Soybean is an important crop providing edible oil and protein source. Soybean oil and protein contents are quantitatively inherited and significantly affected by environmental factors. In this study, meta-analysis was conducted based on soybean physical maps to integrate quantitative trait loci (QTLs) from multiple experiments in different environments. Meta-QTLs for seed oil, fatty acid composition, and protein were identified. Of them, 11 meta-QTLs were located on hot regions for both seed oil and protein. Next, we selected 4 chromosome segment substitution lines with different seed oil and protein contents to characterize their 3 years of phenotype selection in the field. Using strand-specific RNA-sequencing analysis, we profile the time-course transcriptome patterns of soybean seeds at early maturity, middle maturity, and dry seed stages. Pairwise comparison and K-means clustering analysis revealed 7,482 differentially expressed genes and 45 expression patterns clusters. Weighted gene coexpression network analysis uncovered 46 modules of gene expression patterns. The 2 most significant coexpression networks were visualized, and 7 hub genes were identified that were involved in soybean oil and seed storage protein accumulation processes. Our results provided a transcriptome dataset for soybean seed development, and the candidate hub genes represent a foundation for further research.

Trihelix transcription factors play a role in plant growth, development and various stress responses. Here, we identified 41 trihelix family genes in the rice genome. These OsMSLs (Myb/SANT-LIKE) were located on twelve chromosomes. Synteny analysis indicated only six duplicated gene pairs in the rice trihelix family. Phylogenetic analysis of these OsMSLs and the trihelix genes from other species divided them into five clusters. OsMSLs from different groups significantly diverged in terms of gene structure and conserved functional domains. However, all OsMSLs contained the same five cis-elements. Some of these were responsive to light and dehydration stress. All OsMSLs expressed in four tissues and six developmental stages of rice but with different expression patterns. Quantitative real-time PCR analysis revealed that the OsMSLs responded to abiotic stresses including drought and high salt stress and stress signal molecule including ABA (abscisic acid), hydrogen peroxide. OsMSL39 were simultaneously expressed under all treatments, while OsMSL28 showed high expression under hydrogen peroxide, drought, and high salt treatments. Moreover, OsMSL16/27/33 displayed significant expression under ABA and drought treatments. Nevertheless, their responses were regulated by light. The expression levels of the 12 chosen OsMSLs differed between light and dark conditions. In conclusion, our results helped elucidate the biological functions of rice trihelix genes and provided a theoretical basis for further characterizing their biological roles in responding to abiotic stresses.

Heavy metal exposure is a serious environmental stress in plants. However, plants have evolved several strategies to improve their heavy metal tolerance. Heavy metal-associated proteins (HMPs) participate in heavy metal detoxification. Here, we identified 46 and 55 HMPs in rice and Arabidopsis, respectively, and named them OsHMP 1-46 and AtHMP 1-55 according to their chromosomal locations. The HMPs from both plants were divided into six clades based on the characteristics of their heavy metal-associated domains (HMA). The HMP gene structures and motifs varied greatly among the different classifications. The HMPs had high collinearity and were segmentally duplicated. A cis-element analysis revealed that the HMPs may be regulated by different transcription factors. An expression profile analysis disclosed that only eight OsHMPs were constitutive in rice tissues. Of these, the expression of OsHMP37 was far higher than that of the other seven genes while OsHMP28 was expressed exclusively in the roots. For Arabidopsis, nine AtHMPs presented with very high transcript levels in all organs. Most of the selected OsHMPs were differentially expressed in various tissues under different heavy metal stresses. Only OsHMP09, OsHMP18, and OsHMP22 showed higher expression levels in all tissues under different heavy metal stresses. In contrast, most of the selected AtHMPs had nearly constant expression levels in different tissues under various heavy metal stresses. The AtHMP20, AtHMP23, AtHMP25, AtHMP31, AtHMP35, AtHMP46 expression levels under different heavy metal stresses were higher in the leaves and roots. The foregoing discoveries elucidated HMP evolution in monocotyledonous and dicotyledonous plants and may helpful functionally characterize HMPs in the future.

The concentration of protein in soybean is an important trait that drives successful soybean quality. A recombinant inbred line derived from a cross between the Charleston and Dongnong594 cultivars was planted in one location across 10 years and two locations across 5 years in China (20 environments in total), and the genetic effects were partitioned into additive main effects, epistatic main effects and their environmental interaction effects using composite interval mapping and inclusive composite interval mapping models based on a high-density genetic map. Ten main-effect quantitative trait loci (QTLs) were identified on chromosomes 3, 6, 7, 13, 15 and 20 and detected in more than three environments, with each of the main-effect QTLs contributing a phenotypic variation of around 10 %.Between the intervals of the main-effect QTLs, 93 candidate genes were screened for their involvement in seed protein storage and/or amino acid biosynthesis and metabolism processes based on gene ontology and annotation information. Furthermore, an analysis of epistatic interactions showed that three epistatic QTL pairs were detected, and could explain approximately 50 % of the phenotypic variation. The additive maineffect QTLs and epistatic QTL pairs contributed to high phenotypic variation under multiple environments, and the results were also validated and corroborated with previous research, indicating that marker-assisted selection can be used to improve soybean protein concentrations and that the candidate genes can also be used as a foundation data set for research on gene function.

As soybean seed fatty acid content is valued in food, animal feed and some industrial applications, plant breeders continually aim to improve seed fatty acid constituent value. This study analysed 163 original quantitative trait loci (QTLs) related to soybean fatty acid content from databases and references and revealed 43 consensus QTLs. Meta‐analysis using BioMercator ver.2.1 indicated that these were located across 16 linkage groups (LGs) excluding LG D1a, LG C1, LG M and LG H. Moreover, the overview method was used to optimize these QTLs based on statistical analysis. Some valid QTL regions were narrowed down to 0.5 Mb and mapped on the same LGs as the meta‐analysis result. Furthermore, the functions of all genes located in these consensus QTL intervals were predicted and eight candidate genes were identified. KEGG pathway analysis indicated that Glyma.13G127900 and Glyma.18G232000 were involved in the fatty acid synthesis metabolic (pathway ID ko00071, ko00062, ko01040). These results lay a foundation for fine mapping of QTLs related to fatty acid content and marker‐assisted breeding in soybean.