Next Article in Journal
Impact of LED Combinations and Light Intensity on Growth and Yields of Wasabi
Previous Article in Journal
Development of Genomic SSR Markers for Assessing Genetic Diversity in Korean Native Fallopia multiflora
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Horticulturae
Volume 11
Issue 1
10.3390/horticulturae11010001
horticulturae-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Genome-Wide Identification of the ABC Gene Family in Rosaceae and Its Evolution and Expression in Response to Valsa Canker

by
Chenglong Du
1,
Hongqiang Yu
1,
Huanhuan Hu
1,
Zhiqi Dou
1,
Cunwu Zuo
1,2,* and
Junqiang Niu
3,*
1
College of Horticulture, Gansu Agricultural University, Lanzhou 730070, China
2
Key Laboratory of Crop Science in Arid Environment of Gansu Province, Lanzhou 730070, China
3
Institute of Fruit and Floriculture of Gansu Academy of Agricultural Sciences, Lanzhou 730070, China
*
Authors to whom correspondence should be addressed.
Horticulturae 2025, 11(1), 1; https://doi.org/10.3390/horticulturae11010001
Submission received: 15 November 2024 / Revised: 19 December 2024 / Accepted: 21 December 2024 / Published: 24 December 2024
(This article belongs to the Section Genetics, Genomics, Breeding, and Biotechnology (G2B2))
Browse Figures
Versions Notes

Abstract

The ATP-binding cassette (ABC) transporter family plays a critical role in plant growth, development, and disease resistance. However, the evolution and functional characteristics of the ABC gene family in Rosaceae species have not been fully studied. In this study, we performed the first whole-genome identification, as well as an evolutionary analysis and comparative analysis of ABC genes in Rosaceae plants. We identified 3037 ABC genes in 20 plant species, classifying them into eight subfamilies. Comparative analysis revealed significant variations in family size and expansion patterns among species, suggesting adaptive evolution. Tandem duplication (TD: where genes are duplicated in sequence) and whole-genome duplication (WGD: duplication of the entire genome) were identified as the primary drivers of ABC family expansion. In pears, gene pairs produced by WGD underwent purifying selection. Gene ontology (GO) enrichment analysis indicated the involvement of ABC proteins in transmembrane transport and signal transduction pathways. Under Valsa pyri infection, most ABC genes were upregulated in the early stages, highlighting the role of ABCG genes in pathogen response. A weighted gene co-expression network analysis (WGCNA) identified five key ABCG genes potentially involved in pathogen resistance regulation. Our findings provide insights into the evolutionary adaptability of the ABC gene family and their potential applications in plant disease defense.

1. Introduction

The Rosaceae family is rich in biological resources, and its species hold significant economic, ecological, and cultural value [1]. Pear (Pyrus) is one of the most important economic fruit trees globally and is widely cultivated in fruit tree planting and related industries [2]. However, diseases caused by various fungi, such as Valsa canker and powdery mildew, and bacteria, such as soft rot, pose serious challenges [3,4]. Valsa canker is prevalent in woody plants, primarily affecting branches, trunks, and other parts of the tree [5]. The pathogen, Valsa pyri (Vp), secretes proteases that enable its hyphae to penetrate the xylem, posing a severe threat to fruit trees worldwide [6,7]. In particular, pear valsa canker significantly impacts the yield and quality of pears. Pear trees also exhibit a high incidence and widespread occurrence of Vp [8]. Current control methods have limited efficacy and may even lead to substantial mortality or destruction of fruit trees in severe cases [9]. Thus, it is crucial to identify and screen for disease-resistance genes in pear.
The (ATP-binding cassette) ABC gene family is a significant group of transmembrane transporters widely distributed across the biological realm [10,11]. Structurally, ABC transporters are typically composed of a transmembrane domain (TMD) and a nucleotide-binding domain (NBD) [12,13]. The TMD is responsible for the transmembrane transport of substrates, while the NBD binds to ATP, providing the energy necessary to drive the transport process [14,15,16]. ABC transporters are classified into eight families, from ABCA to ABCI, with each subfamily exhibiting specific functions across different species [17,18]. The ABC gene family plays a crucial role in plant growth and development, as well as in fruit and fiber development and photosynthetic efficiency [19,20,21,22,23]. In recent years, the significance of the ABC gene family in plant immunity has garnered considerable attention. Several studies have demonstrated that ABC transporters are involved in plant responses to pathogens by regulating signal transduction, facilitating substance transport, and initiating defensive responses [24,25]. For instance, it has been proposed that ABCG13 transporters participate in the formation of the cuticle and its associated wax [26]. Additionally, ABCG10 proteins can transport secondary metabolites linked to disease resistance, thereby enhancing the defense capabilities of plants [27]. Further research has indicated that ABC transporters play a role in hormone transport and signal transduction, which in turn influences the immune response and adaptability of plants [28,29].
In addition, ABC genes play a significant role in the identification and response to plant pathogens. For instance, TaABCB15-3B and TaABCG38 have been shown to respond to powdery mildew in wheat, while TaABCG2 enhances resistance to fusarium wilt by mediating salicylic acid transport in this species [30,31]. Moreover, OsPDR1 positively regulates jasmonic acid levels, plant cell death, and pathogen resistance in rice [32]. These findings provide compelling evidence for understanding the role of ABC genes in plant immunity. Interestingly, the pattern-triggered immunity (PTI) response that has evolved in plants also involves ABC proteins [33,34]. This further elucidates the complex mechanisms underlying plant resistance to disease and presents potential targets for future breeding programs aimed at improving disease resistance.
In the context of molecular breeding, it is essential to identify genes related to disease resistance using genomics and functional genomics approaches. Currently, research on the role of ABC transporters in the regulation of rot resistance remains limited. In this study, we performed the first genome-wide identification of ABC genes in 20 plant genomes and systematically analyzed the phylogenetic characteristics, expansion rates, and duplication events of the gene superfamily through multi-species comparison systems. Subsequently, we performed a weighted gene co-expression network analysis (WGCNA), protein–protein interaction network analysis, and expression profiling on the disease-resistant variety of Pyrus betulaefolia. Our results elucidate the mechanism of resistance to Valsa canker, identify key disease resistance genes and, for the first time, elucidate the specific role of the ABC gene family in resistance to Vp disease. This study provides a theoretical basis and practical guidance for pear disease resistance breeding.

2. Materials and Methods

2.1. Genome-Wide Identification of ABC Gene Families Across 20 Plant Species

We downloaded the required genomic data from the public genome database (Table S1) and obtained the Hidden Markov Model (HMM) of the ABC domain (PF00005.32) from the InterPro v101.0 database (https://www.ebi.ac.uk/interpro/) (accessed on 5 August 2024) [35]. First, we scanned the whole genomes of 20 species using the hmmscan component of HMMER v3.3.1 (http://hmmer.org) (accessed on 5 August 2024) with an E-value < 1 × 10−10. The identified sequences were then annotated through the Pfam database to obtain candidate family members [36].

2.2. Phylogenetic Analyses

The gene expansion rate refers to the increase in the number of genes within a subfamily over a specific period or at a particular branch point of the evolutionary tree. In calculating this rate, we consider only those common ancestors that possess at least one ancestral gene. To identify orthologous groups formed among different species and to infer the number of ancestral genes, we utilized OrthoFinder v2.5.4 [37]. For the analysis of gene duplication events, we performed multiple alignments of protein sequences from each species using BLASTP v2.11.0, setting the significance threshold to e < 1 × 10−5, and selecting the top five matches. Subsequently, we employed the MCScanX tool to generate homologous gene pairs within each species and to identify ABC-related genes [38]. Additionally, MCScanX was also used to detect tandem duplications (TD) and whole genome duplications (WGD) within the ABC gene family, allowing us to calculate synonymous site (Ks) and non-synonymous site (Ka) substitution rates [39].

2.3. Expression Profiling of Apple ABC Transporters in Different Tissues

To investigate the tissue-specific expression of ABC transporters, we extracted expression data of ABC in apples from previously published transcriptome data (PRJNA183725) [40]. This dataset includes expression patterns from seven tissue types: leaf, root, pulp, apex, stem, whole seedling, and fully flowering flower. The expression levels of Malus x domestica ABC (MdoABC) genes were quantified using fragments per kilobase of transcript per million mapped reads (FPKM). We employed the R package ggplot2 (https://cran.r-project.org/web/packages/ggplot2/) (accessed on 10 August 2024)to construct box plots for data visualization.2.1 genome-wide identification of ABC gene families across 20 plant species.

2.4. Analysis of the ABC Family Protein Interaction Network in Pyrus betulaefolia

Based on the amino acid sequence of Pyrus betulaefolia ABC (PbeABC), we utilized the STRING v12.0 database (https://string-db.org/) (accessed on 14 August 2024) to generate a protein interaction network for PbeABC proteins [41]. This database evaluates protein interactions, retaining only those with an interaction score greater than 0.400 to ensure the reliability of the results. The constructed network was imported into Cytoscape v3.10.2 for visualization, allowing for a more intuitive exploration of the interactions among proteins in the PbeABC gene family and facilitating further evaluation and prediction of their biological functions [42].

2.5. GO and KEGG Enrichment Analysis

Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed for the ABC protein. In this process, we first upload the full-length protein sequence to eggNOG-mapper v2.1.12 and perform a gene annotation search to obtain the GO terms related to each query sequence [43]. This approach enables us to effectively link the target sequences with known protein functions, thereby revealing their potential biological roles. Enrichment analysis was carried out using the clusterProfiler v4.14.4 package in R [44].

2.6. Expression Profile of ABC Under Valsa pyri Stress

RNA-seq data for the PbeABC transporter genes under Vp stress were obtained from our laboratory. Suspension cells were treated with Valsa pyri metabolite (VpM) for durations of 0, 1, 3, and 6 h. Clean reads were mapped to the Pbe genome using the STAR v2.7.11 algorithm [45]. Differentially expressed genes (DEGs) were identified using the DESeq2 v1.46.0 software package, with criteria of |log2Fold-Change| ≥ 2 and p < 0.05. The R package pheatmap (https://CRAN.R-project.org/package=pheatmap) (accessed on 21 August 2024) was utilized to generate a heatmap for visualizing the expression patterns [46]. These analyses were conducted to identify candidate ABC genes in response to Vp infection.

2.7. Weighted Correlation Network Analysis (WGCNA)

Based on the RNA-seq data from a previous transcriptomic study conducted in the laboratory, an FPKM expression matrix was constructed. The R package WGCNA (https://CRAN.R-project.org/package=WGCNA) (accessed on 25 August 2024)was utilized to identify modules with highly similar expression patterns. The fitting parameters employed were as follows: soft threshold = 10, minimum module size = 30, and merging cut height = 0.20. These parameters facilitated the statistical generation of modules using a one-step automatic construction method, which was subsequently distinguished by color coding [47]. The constructed network was imported into Cytoscape v3.10.2 for visualization.

2.8. Statistical Analysis

In this study, we employed the statistical software R for data processing (multcompView: https://CRAN.R-project.org/package=multcompView, tidyverse: https://CRAN.R-project.org/package=tidyverse) (accessed on 20 August 2024), allowing us to perform an analysis of variance (ANOVA) and Tukey’s honestly significant difference (HSD) test. Additionally, basic data statistical analysis was conducted using the Student’s t-test tool in Microsoft Excel 2021. To ensure the reliability and consistency of the experimental results, all experimental designs were independently repeated three times.

3. Results

3.1. Genome-Wide Identification and Phylogenetic Analysis of ATP-Binding Cassette (ABC) Transporters in 20 Plant Species

Building on the ABC transporter HHM, we analyzed gene families from 20 plant species, including monocots, dicots, bryophytes, and ferns (Supplementary Tables S1 and S2). The Pfam database was utilized to assess the integrity of the domains, resulting in the identification of a total of 3037 ABC genes. Phylogenetic trees do not adequately represent grouping due to the complexity of the number of species and genes. To investigate the evolutionary relationship between ABC transporters, we constructed ABC group HMMs using Arabidopsis ABC group members. The similarity and relationship with Arabidopsis thaliana members were then determined based on the results of hmmscan annotation. The ABC transporters were categorized into eight subgroups (Figure 1A). The ABC transporter gene subfamilies varied in size: ABCG comprises the largest subfamily with 1263 members, while ABCE is the smallest with only 59 members, making ABCG the most substantial subfamily. ABCG, ABCB, and ABCC are the subfamilies with the highest member count in Rosaceae (Figure 1B). Supplementary Table S3 provides a summary of the detailed information regarding ABC gene identification.

3.2. Expansion Rate Analysis

The number of ABC transporter members varies significantly among different species and subfamilies, indicating evolutionary specificity. By analyzing the expansion rates of the eight subfamilies, we identified a total of 83 common ancestral genes. Notably, the ABCG, ABCB, and ABCC subfamilies contained a large number of ancestral genes, with counts of 28, 25, and 10, respectively. Many subfamilies have experienced gene loss, resulting in copy numbers that are significantly lower than those of their ancestral genes. This observation suggests subfamily-specific expansions within the ABC transporters. Additionally, we investigated the ABC expansion rates among species; Pbe exhibited higher expansion rates compared to other investigated species.
Through analysis of the expansion patterns of specific subfamilies, we constructed a clustering tree using a complete linkage algorithm. The third group, consisting of five subfamilies (ABCD, ABCB, ABCI, ACBF, and ABCA), was defined as “conservatively extended” subfamilies. By contrast, the first group (ABCF) and the second group (ABCG and ABCC) were considered to be “actively expanding” subfamilies (Figure 1C). A Tukey’s HSD test was employed to identify differences among the various subfamilies within Rosaceae, providing further clarity on the specific expansions of ABCG, ABCB, and ABCC in this plant family (Figure 1D).

3.3. Rapid Amplification of the ABC Family Driven by Repetitive Events

Gene duplication events play a critical role in the expansion of gene families, including mechanisms such as tandem duplication (TD) and whole-genome duplication (WGD). To elucidate the amplification of the ABC gene family, we conducted a gene duplication event analysis. A total of 859 gene pairs were identified across 20 species, comprising 321 TD events and 538 WGD events (Tables S4 and S5, Figure 2A,B). Moreover, significant differences were observed between species and subgroups. For instance, Mba exhibited 29 TD events, while Pda demonstrated only 4 TD events. In the Rosaceae family, TD events were predominantly found in the ABCG, ABCC, and ABCB subgroups, whereas WGD events occurred across most subgroups (Figure 2C). Notably, in the species Ppe, Par, Roc, Fve, and Rch, only ABCG displayed a higher number of WGD events, while other subgroups showed few or no WGD events (Figure 2D). These findings suggest that both TD and WGD contribute to the expansion of the ABC family, exhibiting species specificity. Importantly, Pbe is recognized as a significant species resistant to various stresses, displaying a high rate of expansion and the most gene duplication events. We categorized these events by subfamily and chromosome.

3.4. Tissue-Specific Expression of ABC Genes in Apples

To investigate the tissue-specific expression of the ABC gene family, we extracted expression data for ABC genes in apples from the previously published transcriptome dataset (PRJNA183725). This dataset includes seven tissue types: leaf, root, pulp, apex, stem, whole seedling, and fully flowering flower. Overall, ABC genes are primarily expressed in the flower, root, stem, and other tissues (Figure 3A). Notably, the expression level of ABCF was higher than that of other groups; however, in flowers, the expression of ABCC and ABCD surpassed that of ABCF (Figure 3B).

3.5. Analysis of Chromosomal Position and Evolutionary Selection Pressure of PbeABC Genes

A total of 187 ABC transporters were physically localized on chromosome 17 of PbeABC, with 7 transporters residing on assembled chromosomes (Table S6). The distribution of ABC transporters among all chromosomes was uneven. Chromosome 11 contained the highest number of ABC members, totaling 19; followed by chromosomes 9, 10, and 17, which had 14, 17, and 14 members, respectively; while chromosome 4 harbored only 5 members. The distribution pattern of ABC transporters on individual chromosomes suggests that certain physical regions exhibit a relatively high accumulation of multiple ABC gene clusters (Figure 4A). Additionally, we identified synonymous site (Ks) and nonsynonymous site (Ka) values to explore the selection pressure acting on the ABC gene family in Pbe. The ratio of Ka to synonymous Ks substitutions is often greater than 1. The majority of Ka values fall between 0 and 1, while Ks values exhibit a flatter distribution with a wider range (Figure 4B). The Ka/Ks (ω) ratio for whole-genome duplication (WGD) events ranged from 0.04 to 3.81, with an average of 0.49. Of the 89 pairs of paralogues analyzed, 75 were found to be under purifying selection, The ω ratio of six pairs is >1, indicating positive selection effects. (Figure 4C).

3.6. GO and KEGG Enrichment Analysis of PbeABC Proteins

The diverse protein sequences suggest that the PbeABC gene family is involved in multiple regulatory processes. To further investigate this, we performed GO and KEGG enrichment analyses. The results indicated that the PbeABC proteins are primarily associated with ATPase-coupled transmembrane transporter activity, primary active transmembrane transporter activity, auxin efflux, regulation of auxin-mediated signaling pathways, cotyledon morphogenesis, and hormone transport, among other pathways (Table S7, Figure 5A). Notably, a KEGG enrichment analysis revealed significant involvement in ’ABC Transporters’ and ’RNA Degradation’, suggesting that the ABC gene family plays crucial roles in plant growth and development, morphogenesis, stress response regulation, plant homeostasis, hormone transport, and signal transduction (Figure 5B).

3.7. Protein Interaction Network Analysis of the PbeABC Family

To elucidate the potential regulatory network of the PbeABC proteins, we utilized the STRING database to predict protein interactions. The results revealed direct interactions within the ABC family, which was categorized into six modules based on different subfamilies. Notably, members of the ABCC family serve as key nodes within this network. Furthermore, interactions among PbeABC family members extend beyond direct correlations, involving indirect interactions through multiple intermediary molecules. These findings suggest that PbeABC proteins play a significant role in plant biological processes by interacting with various proteins. Importantly, the nodes ABCC13, ABCC1, ABCF1, ABCF7, and ABCB29 occupy central positions within the network and exhibit extensive connections with numerous other genes, indicating their crucial roles in the regulatory network of PbeABC proteins (Table S8, Figure 6).

3.8. Expression Patterns of PbeABC Under Biotic Stress

Given the extensive regulatory role of the ABC gene family in plants, we aimed to further elucidate its function in regulating the rot of Pbe. Utilizing previous transcriptome data from our laboratory, we analyzed the expression patterns of ABC genes under Vp stress and screened for functional genes. The criteria for significant differential expression were set at |log2FoldChange| > 2 and FDR < 0.05. Notably, most PbeABC genes were significantly up-regulated at the T1 and T2 stages. For instance, genes such as ABCG38, ABCG33, ABCG79, and ABCA3 exhibited fold changes ranging from 3 to 9. However, expression was down-regulated at T3, with partial down-regulation observed at T1 and T2, while certain genes, including ABCB1 and ABCD5, were up-regulated at T3. Interestingly, 22 ABCG genes (75.86%) were up-regulated at T1 and T2 but down-regulated at T3 upon induction by Vp. These findings suggest that ABCG genes have different regulatory effects in response to Vp (Figure 7).

3.9. The Response of the ABC Gene to Vp Is Crucial

Based on the ’Duli-G03′ RNA-seq data under VpM treatment, an FPKM expression matrix was constructed, and co-expression network analysis was performed. All related genes were screened according to a reliability threshold (weight > 0.4), and the ABC genes were annotated. Additionally, a co-expression network of ABC genes was constructed. Notably, Seven genes (ABCG13, ABCG20, ABCG19, ABCG21, ABCG38, ABCG35, and ABC23) were identified as key nodes in the network. The subfamily these genes belong to also had the fastest expansion rate and the most repeated events. The five genes that are located in the most central position and belong to the ABCG subfamily may play a key role in the regulation of Vp (Figure 8).

4. Discussion

4.1. Evolutionary Insights and Subgroup Specialization

ABC transporters represent one of the most ancient and ubiquitous protein families, found across diverse organisms. They play crucial roles in various physiological processes, including growth and development, signal transduction, hormone transport, and stress tolerance [20,21,22]. ABC transporters have been extensively studied in several plant species, such as Arabidopsis, pepper, rice, and pear [48,49,50]. However, comparative analyses and evolutionary studies across multiple species remain limited, especially in the context of disease-resistant plant varieties. In this study, we conducted a comprehensive genomic identification, phylogenetic, and evolutionary analysis of the ABC transporter family in 20 plant species. Our analysis identified 3037 ABC genes, which were divided into eight different subgroups. This classification highlights significant evolutionary divergence and functional specialization among the different subgroups. Notably, the ABCG subfamily emerged as the most abundant, suggesting its potential importance in the adaptive evolution of plant species (Figure 1).

4.2. Gene Duplication and Evolutionary Processes

Gene duplication events, including TD and WGD, play significant roles in gene regulation during evolution [51,52]. Our analysis of 859 gene pairs revealed substantial variation in TD and WGD events among the different subfamilies of ABC transporters (Figure 2). Interestingly, compared with other Rosaceae species, the resistant variety Pbe has the most repeated events. WGD is significant, and the ABCG genes have the most events. This indicates that the evolution of PbeABC is inseparable from the WGD event. This variation highlights the subfamily-specific nature of evolutionary processes, suggesting that different species may employ distinct environmental adaptation strategies. Transcriptome data analysis revealed that ABC transporters exhibit tissue-specific expression patterns. For example, high expression of ABC genes in flowers promotes petal development, and overexpression in roots responds to drought stress [53,54]. Notably, the ABCF subfamily exhibits higher expression levels than other subfamilies, suggesting its potential involvement in specific biological functions. In Arabidopsis, AtABCF3 regulates endoplasmic reticulum stress response and adaptive H2O2 uptake [55]. Rice (Oryza sativa) ABCF5 is also implicated in stress response. Under drought, salt, and Cr-rich heavy metal stress conditions, OsABCF5 expression is significantly upregulated in roots and seedling leaves, indicating its role in rice adaptation to various environmental stresses [56], underscoring their importance in diverse physiological processes (Figure 3).

4.3. Expression Patterns and Their Physiological Implications

ABC transporters play a crucial role in regulating biotic stress responses in plants [24,25,26]. For instance, ABC transporters can modulate wax layer formation for physical defense [27], transport secondary metabolites to enhance defense [28], and interact with receptor-like kinases (RLKs) to regulate plant innate immunity [33]. Our results revealed that the expression pattern of the PbeABC transporter displayed early induction under Vp stress, which aligns with observations reported in previous studies [30]. Our findings demonstrate that, under Vp stress, the expression patterns and up/down-regulation dynamics of PbeABC transporters exhibit temporal variation. Notably, the expression profile changes observed in the ABCG family upon Vp induction suggest a significant role in disease resistance responses (Figure 7). It has been found that Arabidopsis ABCG34 contributes to defense against necrotrophic pathogens by mediating camalexin secretion [57]. Tobacco LkABCG36 and LkABCG40 play important roles in plant development and environmental adaptation [58]. Loss of ABCG14 inhibits the SNC1-mediated defense response [59], further highlighting the importance of the ABCG subgroup.

4.4. Stress Resistance and Biotic Interactions

An analysis of paralogous gene pairs revealed that most exhibited purified selection, indicating stringent selective pressure during evolution. It maintains the frequency of favorable alleles in a population by eliminating deleterious mutations. This suggests that the ABC transporter gene family has been maintained to ensure adaptability to plant growth and development (Figure 4). An interaction network analysis of the ABC transporter family in PbeABC demonstrated not only direct interactions among family members but the formation of a complex regulatory network involving other proteins via intermediary molecules. Subsequently, the interaction can be verified by bimolecular fluorescence complementation (BiFC), luciferase complementation imaging (LUC), yeast two-hybrid, and co-immunoprecipitation (Co-IP) experimental techniques to further analyze the regulatory mechanism. This network provides novel insights into the role of PbeABC in plant biology and signal transduction, particularly highlighting the importance of key nodes such as ABCA5, ABCF1, and ABCD10 (Figure 6).

4.5. Future Directions for Functional Studies

A WGCNA provides a systems-level view of interactions between different modules, facilitating the elucidation of complex biological processes. Researchers have successfully employed a WGCNA to identify RLPs and NLRs that positively regulate Vp resistance in plants [60,61]. We analyzed the expression and function of ABC genes through a weighted gene co-expression network analysis (WGCNA) and further constructed the ABC co-expression network diagram. Our results corroborate the role of the ABC transporter family in stress resistance (Figure 8). Despite being an important stress-resistant gene family, ABC genes have received less research and mechanistic analysis on their stress resistance function. Future functional studies should focus on unraveling the regulatory mechanisms of these genes under specific biotic stresses to uncover their potential applications in plant disease defense. Additionally, these studies can shed light on their potential value in plant growth, development, and stress tolerance, paving the way for further elucidation of the role of ABC transporters in plant growth, development, and pathogen response.

5. Conclusions

This study analyzed the genomic distribution and evolution of ATP-binding cassette (ABC) transporters in 20 plant species. The size of the ABC gene family was found to vary significantly among species through the expansion rate analysis, indicating potential evolutionary adaptability. TD and WGD events were identified as major drivers of ABC gene family expansion, with species-specific patterns; this is similar to previous studies. ABC genes exhibited tissue-specific expression in apples; while in pears, purifying selection acted on gene pairs generated by WGD. The protein interaction network revealed direct and indirect interactions between ABC family members, with ABCC family members emerging as key nodes. GO and KEGG enrichment analyses indicated that ABC proteins are involved in transmembrane transport and signaling pathway regulation. Under Valsa pyri stress, most ABC genes were upregulated in the early stages of infection, suggesting a regulatory role for ABCG genes in pathogen response. A WGCNA further identified five ABCG genes that may play a critical role in the regulation of pathogen resistance. This study provides valuable insights for future research in plant biology and crop science. It can serve as a foundation for prioritizing functional verification and guiding crop improvement strategies.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/horticulturae11010001/s1, Table S1: Species Information and Online Data Websites, Table S2: ABC Gene Family Number in 20 Species, Table S3: ABC Gene Family Identification Details in 20 Species, Table S4: Tandem Duplication Events in 20 Species, Table S5: Whole-Genome Duplication Events in 20 Species, Table S6: PbeABC Gene Family Grouping and Naming, Table S7: PbeABC Gene Family GO Enrichment Details, Table S8: PbeABC Protein Interaction Network Details. ABC_hmm: HMM files for ABC gene family grouping.

Author Contributions

C.Z. and J.N. conceived, designed, and coordinated this study. C.D. and H.Y. performed the experiments. H.H. and Z.D. performed, collected, analyzed, and deposited the data. C.Z., J.N. and C.D. proofread the final draft. All authors have read and agreed to the published version of the manuscript.

Funding

The Science and Technology Major Project of Gansu Province (22ZD6NA045); Gansu Province Science and Technology Mission Special (22CX8NA026); This research was funded by the National Natural Science Foundation of China, grant number 32260741.

Data Availability Statement

The original contributions presented in this study are included in the article and supplementary material. Further inquiries can be directed to the corresponding authors.

Acknowledgments

The authors would like to thank China National Knowledge Infrastructure (CNKI) for providing access to e-resources.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Soundararajan, P.; Won, S.Y.; Kim, J.S. Insight on Rosaceae family with genome sequencing and functional genomics perspective. BioMed Res. Int. 2019, 2019, 7519687. [Google Scholar] [CrossRef] [PubMed]
  2. Shulaev, V.; Korban, S.S.; Sosinski, B.; Abbott, A.G.; Aldwinckle, H.S.; Folta, K.M.; Veilleux, R.E. Multiple models for Rosaceae genomics. Plant Physiol. 2008, 147, 985–1003. [Google Scholar] [CrossRef]
  3. Sardella, D.; Muscat, A.; Brincat, J.P.; Gatt, R.; Decelis, S.; Valdramidis, V. A comprehensive review of the pear fungal diseases. Int. J. Fruit. Sci. 2016, 16, 351–377. [Google Scholar] [CrossRef]
  4. Mizuno, A.; Tsukamoto, T.; Shimizu, Y.; Ooya, H.; Matsuura, T.; Saito, N.; Azegami, K. Occurrence of bacterial black shoot disease of European pear in Yamagata Prefecture. J. Gen. Plant Pathol. 2010, 76, 43–51. [Google Scholar] [CrossRef]
  5. Feng, H.; Wang, C.; He, Y.; Tang, L.; Han, P.; Liang, J.; Huang, L. Apple Valsa canker: Insights into pathogenesis and disease control. Phytopathol. Res. 2023, 5, 45. [Google Scholar] [CrossRef]
  6. Yuan, H.; Shi, B.; Wang, Z.; Qin, G.; Hou, H.; Tu, H.; Wang, L. Exploration of the biocontrol activity of Bacillus atrophaeus strain HF1 against pear Valsa canker caused by Valsa pyri. Int. J. Mol. Sci. 2023, 24, 15477. [Google Scholar] [CrossRef] [PubMed]
  7. Ogilvie, L. Canker and die-back of apples associated with Valsa ambiens. J. Pomol. Hortic. Sci. 1933, 11, 205–213. [Google Scholar] [CrossRef]
  8. Yin, Z.; Liu, H.; Li, Z.; Ke, X.; Dou, D.; Gao, X.; Huang, L. Genome sequence of Valsa canker pathogens uncovers a potential adaptation of colonization of woody bark. New Phytol. 2015, 208, 1202–1216. [Google Scholar] [CrossRef]
  9. Chen, C.; Li, B.H.; Dong, X.L.; Wang, C.X.; Lian, S.; Liang, W.X.; Chen, C.; Li, B.H.; Dong, X.L.; Wang, C.X.; et al. Effects of temperature, humidity, and wound age on Valsa mali infection of apple shoot pruning wounds. Plant Dis. 2016, 100, 2394–2401. [Google Scholar] [CrossRef]
  10. Higgins, C.F.; Linton, K.J. The ATP switch model for ABC transporters. Nat. Struct. Mol. Biol. 2004, 11, 918–926. [Google Scholar] [CrossRef]
  11. Rees, D.C.; Johnson, E.; Lewinson, O. ABC transporters: The power to change. Nat. Rev. Mol. Cell Biol. 2009, 10, 218–227. [Google Scholar] [CrossRef] [PubMed]
  12. Srikant, S.; Gaudet, R. Mechanics and pharmacology of substrate selection and transport by eukaryotic ABC exporters. Nat. Struct. Mol. Biol. 2019, 26, 792–801. [Google Scholar] [CrossRef] [PubMed]
  13. Sánchez-Fernández, R.; Davies, T.E.; Coleman, J.O.; Rea, P.A. The Arabidopsis thaliana ABC protein superfamily, a complete inventory. J. Biol. Chem. 2001, 276, 30231–30244. [Google Scholar] [CrossRef] [PubMed]
  14. Xie, T.; Zhang, Z.; Fang, Q.; Du, B.; Gong, X. Structural basis of substrate recognition and translocation by human ABCA4. Nat. Commun. 2021, 12, 3853. [Google Scholar] [CrossRef] [PubMed]
  15. Dassa, E.; Bouige, P. The ABC of ABCs: A phylogenetic and functional classification of ABC systems in living organisms. Res. Microbiol. 2001, 152, 211–229. [Google Scholar] [CrossRef] [PubMed]
  16. Mishra, A.K.; Choi, J.; Rabbee, M.F.; Baek, K.H. In silico genome-wide analysis of the ATP-binding cassette transporter gene family in soybean (Glycine max L.) and their expression profiling. BioMed Res. Int. 2019, 2019, 8150523. [Google Scholar] [CrossRef] [PubMed]
  17. Roth, C.W.; Holm, I.; Graille, M.; Dehoux, P.; Rzhetsky, A.; Wincker, P.; Brey, P.T. Identification of the Anopheles gambiae ATP-binding cassette transporter superfamily genes. Mol. Cells 2003, 15, 150–158. [Google Scholar] [CrossRef] [PubMed]
  18. Dean, M.; Hamon, Y.; Chimini, G. The human ATP-binding cassette (ABC) transporter superfamily. J. Lipid Res. 2001, 42, 1007–1017. [Google Scholar] [CrossRef] [PubMed]
  19. Kou, X.; Zhao, Z.; Xu, X.; Li, C.; Wu, J.; Zhang, S. Identification and expression analysis of ATP-binding cassette (ABC) transporters revealed its role in regulating stress response in pear (Pyrus bretchneideri). BMC Genom. 2024, 25, 169. [Google Scholar] [CrossRef]
  20. Do, T.H.T.; Martinoia, E.; Lee, Y. Functions of ABC transporters in plant growth and development. Curr. Opin. Plant Biol. 2018, 41, 32–38. [Google Scholar] [CrossRef] [PubMed]
  21. Zhang, M.; Zhao, Y.; Nan, T.; Jiao, H.; Yue, S.; Huang, L.; Yuan, Y. Genome-wide analysis of Citrus medica ABC transporters reveals the regulation of fruit development by CmABCB19 and CmABCC10. Plant Physiol. Biochem. 2024, 215, 109027. [Google Scholar] [CrossRef] [PubMed]
  22. Cui, B.; Li, Y.; Zhang, Y. A comparative genome-wide analysis of the ABC transporter gene family among three Gossypium species. Crop Sci. 2021, 61, 2489–2509. [Google Scholar] [CrossRef]
  23. Ma, F.; Liu, M.; Yan, P.; He, S.; Hu, J.; Zhang, X.; Luo, X. Multi-genome evolutionary study of the ABC1 gene family and identification of the pleiotropic effects of OsABC1-13 in rice development. Crop J. 2024, 12, 1022–1030. [Google Scholar] [CrossRef]
  24. Dhara, A.; Raichaudhuri, A. ABCG transporter proteins with beneficial activity on plants. Phytochemistry 2021, 184, 112663. [Google Scholar] [CrossRef] [PubMed]
  25. Davidson, A.L.; Dassa, E.; Orelle, C.; Chen, J. Structure, function, and evolution of bacterial ATP-binding cassette systems. Microbiol. Mol. Biol. Rev. 2008, 72, 317–364. [Google Scholar] [CrossRef] [PubMed]
  26. Panikashvili, D.; Shi, J.X.; Schreiber, L.; Aharoni, A. The Arabidopsis ABCG13 transporter is required for flower cuticle secretion and patterning of the petal epidermis. New Phytol. 2011, 190, 113–124. [Google Scholar] [CrossRef] [PubMed]
  27. Biała, W.; Banasiak, J.; Jarzyniak, K.; Pawela, A.; Jasiński, M. Medicago truncatula ABCG10 is a transporter of 4-coumarate and liquiritigenin in the medicarpin biosynthetic pathway. J. Exp. Bot. 2017, 68, 3231–3241. [Google Scholar] [CrossRef] [PubMed]
  28. An, L.; Ma, Q.; Du, J.; Yu, M.; Li, F.; Luan, J.; Li, H. Preliminary classification of the ABC transporter family in Betula halophila and expression patterns in response to exogenous phytohormones and abiotic stresses. Forests 2019, 10, 722. [Google Scholar] [CrossRef]
  29. Kang, J.; Hwang, J.U.; Lee, M.; Kim, Y.Y.; Assmann, S.M.; Martinoia, E.; Lee, Y. PDR-type ABC transporter mediates cellular uptake of the phytohormone abscisic acid. Proc. Natl. Acad. Sci. USA 2010, 107, 2355–2360. [Google Scholar] [CrossRef]
  30. Wang, G.; Gu, J.; Long, D.; Zhang, X.; Zhao, C.; Zhang, H.; Ji, W. Genome-wide identification of wheat ABC gene family and expression in response to fungal stress treatment. Plant Biotechnol. Rep. 2024, 18, 401–413. [Google Scholar] [CrossRef]
  31. Zhang, Y.Z.; Man, J.; Wen, L.; Tan, S.Q.; Liu, S.L.; Li, Y.H.; Wei, Y.M. ATP-binding cassette transporter TaABCG2 contributes to Fusarium head blight resistance by mediating salicylic acid transport in wheat. Mol. Plant Pathol. 2024, 25, e70013. [Google Scholar] [CrossRef]
  32. Zhang, H.; Jing, W.; Zheng, J.; Jin, Y.; Wu, D.; Cao, C.; Zhang, W. The ATP-binding cassette transporter OsPDR1 regulates plant growth and pathogen resistance by affecting jasmonates biosynthesis in rice. Plant Sci. 2020, 298, 110582. [Google Scholar] [CrossRef] [PubMed]
  33. Burra, D.D.; Lenman, M.; Levander, F.; Resjö, S.; Andreasson, E. Comparative membrane-associated proteomics of three different immune reactions in potato. Int. J. Mol. Sci. 2018, 19, 538. [Google Scholar] [CrossRef]
  34. Aryal, B.; Xia, J.; Hu, Z.; Stumpe, M.; Tsering, T.; Liu, J.; Geisler, M.M. An LRR receptor kinase controls ABC transporter substrate preferences during plant growth-defense decisions. Curr. Biol. 2023, 33, 2008–2023.e8. [Google Scholar] [CrossRef]
  35. Paysan-Lafosse, T.; Blum, M.; Chuguransky, S.; Grego, T.; Pinto, B.L.; Salazar, G.A.; Bateman, A. InterPro in 2022. Nucleic Acids Res. 2023, 51, D418–D427. [Google Scholar] [CrossRef] [PubMed]
  36. Mistry, J.; Chuguransky, S.; Williams, L.; Qureshi, M.; Salazar, G.A.; Sonnhammer, E.L.; Bateman, A. PFAM: The protein families database in 2021. Nucleic Acids Res. 2021, 49, D412–D419. [Google Scholar] [CrossRef] [PubMed]
  37. Emms, D.M.; Kelly, S. OrthoFinder: Solving fundamental biases in whole genome comparisons dramatically improves orthogroup inference accuracy. Genome Biol. 2015, 16, 157. [Google Scholar] [CrossRef] [PubMed]
  38. Wang, Y.; Tang, H.; DeBarry, J.D.; Tan, X.; Li, J.; Wang, X.; Paterson, A.H. MCScanX: A toolkit for detection and evolutionary analysis of gene synteny and collinearity. Nucleic Acids Res. 2012, 40, e49. [Google Scholar] [CrossRef] [PubMed]
  39. Qiao, X.; Li, Q.; Yin, H.; Qi, K.; Li, L.; Wang, R.; Paterson, A.H. Gene duplication and evolution in recurring polyploidization–diploidization cycles in plants. Genome Biol. 2019, 20, 38. [Google Scholar] [CrossRef]
  40. Celton, J.; Gaillard, S.; Bruneau, M.; Pelletier, S.; Aubourg, S.; Martin-Magniette, M.; Renou, J. Widespread anti-sense transcription in apple is correlated with si RNA production and indicates a large potential for transcriptional and/or post-transcriptional control. New Phytol. 2014, 203, 287–299. [Google Scholar] [CrossRef] [PubMed]
  41. Szklarczyk, D.; Kirsch, R.; Koutrouli, M.; Nastou, K.; Mehryary, F.; Hachilif, R.; Von Mering, C. The STRING database in 2023: Protein–protein association networks and functional enrichment analyses for any sequenced genome of interest. Nucleic Acids Res. 2023, 51, D638–D646. [Google Scholar] [CrossRef] [PubMed]
  42. Shannon, P.; Markiel, A.; Ozier, O.; Baliga, N.S.; Wang, J.T.; Ramage, D.; Ideker, T. Cytoscape: A software environment for integrated models of biomolecular interaction networks. Genome Res. 2003, 13, 2498–2504. [Google Scholar] [CrossRef] [PubMed]
  43. Cantalapiedra, C.P.; Hernández-Plaza, A.; Letunic, I.; Bork, P.; Huerta-Cepas, J. eggNOG-mapper v2: Functional annotation, orthology assignments, and domain prediction at the metagenomic scale. Mol. Biol. Evol. 2021, 38, 5825–5829. [Google Scholar] [CrossRef]
  44. Yu, G.; Wang, L.G.; Han, Y.; He, Q.Y. clusterProfiler: An R package for comparing biological themes among gene clusters. Omics A J. Integr. Biol. 2012, 16, 284–287. [Google Scholar] [CrossRef]
  45. Dobin, A.; Davis, C.A.; Schlesinger, F.; Drenkow, J.; Zaleski, C.; Jha, S.; Gingeras, T.R. STAR: Ultrafast universal RNA-seq aligner. Bioinformatics 2013, 29, 15–21. [Google Scholar] [CrossRef] [PubMed]
  46. Love, M.I.; Huber, W.; Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014, 15, 550. [Google Scholar] [CrossRef]
  47. Langfelder, P.; Horvath, S. WGCNA: An R package for weighted correlation network analysis. BMC Bioinform. 2008, 9, 559. [Google Scholar] [CrossRef] [PubMed]
  48. Sugiyama, A.; Shitan, N.; Sato, S.; Nakamura, Y.; Tabata, S.; Yazaki, K. Genome-wide analysis of ATP-binding cassette (ABC) proteins in a model legume plant, Lotus japonicus: Comparison with Arabidopsis ABC protein family. DNA Res. 2006, 13, 205–228. [Google Scholar] [CrossRef] [PubMed]
  49. Lopez-Ortiz, C.; Dutta, S.K.; Natarajan, P.; Peña-Garcia, Y.; Abburi, V.; Saminathan, T.; Nimmakayala, P.; Reddy, U.K. Genome-wide identification and gene expression pattern of ABC transporter gene family in Capsicum spp. PLoS ONE 2019, 14, e0215901. [Google Scholar] [CrossRef]
  50. Gupta, B.B.; Selter, L.L.; Baranwal, V.K. Updated inventory, evolutionary and expression analyses of G (PDR) type ABC transporter genes of rice. Plant Physiol. Biochem. 2019, 142, 429–439. [Google Scholar] [CrossRef]
  51. Badouin, H.; Gouzy, J.; Grassa, C.J.; Murat, F.; Staton, S.E.; Cottret, L.; Lelandais-Brière, C.; Owens, G.L.; Carrère, S.; Mayjonade, B. The sunflower genome provides insights into oil metabolism, flowering and Asterid evolution. Nature 2017, 546, 148–152. [Google Scholar] [CrossRef] [PubMed]
  52. Ren, R.; Wang, H.; Guo, C.; Zhang, N.; Zeng, L.; Chen, Y.; Ma, H.; Qi, J. Widespread whole genome duplications contribute to genome complexity and species diversity in Angiosperms. Mol. Plant 2018, 11, 414–428. [Google Scholar] [CrossRef]
  53. Zhang, D.; Yu, Z.; Zeng, B.; Liu, X. Genome-wide analysis of the ABC gene family in almond and functional predictions during flower development, freezing stress, and salt stress. BMC Plant Biol. 2024, 24, 12. [Google Scholar] [CrossRef]
  54. Yang, X.; Cui, X.; Chang, J.; Wang, J.; Wang, Y.; Liu, H.; Zhou, Y. Variations in Protein and Gene Expression Involved in the Pathways of Carbohydrate, Abscisic Acid, and ATP-Binding Cassette Transporter in Soybean Roots under Drought Stress. Agronomy 2024, 14, 843. [Google Scholar] [CrossRef]
  55. Li, S.; Li, D.; Zhang, P.; Wang, R.; Sun, L.; Wan, J.; Xu, J. ABCF3 regulates the expression of aquaporin genes and endoplasmic reticulum stress-related genes in Arabidopsis. Theor. Exp. Plant Physiol. 2018, 30, 215–222. [Google Scholar] [CrossRef]
  56. Moon, S.; Jung, K.H. Genome-wide expression analysis of rice ABC transporter family across spatio-temporal samples and in response to abiotic stresses. J. Plant Physiol. 2014, 171, 1276–1288. [Google Scholar]
  57. Khare, D.; Choi, H.; Huh, S.U.; Bassin, B.; Kim, J.; Martinoia, E.; Lee, Y. Arabidopsis ABCG34 contributes to defense against necrotrophic pathogens by mediating the secretion of camalexin. Proc. Natl. Acad. Sci. USA 2017, 114, E5712–E5720. [Google Scholar] [CrossRef] [PubMed]
  58. Sun, N.; Li, C.; Jiang, X.; Gai, Y. Transcriptomic Insights into Functions of LkABCG36 and LkABCG40 in Nicotiana tabacum. Plants 2023, 12, 227. [Google Scholar] [CrossRef] [PubMed]
  59. Wang, S.; Wang, S.; Sun, Q.; Yang, L.; Zhu, Y.; Yuan, Y.; Hua, J. A role of cytokinin transporter in Arabidopsis immunity. Mol. Plant-Microbe Interact. 2017, 30, 325–333. [Google Scholar] [CrossRef] [PubMed]
  60. Yu, H.; Sun, E.; Mao, X.; Chen, Z.; Xu, T.; Zuo, L.; Zuo, C. Evolutionary and functional analysis reveals the crucial roles of receptor-like proteins in resistance to Valsa canker in Rosaceae. J. Exp. Bot. 2023, 74, 162–177. [Google Scholar] [CrossRef] [PubMed]
  61. Cao, Y.; Yu, H.; Tian, D.; Sun, E.; Zuo, L.; Jiang, D.; Zuo, C.; Fan, R. Phylogeny, Expression Profiling, and Coexpression Networks Reveals the Critical Roles of Nucleotide-BindingLeucine-Rich Repeats on Valsa Canker Resistance. Horticulturae 2023, 9, 345. [Google Scholar] [CrossRef]
Horticulturae 11 00001 g001
Figure 1. ABC System Analysis and Expansion Rate Analysis of 20 Plant Species. (A) The heat map shows the number of characteristics of the ABC subfamily of 20 species. (B) Box plot of the number of ABCs in Rosaceae. Different letters at the top of the map indicate significant differences in the expansion rate between subfamilies. (C) The heat map shows the expansion rate of different subfamilies in different species. (D) The box plot shows the expansion rate of different subfamilies in Rosaceae. Different letters at the top of the figure indicate significant differences in the expansion rate among subfamilies. Analysis of variance was used, followed by Tukey’s HSD test (p < 0.05).
Figure 1. ABC System Analysis and Expansion Rate Analysis of 20 Plant Species. (A) The heat map shows the number of characteristics of the ABC subfamily of 20 species. (B) Box plot of the number of ABCs in Rosaceae. Different letters at the top of the map indicate significant differences in the expansion rate between subfamilies. (C) The heat map shows the expansion rate of different subfamilies in different species. (D) The box plot shows the expansion rate of different subfamilies in Rosaceae. Different letters at the top of the figure indicate significant differences in the expansion rate among subfamilies. Analysis of variance was used, followed by Tukey’s HSD test (p < 0.05).
Horticulturae 11 00001 g001
Horticulturae 11 00001 g002
Figure 2. Gene duplication event analysis. (A) Number of gene pairs of tandem duplication (TD) and whole-genome duplication (WGD) events in different species. (B) TD and WGD events in different subfamilies of 20 species. (C) Heat map of the number of TD events in Rosaceae. (D) Heat map of the number of WGD events in Rosaceae.
Figure 2. Gene duplication event analysis. (A) Number of gene pairs of tandem duplication (TD) and whole-genome duplication (WGD) events in different species. (B) TD and WGD events in different subfamilies of 20 species. (C) Heat map of the number of TD events in Rosaceae. (D) Heat map of the number of WGD events in Rosaceae.
Horticulturae 11 00001 g002
Horticulturae 11 00001 g003
Figure 3. Tissue specificity analysis. (A) The figure shows the distribution characteristics of ABCs in different subfamilies in different tissues. Significant differences among organizations were indicated by different letters at the top of the figure. Analysis of variance was used, followed by Tukey’s HSD test (p < 0.05). (B) The distribution characteristics of different tissues in different subgroups, and blue is the average value of each tissue.
Figure 3. Tissue specificity analysis. (A) The figure shows the distribution characteristics of ABCs in different subfamilies in different tissues. Significant differences among organizations were indicated by different letters at the top of the figure. Analysis of variance was used, followed by Tukey’s HSD test (p < 0.05). (B) The distribution characteristics of different tissues in different subgroups, and blue is the average value of each tissue.
Horticulturae 11 00001 g003
Horticulturae 11 00001 g004
Figure 4. Analysis of chromosome location and evolutionary selection. (A) Figure A shows the distribution of different subgroups of PbeABC on chromosomes, and the number on top is the number of genes. (B) Density plot representing the distribution of Ka and Ks values. (C) Figure C shows the Ka/Ks analysis of WGD gene pairs. The line is the regression line, and the gene ID of Ka/Ks > 1 is displayed.
Figure 4. Analysis of chromosome location and evolutionary selection. (A) Figure A shows the distribution of different subgroups of PbeABC on chromosomes, and the number on top is the number of genes. (B) Density plot representing the distribution of Ka and Ks values. (C) Figure C shows the Ka/Ks analysis of WGD gene pairs. The line is the regression line, and the gene ID of Ka/Ks > 1 is displayed.
Horticulturae 11 00001 g004
Horticulturae 11 00001 g005
Figure 5. PbeABC GO and KEGG enrichment analysis. (A) Bubble diagram showing the top 20 GO enrichments. (B) Network diagram showing KEGG enrichment analysis.
Figure 5. PbeABC GO and KEGG enrichment analysis. (A) Bubble diagram showing the top 20 GO enrichments. (B) Network diagram showing KEGG enrichment analysis.
Horticulturae 11 00001 g005
Horticulturae 11 00001 g006
Figure 6. PbeABC protein interaction network. The larger the circle is, the more central the node it represents.
Figure 6. PbeABC protein interaction network. The larger the circle is, the more central the node it represents.
Horticulturae 11 00001 g006
Horticulturae 11 00001 g007
Figure 7. Analysis of PbeABC expression pattern. The figure shows the expression pattern of PbeABC when induced by Vp. All the differential genes in the ABC family are shown in the figure, and the value is log2FC. T1, T2, and T3 were treated for 1h, 3h, and 6h, respectively. FC: fold change.
Figure 7. Analysis of PbeABC expression pattern. The figure shows the expression pattern of PbeABC when induced by Vp. All the differential genes in the ABC family are shown in the figure, and the value is log2FC. T1, T2, and T3 were treated for 1h, 3h, and 6h, respectively. FC: fold change.
Horticulturae 11 00001 g007
Horticulturae 11 00001 g008
Figure 8. Weighted co-expression network diagram. The key node gene is shown on the right, and different colors represent different subfamilies. The weight is set to 0.4.
Figure 8. Weighted co-expression network diagram. The key node gene is shown on the right, and different colors represent different subfamilies. The weight is set to 0.4.
Horticulturae 11 00001 g008
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Du, C.; Yu, H.; Hu, H.; Dou, Z.; Zuo, C.; Niu, J. Genome-Wide Identification of the ABC Gene Family in Rosaceae and Its Evolution and Expression in Response to Valsa Canker. Horticulturae 2025, 11, 1. https://doi.org/10.3390/horticulturae11010001

AMA Style

Du C, Yu H, Hu H, Dou Z, Zuo C, Niu J. Genome-Wide Identification of the ABC Gene Family in Rosaceae and Its Evolution and Expression in Response to Valsa Canker. Horticulturae. 2025; 11(1):1. https://doi.org/10.3390/horticulturae11010001

Chicago/Turabian Style

Du, Chenglong, Hongqiang Yu, Huanhuan Hu, Zhiqi Dou, Cunwu Zuo, and Junqiang Niu. 2025. "Genome-Wide Identification of the ABC Gene Family in Rosaceae and Its Evolution and Expression in Response to Valsa Canker" Horticulturae 11, no. 1: 1. https://doi.org/10.3390/horticulturae11010001

APA Style

Du, C., Yu, H., Hu, H., Dou, Z., Zuo, C., & Niu, J. (2025). Genome-Wide Identification of the ABC Gene Family in Rosaceae and Its Evolution and Expression in Response to Valsa Canker. Horticulturae, 11(1), 1. https://doi.org/10.3390/horticulturae11010001

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