1. Introduction
Soybean (Glycine max) is one of the most important crops globally, serving as a fundamental component of agriculture by providing essential protein and oil for human and animal consumption [1,2]. Additionally, soybeans are increasingly used in biodiesel production, a renewable energy source that can reduce reliance on fossil fuels [3]. However, various biotic stressors such as pests, diseases, and weeds, along with abiotic stresses including extreme temperatures, drought, and saline conditions, pose significant threats to soybean yield and quality worldwide [4,5,6,7]. In plant biology, serine carboxypeptidases (SCPs) and their closely related serine carboxypeptidase-like proteins (SCPLs) have drawn considerable interest due to their complex roles in plant growth, development, and responses to various stresses [8,9,10,11,12].
Both SCPs and SCPLs are part of the S10 subgroup within the Serine Carboxypeptidase (SCP) family, noted for their highly conserved α/β hydrolase fold. This structural motif includes a central β-sheet surrounded by α-helices on both sides, creating a sturdy globular shape [13,14]. Typically, SCPL proteins contain a conserved triad of amino acids: Serine, aspartate, and histidine (Ser-Asp-His) [14,15]. Most SCPL proteins, characterized by the PF00450 domain in the Pfam database, share structural features that include four evolutionarily conserved domains involved in substrate binding and catalytic activities, a signal peptide for internal transport or secretion, and several N-linked glycosylation sites [16].
SCPs are proteolytic enzymes that facilitate the cleavage of peptide bonds at the carboxyl terminus of proteins and peptides. In contrast, SCPLs, while structurally similar to SCPs, have adapted to engage in a wider array of biochemical processes, notably the modification of secondary metabolites and the regulation of phytohormones. A notable feature of SCPLs is their important role in plant defense mechanisms [17,18]. It was found that the expression of the OsBISCPL1 gene in rice significantly increased when exposed to defense-related signaling compounds such as salicylic acid (SA) and jasmonic acid (JA) or following bacterial infection [11]. More severe symptoms of Verticillium wilt in cotton (Gossypium hirsutum) were displayed when GhSCPL42 was silenced by virus-induced gene silencing (VIGS) [19]. An increase in proline levels and a reduction in malondialdehyde, leading to enhanced resistance to drought and salt stress, were reported to result from the overexpression of TaSCPL184-6D in Arabidopsis plants [20].
In this study, we conducted a comprehensive examination of the entire SCPL gene family in soybean using the well-established Williams 82 soybean reference genome (
2. Results
2.1. Genome-Wide Identification and Analysis of the SCPL Gene Family
SCPL genes were examined in various plant species, including Arabidopsis thaliana, rice (Oryza sativa), and bread wheat (Triticum aestivum), as reported by several studies [20,22,23]. However, the specific functions and characteristics of SCPL genes in soybean (Glycine max) have not been fully explored. The specific locus identifiers and genetic sequences of these genes are comprehensively listed in Supplementary Table S1. A genome-wide search was conducted within the soybean genome using Tbtools to identify all members of the SCPL family. Following this, candidates were verified through the protein family database (Pfam) search and NCBI Batch CDD for functional annotations. In soybean, we identified and characterized a total of 73 serine carboxypeptidase-like (SCPL) genes. These genes were assigned unique identifiers, ranging from GmSCPL1 to GmSCPL73, according to their specific locations on the soybean chromosomes (Table 1). The detailed information about each identified SCPL gene in soybean, including open reading frame (ORF) lengths, amino acid lengths, molecular weights (MWs), theoretical isoelectric points (PIs), numbers of introns, splice variants, and subcellular locations, is provided in Table 1. The ORF lengths of the identified GmSCPLs ranged from 654 base pairs (GmSCPL38, Glyma.12G179400.1) to 1596 base pairs (GmSCPL40, Glyma.13G028800.1). The sizes of the proteins varied from 218 to 532 amino acids, with molecular weights ranging from 18.63 kDa to 59.81 kDa, and PI values between 4.81 (GmSCPL63, Glyma.19G128100.1) and 9.17 (GmSCPL23, Glyma.09G249500.1). The count of introns, along with splice variants, varied from 0 to 13 and 1 to 9, respectively. Subcellular localization prediction, using the Plant-mPLoc tool, indicated that most GmSCPLs are located in the vacuole.
2.2. Phylogenetic Analysis of the SCPL Family
To elucidate the evolutionary relationships among SCPL proteins from GmSCPLs and other well-documented plant SCPLs, we utilized protein sequences from Arabidopsis thaliana, rice (Oryza sativa), bread wheat (Triticum aestivum), soybean (Glycine max), and wild soybean (Glycine soja). These sequences were analyzed to construct a maximum likelihood phylogenetic tree using the IQ-TREE 2.2.5 software(IQ-TREE 2.2.5, Canberra, Australia), employing the Q.pfam+R6 model (Figure 1). Additionally, a separate phylogenetic tree was generated using only the 73 GmSCPL protein sequences, applying the LG+R4 model to further refine our understanding (Figure 2A). NCBI Batch CDD analysis confirmed that each GmSCPL sequence contained one or two conserved S10 regions (Figure 2B). The identified GmSCPLs were classified into three distinct subgroups:Ⅰ, Ⅱ, and Ⅲ, consistent with several previous studies [19,20,23].
2.3. Chromosomal Distribution and Gene Duplication of the GmSCPL Family
To investigate the chromosomal distribution characteristics of the GmSCPL family, we analyzed their locations across soybean chromosomes. Figure 3 and Figure S1 show that chromosome 13 harbors the highest number of GmSCPL genes. In contrast, chromosome 2 contains only one GmSCPL gene, highlighting an uneven distribution of the 73 GmSCPLs across the 20 chromosomes of soybean. The distribution pattern of SCPL genes across the chromosomes does not exhibit a strong correlation with gene density, GC content, or GC skew (Figure 3).
The soybean cyst nematode (SCN) is recognized as a significant global threat to soybean production [4,24]. Notably, our analysis revealed that 38.35% (28 out of 73) of the identified GmSCPL genes are located within regions corresponding to known SCN-related quantitative trait loci (QTLs), as shown in Figure S1 and Table S2. Additionally, RNA-seq analysis indicated that the expression of these SCPL genes was significantly induced 5 days post-inoculation with SCN (Figure S2). While this study provides a comprehensive identification and characterization of SCPL genes, future research will focus on real-world verification and functional studies to further elucidate the roles of these genes in soybean’s defense mechanisms against SCN.
2.4. Analysis of SCPL Paralogs and Orthologs
To delve deeper into uncovering the evolutionary links within the SCPL gene family, we conducted a syntenic analysis aimed at identifying SCPL paralogous gene pairs within soybean (G. max) and SCPL orthologous gene pairs between soybean and monocotyledonous plants (O. sativa) as well as dicotyledonous plants (Arabidopsis and G. soja) using Multiple Collinearity Scan Toolkit (MCScanX, Athens, Greece). We identified 40 paralogs in soybean (Gm-Gm) (Table S3). Among these, 33 orthologous gene pairs were detected between Arabidopsis and soybean (Gm-At), 117 orthologous gene pairs between G. soja and soybean (Gm-G. soja), and only eight SCPL orthologous gene pairs between rice and soybean (Gm-Os) (Figure 4). These findings suggest a close linkage between SCPL genes in soybean and those in G. soja, possibly due to their close genetic relationship [25,26,27].
The Ka/Ks ratio, a crucial parameter reflecting selective pressure on plant genes, was utilized to assess evolutionary patterns [28]. The Ka (non-synonymous substitution rate) measures the rate of amino acid-changing mutations, while the Ks (synonymous substitution rate) measures the rate of mutations that do not change the amino acid sequence. The Ka/Ks ratio indicates the type of selective pressure acting on a gene: A ratio greater than 1 suggests positive selection (adaptive evolution), a ratio equal to 1 suggests neutral evolution, and a ratio less than 1 suggests purifying selection (removal of deleterious mutations) [29]. Divergence time (T) was calculated based on Ks values to estimate the evolutionary time scale of gene duplications. For each SCPL gene pair, we calculated the Ka, Ks, Ka/Ks, and T values. Our analysis revealed that the Ka/Ks ratios of all paralogous genes (Gm-Gm) and most orthologous genes (Gm-G. soja, Gm-Os, and Gm-At) were below 1 (see Tables S3 and S4), indicating that purifying selection plays a dominant role in the evolution of the SCPL family. Additionally, the divergence time (T) of the 40 paralogs (Gm-Gm) ranged from 2.03 to 58.61 million years ago (Mya) (Table S3). The divergence time of orthologs (Gm-G. soja) ranged from 0.09 to 58.6 Mya, while it ranged from 51.41 to 152.16 Mya in Gm-At and from 69.51 to 74.02 Mya in Gm-Os. These results further underscore the closer genetic relationship between soybeans and wild soybeans (G. soja) on an evolutionary scale [30]. It is important to note that these divergence times are specific to the evolutionary history of the SCPL gene family within these plant lineages.
2.5. Analysis of Codon Usage Patterns in SCPL Genes across Plant Species
Each codon uniquely specifies an amino acid, and multiple codons can encode the same amino acid, termed synonymous codons [31,32]. The frequency of usage for these synonymous codons varies significantly among different species and even within different genes, underscoring the importance of codon preference in evolutionary dynamics [33]. We examined codon usage bias (CUB) across five species, including Clycine max, Clycine soja, Oryza sativa, Arabidopsis thaliana, and Triticum aestivum, utilizing identified SCPL CDS sequences, with detailed information provided in Table S5. Our findings revealed that the average GC content and GC3s of SCPL genes ranged from 0.422164384 to 0.575114286 and 0.3610685 to 0.7024667, respectively, across the five species. Notably, the average effective number of codons (ENC) of SCPL genes in monocotyledonous species (O. sativa and T. aestivum) was lower compared to that in dicotyledonous ones (G. max, G. soja, and Arabidopsis) (Table 2), indicating stronger codon usage bias in monocotyledonous plants.
Analysis of relative synonymous codon usage (RSCU) provided insights into CUB [34]. We observed that the RSCU patterns of SCPL genes in G. max and G. soja were similar, whereas those in O. sativa and T. aestivum were clustered (Figure 5C), potentially reflecting their natural evolutionary relationships. Parity rule 2 (PR2) analysis explored GC and AT composition bias at the third codon position [35]. Investigation of PR2 revealed varying ratios of G3s/(G3s+C3s) and A3s/(A3s+T3s) among different species, with most identified SCPL members in the five species preferring C and T over G and A (Figure 5B). Neutral plot analysis confirmed additional factors influencing codon preference beyond base composition. Relatively slight positive correlations between GC3s and GC12 of SCPL gene CDS sequences were observed in G. max (r2 = 0.01058, p < 0.01) (Figure 5A), G. soja (r2 = 0.01346, p < 0.01) (Figure S3A), and Arabidopsis (r2 = 0.4409, p < 0.01) (Figure S3B), indicating that both mutation pressure and natural selection influenced the codon preference of SCPLs in dicots (G. max, G. soja, and Arabidopsis). Interestingly, notably positive correlations between GC3s and GC12 of SCPL gene CDS sequences were evident in rice (r2 = 0.7020, p < 0.01) (Figure S3C) and bread wheat (r2 = 0.6118, p < 0.01) (Figure S3D), likely attributable to their monocot classification.
2.6. Analysis of Conserved Motifs and Gene Structure in GmSCPLs
Examining the exon–intron architecture of genes provides valuable insights into their evolutionary paths and functional diversification. We conducted an analysis of the gene structure and conserved motifs of GmSCPLs, revealing a range of exon numbers from 1 to 14 (Table 1). Notably, this analysis highlights a degree of conservation in exon–intron structures within each branch of the evolutionary tree (Figure 6C).
To identify potential motifs within the soybean SCPL gene family, we subjected the deduced amino acid sequences of 73 GmSCPL proteins to motif prediction analysis using the MEME suite. As illustrated in Figure 6B, ten conserved motifs (designated as Motif1-10) were predicted and visualized across all identified GmSCPLs. The distribution of motifs among the GmSCPLs varied, with counts ranging from three to ten. Remarkably, certain motifs were prevalent among most GmSCPLs, while others were specific to particular clusters. For example, Motifs 1, 3, 4, 5, 9, and 10 were consistently found at the 5′ terminal of 98% of identified GmSCPL members, whereas motif 2 or 8 existed at the 3′ terminal of 95.8% of identified GmSCPL members (Figure 6B). Additionally, we observed that GmSCPLs within the same subgroup exhibited a similar order of motif distribution, suggesting potential functional homogeneity.
2.7. Prediction of cis-Acting Regulatory Elements in Promoter Regions of GmSCPLs
In the realm of plants, a subset of cis-acting regulatory elements holds considerable importance in orchestrating responses to diverse stressors, such as hormonal fluctuations, dehydration, cold, and light exposure, through the binding of specific transcription factors [36,37,38,39,40,41]. Furthermore, certain cis-regulatory elements have been identified as pivotal mediators of plant immune mechanisms [42,43,44,45]. To explore the expression patterns of GmSCPL genes, we screened their 2.0 kb promoter region sequences using the PlantCARE database [46]. A total of 12,469 cis-acting regulatory elements were predicted and identified, categorized into groups related to development, environmental stress response, hormone signaling, light responsiveness, and promoter and site-binding elements (Figure 7A). This underscores the significant role of cis-acting elements in governing SCPL gene expression during soybean growth and development. As depicted in Figure 7B,C, a total of 590 environmental-related elements and 722 hormone-related elements were characterized, suggesting that GmSCPL genes may not only impact soybean growth and development but also play a profound role in regulating and responding to various biotic and abiotic stresses.
2.8. Gene Ontology (GO) Enrichment Analysis of GmSCPLs
Gene Ontology (GO) enrichment analysis is commonly employed as a fundamental approach for elucidating gene functionality [47]. Consequently, we conducted GO enrichment analysis of all identified GmSCPL members. GmSCPLs within the biological processes (BP) category were enriched in secondary metabolic process; those within the cellular components (CC) category were associated with plant-type cell wall; while those within the molecular function (MF) category were primarily enriched in serine-type peptidase activity, serine-type exopeptidase activity, serine-type carboxypeptidase activity, exopeptidase activity, serine hydrolase activity, and peptidase activity (Figure 8). These findings suggest that the GmSCPL family may be involved in the stress response and regulation of plant cell wall dynamics.
2.9. Analysis of Tissue-Specific Expression Patterns of Selected GmSCPLs
To explore the functions of GmSCPLs, we analyzed the transcriptional levels of six specific GmSCPL genes in various tissues using RNA-seq Tools of SoyMD [48]. These genes included two from each subgroup (Ⅰ, Ⅱ, and Ⅲ) and were all located within SCN-related QTLs (soybean cyst nematode-related quantitative trait loci) (Figure S1 and Table S2). We measured expression levels in terms of transcripts per kilobase million (TPM). Figure 9 shows that each GmSCPL was transcriptionally active in at least one specific organ. Notably, while the expression patterns varied among different phylogenetic subgroups, they were quite consistent within each subgroup. This indicates that GmSCPLs may have important roles in tissue-specific developmental processes at various stages of growth.
2.10. Expression Analysis of GmSCPLs under Abiotic and Biotic Stress
Previous studies have established that SCPLs in plants are crucial for various physiological and biochemical functions, and their transcription is influenced by a range of stimuli, including pathogenic attacks and environmental stresses such as drought, salt, and cold [19,20,49]. To investigate the roles of GmSCPLs under biotic and abiotic stress conditions, we analyzed how soybean cyst nematode (SCN, Heterodera glycines), cold, drought, and saline-alkali stresses affect the transcription levels of selected GmSCPL genes. Our data show significant up-regulation of all selected genes five days after inoculation with SCN (5 dpi) (Figure 10A). Ten days post-SCN inoculation, GmSCPL16, GmSCPL52, GmSCPL41, and GmSCPL55 showed significant expulsion, whereas GmSCPL14 and GmSCPL36 exhibited no significant changes (Figure 10A). Under saline-alkali or cold stress, GmSCPL41 and GmSCPL55 (Group Ⅲ) displayed a strong induction on the fifth day and suppression on the tenth day (Figure 10B,C). Regarding drought stress, the expression of GmSCPL41 was significantly induced, while GmSCPL55 displayed no significant change (Figure 10D). The response of Group Ⅰ and Ⅱ members varied significantly under different abiotic stresses. For example, GmSCPL16 and GmSCPL36 (Group Ⅰ) showed strong induction under saline-alkali stress on the fifth day, but their expression was not significantly changed under the same condition on the tenth day (Figure 10B). As for GmSCPL14 and GmSCPL52 (Group Ⅱ), their expression was vitally suppressed under saline-alkali stress while induced under drought stress on the fifth day (Figure 10B,C). These findings suggest that GmSCPLs play significant roles in response to nematode infection and various environmental stresses.
3. Discussion
The serine carboxypeptidase-like genes (SCPLs) hold a significant position in plant growth, development, and responses to various stress [11,50,51,52]. Genome-wide investigation of SCPLs in multiple plants, including Arabidopsis thaliana, rice (Oryza sativa), bread wheat (Triticum aestivum), cotton (Gossypium hirsutum), rapeseed (Brassica napus), and the tea plant (Camellia sinensis), had been performed previously [19,20,22,53,54]. As one of the most important protein feed and vegetable oil crops for human consumption, cultivated soybean (Glycine max) originated from wild soybean (Glycine soja) in China about 5000 years ago [26,27,55]. Williams 82 (Wm82) was the first-released reference genome among plenty of cultivated soybeans [56,57]. Nevertheless, a systemic analysis of the SCPL gene family in soybean has been limited until now. Here, 73 SCPL members were identified and characterized based on the reference genome of Wm82. All identified GmSCPLs could be stratified into three distinct clusters (termed Group Ⅰ, Ⅱ, and Ⅲ) on the bias of their gene structure and phylogenetic analysis (Figure 2A and Figure 3), in accordance with several earlier observations [19,20,23]. Our analysis revealed that the conserved domain, motif, and gene structure of most identified GmSCPLs were relatively conserved within the same cluster (Figure 2 and Figure 6). Additionally, most members of the identified GmSCPLs were predicted to be localized in the vacuole or peroxisome (Table 1), which might be due to the indispensable role SCPLs played in the presence of plant secondary metabolites [58,59].
The number of SCPLs varies a lot across different species (Table 1 and Table S1). For instance, bread wheat (T. aestivum) owns the largest number (210) of SCPL gene family members, which can be attributed to the fact that wheat is a complex allohexaploid and has experienced two whole genome duplications. The number of SCPL members in soybean (G. max) and wild soybean (G. soja) is quite comparable (Table 1 and Table S1). Furthermore, 117 orthologous gene pairs were identified between soybean and wild soybean (G. max-G. soja), much more abundant than those in other species (Figure 4 and Table S4). These observations may be due to the fact that G. max and G. soja are closely related wild relatives [26,27,60]. Gene duplication events are fundamental for the gene family, and they can facilitate plants in nature becoming more and more adapted to diverse environmental conditions [61,62,63]. Our exploration revealed that six tandem duplication events and 34 fragment duplication events contributed to the SCPL gene family in soybean (Figure 3), suggesting both fragment and tandem duplication events were vital for GmSCPLs’s expansion.
It is highly frequent for codon usage bias (CUB) to occur within the plant genome [64,65]. CUB occupies a significant position in the regulation of gene expression and molecular evolution [66,67]. CUB, including codon bias index (CBI), frequency of optimal codons (Fop), effective number of codons (ENC), GC content at the third position (GC3s), and overall GC content of SCPL gene family analysis, was performed in soybean. Taking these CUB indicators into account, we found that the CUB of SCPL genes in dicotyledonous plants (G. max, G. soja, and Arabidopsis) was more intense than that in monocotyledonous ones (O.sativa and T. aestivum) (Table 2). We also examined the relative synonymous codon usage (RSCU) values of the SCPL gene family across five species. A relatively conserved RSCU pattern within monocotyledons or dicotyledons was also observed (Figure 5C). Furthermore, neutral plot and parity rule 2 (PR2) analysis showed that CUB of the SCPL gene family in monocotyledonous plants is mainly influenced by natural selection, while both mutation and natural pressure function in dicotyledonous ones (Figure 5A,B).
The SCPL gene family exhibits a broad spectrum of expression across different tissues [19]. RNA-seq analysis revealed that all selected GmSCPLs exhibited higher expression levels in the upper flower, indicating their potential involvement in plant growth and development (Figure 9). The GmSCPLs promoter analysis identified a series of cis-acting elements, encompassing those elements related to development, environmental stress, and hormone responsiveness (Figure 7), which suggests GmSCPLs may play an important role in soybean response to abiotic or biotic stresses. Then, we explored the expression of GmSCPLs under biotic stress (nematode infection) and abiotic stress (NaCl, cold, and drought treatments). As shown in Figure 10, the outcomes revealed that the expression levels of all selected GmSCPLs were significantly influenced by abiotic or biotic stress. These results suggest that GmSCPLs may have distinct functions in combating various natural stresses.
Through a blend of genomic, bioinformatic, and experimental approaches, this study lays a solid foundation for future functional studies and genetic engineering efforts aimed at exploiting the potential of SCPL genes to improve stress tolerance in soybean. Further research into the specific roles of individual SCPL genes will elucidate their contributions to soybeans’ adaptive responses and facilitate the development of targeted breeding strategies for stress resistance.
4. Materials and Methods
4.1. Identification and Characterization of the SCPL Family in Soybean
For this study, Williams 82 soybean seeds were obtained from the Chinese Academy of Agricultural Sciences in Beijing, China. Reference genomic sequences for Oryza sativa (Oryza sativa v7.0), Glycine max (Wm82.a2.v1), Arabidopsis thaliana (Arabidopsis thaliana TAIR10), and Glycine soja (G. soja v1.1) were obtained from the Phytozome Plants database (
4.2. Phylogenetic Analysis
Multiple sequence alignments of GmSCPL proteins from G. max, G. soja, Arabidopsis, O. sativa, and T. aestivum were carried out using ClustalW. Following this, a maximum likelihood (ML) phylogenetic tree was constructed with IQ-Tree 2.2.5 software (IQ-TREE2.2.5, Canberra, Australia) [71] and refined using the iTOL online tool (
4.3. Chromosome Location and Collinearity Analysis
Synteny relationships within the SCPL family across G. max, G. soja, Arabidopsis, and O. sativa were explored using McscanX [72] and visualized with TBtools [73]. The ratio of nonsynonymous to synonymous substitutions (Ka/Ks) for tandem duplications was determined using the Ka/Ks Calculator in TBtools, and divergence times (T) were calculated with the formula T = Ks/(2 × 9.1 × 10−9) million years ago (Mya) [29,74].
4.4. Codon Usage Bias Analysis
Codon usage bias for SCPL coding sequences (CDS) from G. max, G. soja, Arabidopsis, O. sativa, and T. aestivum was assessed using CodonW 1.4.2 software (CodonW 1.4.2, Houston, USA). The frequency of optimal codons, effective number of codons (ENC), GC content, and GC3s content, along with relative synonymous codon usage (RSCU), were estimated using the EMBOSS online tool.
4.5. Motif and Gene Structure Analysis
Conserved motifs within the GmSCPLs were predicted using the MEME sequence analysis tool (
4.6. Promoter Analysis
Promoter regions, extending 2000 base pairs upstream from the transcription start sites of 73 GmSCPL genes, were extracted from the soybean genome GTF file. These sequences were analyzed using the PlantCARE website (
4.7. Gene Ontology (GO) Enrichment Analysis
GO annotation enrichment analysis for GmSCPLs was performed using the GO Enrichment function of TBtools software (TBtools, Guangzhou, China), which involved transforming the p-values using the -log10 conversion [74]. The results were subsequently visualized using the clusterProfiler tool [76].
4.8. RNA Isolation and Real-Time Quantitative Polymerase Chain Reaction (RT-qPCR)
Total RNA was isolated following the manufacturer’s instructions using TRIzol Reagent (Vazyme, Nanjing, China). Single-stranded cDNA was synthesized using a First Strand cDNA Synthesis Kit (Vazyme, Nanjing, China). Real-time quantitative PCR (RT-qPCR) was performed using an ABI QuantStudio5 Detection System (Applied Biosystems, Foster City, CA, USA) with Hieff qPCR SYBR Green Master Mix (YEASEN, Shanghai, China). Each experimental condition included at least three biological replicates and three technical replicates. The relative expression levels of target genes were quantified using the 2−ΔΔC(t) method as described by [77]. The actin gene served as the internal control for each assay. Primers involved in RT-qPCR are shown in Table S6.
4.9. Tissue Expression by RNA-seq
Tissue expression analysis was performed using RNA-seq data obtained from the Soybean multi-omics database (SoyMD) (Soybean: Home (hzau.edu.cn); accessed on 6 January 2024) [48]. The RNA-seq data were normalized using TPM (transcripts per million) values to ensure accurate and comparable expression levels across different tissues and developmental stages. The RNA-seq analysis was visualized using the efp tool for the transcriptomics module of the SoyMD database.
4.10. Plant Growth and Stress Treatments
Williams 82 soybean seeds were grown in a controlled environment greenhouse at 25 °C with a 16/8 h light/dark photoperiod. At the five-leaf stage, seedlings underwent nematode inoculations, and were subjected to drought, saline, and cold stress treatments.
Eggs of the soybean cyst nematode (SCN, Heterodera glycines) were incubated in a hatching buffer containing 2.99 mM ZnCl2 at room temperature for 72 h. The resulting stage 2 juveniles (J2) were sterilized using a solution containing 0.1 g/L HgCl2 and 0.01% sodium azide for 80 s, followed by two rinses in sterile water. The J2 SCNs were then resuspended in 0.048% sterile agarose solution for inoculation. For temperature stress experiments, seedlings were maintained at 4 °C. For drought stress, watering was withheld, and for saline stress, seedlings were treated with 0.9% NaCl.
5. Conclusions
In conclusion, this comprehensive study has elucidated the structural, evolutionary, and functional dynamics of the SCPL gene family in soybean, classifying 73 members into three distinct subgroups. Detailed analyses of gene architecture, conserved domains, and cis-acting regulatory elements highlighted the complexity and specialization of these genes in response to various environmental stresses. The findings from codon usage bias analysis and gene expression profiling under different stress conditions have further underscored the significant roles these genes play in plant stress responses. This foundational work not only advances our understanding of the SCPL family’s contribution to soybeans’ resilience and adaptability but also sets the stage for future research aimed at harnessing these genes for the development of stress-resistant soybean varieties. These insights provide invaluable resources for improving soybean cultivation and stress management strategies, paving the way for enhanced agricultural productivity and sustainability.
L.H. designed the experiment and prepared the manuscript; L.H. performed experiments; L.H. and Q.L. performed the bioinformatics analysis; L.H. wrote the draft, S.H. revised the manuscript. All authors have read and agreed to the published version of the manuscript.
Not applicable.
Not applicable.
Data are contained within the article.
We thank Shiming Liu from Chinese Academy of Agricultural Sciences in Beijing, China for providing Williams 82 seeds.
The authors declare no conflicts of interest.
Footnotes
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Enlarge this image.Figure 1. The maximum likelihood (ML) phylogenetic tree was constructed based on the SCPL amino acid sequences in Arabidopsis thaliana, Oryza sativa, Triticum aestivum, Glycine max, and Glycine soja using IQ-TREE 2.2.5 software(Q-TREE 2.2.5, Canberra, Australia) with Q. pfam+R6 model. All SCPLs are divided into three phylogenetic groups.
Enlarge this image.Figure 2. Phylogenetic and conserved domain analysis of the GmSCPL family. (A) Maximum likelihood (ML) phylogenetic tree of GmSCPLs using IQ-tree with LG+R4 model. All GmSCPLs are divided into three phylogenetic groups. (B) Conserved domains of all identified GmSCPLs.
Enlarge this image.Figure 3. Chromosome location and gene duplication analysis of GmSCPL genes. Slight gray lines indicate all synteny blocks within soybean genome. The duplicated gene pairs are highlighted with colored lines. Heat map in the inner circle indicates chromosomal gene density; Heat map in the middle circle indicates chromosomal GC skew; Heat map in the outer circle indicates chromosomal GC contents.
Enlarge this image.Figure 4. Syntenic relationships of the SCPL genes in Glycine max and three other species, including Arabidopsis thaliana, Oryza sativa, and Glycine soja.
Enlarge this image.Figure 5. Condon usage bias analysis. (A) Neutrality plot analysis of all identified GmSCPLs CDS sequences. (B) Parity rule 2 (PR2) analysis of GmSCPLs CDS sequences in five species including Arabidopsis thaliana, Oryza sativa, Triticum aestivum, Glycine max, and Glycine soja. (C) Heatmap showing relative synonymous codon usage (RSCU) values of five species including Arabidopsis thaliana, Oryza sativa, Triticum aestivum and Glycine max and Glycine soja. Blue-to-red color indicates low-to-high RSCU values of codons.
Enlarge this image.Figure 6. Analysis of the phylogenetic relationship, gene struchure and conserved motfs of GmSCPLs. (A) Phylogenetic tree of GmSCPLs. (B) Conserved motifs of GmSCPLs. Different colors indicate different motifs numbered 1 to 10. (C) Gene structure of all identified GmSCPLs. Green boxes indicate untranslated regions (UTRs), and yellow boxes indicate coding sequence (CDS) regions.
Enlarge this image.Figure 7. Analysis of cis-acting regulatory elements in GmSCPLs. (A) The number of seven distinct types of cis-acting elements within the promoter regions of each GmSCPL.; (B) overview of environmental-related cis-acting regulatory elements in each GmSCPL.; (C) overview of hormone-relate cis-acting regulatory elements in each GmSCPL.
Enlarge this image.Figure 8. Gene Ontology (GO) enrichment analysis of GmSCPL genes, organized into three categories: biological process (BP), cellular component (CC), and molecular function (MF). GO terms with a p-value below 0.05 were deemed statistically significant, indicating notable enrichment.
Enlarge this image.Figure 9. Differential expression of selected GmSCPLs in different tissues by RNA-seq. (A) Expression profiles of GmSCPL16 (Glyma.07G218400.1) and GmSCPL36 (Glyma.12G083100.1) across various soybean tissues at different developmental stages. (B) Expression profiles of GmSCPL14 (Glyma.06G181700.1) and GmSCPL52 (Glyma.15G090300.1) across various soybean tissues at different developmental stages. (C) Expression profiles of GmSCPL41 (Glyma.13G029200.1) and GmSCPL55 (Glyma.16G145300.1) across various soybean tissues at different developmental stages. The heatmaps indicate the expression levels, with red representing high expression and yellow representing low expression. Each diagram illustrates the expression patterns in tissues such as roots, stems, leaves, flowers, and pods, providing a comprehensive overview of the spatial and temporal expression of these genes.
Enlarge this image.Figure 10. Analysis of the expression of certain GmSCPLs in response to biotic and abiotic stresses. (A) Expression profiles of certain GmSCPLs in response to soybean cyst nematode (SCN, Heterodera glycines) infection were analyzed by RT-qPCR. The mean values and standard errors (SE) were calculated from three biological replicates, each consisting of three technical replicates: ns indicates non-significance; ** p < 0.01; * p < 0.05 (Student’s t-test). (B) Expression profiles of certain GmSCPLs in response to 0.9% NaCl treatment were analyzed by RT-qPCR. Mean values and standard errors (SE) were calculated from three biological replicates, each consisting of three technical replicates. Note: “ns” indicates non-significance; “**” p < 0.01; “*” p < 0.05 (Student’s t-test). (C) Expression profiles of certain GmSCPLs in response to 4 ℃ treatment were analyzed by RT-qPCR. The mean values and standard errors (SE) were calculated from three biological replicates, each consisting of three technical replicates: “**” p < 0.01 (Student’s t-test). (D) Expression profiles of certain GmSCPLs in response to drought treatment were analyzed by RT-qPCR. The mean values and standard errors (SE) were calculated from three biological replicates, each consisting of three technical replicates: “ns” indicates non-significance; “**” p < 0.01 (Student’s t-test).
Detailed information of the putative SCPLs in soybean.
| mRNA ID | Gene Name | Chr | Gene Location | ORF Length (bp) | Size(aa) | MW(KDa) | pI | Intron | Splice | Subcellular |
|---|---|---|---|---|---|---|---|---|---|---|
| Glyma.02G204700.1 | GmSCPL1 | Chr02 | 38993365–39000790 | 1386 | 462 | 53.58417 | 6.76 | 8 | 1 | Extracell |
| Glyma.03G070300.1 | GmSCPL2 | Chr03 | 16324083–16330477 | 1389 | 463 | 55.86286 | 5.67 | 13 | 1 | Vacuole |
| Glyma.03G090900.1 | GmSCPL3 | Chr03 | 26981330–26988564 | 693 | 231 | 53.92149 | 5.34 | 7 | 1 | Vacuole |
| Glyma.03G125200.1 | GmSCPL4 | Chr03 | 33883674–33887698 | 1446 | 482 | 53.43581 | 8.67 | 9 | 2 | Vacuole |
| Glyma.03G125400.1 | GmSCPL5 | Chr03 | 33909174–33912239 | 1389 | 463 | 53.78 | 7.19 | 9 | 2 | Vacuole |
| Glyma.03G125500.1 | GmSCPL6 | Chr03 | 33918983–33921895 | 1380 | 460 | 26.54959 | 4.89 | 9 | 1 | Vacuole |
| Glyma.03G125600.1 | GmSCPL7 | Chr03 | 33929465–33932834 | 1386 | 462 | 33.38494 | 6.5 | 8 | 2 | Vacuole |
| Glyma.04G155900.1 | GmSCPL8 | Chr04 | 36484956–36492419 | 1452 | 484 | 54.80313 | 5.73 | 9 | 1 | Vacuole |
| Glyma.04G200200.1 | GmSCPL9 | Chr04 | 47272565–47276234 | 1410 | 470 | 53.0337 | 5.45 | 9 | 1 | Vacuole |
| Glyma.04G240600.1 | GmSCPL10 | Chr04 | 50888492–50892907 | 1422 | 474 | 54.82872 | 5.68 | 9 | 3 | Vacuole |
| Glyma.06G047400.1 | GmSCPL11 | Chr06 | 3584404–3590095 | 1416 | 472 | 42.33745 | 8 | 13 | 9 | Vacuole |
| Glyma.06G122800.1 | GmSCPL12 | Chr06 | 10009186–10013239 | 1422 | 474 | 34.27499 | 7.07 | 9 | 4 | Vacuole |
| Glyma.06G165400.1 | GmSCPL13 | Chr06 | 13723574–13727195 | 1413 | 471 | 56.7101 | 6.18 | 9 | 1 | Vacuole |
| Glyma.06G181700.1 | GmSCPL14 | Chr06 | 15515094–15520222 | 1254 | 418 | 53.34864 | 9.14 | 12 | 5 | Vacuole |
| Glyma.07G192700.1 | GmSCPL15 | Chr07 | 36045428–36052232 | 1461 | 487 | 33.0789 | 8.86 | 9 | 1 | Vacuole |
| Glyma.07G218400.1 | GmSCPL16 | Chr07 | 39141266–39142853 | 1365 | 455 | 49.14665 | 9.15 | 0 | 1 | Vacuole |
| Glyma.07G236600.1 | GmSCPL17 | Chr07 | 41820157–41824129 | 1446 | 482 | 55.4932 | 5.45 | 9 | 5 | Vacuole |
| Glyma.08G008700.1 | GmSCPL18 | Chr08 | 682896–686265 | 1425 | 475 | 47.72612 | 5.5 | 9 | 6 | Vacuole |
| Glyma.08G245500.1 | GmSCPL19 | Chr08 | 21195019–21201951 | 1416 | 472 | 51.05139 | 6.08 | 7 | 3 | Extracell |
| Glyma.08G257800.1 | GmSCPL20 | Chr08 | 23162701–23166441 | 1386 | 462 | 59.81874 | 5.54 | 9 | 2 | Vacuole |
| Glyma.09G049500.1 | GmSCPL21 | Chr09 | 4298702–4302403 | 1494 | 498 | 53.40589 | 8.32 | 8 | 2 | Peroxisome/Vacuole |
| Glyma.09G226700.1 | GmSCPL22 | Chr09 | 45147433–45152456 | 1491 | 497 | 56.67716 | 6.07 | 6 | 1 | Vacuole |
| Glyma.09G249500.1 | GmSCPL23 | Chr09 | 47056885–47062577 | 1521 | 507 | 24.22614 | 9.17 | 13 | 1 | Peroxisome |
| Glyma.10G102100.1 | GmSCPL24 | Chr10 | 20236973–20240885 | 1395 | 465 | 51.6027 | 6.37 | 9 | 1 | Vacuole |
| Glyma.10G104300.1 | GmSCPL25 | Chr10 | 22636718–22663087 | 1497 | 499 | 54.59697 | 6.28 | 8 | 2 | Peroxisome/Vacuole |
| Glyma.10G207300.1 | GmSCPL26 | Chr10 | 43879369–43883196 | 1500 | 500 | 47.35157 | 5.82 | 8 | 1 | Peroxisome/Vacuole |
| Glyma.10G212500.1 | GmSCPL27 | Chr10 | 44500805–44506389 | 1383 | 461 | 52.77113 | 6.72 | 8 | 2 | Vacuole |
| Glyma.11G099600.1 | GmSCPL28 | Chr11 | 7551710–7556030 | 1422 | 474 | 51.0712 | 4.84 | 9 | 1 | Vacuole |
| Glyma.11G099700.1 | GmSCPL29 | Chr11 | 7558753–7566979 | 1401 | 467 | 52.15427 | 8.9 | 9 | 1 | Vacuole |
| Glyma.11G191200.1 | GmSCPL30 | Chr11 | 26434930–26442035 | 1377 | 459 | 54.72837 | 5.42 | 12 | 1 | Vacuole |
| Glyma.11G193800.1 | GmSCPL31 | Chr11 | 26725185–26729444 | 1467 | 489 | 51.67685 | 6.02 | 8 | 5 | Peroxisome/Vacuole |
| Glyma.11G193900.1 | GmSCPL32 | Chr11 | 26730950–26734235 | 1434 | 478 | 53.33445 | 5.98 | 8 | 1 | Peroxisome/Vacuole |
| Glyma.12G010100.1 | GmSCPL33 | Chr12 | 718029–722960 | 1491 | 497 | 52.87489 | 6.24 | 6 | 1 | Vacuole |
| Glyma.12G025600.1 | GmSCPL34 | Chr12 | 1844961–1853018 | 1449 | 483 | 51.18424 | 6.42 | 9 | 2 | Vacuole |
| Glyma.12G025900.1 | GmSCPL35 | Chr12 | 1873092–1878613 | 1419 | 473 | 54.41969 | 6.89 | 7 | 1 | Vacuole |
| Glyma.12G083100.1 | GmSCPL36 | Chr12 | 6586692–6592302 | 1380 | 460 | 52.64793 | 6.72 | 12 | 2 | Vacuole |
| Glyma.12G177900.1 | GmSCPL37 | Chr12 | 33699331–33703039 | 1515 | 505 | 56.47516 | 5.49 | 8 | 2 | Peroxisome/Vacuole |
| Glyma.12G179400.1 | GmSCPL38 | Chr12 | 33972888–33973824 | 654 | 218 | 54.03901 | 5.25 | 3 | 1 | Vacuole |
| Glyma.13G028500.1 | GmSCPL39 | Chr13 | 8018267–8022397 | 1473 | 491 | 54.19511 | 6.14 | 7 | 1 | Vacuole |
| Glyma.13G028800.1 | GmSCPL40 | Chr13 | 8182077–8185659 | 1596 | 532 | 51.98603 | 8.68 | 5 | 1 | Vacuole |
| Glyma.13G029200.1 | GmSCPL41 | Chr13 | 8614070–8618166 | 1467 | 489 | 51.35516 | 5.49 | 7 | 1 | Vacuole |
| Glyma.13G075200.1 | GmSCPL42 | Chr13 | 17816382–17822985 | 879 | 293 | 49.38054 | 6.42 | 9 | 3 | Vacuole |
| Glyma.13G183700.1 | GmSCPL43 | Chr13 | 29723122–29727602 | 1482 | 494 | 51.78898 | 6.15 | 9 | 2 | Vacuole |
| Glyma.13G221900.1 | GmSCPL44 | Chr13 | 33488305–33492501 | 1410 | 470 | 49.87419 | 6.57 | 13 | 1 | Vacuole |
| Glyma.13G243500.1 | GmSCPL45 | Chr13 | 35288591–35293220 | 1437 | 479 | 55.6809 | 6.25 | 9 | 1 | Vacuole |
| Glyma.13G321200.1 | GmSCPL46 | Chr13 | 41546470–41550353 | 1371 | 457 | 52.03607 | 8.72 | 12 | 1 | Vacuole |
| Glyma.13G321700.1 | GmSCPL47 | Chr13 | 41602238–41606724 | 1377 | 459 | 54.5101 | 8.29 | 12 | 1 | Vacuole |
| Glyma.13G322600.1 | GmSCPL48 | Chr13 | 41709896–41713941 | 1521 | 507 | 51.37635 | 6.19 | 8 | 1 | Peroxisome/Vacuole |
| Glyma.14G080500.1 | GmSCPL49 | Chr14 | 6965564–6972041 | 1497 | 499 | 55.45726 | 5.77 | 7 | 2 | Extracell |
| Glyma.14G122200.1 | GmSCPL50 | Chr14 | 17801426–17807621 | 1464 | 488 | 51.05933 | 5.34 | 9 | 3 | Vacuole |
| Glyma.15G070200.1 | GmSCPL51 | Chr15 | 5375186–5380088 | 1449 | 483 | 55.43504 | 7.6 | 9 | 1 | Vacuole |
| Glyma.15G090300.1 | GmSCPL52 | Chr15 | 6952810–6957605 | 1458 | 486 | 51.19083 | 5.13 | 13 | 2 | Vacuole |
| Glyma.15G156200.1 | GmSCPL53 | Chr15 | 13086610–13091482 | 1482 | 494 | 56.10161 | 5.27 | 8 | 2 | Peroxisome/Vacuole |
| Glyma.16G082700.1 | GmSCPL54 | Chr16 | 9310673–9320591 | 1497 | 499 | 52.89716 | 6.07 | 13 | 4 | Peroxisome |
| Glyma.16G145300.1 | GmSCPL55 | Chr16 | 30604586–30608656 | 1482 | 494 | 54.96599 | 5.56 | 8 | 2 | Vacuole |
| Glyma.17G037000.1 | GmSCPL56 | Chr17 | 2697476–2701132 | 1449 | 483 | 54.82264 | 5.96 | 9 | 1 | Vacuole |
| Glyma.17G073200.1 | GmSCPL57 | Chr17 | 5720584–5728156 | 1383 | 461 | 52.40136 | 8.69 | 8 | 2 | Vacuole |
| Glyma.17G244900.1 | GmSCPL58 | Chr17 | 40030818–40036322 | 1500 | 500 | 18.63345 | 4.9 | 7 | 2 | Extracell |
| Glyma.18G242900.1 | GmSCPL59 | Chr18 | 53113341–53119592 | 1521 | 507 | 50.63926 | 6.41 | 13 | 1 | Peroxisome |
| Glyma.18G266700.1 | GmSCPL60 | Chr18 | 55105365–55112399 | 1404 | 468 | 52.77681 | 8.51 | 7 | 1 | Extracell |
| Glyma.18G282200.1 | GmSCPL61 | Chr18 | 56302289–56306074 | 1386 | 462 | 55.66993 | 6.65 | 9 | 1 | Vacuole |
| Glyma.19G128000.1 | GmSCPL62 | Chr19 | 38717520–38722550 | 1125 | 375 | 52.91801 | 5.75 | 11 | 1 | Vacuole |
| Glyma.19G128100.1 | GmSCPL63 | Chr19 | 38728037–38732422 | 1389 | 463 | 54.65352 | 4.81 | 10 | 2 | Vacuole |
| Glyma.19G128200.1 | GmSCPL64 | Chr19 | 38739769–38743404 | 1383 | 461 | 52.80598 | 5.72 | 8 | 2 | Vacuole |
| Glyma.20G014900.1 | GmSCPL65 | Chr20 | 1375276–1376799 | 903 | 301 | 43.96814 | 6.66 | 0 | 1 | Vacuole |
| Glyma.20G015100.1 | GmSCPL66 | Chr20 | 1379240–1380596 | 1338 | 446 | 54.53818 | 6.36 | 1 | 1 | Vacuole |
| Glyma.20G015400.1 | GmSCPL67 | Chr20 | 1393894–1395216 | 1323 | 441 | 54.39402 | 5.96 | 0 | 1 | Vacuole |
| Glyma.20G015600.1 | GmSCPL68 | Chr20 | 1406934–1408603 | 1317 | 439 | 56.00173 | 5.17 | 0 | 1 | Vacuole |
| Glyma.20G016800.1 | GmSCPL69 | Chr20 | 1545314–1546525 | 1182 | 394 | 54.05284 | 6.33 | 1 | 1 | Vacuole |
| Glyma.20G043400.1 | GmSCPL70 | Chr20 | 7902915–7918077 | 1245 | 415 | 55.68712 | 5.76 | 11 | 3 | Vacuole |
| Glyma.20G056200.1 | GmSCPL71 | Chr20 | 13855383–13860273 | 1452 | 484 | 51.60472 | 5.4 | 7 | 1 | Vacuole |
| Glyma.20G178600.1 | GmSCPL72 | Chr20 | 41603247–41609549 | 1383 | 461 | 55.58359 | 5.07 | 8 | 1 | Vacuole |
| Glyma.U001900.1 | GmSCPL73 | NA | NA | 900 | 300 | 55.51719 | 5.73 | 0 | 1 | Vacuole |
Codon usage indicators of the SCPL family in five different species. Abbreviations: CBI, codon bias index; Fop, frequency of optimal codons; ENC, effective number of codons; and GC3s, contents of G or C bases at the third position of the codons; and GC content, the contents of the G and C bases of the codons.
| Species Name | CAI | CBI | Fop | ENC | GC3s | GC Content |
|---|---|---|---|---|---|---|
| Glycine max | 0.1953835 | 0.089274 | 0.3687671 | 50.513836 | 0.3610685 | 0.42216438 |
| Arabidopsis thaliana | 0.2068823 | −0.02584 | 0.405725 | 54.11863 | 0.40149 | 0.43554902 |
| Oryza sativa | 0.2271041 | 0.081895 | 0.4657083 | 48.638333 | 0.6486042 | 0.55472916 |
| Glycine soja | 0.1954927 | 0.086768 | 0.3701449 | 50.683043 | 0.3628841 | 0.42288405 |
| Triticum aestivum | 0.2342428 | 0.118742 | 0.4871667 | 48.045762 | 0.7024667 | 0.57511428 |
Supplementary Materials
The following supporting information can be downloaded at:
References
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; Liu, Qiannan 2 ; Han, Shaojie 1
1 State Key Laboratory of Rice Biology and Breeding, Key Laboratory of Biology of Crop Pathogens and Insects of Zhejiang Province, Institute of Biotechnology, Zhejiang University, Hangzhou 310058, China;
2 State Key Laboratory of Rice Biology and Breeding, Key Laboratory of Biology of Crop Pathogens and Insects of Zhejiang Province, Institute of Biotechnology, Zhejiang University, Hangzhou 310058, China;