(Fold Change) absolute value > 6 and −Log10(p-value) > 10)) are labeled with gene ID. (A) Differential expression of S. lycopersicum genes in MG vs. BR phase, up-regulated genes (red), down-regulated genes (blue). (B) Differential expression of S. lycopersicum gene at BR vs. BR10 stage. (C) Differential expression of S. lycopersicum gene in MG vs. BR10 phase. (D) Differential expression of S. lycopersicum NAC gene at MG vs. BR stage. (E) Differential expression of S. lycopersicum NAC gene at BR vs. BR10 stage. (F) Differential expression of S. lycopersicum NAC gene at MG vs. BR10 stage.
Figure 7. Volcano plot of differential expression at different ripening stages of S. lycopersicum. The horizontal coordinate is the log2 value of Fold Change and the vertical coordinate is the −Log10 value of p-value, highly significant differentially expressed genes (Log2(Fold Change) absolute value > 6 and −Log10(p-value) > 10)) are labeled with gene ID. (A) Differential expression of S. lycopersicum genes in MG vs. BR phase, up-regulated genes (red), down-regulated genes (blue). (B) Differential expression of S. lycopersicum gene at BR vs. BR10 stage. (C) Differential expression of S. lycopersicum gene in MG vs. BR10 phase. (D) Differential expression of S. lycopersicum NAC gene at MG vs. BR stage. (E) Differential expression of S. lycopersicum NAC gene at BR vs. BR10 stage. (F) Differential expression of S. lycopersicum NAC gene at MG vs. BR10 stage.
Life 12 01236 g007
Figure 8. Clustering of differential expression of NAC genes in different ripening stages of S. lycopersicum. The stage represents three different stages of S. lycopersicum fruit ripening; the source represents different sources of NAC genes.
Figure 8. Clustering of differential expression of NAC genes in different ripening stages of S. lycopersicum. The stage represents three different stages of S. lycopersicum fruit ripening; the source represents different sources of NAC genes.
Life 12 01236 g008
Figure 9. KEGG enrichment map of S. lycopersicum MG vs. BR. Horizontal coordinate RichFactor is the ratio of the number of genes enriched by S. lycopersicum in a pathway to the total number of genes in that pathway, and the vertical coordinate is the different pathways defined by KEGG. (A) Enrichment results of upregulated genes in KEGG. (B) Enrichment results of downregulated genes in KEGG.
Figure 9. KEGG enrichment map of S. lycopersicum MG vs. BR. Horizontal coordinate RichFactor is the ratio of the number of genes enriched by S. lycopersicum in a pathway to the total number of genes in that pathway, and the vertical coordinate is the different pathways defined by KEGG. (A) Enrichment results of upregulated genes in KEGG. (B) Enrichment results of downregulated genes in KEGG.
Life 12 01236 g009
Figure 10. Phylogenetic tree and model of C. canephora, S. pennellii, and S. lycopersicum NAC genes. (A) Phylogenetic tree of NAC genes in the three species. (B) Phylogenetic model of the three species, C. canephora:S. pennellii:S. lycopersicum = 1:3:3. (C) Phylogenetic tree of the α branch in (A), consistent with model B. (D) The Phylogenetic tree of the β branch in A with gene loss in both tomatoes.
Figure 10. Phylogenetic tree and model of C. canephora, S. pennellii, and S. lycopersicum NAC genes. (A) Phylogenetic tree of NAC genes in the three species. (B) Phylogenetic model of the three species, C. canephora:S. pennellii:S. lycopersicum = 1:3:3. (C) Phylogenetic tree of the α branch in (A), consistent with model B. (D) The Phylogenetic tree of the β branch in A with gene loss in both tomatoes.
Life 12 01236 g010
Table 1. Identification information of NAC.
Table 1. Identification information of NAC.
Species NameData VersionChromosome NumberTotal Gene NumberNAC Candidate Number
Coffea canephoraAUK _v12n = 2225,57460
Solanum lycopersicumITAG 4.02n = 2434,07585
Solanum pennelliiSpenn-v2.02n = 2448,92388
Table 2. Statistical table of the number of genes from different sources.
Table 2. Statistical table of the number of genes from different sources.
Species NameCount TypeSingletonDispersedProximalTandemSWGTDWGT
C. canephoraNumber71538354300659——9108
Percentage27.97%32.67%1.17%2.58%——35.61%
S. lycopersicumNumber578410,79416724012325414,394
Percentage16.97%31.68%4.91%11.77%9.55%42.24%
S. pennelliiNumber318470541035755620,86114,027
Percentage6.51%14.42%2.12%15.44%42.64%28.67%
Segmental: match genes in syntenic blocks; tandem: continuous repeat; proximal: in nearby chromosomal region but not adjacent; dispersed: other modes than segmental, tandem, and proximal. Number: number of genes by type; percentage (%): percentage between the number of each gene type and the total number of genes in the whole genome.
Table 3. Information on the source of the NAC gene.
Table 3. Information on the source of the NAC gene.
Species NameCount TypeTandemSWGTDWGT
C. canephoraNumber1——38
Percentage1.67%——63.33%
S. lycopersicumNumber31061
Percentage3.53%11.76%71.76%
S. pennelliiNumber71957
Percentage7.95%21.59%64.77%
Number: Number of NAC genes produced by different sources; percentage (%): percentage of the number of NAC genes produced by each source to the total number of NAC genes of the corresponding species.
Table 4. Information on the source of the NAC gene.
Table 4. Information on the source of the NAC gene.
Species NameCount TypeSWGTDWGTNAC SWGTNAC DWGT
C. canephoraKa/Ks < 1——2692——13
Ka/Ks > 1——545——1
S. lycopersicumKa/Ks < 133977814
Ka/Ks > 13631546010
S. pennelliiKa/Ks < 169473065419
Ka/Ks > 182324522
Count type represents different selection pressure directions (columns) and different source gene pair types (rows); numbers represent the number of collinear gene pairs.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Yuan, J.; Liu, Y.; Wang, Z.; Lei, T.; Hu, Y.; Zhang, L.; Yuan, M.; Wang, J.; Li, Y. Genome-Wide Analysis of the NAC Family Associated with Two Paleohexaploidization Events in the Tomato. Life 2022, 12, 1236. https://doi.org/10.3390/life12081236

AMA Style

Yuan J, Liu Y, Wang Z, Lei T, Hu Y, Zhang L, Yuan M, Wang J, Li Y. Genome-Wide Analysis of the NAC Family Associated with Two Paleohexaploidization Events in the Tomato. Life. 2022; 12(8):1236. https://doi.org/10.3390/life12081236

Chicago/Turabian Style

Yuan, Jiale, Ying Liu, Zhenyi Wang, Tianyu Lei, Yanfang Hu, Lan Zhang, Min Yuan, Jinpeng Wang, and Yuxian Li. 2022. "Genome-Wide Analysis of the NAC Family Associated with Two Paleohexaploidization Events in the Tomato" Life 12, no. 8: 1236. https://doi.org/10.3390/life12081236

APA Style

Yuan, J., Liu, Y., Wang, Z., Lei, T., Hu, Y., Zhang, L., Yuan, M., Wang, J., & Li, Y. (2022). Genome-Wide Analysis of the NAC Family Associated with Two Paleohexaploidization Events in the Tomato. Life, 12(8), 1236. https://doi.org/10.3390/life12081236

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

Article Metrics

Back to TopTop