The soybean yield is a complex quantitative trait that is significantly influenced by environmental factors. G × E interaction (GEI), which derives the performance of soybean genotypes differentially in various environmental conditions, is one of the main obstacles to increasing the net production. The primary goal of this study is to identify the outperforming genotypes in different latitudes, which can then be used in future breeding programs. A total of 96 soybean genotypes were examined in two different ecological regions: Faisalabad and Tando Jam in Pakistan. The evaluation of genotypes in different environmental conditions showed a substantial amount of genetic diversity for grain yield. We identified 13 environment-specific genotypes showing their maximum grain yield in each environment. Genotype G69 was found to be an ideal genotype with higher grain yield than other genotypes tested in this study and is broadly adapted for environments E1 and E2 and also included in top-yielding genotypes in E3, E4, and E5. G92 is another genotype that is broadly adapted in E1, E3, and E4. In the case of environments, E3 is suggested to be a more ideal environment as it is plotted near the concentric circle and is very informative for the selection of genotypes with high yield. Despite the presence of GEI, advances in DNA technology provided very useful tools to investigate the insight of advanced genotypes. Association mapping is a useful method for swiftly and efficiently investigating the genetic basis of significant plant traits. A total of 26 marker–trait associations were found for six agronomic traits in five environments, with the highest significance (p-value = 2.48 × 10^–08) for plant height and the lowest significance (1.03 × 10^–03) for hundred-grain weight. Soybean genotypes identified in the present study could be a valuable source for future breeding programs as they are adaptable to a wide range of environments. Genetic selection of genotypes with the best yields can be used for gross grain production in a wide range of climatic conditions, and it would give an essential reference in terms of soybean variety selection.

Soybean (Glycine max) is an important legume that is used to fulfill the need of protein and oil of large number of population across the world. There are large numbers of soybean germplasm present in the USDA germplasm resources. Finding and understanding genetically diverse germplasm is a top priority for crop improvement programs. The current study used 20 functional EST-SSR and 80 SSR markers to characterize 96 soybean accessions from diverse geographic backgrounds. Ninety-six of the 100 markers were polymorphic, with 262 alleles (average 2.79 per locus). The molecular markers had an average polymorphic information content (PIC) value of 0.44, with 28 markers ≥ 0.50. The average major allele frequency was 0.57. The observed heterozygosity of the population ranged from 0–0.184 (average 0.02), while the expected heterozygosity ranged from 0.20–0.73 (average 0.51). The lower value for observed heterozygosity than expected heterozygosity suggests the likelihood of a population structure among the germplasm. The phylogenetic analysis and principal coordinate analysis (PCoA) divided the total population into two major groups (G1 and G2), with G1 comprising most of the USA lines and the Australian and Brazilian lines. Furthermore, the phylogenetic analysis and PCoA divided the USA lines into three major clusters without any specific differentiation, supported by the model-based STRUCTURE analysis. Analysis of molecular variance (AMOVA) showed 94% variation among individuals in the total population, with 2% among the populations. For the USA lines, 93% of the variation occurred among individuals, with only 2% among lines from different US states. Pairwise population distance indicated more similarity between the lines from continental America and Australia (189.371) than Asia (199.518). Overall, the 96 soybean lines had a high degree of genetic diversity.

Soybean (Glycine max [L.] Merr.) is one of the most significant crops in the world in terms of oil and protein. Owing to the rising demand for soybean products, there is an increasing need for improved varieties for more productive farming. However, complex correlation patterns among quantitative traits along with genetic interactions pose a challenge for soybean breeding. Association studies play an important role in the identification of accession with useful alleles by locating genomic sites associated with the phenotype in germplasm collections. In the present study, a genome-wide association study was carried out for seven agronomic and yield-related traits. A field experiment was conducted in 2015/2016 at two locations that include 155 diverse soybean germplasm. These germplasms were genotyped using SoySNP50K Illumina Infinium Bead-Chip. A total of 51 markers were identified for node number, plant height, pods per plant, seeds per plant, seed weight per plant, hundred-grain weight, and total yield using a multi-locus linear mixed model (MLMM) in FarmCPU. Among these significant SNPs, 18 were putative novel QTNs, while 33 co-localized with previously reported QTLs. A total of 2,356 genes were found in 250 kb upstream and downstream of significant SNPs, of which 17 genes were functional and the rest were hypothetical proteins. These 17 candidate genes were located in the region of 14 QTNs, of which ss715580365, ss715608427, ss715632502, and ss715620131 are novel QTNs for PH, PPP, SDPP, and TY respectively. Four candidate genes, Glyma.01g199200, Glyma.10g065700, Glyma.18g297900, and Glyma.14g009900, were identified in the vicinity of these novel QTNs, which encode lsd one like 1, Ergosterol biosynthesis ERG4/ERG24 family, HEAT repeat-containing protein, and RbcX2, respectively. Although further experimental validation of these candidate genes is required, several appear to be involved in growth and developmental processes related to the respective agronomic traits when compared with their homologs in Arabidopsis thaliana. This study supports the usefulness of association studies and provides valuable data for functional markers and investigating candidate genes within a diverse germplasm collection in future breeding programs.

The J-protein family comprises molecular chaperones involved in plant growth, development, and stress responses. Little is known about this gene family in soybean. Hence, we characterized J-protein genes in soybean, with the most highly expressed and responsive during flower and seed development. We also revealed their phylogeny, structure, motif analysis, chromosome location, and expression. Based on their evolutionary links, we divided the 111 potential soybean J-proteins into 12 main clades (I–XII). Gene-structure estimation revealed that each clade had an exon-intron structure resembling or comparable to others. Most soybean J-protein genes lacked introns in Clades I, III, and XII. Moreover, transcriptome data obtained from a publicly accessible soybean database and RT-qPCR were used to examine the differential expression of DnaJ genes in various soybean tissues and organs. The expression level of DnaJ genes indicated that, among 14 tissues, at least one tissue expressed the 91 soybean genes. The findings suggest that J-protein genes could be involved in the soybean growth period and offer a baseline for further functional research into J-proteins' role in soybean. One important application is the identification of J-proteins that are highly expressed and responsive during flower and seed development in soybean. These genes likely play crucial roles in these processes, and their identification can contribute to breeding programs to improve soybean yield and quality.