Genome-wide survey and expression analysis of peptides containing tyrosine sulfation (PSY) gene family in Cicer arietinum L.

Abstract

Background

Plant growth and developmental processes are tightly regulated by small secreted peptides, however, the functions and mechanisms of Tyrosine Sulfation-containing Peptides (PSY) remain unclear. In chickpea, knowledge of PSY genes family is limited.

Results

This study employed comprehensive bioinformatics approaches to identify and characterize seven CaPSY genes in the chickpea genome. The analyses encompass chromosomal localization, evolutionary relationships, gene structure, conserved motif identification, promoter architecture, prediction of PSY-targeting miRNAs, and expression profiling. Chromosomal mapping revealed that CaPSY genes are confined to four specific chromosomes rather than being evenly distributed across the genome. Phylogenetic analysis resolved nine distinct groups, each further subdivided into subgroups. Additionally, CaPSY genes were found to contain one to two introns. Amino acid sequence comparisons demonstrated that each CaPSY gene consistently harbors a PSY domain in its C-terminal end. Promoter analysis of CaPSY genes revealed the presence of multiple hormone-responsive elements, including ABRE, SARE, AuxRE, and MeJARE, as well as stress-related elements such as the drought-responsive MBS, suggesting potential regulatory roles in development and stress adaptation. Further, the expression patterns of CaPSY were evaluated in multiple tissues as well as in response to abiotic stresses. The results indicated differential expression of CaPSY genes among tissues and under multiple abiotic stress conditions. We further detected several miRNAs likely to target CaPSY genes and assessed how they are expressed in different tissues.

Conclusion

Thus, these findings serve as a crucial resource for basic and applied research, enabling advancements in chickpea productivity and stress tolerance via precise genome editing and innovative breeding methods.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-026-12662-6.

Introduction

The intricate network of cell-to-cell communication in plants orchestrates both developmental processes and adaptive responses to environmental stress [1]. Within this network, secreted peptides function as key signaling molecules, playing critical roles in regulating plant responses to changing environmental conditions [2]. Signaling peptides, particularly those containing sulfated tyrosine residues (PSYs), are of special significance due to their roles in regulating developmental pathways and mediating defense responses to both biotic and abiotic stresses [3]. Signaling peptides originate from prepropeptides that typically range from 70 to 200 amino acids in length. The presence of an N-terminal signal peptide directs these prepropeptides into the secretory pathway, where they undergo proteolytic processing and various post-translational modifications essential for peptide maturation [3–6]. Post-translational changes such as proline hydroxylation, hydroxy proline arabinosylation, and tyrosine sulfation are pivotal in facilitating plant signaling processes [7–9]. Leucine-rich repeat-receptor kinases (LRR-RKs) play a significant role in detecting various endogenous peptide hormones. To date, four distinct tyrosine-sulfated peptides known: Casparian strip integrity factors (CIFs), root growth meristem factors (RGFs), phytosulfokines (PSKs), and PSYs [8]. As the earliest-discovered tyrosine-sulfated peptide in plants, PSK is a pentapeptide whose function relies on the sulfation of two tyrosine residues. Recent findings uncovered three PSYRs that recognize PSY peptides. When unbound by these peptides, the receptors inhibit plant growth and initiate stress tolerance responses [10, 11]. The PSY–PSYR signaling module balances plant growth with stress responses, allowing plants to adapt to changing environments [12, 13].

PSY1, an 18–amino acid peptide identified in Arabidopsis, is a key PSY family member involved in cell elongation, proliferation, and immune regulation [3, 6, 14]. Upon binding, it initiates the activation of PSY1R, subsequently amplifying plasma membrane H⁺-ATPase activity. This function plays a pivotal role in secondary active transport and adaptation to stress [15, 16]. PSY1 offers a model for studying how plants balance growth and immunity, ultimately enhancing their capacity to withstand stress. Investigations into PSY peptides now includes PSY1 and seven homologous genes identified in Arabidopsis, unveiling PSY peptides are widely conserved in both mosses and higher plants [6, 13, 16]. This avenue of research has proposed a model implicating subtilisin-like subtilases in the processing of PSY propeptides, offering insights into their diverse roles in plant development [6, 17]. While notable strides have been taken, a comprehensive understanding of PSY peptides functions remains elusive, highlighting the imperative for sustained exploration in higher plants. Despite significant progress in understanding PSY1, the wider functional contributions of the PSY family to plant intercellular signaling remains to be elucidated. Decoding the complexity of PSY genes can shed light on developmental and stress-related processes in plants, paving the way for strategies to boost agricultural productivity. PSY genes play vital roles in cellular processes, yet many members of this gene family in newly sequenced crop genomes remain insufficiently explored. Notably, OsPSY genes and miRNAs characterized in rice represent attractive avenues for genome-editing interventions to achieve higher yield and greater stress resilience [17].

Chickpea (Cicer arietinum) stands as the second most important legume in terms of global cultivation, with a vital contribution to food security, especially in developing countries and its ability to engage in symbiotic nitrogen fixation [18, 19]. In addition, chickpea is a versatile crop, providing protein, minerals, fiber, and vitamins to many people across Asia and Africa [20, 21]. India accounts for the majority of the world’s chickpea production [22]. Chickpea productivity faces numerous challenges due to biotic and abiotic stress. However, attempts to enhance production have been hampered by restricted genetic diversity found in cultivated chickpea varieties [23]. Climate change is expected to amplify stresses for instance, heat and salt stress, heightening the need for chickpea varieties capable of coping with these challenges. The objective of this study is to identify and characterize candidate genes associated with plant growth, development, and abiotic stress tolerance. However, information regarding the PSY gene family in legumes remains limited. The identification of these genes is expected to facilitate the development of improved chickpea varieties with enhanced tolerance to abiotic stresses. To address this objective, we employed a suite of bioinformatics tools to perform a comprehensive genome-wide analysis of PSY genes in chickpea. Our comprehensive investigation involved detailed analyses of chromosomal localization, gene duplication events, gene structure, conserved motifs, three-dimensional protein structures, promoter cis-regulatory elements, miRNA interactions, and tissue-specific expression patterns of CaPSY genes. In addition, we scrutinized their expression responses under diverse abiotic stress conditions. The findings of this study provide a robust biological framework for understanding the roles of CaPSY genes and facilitate the identification of promising candidate genes for genetic manipulation and breeding applications. Collectively, this work represents an important step toward the effective use of genomic resources to improve chickpea productivity and resilience, thereby contributing to efforts to address global food security challenges.

Materials and methods

Discovery and characterization of PSY genes in Chickpea

Genomic data for Cicer arietinum was retrieved from the Phytozome database using the CDC Frontier v1.0 genome assembly (accessed on 10 May 2024; release date: 27 January 2013; DOI: 10.1038/nbt.2491) for genome-wide analysis. Protein-coding sequences, including CDS and corresponding peptide FASTA files, were used, and redundant isoforms were removed prior to downstream analyses. We used two approaches to find potential PSY genes in chickpea genome. First, a local databank of chickpea protein sequences was created utilizing the BioEdit (BioEdit v7.1.1; accessed on 10 May 2024). Then, BLASTp searches were performed against this local database employed PSY proteins from wheat, rice, soybean, and Arabidopsis as queries. Potential PSY proteins in chickpea genome were discovered using a cut off of e-value ≤ 10⁻⁵ and bit scores greater than 100. In the second method, protein sequences from Arabidopsis, rice, soybean, and wheat were obtained from Phytozome (Accessed on 12 May 2024). A BLASTp search of the chickpea proteome was performed using these sequences, applying an E-value threshold of 1 × 10⁻⁵, with default word size, the BLOSUM62 substitution matrix, bit scores greater than 100, and default gap penalties. Putative candidate PSY genes were identified using both approaches. Furthermore, the InterPro database (Accessed on 13 May 2024) was used to screened for domain of PSY, designated as IPR034430 [24]. The identified sequences were then submitted to InterProScan [25] to identify the conserved PSY domains [26]. To confirm the PSY domain, the sequences were submitted to HMMER searches (https://www.ebi.ac.uk/Tools/hmmer/home), SMART databases (Accessed on 13 May 2024) [27] and NCBI-CDD [28] (Accessed on 13 May 2024) with thresholds set at an E-value ≤ 1 × 10⁻⁵ and domain coverage ≥ 50%. Ultimately, genes containing PSY domains were isolated and named sequentially based on their positions on the chromosomes.

Analysis and characterization of PSY protein phylogeny

Phylogenetic analysis was conducted to discern similarity and evolutionary relationships among the genes, enabling the classification of PSY proteins into distinct groups in chickpea. Phylogenetic tree was produced using NJ method in MEGA 10 (MEGA v10.2.6.; accessed on 15 May 2024), 1,000 bootstrap to assess branch support [29] employing the p-distance substitution model and treating all gaps and missing data by complete deletion. Subsequently, the phylogenetic tree was refined utilizing the iTOL [30] (Accessed on 16 May 2024). The coding and noncoding regions of the PSY genes were identified using the GSDS [31] (Accessed on 16 May 2024).

Analysis of physicochemical characteristics and conserved motifs in PSY genes

The protein motifs in PSY were identified using Multiple Em for Motif Elicitation [32] (MEME v5.5.7; accessed 13 May 2024). The analysis parameters included a maximum motif number of 10, motif widths ranging from a minimum of 6 to a maximum of 50 amino acids, and a statistical significance threshold set at an E-value ≤ 0.05. The molecular weight (MW), isoelectric point (pI), and other physicochemical properties of the corresponding PSY proteins were computed using ExPASy, ProtParam [33] and Isoelectric Point Calculator [34] (Accessed on 17 May 2024) using default parameter settings. The subcellular localization of all seven PSY proteins was predicted using the BUSCA server using default parameter settings [35, 36].

Genome-wide chromosomal localization and duplication analysis of PSY genesGenome-wide chromosomal localization and duplication analysis of PSY gen

Gene locations were mapped based on their chromosomal start and end positions. Ritchielab [37] (Accessed on 18 May 2024) was used to visualize chromosomal positions of genes. Gene duplication events were investigated using the MCScan toolkit [38]. Subsequently, the Ka/Ks ratio was computed via TBtools (TBtools v2.84.0.0.; accessed on 19 May 2024) [39] using default parameter settings.

Promoter analysis and homology modeling of PSY genes

For each of the seven genes, promoter sequences spanning 1,500 bp upstream of the annotated transcription start sites (TSS) were retrieved using genomic coordinates from the chickpea genome CDC Frontier v1.0 assembly available in the Phytozome database. Strand orientation was verified to ensure correct strand specificity, and upstream regions overlapping with adjacent genes were carefully excluded. A 1,500 bp upstream region is commonly employed in plant cis-regulatory element analyses, as it effectively captures core and proximal promoter elements while minimizing the inclusion of unrelated regulatory regions. The extracted promoter sequences were analyzed in the PlantCARE database to identify and annotate putative cis-regulatory elements [40] (Accessed on 20 May 2024). Additionally, the 3D models of the seven genes were predicted using phyre web server [41] (Accessed on 22 May 2024). Phyre2 was employed in intensive modeling mode to maximize structural prediction accuracy. The predicted structures were validated using Ramachandran plot analysis to assess stereochemical quality and overall model reliability.

Expression pattern analysis and MiRNA target prediction in PSY genes

To investigate tissue-specific and stress-responsive expression of PSY, RNA-seq datasets were obtained from the NCBI-SRA database (SRA; http://www.ncbi.nlm.nih.gov/sra/; accessed on 24 May 2024). The analysis incorporated these SRA datasets: shoot drought (SRX402844), root drought (SRX402840), shoot salinity (SRX402845), root salinity (SRX402841), shoot cold (SRX402846), root cold (SRX402842), shoot control (SRX402843), and root control (SRX402839). The above RNA-seq datasets used in this study were originally generated by Garg et al. [42]. In the original experiment, root and shoot tissues were harvested from 10-day-old chickpea seedlings exposed to various abiotic stress treatments. Seedlings grown in water served as controls. Drought stress was induced by transferring seedlings onto folded tissue paper, salinity stress by placing seedlings in a 150 mM NaCl solution, and cold stress by maintaining seedlings in water at 4 ± 1 °C. All stress treatments were applied for 5 h. Total RNA was isolated from the treated and control tissues and subjected to Illumina-based high-throughput sequencing. Raw sequencing reads were quality-filtered using the NGS QC Toolkit to obtain clean, high-quality reads, which were subsequently aligned to the annotated chickpea reference genome using TopHat. Gene expression levels were estimated as fragments per kilobase of exon per million mapped reads (FPKM) using Cufflinks, and differential expression analysis was performed with Cuffdiff. The processed RNA-seq expression data were retrieved, and FPKM values corresponding to the genes identified in the present study were extracted. RNA-seq datasets from multiple chickpea tissues and developmental stages, such as young leaves (SRX208031), shoot (SRX402843), root (SRX402839), apical meristem (SRX208032), flower bud (SRX208034, SRX208033, SRX208036, SRX208035), flower (SRX208037, SRX208038, SRX208039), and young pod (SRX361953) were obtained. The RNA-seq datasets used in this study were originally generated by Singh et al. [43]. Different chickpea tissue samples were collected, and total RNA was extracted and subjected to Illumina sequencing. The raw sequencing data were filtered using the NGS QC Toolkit to obtain high-quality reads. Gene expression levels were quantified as reads per kilobase per million mapped reads (RPKM) for each sample. Differential expression analysis was performed using DESeq. The processed RNA-seq expression data were retrieved, and RPKM values corresponding to the genes identified in the present study were extracted for further analysis. Furthermore, ClustVis [44] were employed to produce heatmaps. In addition, to uncover potential chickpea miRNAs, a total of 303 mature sequences were obtained from PmiREN (https://pmiren.com/download; accessed on 30 May 2024). These sequences were analyzed with the psRNATarget server (https://www.zhaolab.org/psRNATarget/analysis; accessed on 30 May 2024) to predict their possible targets among CaPSY genes. miRNA–target interactions were predicted using the psRNATarget server with the following parameters: maximum expectation score of 5.0; complementarity scoring length (HSP size) of 19; and a maximum of 200 predicted targets per miRNA. The penalty for G: U wobble pairing was set to 0.5, with an additional seed region weight of 1.5. Up to two mismatches were permitted within the seed region (nucleotides 2–13). Gap opening and extension penalties were set to 2.0 and 0.5, respectively, while the penalty for other mismatches was fixed at 1. Translation inhibition was evaluated within the 10–11 nucleotide region.

Analysis of protein–protein interactions

The interaction network of chickpea PSY proteins was derived from the STRING database (https://string-db.org/; accessed on 31 May 2024) with confidence score thresholds (medium ≥ 0.4) and default settings. This platform enables prediction and mapping of PPIs, providing insights into complex regulatory networks.

Plant growth, stress applications, and gene expression analysis by RT-qPCR

Seeds of the chickpea variety RSG-888 were obtained from IARI, New Delhi, India. After germinating the seeds in petri plates, one-week-old seedlings were exposed to dehydration stress for a duration of three hours. Control seedlings, not exposed to dehydration stress, were maintained at 24 °C. Seedling tissues, representing both stress-treated and control conditions, were harvested and stored at − 80 °C. RNA was subsequently extracted from these tissues using the XpressRNA Plant Kit (MagGenome, Cochin, India) following the manufacturer's instructions. The integrity and purity of RNA were confirmed by A260/A280 ratios ranging from 1.8 to 2.0 using a multimode reader (BioTeck CYTATION5 imaging reader, Winooski, Vermont, USA). In addition, RNA integrity was verified by electrophoresis on 1.5% agarose gel made in 0.5X TAE. The PrimeScript™ cDNA Synthesis Kit was employed to generate cDNA from the isolated RNA samples (Takara Bio, USA). Chickpea eukaryotic initiation factor 4 A (eIF4A) was used as the internal control. The Applied Biosystems QuantStudio 7 Flex PCR System (Thermo Fisher Scientific, USA) was used to perform RT-qPCR. RT-qPCR reactions were performed in 20 µL volumes with an initial denaturation at 95 °C for 3 min, followed by 40 cycles of 95 °C for 15 s, 58 °C for 30 s, and 72 °C for 30 s using three biological and three technical replicates per sample. Relative expression levels were calculated following the method described by [45, 46], and the resulting values were used to create the graph. Primers were designed using the IDT PrimerQuest tool (https://www.idtdna.com/pages/tools/primerquest). The complete list of primers used in this work is given in Table S8.

Results

Discovery and evolutionary relationships of CaPSY genes

This study employed multiple computational methods to detect seven PSY genes in the chickpea genome (Table 1 and Table S1). The PSY gene count in chickpea is comparable to that of other plant species. Specifically, C. cajan contains 5 PSY genes, A. thaliana has 8, Z. mays, P. vulgaris, and O. sativa each have 7, P. sativum has 9, G. max possesses 11, A. hypogaea has 10, and T. aestivum stands out with 29 PSY genes (Table 2). The 7 CaPSY genes demonstrate distinct physicochemical features. The gene predictions reveal proteins with sizes between 59 and 95 amino acids. The MW of the PSY proteins vary from 6.72 (CaPSY6) to 10.79 (CaPSY2) kilo Dalton, as shown in Table 1. In addition, pI values vary from 4.64 (CaPSY1) to 9.57 (CaPSY4). Remarkably, GRAVY values range from − 0.90 (CaPSY6) to -0.1 (CaPSY5) for the 7 CaPSY proteins examined, indicating a predominantly hydrophilic nature among the majority of CaPSY proteins. Most CaPSY proteins are predicted to localize to the extracellular space, while CaPSY4 is predicted to be chloroplast-localized (Table 1). Further, we observed a connection between the MW and pI of CaPSY proteins, which allowed us to scrutinize the distribution trends of these proteins (Figure S1). These outcomes demonstrate that the seven CaPSY proteins are largely scattered, with notable deviations in their pI and MW. To explore the evolutionary relationships of PSY genes across different lineages, a phylogenetic tree was generated based on protein sequences from A. thaliana (8), C. arietinum (7), G. max (12), T. aestivum (29), Z. mays (8), M. truncatula (1), O. sativa (7), and P. patens (1) (Table S2). Based on phylogenetic analysis, the PSY family can be classified into nine distinct groups (Fig. 1). While Groups VII and VIII include three members each, Groups I, II, III, IV, V, VII, and IX contain 0, 0, 1, 0, 0, 0, and 0 members, as shown in Figure S2. Moreover, phylogenetic tree, based on the seven CaPSY protein sequences was categorized into four distinct groups (Figure S3).

Table 1.

The nomenclature and biophysical properties of PSY genes in Chickpea were systematically characterized through diverse bioinformatics tools

Assigned gene name	ID of the gene	Chromosomal location	Orientation	Length of CDS (bp)	Length of protein (aa)	Molecular mass (kDa)	pI value	GRAVY	Predicted cellular location
CaPSY1	Ca_19706	Ca2:6033032.6033806	Forward	288	95	10.68	4.64	-0.621	extracellular space
CaPSY2	Ca_08187	Ca3:27177499.27178826	Reverse	288	95	10.79	5.25	-0.243	extracellular space
CaPSY3	Ca_08178	Ca3:27329396.27330477	Reverse	255	84	9.4	5.58	-0.502	extracellular space
CaPSY4	Ca_03999	Ca5:45516531.45517093	Reverse	237	78	8.97	9.57	-0.413	chloroplast
CaPSY5	Ca_13156	Ca7:8496533.8497011	Forward	270	89	10.2	6.9	-0.109	extracellular space
CaPSY6	Ca_24205	scaffold864:63317.63904	Reverse	180	59	6.72	6.82	-0.903	extracellular space
CaPSY7	Ca_24207	scaffold864:97302.97851	Reverse	180	59	6.72	6.82	-0.903	extracellular space

ID Identity, bp Base pair, aa Amino acids, pI Isoelectric point, MW Molecular weight, kDa kilodalton

Table 2.

Comparative analysis of PSY genes across various crop species

Crop species	Genome size	Coding genes	PSY genes
Cicer arietinum	740 Mb	25,365	7
Arachis hypogaea	2.54 Gb	83,709	10
Phaseolus vulgaris	537 Mb	36,018	7
Glycine max	1.15 Gb	55,897	11
Pisum sativum	3.8 Gb	40,025	9
Cajanus cajan	833 Mb	48,680	5
Arabidopsis thaliana	135 Mb	27,655	8
Zea mays	2.4 Gb	39,591	7
Oryza sativa	500 Mb	37,960	7
Triticum aestivum	17 Gb	107,891	29
Medicago truncatula	412 Mb	31,394	6
Lotus japonicus	472 Mb	28,251	5

Fig. 1.

Phylogenetic relationships of PSY proteins were analyzed across multiple crop and model species including A. thaliana (8), C. arietinum (7), T. aestivum (29), Z. mays (8), O. sativa (7), G. max (12), M. truncatul (1) and P. patens (1). The phylogenetic tree was constructed using the MEGA10 and revealed clearly defined clusters, with each group represented by distinct colors

Genomic localization of CaPSY genes across chromosomes

The CaPSY genes are distributed across chromosomes 2, 3, 5, and 7, with two genes located on an unanchored scaffold. Chromosomes 2, 5, and 7 each harbor a single CaPSY gene, whereas chromosome 3 contains two CaPSY genes (Fig. 2). Chromosomal mapping revealed that the seven identified CaPSY genes are located on four chromosomes of the chickpea genome. We examined gene duplication within the CaPSY family to uncover potential duplicated genes in chickpea. The results shed light on the evolutionary patterns of these genes, revealing two pairs of duplicated gene in PSY family (Fig. 3, Figure S3, and Table S3). Gene duplication likely contributed to the functional diversification and expansion of the PSY family in chickpea. To explore selection forces, selective pressures, we calculated Ka/Ks ratios for the duplicated gene pairs CaPSY1/CaPSY2 (0.44) and CaPSY6/CaPSY7 (0.28) (Table S3). Ka/Ks value was < 1, suggesting purifying selection on the duplicated genes. Furthermore, we investigated the syntenic relationships of CaPSY genes with G. max, A. thaliana, T. aestivum, and O. sativa. We applied MCScanX to detect orthologous gene pairs across the genomes of multiple crops (Fig. 4). Genome conservation was depicted using the Circoletto Tool for comparative synteny analysis. Comparative synteny analysis across G. max, M. truncatula, and C. arietinum revealed that CaPSY1 is syntenic with MtPSY5, and CaPSY2 with GmPSY8. Overall, synteny patterns suggest that CaPSY genes evolved from conserved ancestral orthologs (Fig. 5).

Fig. 2.

Chromosomal mapping of CaPSY genes in chickpea. Schematic diagrams depict the arrangement of genes on each chromosome, with gene names indicated on the right. CaPSY gene positions are highlighted with colored circles, and chromosome numbers are shown at the top

Fig. 3.

PSY genes in chickpea were mapped onto chromosomes, and duplicated gene pairs were identified. Colored lines illustrate the relationships among duplicated genes. Visualization was performed using TBtools

Fig. 4.

Syntenic relationships of CaPSY genes across A. thaliana, G. max, O. sativa, and T. aestivum were analyzed. Collinear blocks in chickpea and other genomes are shown in gray, and orthologous gene pairs are highlighted with red lines

Fig. 5.

Synteny analysis of CaPSY genes across G. max, M. truncatula, and C. arietinum. Colors red, pink, and orange represent different levels of evolutionary conservation among the genes

Investigation of gene structure and motif organization in CaPSY genes

GSDS was used to analyze intron–exon junctions and overall structure of seven CaPSY genes. This analysis also showed that CaPSY genes have minor differences in their gene structure (Fig. 6; Figure S4). All CaPSY genes contain between two and three exons. CaPSY6 and CaPSY7 each comprise two exons, whereas CaPSY1, CaPSY2, CaPSY3, CaPSY4, and CaPSY5 contain three exons. Protein motifs, composed of short conserved amino acid residues, are vital for maintaining structural integrity and functional activity. MEME-based analysis of the seven CaPSY proteins revealed ten motifs, numbered from Motif 1 to Motif 10 (Fig. 7A, B). Motif 1 corresponds to the PSY functional domain (IPR034430), whereas the remaining motifs are predicted to function as signal peptides. Amino acid sequence alignment confirmed that all seven proteins share the PSY domain including DY, N, H, and P motifs (Fig. 8; Figure S5A). Moreover, the predicted three-dimensional structures of CaPSY proteins offer preliminary insights into structural features and conserved motifs, which may guide hypotheses concerning their involvement in developmental regulation and stress responses in chickpea, however, the subject to experimental validation (Figure S5B).

Fig. 6.

Diagram illustrating the structural organization of CaPSY genes. Exons are colored yellow, and introns represented by black lines. Box and line lengths are scaled to reflect the true sizes of the corresponding gene regions

Fig. 7.

MEME analysis of conserved motifs in CaPSY proteins. A Each colored box corresponds to a unique motif with specific sequence and length. B Sequence logos illustrate the degree of amino acid conservation and variability for each motif

Fig. 8.

Multiple sequence alignment of CaPSY proteins. Conserved PSY domains are shown in sky-blue, residues with similar chemical properties are color-coded, and dashes represent gaps in the alignment

Analysis of cis-regulatory elements of CaPSY

The 1500 bp promoter region upstream of the transcriptional start site of each PSY gene was analyzed with PlantCARE to identify cis-regulatory elements (CREs). This analysis unveiled a collective existence of 115 CREs across the seven CaPSY genes (Fig. 9A and B, Table S4). Based on their predicted biological functions, CREs were classified into seven functional categories: light-responsive elements (LREs), hormone-responsive elements (HREs), defense- and stress-responsive elements (DSREs), tissue-specific responsive elements (TREs), metabolic-responsive elements (MREs), growth- and development-responsive elements (GDREs), and other functional responsive elements (OREs). Among these categories, LREs were the most abundant, accounting for 54% of the total CREs, followed by HREs (26%) and DSREs (12%) (Figure S6A, B; Table S4). The putative promoter region of each CaPSY gene family member contained at least one CRE from multiple functional categories, indicating broad regulatory potential. Notably, certain CREs exhibited gene-specific enrichment; for instance, CaPSY4 harbored a higher number of HREs, including ABRE, AuxRE, GARE, and MeJARE motifs, whereas CaPSY5 was particularly enriched in ABRE, MeJARE, and SARE elements (Figure S6A, B; Table S4). Collectively, these findings indicate that CaPSY genes play key roles in growth, development, and stress adaptation. CREs linked to cell cycle control, zein metabolism, meristem activity, and circadian regulation underscore their multifunctionality, highlighting the importance of CaPSY genes in chickpea physiology and regulatory networks.

Fig. 9.

Distribution and composition of identified cis-regulatory elements in the 1.5 kb promoter regions of seven CaPSY genes. A Promoter regions of CaPSY genes showing different CREs indicated by distinct colors. B Distribution of multiple CREs across all CaPSY genes

CaPSY gene expression profiling in multiple tissues and environmental stress conditions

RNA-seq datasets retrieved from the NCBI-SRA were used to examine the expression patterns of CaPSY genes across diverse tissues and under various abiotic stress conditions. The analysis aimed to infer the potential functional roles of CaPSY genes, and the resulting expression values were visualized using heatmaps (Fig. 10A and B). The expression of CaPSY genes differed among tissues and under stress conditions (Fig. 10A & B). For instance, CaPSY1, CaPSY3, and CaPSY4 were highly expressed in flower stage 3 (FL3), while CaPSY5 was up-regulated in flower stage 2 (FL2) and shoot apical meristem (SAM). Additionally, CaPSY2 showed significantly increased expression in fully bloomed flower stage 3 (FB3). Both CaPSY1 and CaPSY3 were also induced in roots. These observations suggest a potential role for CaPSY genes in tissue development, while transcriptome analyses under abiotic stress conditions including drought, salinity, and cold provided additional insights into their regulatory functions (Fig. 10B). These conditions revealed differential expression for the CaPSY genes. For example, CaPSY3, CaPSY4, and CaPSY5 showed significantly elevated expression in root tissues under cold stress. Under salinity stress, the expression of CaPSY1, CaPSY2, CaPSY4, and CaPSY5 was markedly increased in roots. Similarly, CaPSY3 expression was induced in shoots under salinity stress (Fig. 10B). In addition, RNA-seq data related to drought stress were further validated using RT-qPCR. CaPSY1, CaPSY2, CaPSY3, CaPSY4, CaPSY5, and CaPSY6 genes were significantly down-regulated under drought stress compared to the control (Fig. 11). However, the CaPSY7 gene exhibited slight down-regulation under drought conditions compared to the control. This differential expression indicates that CaPSY7 may play a specific role in chickpea adaptation to drought stress. The RT-qPCR analysis yielded results that were consistent with and closely aligned to the drought stress RNA-seq data (Fig. 11). In summary, the study highlights the involvement of CaPSY genes in diverse developmental pathways as well as in stress-responsive mechanisms in chickpea.

Fig. 10.

Heatmaps illustrating CaPSY gene expression in chickpea tissues and in response to stress. Genes exhibiting upregulation are indicated in maroon, whereas downregulated genes are shown in green. Expression levels were quantified using RPKM values. A The expression patterns of CaPSY genes across different chickpea tissues. FB1–FB4 represent flower bud stages 1–4, YL indicates young leaf, SAM denotes shoot apical meristem, and FL1–FL3 correspond to flower stages 1–3. B CaPSY gene expression in chickpea subjected to different abiotic stresses. DS denotes drought stress, CS cold stress, and SS salinity stress. Expression levels were quantified using FPKM values

Fig. 11.

Expression patterns of CaPSY genes in chickpea under drought stress were analyzed using RT-qPCR. Statistical significance between treatment and control groups was assessed using one-way ANOVA followed by Tukey HSD test, with significance set at p < 0.05. Data are presented as mean ± standard deviation (SD; n = 3)

Characterization of PSY-specific miRNA targets in Chickpea

A total of 303 mature miRNA sequences were obtained from PmiREN and analyzed via psRNATarget to identify miRNAs potentially targeting CaPSY genes in chickpea. Three miRNAs including Car-miRN77, Car-miRN70, and Car-miR156a were found to target three CaPSY genes (CaPSY2, CaPSY4, and CaPSY5) (Table S5). We also examined miRNA expression patterns across various tissues, including flowers, buds, leaves, pods, roots, seedlings, shoots, and stems (Fig. 12, Table S6). Distinct expression profiles of the miRNAs were observed among various chickpea tissues. Interestingly, we discovered that the expression of Car-miR156a and Car-miR156b was significantly elevated during the seedling stage, leading to the repression of CaPSY1, CaPSY2, CaPSY3, CaPSY4, and CaPSY5 gene expression. This repression might occur in the shoot and young leaves through mechanisms such as gene silencing or translational inhibition, driven by the increased levels of Car-miR156a and Car-miR156b. These results indicate that the miRNAs may regulate the expression of CaPSY genes during chickpea development (Fig. 12). This discovery provides valuable insights into the roles of miRNAs in chickpea cellular processes. A deeper understanding of their regulatory functions may elucidate the complex mechanisms underlying chickpea development and stress responses, with potential applications in enhancing yield and improving resilience to diverse environmental stresses.

Fig. 12.

The heatmap illustrates miRNA expression patterns across different chickpea tissues and developmental stages

Examining interactions between proteins encoded by CaPSY family proteins

A PPI network was generated utilizing STRING to examine interactions of CaPSY proteins with other chickpea proteins (Fig. 13 and Table S7). The results revealed three CaPSY proteins that interact with seven distinct chickpea-specific proteins. Notably, CaPSY5 interacted with LOC101511790, LOC101498792, LOC101509598, LOC101491762, LOC101499067, LOC101501969, and LOC101514864. LOC101511790 is homologous to the target of rapamycin complex subunit LST8, also known as mammalian lethal with Sect. 13 protein 8 (mLST8) [47]. In humans, this protein is encoded by the MTOR-associated protein LST8 gene. LST8 is an essential component of both mTORC1 and mTORC2 complexes, which play central roles in regulating cell growth, metabolism, and survival in response to nutrient availability, cellular energy status, redox balance, and hormonal signals [48, 49]. LOC101498792 encodes a probable ethanolamine kinase, whereas LOC101514864 encodes a regulatory-associated protein of TOR 1 (RAPTOR)-like isoform X1. Similarly, CaPSY2 and CaPSY3 both interacted with CaPSY7. The results provide important information to explore further research into the role of CaPSY genes in various cellular activities.

Fig. 13.

The protein–protein interaction (PPI) networks of CaPSY proteins were analyzed using STRING v12.0. In the network, proteins are represented as nodes and their interactions as edges, with edge colors indicating the type of supporting evidence

Discussion

Signaling peptides are essential for cell differentiation and expansion, stomatal patterning, stem cell maintenance, self-incompatibility, floral organ abscission, and activating stress defense responses [17, 50–58]. PSYs are increasingly recognized as pivotal regulators of growth–stress trade-offs in plants; however, their functional diversification in legumes remains largely unexplored. In this investigation, seven PSY genes were discovered in the chickpea genome through bioinformatics analyses (Table 1; Table S1), and we provide the first integrated analysis of their evolutionary history, promoter architecture, expression profiles, and potential post-transcriptional regulation. Compared with model plants such as Arabidopsis (eight PSYs) and cereals like rice and wheat, the CaPSY gene family is relatively compact, resembling that of other legumes, including C. cajan and P. vulgaris (Table 2). The number of PSY genes identified in chickpea falls within the range reported for other legume species, although direct orthology has not been established. This pattern indicates lineage-specific retention rather than extensive expansion, possibly reflecting selective constraints on peptide signaling pathways in legumes. The CaPSY proteins exhibit unique physicochemical traits, with most predicted to localize in extracellular space, excluding CaPSY4, which is found in chloroplast (Table 1). The seven CaPSY proteins differ in their isoelectric points and molecular weights (Table 1; Figure S1), suggesting functional diversity in signaling pathways. Phylogenetic analysis divided the PSY family into nine groups (Fig. 1). Groups VII and VIII contain three members each, Group III has one member, while Groups I, II, IV, V, VI, and IX are empty (Figure S2). Interestingly, clusters I, II, and VI are monocot-specific, whereas clusters III, IV, and VII occur only in dicots. This partitioning supports the hypothesis that PSY diversification occurred after the monocot–dicot split and suggests that legume PSYs may have evolved specialized regulatory functions associated with symbiosis, reproductive development, and stress adaptation [59–63]. The seven CaPSY genes were mapped to four chickpea chromosomes. Chromosomes 2, 5, and 7 each carry one gene, chromosome 3 has two, and two genes are on a scaffold (Fig. 2). This uneven distribution mirrors patterns observed in wheat and rice for multiple gene families, including BZR, aconitase, PSY, PIN-FORMED, and PERKs [17, 60, 61, 64–66]. The uneven chromosomal distribution of CaPSY genes likely reflects historical gene gain or loss. These evolutionary events drive variation in gene numbers across chromosomes. Gene duplications, in particular, expand and diversify families, promoting adaptation and evolution [60, 64, 67]. The study uncovered two pairs of duplicated gene in PSY family of chickpea including CaPSY1/CaPSY2 and CaPSY6/CaPSY7 (Fig. 3, Figure S3, and Table S3). Two duplicated CaPSY gene pairs were identified, both exhibiting strong purifying selection (Ka/Ks < 1), indicating functional constraint and retention of essential roles. Despite their sequence conservation, these duplicated genes showed distinct promoter architectures and expression profiles, suggesting regulatory divergence rather than neofunctionalization at the protein level. This pattern of divergence is consistent with observations in other signaling peptide families, where duplicated genes are often retained through partitioning of spatial, temporal, or stress-responsive expression [68, 69]. Furthermore, Synteny analysis was conducted to explore the genomic relationships of CaPSY genes with G. max, A. thaliana, T. aestivum, and O. sativa. Orthologous pairs across these species were identified using MCScanX (Fig. 4), and genome conservation was visualized with Circoletto, including G. max, M. truncatula, and C. arietinum. CaPSY1 showed synteny with MtPSY5, while CaPSY2 aligned with GmPSY8. Overall, CaPSY genes exhibit conserved synteny across species (Fig. 5), suggesting retention from ancestral orthologs and a shared evolutionary history.

Gene structure analysis uncovered subtle differences among CaPSY family members (Fig. 6 and Figure S4). CaPSY genes are composed of one or two introns, with CaPSY6 and CaPSY7 each harboring a single intron, while the remaining members contain two introns. Numerous studies highlight the role of introns in shaping gene evolution in crops [70–72]. Plant gene families show variation in intron count, with some having very few or no introns and others having many [71, 72]. It is demonstrated that intron and exon diversity could help in understanding the evolutionary past [73]. Motifs are short, conserved amino acid sequences essential for protein structure and function. We identified 10 conserved motifs (motif 1–10) in CaPSY proteins (Fig. 7A, B), with motifs 1 and 3 highly conserved across most members. Amino acid sequence alignment revealed a conserved motif including DY, N, H, and P residues across all CaPSY proteins (Fig. 7 and Figure S5A). Moreover, the predicted three-dimensional structures of CaPSY proteins provide initial insights into conserved structural features and motifs potentially involved in developmental regulation and stress responses in chickpea, although experimental validation is required (Figure S5B). Collectively, these findings may contribute to a deeper understanding of the potential roles of CaPSY proteins in signaling pathways associated with chickpea development and stress adaptation. CREs within promoter regions are key determinants of gene expression modulation under a wide range of biotic, abiotic, and hormonal signals [66, 74, 75]. Promoter analysis identified 115 CREs in the seven CaPSY genes, which were quantified by functional category rather than merely catalogued (Fig. 9A and B, and Table S4). LREs were the most abundant, accounting for 54% of CREs, followed by HREs 26% and DSREs 12% (Figure S6A, B; Table S4). The remainder included tissue-specific, growth- and development-related, and OREs. Gene-level analysis revealed distinct CRE patterns. CaPSY4 was enriched in HREs, including ABRE, AuxRE, GARE, and MeJARE, while CaPSY5 showed higher abundance of ABRE, MeJARE, and SAREs (Figure S6A, B; Table S4). The observed differences reflect promoter-level regulatory divergence among CaPSY genes, highlighting specialization rather than uniform multifunctionality. Experimental validation, such as promoter–reporter assays, will be essential to confirm motif function and binding specificity. Hence, the CREs identified in CaPSY genes suggest their involvement in cellular regulation, influencing growth and stress adaptation. This points to a potential role for the CaPSY family in coordinating multiple CREs to modulate development and stress responses in chickpea. Evolution has increased gene family sizes via duplication, and changes within these genes can influence how other family members are expressed [64, 76–78].

Signaling peptides are central to numerous cellular processes, including cell differentiation and expansion, stomatal patterning, stem cell maintenance, self-incompatibility, floral organ abscission, and stress defense [17, 50–58]. To elucidate the potential involvement of the PSY gene family in chickpea development and stress tolerance, the expression profiles of the seven CaPSY family members were systematically examined using publicly available RNA-seq datasets from the NCBI-SRA. Collectively, these datasets represented a wide range of tissues, developmental stages, and stress conditions, allowing an in-depth assessment of CaPSY gene expression dynamics. The expression profiles of PSY gene family members varied markedly across different chickpea tissues, developmental stages, and stress conditions. Notably, CaPSY1 and CaPSY3 exhibited predominantly root-specific expression, whereas CaPSY1, CaPSY2, CaPSY3, CaPSY4, and CaPSY5 showed pronounced flower-specific expression patterns (Fig. 10A). Interestingly, CaPSY5 showed distinct expression in the SAM. In contrast, across the remaining tissues and developmental stages, CaPSY family members were either downregulated or exhibited negligible expression levels (Fig. 10A). Enriched expression in floral tissues and the SAM supports roles in reproductive development and meristem maintenance. This parallels findings in Arabidopsis, where PSY1 and related peptides are expressed in actively growing tissues and govern cell expansion and developmental timing. The reports indicate that activation of PSY1 results in cell elongation in hypocotyls and roots [3, 14, 79]. In Arabidopsis, AtPSKR1 overexpression leads to changes in growth and cellular lifespan [50]. The root-specific expression of certain CaPSY genes supports a conserved role for PSY signaling in modulating root growth and environmental responsiveness. Studies have unveiled that PSK regulates nodulation in Lotus [80]. AtPSY1 stood out from its family members by being expressed in all tissues of Arabidopsis. Notably, its levels rose during late silique development, bolting, and senescence. Likewise, AtPSY8 demonstrated a similar expression with especially high levels in roots relative to other tissues [6]. These results suggest that CaPSY genes may have function in tissue development in chickpea. CaPSY genes exhibited pronounced variation in expression across different stress conditions, indicating stress-responsive regulation of CaPSY genes. This study notably integrates promoter architecture with expression profiling, revealing that genes enriched in stress- and hormone-responsive CREs exhibit expression patterns aligned with their predicted regulatory roles. For instance, CaPSY4 and CaPSY5, enriched in ABRE and MeJA-responsive elements, were strongly induced in roots under salinity and cold stress. Conversely, CaPSY genes with fewer DSREs showed weaker or repressed expression under drought stress (Fig. 10B; Figure S6A, B). Although CRE presence alone cannot dictate expression, the correlation highlights the contribution of promoter composition to stress-responsive regulation of CaPSY genes. CaPSY genes displayed divergent responses. Cold and salinity induced several members, particularly in roots, whereas drought triggered broad transcriptional repression. Thus, the chickpea data indicate that PSY-mediated regulation is highly context dependent, varying across tissue types and stress modalities. PSY1 is notably recognized for its crucial involvement in plant defense responses [16]. PSY1 signaling is induced by pathogen attacks, leading to suppression of genes associated with salicylic acid pathways [16]. Studies have shown that X. oryzae yields a sulfated peptide called RaxX, which closely resembles PSY1 [14]. Moreover, RT-qPCR analysis showed that CaPSY1–CaPSY6 were largely down-regulated under drought stress (Fig. 11), suggesting a limited role in drought response or a potential role in resource-conservation strategies in chickpea. In contrast, CaPSY7 exhibited slight downregulation under drought stress compared with control conditions. This differential expression suggests that CaPSY7 may play a specific role in chickpea adaptation to drought stress. Collectively, the distinct expression patterns of the PSY gene family across different tissues, developmental stages, and diverse stress conditions suggest that these genes may play specialized roles in plant development and stress-responsive processes in chickpea. However, further research is required to elucidate the biological roles of PSY genes and their contributions to stress tolerance mechanisms in chickpea.

Three miRNAs such as Car-miRN77, Car-miRN70, and Car-miR156a (Table S5) were predicted to target CaPSY2, CaPSY4, and CaPSY5. This suggests an additional layer of post-transcriptional regulation acting on the CaPSY gene family. miRNA expression dynamics were examined across diverse tissues, including flowers, buds, leaves, pods, roots, seedlings, shoots, and stems (Fig. 12; Table S6). The identified miRNAs displayed distinct tissue-specific expression patterns in chickpea. Although three miRNAs were predicted to target CaPSY genes and showed tissue-specific expression, the miRNA and CaPSY data came from independent datasets. Notably, elevated expression of miR156 family members during the seedling stage coincided with reduced expression of several CaPSY genes, suggesting a plausible regulatory interaction. However, without paired measurements from the same biological samples under identical conditions, these data do not support a definitive miRNA–target relationship. Future studies should integrate small RNA and mRNA sequencing, degradome analysis, or experimental validation methods, such as 5′ RLM-RACE or transient expression assays, to confirm direct targeting and regulatory effects. These results indicate that these miRNAs may modulate CaPSY gene expression during chickpea development (Fig. 12). Elucidating their regulatory roles could advance our understanding of development, stress responses, and other key pathways, with potential implications for improving crop yield and resilience. In addition, a PPI network was constructed using STRING to explore CaPSY interactions with other chickpea proteins (Fig. 13; Table S7). The analysis revealed interactions between three CaPSY proteins and seven distinct chickpea proteins. Remarkably, CaPSY5 interacted with LOC101511790, LOC101498792, LOC101509598, LOC101491762, LOC101499067, LOC101501969, and LOC101514864, while CaPSY2 and CaPSY3 both interacted with CaPSY7. PPI analysis suggests that CaPSY proteins may connect with broader growth and metabolic pathways, including TOR-related components. Although computationally predicted, these interactions raise intriguing hypotheses about cross-talk between peptide signaling and nutrient or energy sensing. Although these links are documented in model plants, they remain unexplored in legumes, highlighting a critical direction for future functional studies. Overall, this study presents the first comprehensive framework for PSY genes in chickpea, highlighting regulatory divergence over mere functional redundancy. By combining evolutionary analysis, quantitative promoter characterization, expression profiling, and miRNA prediction, we place CaPSY genes within the broader context of plant peptide signalling. Although many conclusions remain predictive and await experimental validation, these findings provide a robust foundation for investigating PSY-mediated growth stress trade-offs in legumes and for identifying candidate genes for functional studies and crop improvement.

Conclusion

PSY genes constitute a central yet underexplored layer of plant intercellular signaling, integrating growth, development, and environmental adaptation. Here, we provide the first genome-wide characterization of the PSY gene family in chickpea, identifying seven CaPSY genes and detailing their evolutionary origins, regulatory architecture, expression dynamics, and potential post-transcriptional regulation. Our analysis showed that CaPSY genes possess distinct physicochemical properties. Phylogenetic and synteny analyses indicate that CaPSY genes originate from conserved ancestral lineages and are maintained under strong purifying selection, highlighting their functional significance. Chromosomal mapping showed that CaPSY genes are restricted to four chromosomes rather than being genome-wide. Each gene contains one or two introns, and amino acid sequence alignment revealed a conserved motif shared across all CaPSY proteins. The diverse CRE in CaPSY promoters suggest roles in multiple developmental processes and stress responses in chickpea. Expression profiling across tissues and abiotic stresses revealed distinct, context-dependent expression patterns among CaPSY genes. The discovery of miRNAs targeting specific CaPSY genes highlights the multilayered regulation of this family during chickpea development and stress responses. However, experimental validation such as 5′ RLM-RACE or transient expression assays will be necessary. Thus, these results provide a valuable resource for future studies, enabling functional dissection of PSY signaling and highlighting candidate genes for precision breeding and genome editing to enhance chickpea resilience and productivity under changing climates.

Abbreviations

PSY

Tyrosine Sulfation-containing peptides

LRR-RKs

Leucine-rich repeat-receptor kinases

CIFs

Casparian strip integrity factors

RGFs

Root growth meristem factors

PSKs

Phytosulfokines

SRA

Sequence Read Archive

RT-qPCR

Reverse Transcription quantitative polymerase chain reaction

cDNA

Complementary DNA

MW

Molecular weights

CREs

Cis-regulatory elements

miRNAs

microRNA

Authors’ contributions

M.S.K. conceptualized and designed the study. M.S.K. and F.B.M. prepared the initial draft of the manuscript. M.S.K. and S.K.L. supervised the research activities. M.S.K. and A.S. conducted the experiments and performed the in silico analyses. M.S.K., A.S., and M.R. were responsible for the methodology, while V.K., S.M.C. and S.M. handled data visualization and assisted with editing and revision. D.K. and S.K.L. carried out the RT-qPCR experiments and contributed to formal data analysis. All authors have read and approved the final version of the manuscript.

Funding

Not applicable.

Data availability

The data supporting the findings of this study are available in the following databases and links. Phytozome ( https://phytozome-next.jgi.doe.gov/), HMMscan ( https://www.ebi.ac.uk/Tools/hmmer/search/hmmscan), InterPro (https://www.ebi.ac.uk/interpro/), and PROSITE (https://prosite.expasy.org/scanprosite/), ExPASy ( https://www.expasy.org/), isoelectric point calculator (http://isoelectric.org/), PSORT (https://www.psort.org/psortb/), BacelLO (https://busca.biocomp.unibo.it/bacello/), and BUSCA (https://busca.biocomp.unibo.it/), PhenoGram (https://visualization.ritchielab.org/phenograms/plot), Gene Structure Display Server ( http://gsds.gao-lab.org/), MEME (http://meme-suite.org/tools/meme), PlantCARE (https://bioinformatics.psb.ugent.be/webtools/plantcare/html/), RNA-seq datasets were obtained from the NCBI-SRA database (SRA; http://www.ncbi.nlm.nih.gov/sra/), PmiREN (https://www.pmiren.com/download), Plant Small RNA Target Analysis Server (https://www.zhaolab.org/psRNATarget/analysis), STRING (https://string-db.org/cgi), and Identified gene accession number are: Ca\_19706, Ca\_08187, Ca\_08178, Ca\_03999, Ca\_13156, Ca\_24205 and Ca\_24207.

Declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.