Hexanol is a major compound contributing to the off-flavors (the bean-like odor) of soybean derived soymilk. The most effective way to reduce the off-flavors of soymilk is the screening and utilization of soybean cultivars with improved hexanol content. However, no genome-wide genetic analysis for this particular trait has been conducted to date. The objective of the present study was to dissect the genetic basis of hexanol content in soybean seed through genome-wide association analysis (GWAS). A total of 105 soybean accessions were analyzed for hexanol content in a three-year experiments and genotyped by sequencing using the specific locus amplified fragment sequencing (SLAF-seq) approach. A total of 25 724 single nucleotide polymorphisms (SNPs) were obtained with minor allele frequencies (MAF)>5%. GWAS showed that 25 quantitative trait nucleotides (QTNs) were significantly associated with the hexanol concentration in soybean seed. These identified QTNs distributed on different genomic regions of the 15 chromosomes. A total of 91 genes were predicted as candidate genes underlying the seed hexanol level and six candidates were predicted possibly underlying the seed hexanol by gene based association. In this study, GWAS has been proven to be an effective way to dissect the genetic basis of the hexanol concentration in multiple genetic backgrounds. The identified beneficial alleles and candidate genes might be valuable for the improvement of marker-assisted breeding efficiency for low hexanol level and help to explore possible molecular mechanisms underlying hexanol content in soybean seed.

Using isobaric tags for relative and absolute quantification (iTRAQ) and associated analytic technologies, we have cataloged and compared 7 069 unique wheat proteins expressed during four substages of the filling stage.  Among them, 859 are differentially expressed, showing at least a 2-fold difference in concentration across substages.  Differentially expressed proteins (DEPs) includind high-molecular weight glutenin subunit (W5AIU1), low-molecular weight glutenin subunit (Q8W3V4), gliadin/avenin-like seed protein (D2KFG9), and avenin-like protein (W5DVL2), all of which have previously been identified as important for nutritional quality and bread-making properties, and all of which were found to increase at the latter stages of development.  We have applied statistical techniques to group the proteins into hierarchical clusters, and have consulted databases to infer functional and other relationships among the identified proteins.