Seed oil and protein content in soybean [Glycine max (L.) Merr.] are complex quantitative traits controlled by multiple genes and highly susceptible to environmental influences. To investigate the genetic basis of these traits in Northern China, a major soybean-producing area, we re-sequenced 334 core accessions of soybean landraces and elite cultivars from this area. Based on phenotypic data collected over multiple years, a subsequent SNP/InDel-based GWAS for seed oil and protein content identified fifteen quantitative trait loci (QTLs) significantly associated with the traits. Noticeably, qOil05-1 was consistently detected across three years, accounting for 4.8–14.46

Microbial communities associated with roots play a crucial role in the growth and health of plants and are constantly influenced by plant development and alterations in the soil environment. Despite extensive rhizosphere microbiome research, studies examining multi-kingdom microbial variation across large-scale agricultural gradients remain limited. This study investigates the rhizosphere microbial communities associated with soybean across 13 diverse geographical locations in China. Using high-throughput shotgun metagenomic sequencing on the BGISEQ T7 platform with 10 GB per sample, we identified a total of 43,337 microbial species encompassing bacteria, archaea, fungi, and viruses. Our analysis revealed significant site-specific variations in microbial diversity and community composition, underscoring the influence of local environmental factors on microbial ecology. Principal coordinate analysis (PCoA) indicated distinct clustering patterns of microbial communities, reflecting the unique environmental conditions and agricultural practices of each location. Network analysis identified 556 hub microbial taxa significantly correlated with soybean yield traits, with bacteria showing the strongest associations. These key microorganisms were found to be involved in critical nutrient cycling pathways, particularly in carbon oxidation, nitrogen fixation, phosphorus solubilization, and sulfur metabolism. Our findings demonstrate the pivotal roles of specific microbial taxa in enhancing nutrient cycling, promoting plant health, and improving soybean yield, with significant positive correlations (r = 0.5, p = 0.039) between microbial diversity and seed yield. This study provides a comprehensive understanding of the diversity and functional potential of rhizosphere microbiota in enhancing soybean productivity. The findings underscore the importance of integrating microbial community dynamics into crop management strategies to optimize nutrient cycling, plant health, and yield. While this study identifies key microbial taxa with potential functional roles, future research should focus on isolating and validating these microorganisms for their bioremediation and biofertilization activities under field conditions. This will provide actionable insights for developing microbial-based agricultural interventions to improve crop resilience and sustainability.

The seed oil-to-protein ratio has increased remarkably during soybean domestication; however, the principal genetic determinants governing this critical agronomic trait remain elusive. Integrated genome-wide and transcriptome-wide association studies (GWAS/TWAS) are conducted and identified GmSop20 on chromosome 20 as a pivotal regulator of soybean seed oil and its protein content. Genetic diversity analysis reveals a domestication-selected allele, GmSop20C, which has undergone intense artificial selection and is dominant in cultivars across northern China and the USA. This allele drives a substantial increase in the oil-to-protein ratio from 0.35 in ancestral lines to 0.47 in cultivars. Functional validation reveals that the knockout of GmSop20 significantly reduces the ratio to 0.19, while its overexpression increases it to 0.64. Notably, while mutant lines exhibit a modest increase in total oil and protein content, overexpression maintains stable compositional levels. Mechanistically, GmSop20 directly activates GmSWEET10a expression, synergizing two artificially selected loci within a unified regulatory network to amplify sugar allocation from the seed coat to the embryo, thereby enhancing oil accumulation. The findings establish GmSop20 as a master regulator of seed composition and provide insights for custom-designing soybean nutritional profiles, enabling the precise regulation of the oil-to-protein ratio through targeted manipulation of this key genetic module.

Soybean is one of the most economically important crops worldwide and a valuable source of protein for human consumption and animal feed. The use of wild soybean accessions as a source of new alleles for improvement of soybean quality remains challenging owing to linkage drag. Here, using segregating populations derived from a set of wild soybean chromosome segment substitution lines, we fine-mapped quantitative trait loci (QTLs) (qPC-06-1) for seed protein content to a 48.8-Kb interval on chromosome 6. A gene encoding an S-adenosyl- L-methionine-dependent methyltransferase (GmMET) was determined to be the causal gene underlying the qPC-06-1 locus. Three single-nucleotide polymorphism/insertion-deletion markers (SNPs/InDels) in the coding region were found to modulate the methyltransferase activity of different GmMET alleles, thereby influencing seed protein content. Transgenic and multi-omics analyses provided preliminary evidence for the pathways through which GmMET influences seed protein content and exerts pleiotropic effects on seed oil content, oil composition, and related traits. Additional analyses showed that an elite GmMET allele was under selection during soybean domestication and improvement and is now widespread in modern cultivars, particularly in southern China. Our findings thus reveal that a methyltransferase gene affects the protein content of soybean seeds, providing a foundation for the continued development of high-protein soybean cultivars.

Seed oil represents a key trait in soybeans, which holds substantial economic significance, contributing to roughly 60% of global oilseed production. This research employed genome-wide association mapping to identify genetic loci associated with oil content in soybean seeds. A panel comprising 341 soybean accessions, primarily sourced from Northeast China, was assessed for seed oil content at Heilongjiang Province in three replications over two growing seasons (2021 and 2023) and underwent genotyping via whole-genome resequencing, resulting in 1,048,576 high-quality SNP markers. Phenotypic analysis indicated notable variation in oil content, ranging from 11.00% to 21.77%, with an average increase of 1.73% to 2.28% across all growing regions between 2021 and 2023. A genome-wide association study (GWAS) analysis revealed 119 significant single-nucleotide polymorphism (SNP) loci associated with oil content, with a prominent cluster of 77 SNPs located on chromosome 8. Candidate gene analysis identified four key genes potentially implicated in oil content regulation, selected based on proximity to significant SNPs (≤10 kb) and functional annotation related to lipid metabolism and signal transduction. Notably, Glyma.08G123500, encoding a receptor-like kinase involved in signal transduction, contained multiple significant SNPs with PROVEAN scores ranging from deleterious (−1.633) to neutral (0.933), indicating complex functional impacts on protein function. Additional candidate genes include Glyma.08G110000 (hydroxycinnamoyl-CoA transferase), Glyma.08G117400 (PPR repeat protein), and Glyma.08G117600 (WD40 repeat protein), each showing distinct expression patterns and functional roles. Some SNP clusters were associated with increased oil content, while others correlated with decreased oil content, indicating complex genetic regulation of this trait. The findings provide molecular markers with potential for marker-assisted selection (MAS) in breeding programs aimed at increasing soybean oil content and enhancing our understanding of the genetic architecture governing this critical agricultural trait.

Soybean is one of the most economically important crops worldwide and a valuable source of protein for human consumption and animal feed. The use of wild soybean accessions as a source of new alleles for improvement of soybean quality remains challenging owing to linkage drag. Here, using segregating populations derived from a set of wild soybean chromosome segment substitution lines, we fine-mapped quantitative trait loci (QTLs) ( ) for seed protein content to a 48.8-Kb interval on chromosome 6. A gene encoding an -adenosyl- -methionine-dependent methyltransferase ( ) was determined to be the causal gene underlying the locus. Three single-nucleotide polymorphism/insertion-deletion markers (SNPs/InDels) in the coding region were found to modulate the methyltransferase activity of different alleles, thereby influencing seed protein content. Transgenic and multi-omics analyses provided preliminary evidence for the pathways through which influences seed protein content and exerts pleiotropic effects on seed oil content, oil composition, and related traits. Additional analyses showed that an elite allele was under selection during soybean domestication and improvement and is now widespread in modern cultivars, particularly in southern China. Our findings thus reveal that a methyltransferase gene affects the protein content of soybean seeds, providing a foundation for the continued development of high-protein soybean cultivars.

Plants photoreceptors perceive changes in light quality and intensity and thereby regulate plant vegetative growth and reproductive development. By screening a γ irradiation-induced mutant library of the soybean (Glycine max) cultivar “Dongsheng 7”, we identified Gmeny, a mutant with elongated nodes, yellowed leaves, decreased chlorophyll contents, altered photosynthetic performance, and early maturation. An analysis of bulked DNA and RNA data sampled from a population segregating for Gmeny, using the BVF-IGV pipeline established in our laboratory, identified a 10 bp deletion in the first exon of the candidate gene Glyma.02G304700. The causative mutation was verified by a variation analysis of over 500 genes in the candidate gene region and an association analysis, performed using two populations segregating for Gmeny. Glyma.02G304700 (GmHY2a) is a homolog of AtHY2a in Arabidopsis thaliana, which encodes a PΦB synthase involved in the biosynthesis of phytochrome. A transcriptome analysis of Gmeny using the Kyoto Encyclopedia of Genes and Genomes (KEGG) revealed changes in multiple functional pathways, including photosynthesis, gibberellic acid (GA) signaling, and flowering time, which may explain the observed mutant phenotypes. Further studies on the function of GmHY2a and its homologs will help us to understand its profound regulatory effects on photosynthesis, photomorphogenesis, and flowering time.

Multi-environment trials (METs) are widely used in soybean breeding to evaluate soybean cultivars' adaptability and performance in specific geographic regions. However, METs' reliability is affected by spatial and temporal variation in testing environments, requiring further knowledge to correct such changes. To improve METs' accuracy, the growth of 1303 soybean cultivars was accurately estimated by accounting for climatic effects and spatial heterogeneity using a linear mixed-effect model and a field spatial-correction model, respectively. The METs across 10 sites varied in climate and planting dates, spanning N16 degrees 41 ' 52 '' in latitude. A soybean growth and development monitoring algorithm was proposed based on the photothermal accumulation area (AUC(pt)) rather than using calendar dates to reduce the impact of planting dates variability and climate factors. The AUC(pt) correlates strongly with latitude of the above trial sites (r > 0.77). The proposed merit-based integrated filter decreases the influence of noise on photosynthetic vegetation (f(PV)) and non-photosynthetic vegetation (f(NPV)) more effectively than S-G filter and locally estimated scatterplot smoothing. The field spatial-correction model helped account for spatial heterogeneity with a better estimation accuracy (R-2 >= 0.62, RMSE <= 0.17). Broad-sense heritability (H-2) with the field spatial-correction model outperformed the models without the model by an average of 52 % across the entire aerial surveys. Model transferability was evaluated across Sanya and Nanchang. Rescaled shape models in Sanya (R-2 = 0.97) were consistent with the growth curve in Nanchang (R-2 = 0.89). Finally, the methodology's precision estimations of crop genotypes' growth dynamics under differing environments displayed potential applications in precision agriculture and selecting high-yielding and stable soybean germplasm resources in METs.

Soybean seeds are rich in protein and oil. The selection of varieties that produce high-quality seeds has been one of the priorities of soybean breeding programs. However, the influence of improved seed quality on the rhizosphere microbiota and whether the microbiota is involved in determining seed quality are still unclear. Here, we analyzed the structures of the rhizospheric bacterial communities of 100 soybean varieties, including 53 landraces and 47 modern cultivars, and evaluated the interactions between seed quality traits and rhizospheric bacteria. We found that rhizospheric bacterial structures differed between landraces and cultivars and that this difference was directly related to their oil content. Seven bacterial families (Sphingomonadaceae, Gemmatimonadaceae, Nocardioidaceae, Xanthobacteraceae, Chitinophagaceae, Oxalobacteraceae, and Streptomycetaceae) were obviously enriched in the rhizospheres of the high-oil cultivars. Among them, Oxalobacteraceae (Massilia) was assembled specifically by the root exudates of high-oil cultivars and was associated with the phenolic acids and flavonoids in plant phenylpropanoid biosynthetic pathways. Furthermore, we showed that Massilia affected auxin signaling or interfered with active oxygen-related metabolism. In addition, Massilia activated glycolysis pathway, thereby promoting seed oil accumulation. These results provide a solid theoretical basis for the breeding of revolutionary soybean cultivars with desired seed quality and optimal microbiomes and the development of new cultivation strategies for increasing the oil content of seeds.

Flowering time is important for adaptation of soybean (Glycine max) to different environments. Here, we conducted a genome-wide association study of flowering time using a panel of 1490 cultivated soybean accessions. We identified three strong signals at the qFT02-2 locus (Chr02: 12037319–12238569), which were associated with flowering time in three environments: Gongzhuling, Mengcheng, and Nanchang. By analyzing linkage disequilibrium, gene expression patterns, gene annotation, and the diversity of variants, we identified an AP1 homolog as the candidate gene for the qFT02-2 locus, which we named GmAP1d. Only one nonsynonymous polymorphism existed among 1490 soybean accessions at position Chr02:12087053. Accessions carrying the Chr02:12087053-T allele flowered significantly earlier than those carrying the Chr02:12087053-A allele. Thus, we developed a cleaved amplified polymorphic sequence (CAPS) marker for the SNP at Chr02:12087053, which is suitable for marker-assisted breeding of flowering time. Knockout of GmAP1d in the ‘Williams 82’ background by gene editing promoted flowering under long-day conditions, confirming that GmAP1d is the causal gene for qFT02-2. An analysis of the region surrounding GmAP1d revealed that GmAP1d was artificially selected during the genetic improvement of soybean. Through stepwise selection, the proportion of modern cultivars carrying the Chr02:12087053-T allele has increased, and this allele has become nearly fixed (95%) in northern China. These findings provide a theoretical basis for better understanding the molecular regulatory mechanism of flowering time in soybean and a target gene that can be used for breeding modern soybean cultivars adapted to different latitudes.

Summary Soybean is one of the most economically important crops worldwide and an important source of unsaturated fatty acids and protein for the human diet. Consumer demand for healthy fats and oils is increasing, and the global demand for vegetable oil is expected to double by 2050. Identification of key genes that regulate seed fatty acid content can facilitate molecular breeding of high‐quality soybean varieties with enhanced fatty acid profiles. Here, we analysed the genetic architecture underlying variations in soybean seed fatty acid content using 547 accessions, including mainly landraces and cultivars from northeastern China. Through fatty acid profiling, genome re‐sequencing, population genomics analyses, and GWAS, we identified a SEIPIN homologue at the FA9 locus as an important contributor to seed fatty acid content. Transgenic and multiomics analyses confirmed that FA9 was a key regulator of seed fatty acid content with pleiotropic effects on seed protein and seed size. We identified two major FA9 haplotypes in 1295 resequenced soybean accessions and assessed their phenotypic effects in a field planting of 424 accessions. Soybean accessions carrying FA9 H2 had significantly higher total fatty acid contents and lower protein contents than those carrying FA9 H1 . FA9 H2 was absent in wild soybeans but present in 13% of landraces and 26% of cultivars, suggesting that it may have been selected during soybean post‐domestication improvement. FA9 therefore represents a useful genetic resource for molecular breeding of high‐quality soybean varieties with specific seed storage profiles.

When soybean seeds encounter low temperature during germination, the vigour and germination of soybean seeds are affected, which leads to a lack of seedlings and weak seedlings, resulting in yield reduction. In-depth analysis of the genetic mechanism of soybean seed germination tolerance to low-temperature stress and the cultivation of soybean-tolerant varieties is the key to resisting low-temperature stress at the germination stage. In the present study, a chromosome segment substitution line (CSSL) population constructed by wild soybean ZYD00006 and cultivated soybean SN14 was used to map three quantitative trait loci (QTLs). Five candidate genes were obtained by gene annotation, GO enrichment analysis and protein function prediction. The candidate genes were subjected to bioinformatics analysis, qRT-PCR analysis, trypsin activity analysis and soluble protein content analysis. The results showed that the secondary and tertiary structures of the Glyma.09G162700 proteins were mutated. Within 0-72 h, the expression of Glyma.09G162700 in the two materials with different tolerances was consistent, and the change in trypsin activity was consistent with the change in protein expression. Through haplotype analysis, Glyma.09G162700 produced two haplotypes at -2420 bp. The germination rate (GR) and relative germination rate (RGR) of the two haplotypes were significantly different, indicating that the two haplotypes have wide applicability in soybean resources. In summary, Glyma.09G162700 may be a candidate gene for low-temperature tolerance at the germination stage of soybean. These results provide an important theoretical basis and marker information for analysing the mechanism of low-temperature tolerance in soybean germination stage and cultivating low-temperature-tolerant varieties.

为探究大豆苗期耐低氮资源鉴定的指标与方法,筛选耐低氮大豆种质,本试验以234份国内外大豆品种资源为试验材料,设置低氮和正常氮2个氮水平,在处理24 d时测定茎粗、株高、叶柄长、叶绿素相对含量等12个指标.结果表明:大豆苗期各指标均值在2个氮水平下存在显著差异,耐低氮系数的平均值范围为0.48～1.38;通过主成分分析将12个指标转化为5个主要成分,累计贡献率达85.37％,并构建耐低氮大豆种质资源评价方程:D=0.48 D1+0.21 D2+0.13 D3+0.11 D4+0.08 D5;基于耐低氮综合评价值(D)进行聚类分析将234份大豆品种分为5类,分别为高耐低氮型、耐低氮型、中耐氮型、敏感型和高敏型,筛选出高耐低氮资源,包括茬前田豆、宝丰11和射阳半夏子等8份,高敏型种质,包括ラニホクジロメ、黔豆1号和WDD01135等11份.依据逐步回归分析得出株高、总干重、叶柄长、茎粗和地下干重5个性状的耐低氮系数可作为鉴定资源耐低氮性的主要指标.本研究构建的大豆耐低氮种质资源评价体系,将为耐低氮大豆品种的鉴定与筛选奠定基础.

以中吉602、吉育86、内民大3号和内民大5号为供试材料,试验品种为主区、种植密度为副区,设置35万株·hm-2、40万株·hm-2、45万株·hm-23个密度进行种植,通过测定其农艺性状及产量构成因素分析高产最适种植密度.结果表明:4个品种随种植密度的升高,其株高与底荚高度逐渐升高,而主茎节数与茎粗逐渐下降,每荚粒数、单株荚数、单株粒数、百粒重、单株重均随种植密度的增加而减少;随种植密度的增加,不同品种最高产量的最佳种植密度也不相同,其中,中吉602和内民大3号密度为40万株·hm-2时产量最高,分别为4585.63 kg·hm-2和3567.23 kg·hm-2;而吉育86和内民大5号则是在密度为45万株·hm-2时产量达到最高,分别为4218.78 kg·hm-2和4135.40 kg·hm-2.因此,推荐适合通辽地区种植的优良耐密高产品种为中吉602,最佳种植密度为40万株·hm-2.

大豆是植物油和蛋白质的主要来源.不饱和脂肪酸的含量是影响植物油品质的主要因素,油酸是不饱和脂肪酸中含量最丰富的成分之一,具有较强的氧化稳定性和热稳定性.增加油酸的含量可以提高大豆油的耐储存性,也有利于人体健康.GmFAD2-1A和GmFAD2-1B是大豆编码脂肪酸去饱和酶,调控油酸向亚油酸转化的关键基因.脂氧合酶是大豆种子中的抗营养因子之一.它在酶促氧化的条件下产生豆腥味,限制了大豆产品的应用.为满足不同人群的需要和降低加工成本,有必要培育无脂氧合酶的突变品系.大豆中GmLOX基因(包括GmLOX1、GmLOX2、GmLLOX3)编码脂氧合酶.脂氧酶也能催化亚油酸氧化生成脂质氢过氧化物,然后形成豆腥味.因此,降低亚油酸的含量有助于减少豆腥味的形成.同时编码脂氧酶也能延缓豆油的酸败.本研究利用CRISPR/Cas9对中吉602的GmFAD2-1A、GmFAD2-1B、GmLOX1、GmLOX2和GmLOX3基因进行编辑.通过农杆菌介导的大豆遗传转化,在T2代分离到7个具有不同等位变异的优异新种质.与中吉602相比,突变体种子中脂氧合酶活性显著降低,油酸含量提高至81.7％～83.5％.本研究为有效开发大豆种质资源以满足不断变化的市场需求提供了新材料.

为了全面解析原料大豆蛋白组成对豆腐凝胶特性的影响,本研究对大豆蛋白亚基组成与豆腐得率、质构性质及蛋白凝胶微观结构的关系进行了探讨.结果表明,大豆籽粒11 S/7 S球蛋白组分比值是判断豆腐产量和质构特性的良好指标.原料大豆蛋白组成的差异会导致豆浆pH值的不同,进而影响凝固剂对大豆蛋白的凝聚程度以及豆腐得率;原料大豆籽粒大小也是影响豆腐得率的一个重要因素.另外,7S球蛋白以及β亚基组分含量占比高的原料大豆制作的豆腐质地偏软、蛋白凝胶微观结构疏松且孔洞较多.

This study examined the segregation distortion during the process of constructing wild soybean and cultivated soybean population,to explore the segregation distortion regions(SDRs)and candidate genes,and to shed some light on understanding the mechanism of segregation distortion in soybean.The wild variety'Changling wild soybean'was used as the male parent and the landrace variety'Yiqianli'was used as the female parent to develop a hybrid group,resulting in 200 recombinant inbred lines(RIL).SLAF-seq was used for sequencing analysis and constructing a high-density genetic map.4 564 SNP markers were obtained and reliably identified for this population.Through segregation distortion analysis,648 markers were found to have genetic distortion(P＜0.05),accounting for 14.20％of the total markers.22 SDRs were found,which were distributed across 9 different chromosomes.In SDRs,8 extreme SDRs regions(ESDRs)were found,distributed on 5 different chromosomes,of which 3 ESDRs were biased towards the wild type of the male parent,and 5 ESDRs were biased towards the cultured type of the female parent.Using gene function annotation and genome-wide resequencing data,combined with the ESDR region,the affecting embryonic development(Glyma.01G051400)and female gametophyte development(Glyma.16G072700)genes were identified as candidate genes in ESDR1-1 and ESDR16-1,respectively.This study provides a reliable basis for locating the segregation distortion genes in the future,and lays the foundation for elucidating the segregation distortion.

This research examined the identification method and genetic traits of low nitrogen resistant soybean at the seedling stage. 260 soybean varieties were used and subjected for pot experiments under normal and low nitrogen treatments, followed by examination of nine traits（such as SPAD, plant high, and shoot fresh weight） at the stage of the fourth compound leaf unfolding. By analyzing the phenotypic difference of soybean varieties under low nitrogen stress condition, as well as the low nitrogen tolerance coefficient, correlation analysis, principal component analysis, affiliation function, and regression analysis, the soybean varieties showing low nitrogen tolerance were identified. The significant differences at all the traits were observed under two different nitrogen-supplying levels, showing levels of variation among the traits and the varieties. The indexes of nine traits were refined using three indexes by principal component analysis. Based the value of the affiliation function and the comprehensive evaluation of low nitrogen tolerance in conjugation with cluster analysis, five categories（strong resistant, resistant, middle resistant, sensitive and most sensitive） were suggested. Seventeen soybean varieties were strong resistant categories, while seven were most sensitive categories. Through stepwise regression analysis, total dry weight, root dry weight, shoot fresh weight, SPAD of the second compound leaf, and SPAD of the first compound leaf, might be deployed as the principal indicators for evaluating low nitrogen tolerance in soybean.

吉林省是我国重要的大豆产区,明确吉林省大豆育成品种的遗传多样性特点,可以为本地区大豆品种选育和遗传改良提供一定的理论支撑.本研究利用14个与产量性状连锁的SSR标记,对38份吉林省审定的大豆品种进行遗传多样性分析.结果表明:14个SSR标记在38份试验材料中共检测到31个等位变异位点,平均每个位点2.214 3个,等位变异数2～4个;多态信息含量0.094 8～0.545 4,平均为0.335 7;基因多样性指数均值为0.412 1,Shannon信息指数均值为0.626 2.聚类分析38份大豆品种被划分为两个类群,其中类群Ⅱ可进一步分为4个亚群;38份品种间的遗传距离在0～0.928 6,平均为0.410 7,表明供试品种的遗传多样性不够丰富.因此,在今后新品种选育过程中应当加强国外资源、地方品种、野生大豆血缘材料和不同生态区品种的利用,提高吉林省大豆品种的遗传多样性,进而推动单产持续提升.

Abstract Background The genes in the PRR family are key components of the transcription-translation circadian network in plants, and comprise the core genes in the central oscillator translation feedback loop of Arabidopsis sp. They play important roles in several physiological processes and environmental adaptation. However, there is little information regarding the PRR genes of soybean, which is an important food crop. A genome-wide study of the PRR genes of soybean was performed herein using the available complete genome sequences of Glycine max and Glycine soja. Results In total, 12 PRR genes of G. max (GmPRR) and 14 PRR genes of G. soja (GsPRR) were identified and labelled according to their chromosomal location. The sequence length, relative molecular weight, and subcellular localization of the encoded proteins were predicted, and fundamental information was obtained for the genes. GmPRR and GsPRR were further categorized into three main groups based on their phylogenetic characteristics. The gene structures and characteristics of protein motifs were similar in the same subfamily. Conserved domain analyses of the proteins revealed that the integrity of the conserved domains differed among proteins from different subfamilies. GmPRR genes were absent on chromosomes 11 and 12, contrary to GsPRR genes. The results indicated that fragment replication events played an important role in the amplification of GmPRR and GsPRR genes. Intergenomic collinearity analysis of G. max, G. soja, and A. sp. revealed that the PRR genes of soybean and A. sp. were highly homologous. Analysis of transcriptome data revealed that the expression patterns of GmPRR genes differed at different times. Quantitative polymerase chain reaction (qPCR) analyses determined the relative transcript abundances of the different GmPRR and GsPRR varied across the studied plant materials. Conclusions In this study, 12 PRR genes of G. max (GmPRR) and 14 PRR genes of G. soja (GsPRR) were identified, and the structure, evolution, and expression patterns of the encoded proteins were investigated. The results of systematic analysis provides a basis for the subsequent identification of the functions of PRR genes, and the preliminary data can be used for analyzing the specific functions of the PRR genes of soybean.