Soybean is a major source of protein for human consumption and animal feed. Releasing new cultivars with high nutritional value is one of the major goals in soybean breeding. To achieve this goal, genome-wide association studies of seed amino acid contents were conducted based on 249 soybean accessions from China, US, Japan, and South Korea. The accessions were evaluated for 15 amino acids and genotyped by sequencing. Significant genetic variation was observed for amino acids among the accessions. Among the 231 single nucleotide polymorphisms (SNPs) significantly associated with variations in amino acid contents, fifteen SNPs localized near 14 candidate genes involving in amino acid metabolism. The amino acids were classified into two groups with five in one group and seven amino acids in the other. Correlation coefficients among the amino acids within each group were high and positive, but the correlation coefficients of amino acids between the two groups were negative. Twenty-five SNP markers associated with multiple amino acids can be used to simultaneously improve multi-amino acid concentration in soybean. Genomic selection analysis of amino acid concentration showed that selection efficiency of amino acids based on the markers significantly associated with all 15 amino acids was higher than that based on random markers or markers only associated with individual amino acid. The identified markers could facilitate selection of soybean varieties with improved seed quality.

Soybean [Glycine max (L.) Merr.] is a crop of great interest worldwide. Exploring molecular approaches to increase yield genetic gain has been one of the main challenges for soybean breeders and geneticists. Agronomic traits such as maturity, plant height, and seed weight have been found to contribute to yield. In this study, a total of 250 soybean accessions were genotyped with 10,259 high-quality SNPs postulated from genotyping by sequencing (GBS) and evaluated for grain yield, maturity, plant height, and seed weight over three years. A genome-wide association study (GWAS) was performed using a Bayesian Information and Linkage Disequilibrium Iteratively Nested Keyway (BLINK) model. Genomic selection (GS) was evaluated using a ridge regression best linear unbiased predictor (rrBLUP) model. The results revealed that 20, 31, 37, and 23 SNPs were significantly associated with maturity, plant height, seed weight, and yield, respectively; Many SNPs were mapped to previously described maturity and plant height loci (E2, E4, and Dt1) and a new plant height locus was mapped to chromosome 20. Candidate genes were found in the vicinity of the two SNPs with the highest significant levels associated with yield, maturity, plant height, seed weight, respectively. A 11.5-Mb region of chromosome 10 was associated with both yield and seed weight. Overall, the accuracy of GS was dependent on the trait, year, and population structure, and high accuracy indicates that these agronomic traits can be selected in molecular breeding through GS. The SNP markers identified in this study can be used to improve yield and agronomic traits through the marker-assisted selection and GS in breeding programs.

We demonstrated enhanced mB7-H3 expression and reduced sB7-H3 levels in MS patients which correlated with the clinical characteristics of MS patients. These results suggest that B7-H3 may be a promising biomarker and associated with the pathogenesis of MS.

Photosynthetic rate which acts as a vital limiting factor largely affects the potential of soybean production, especially during the senescence phase. However, the physiological and molecular mechanisms that underlying the change of photosynthetic rate during the developmental process of soybean leaves remain unclear. In this study, we compared the protein dynamics during the developmental process of leaves between the soybean cultivar Hobbit and the high-photosynthetic rate cultivar JD 17 using the iTRAQ (isobaric tags for relative and absolute quantification) method. A total number of 1269 proteins were detected in the leaves of these two cultivars at three different developmental stages. These proteins were classified into nine expression patterns depending on the expression levels at different developmental stages, and the proteins in each pattern were also further classified into three large groups and 20 small groups depending on the protein functions. Only 3.05-6.53 % of the detected proteins presented a differential expression pattern between these two cultivars. Enrichment factor analysis indicated that proteins involved in photosynthesis composed an important category. The expressions of photosynthesis-related proteins were also further confirmed by western blotting. Together, our results suggested that the reduction in photosynthetic rate as well as chloroplast activity and composition during the developmental process was a highly regulated and complex process which involved a serial of proteins that function as potential candidates to be targeted by biotechnological approaches for the improvement of photosynthetic rate and production.

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