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.

EST-derived SSR marker has been developed in many species, but few methods of high efficiency have been reported for the exploitation of EST-SSR markers. Thus, a high efficiency method for mining millions of redundant EST data is needed. A modified method for the EST-SSR development with high efficiency was established based on the redundant EST data of soybean in this study. The method achieved its function through classifying ESTs according to the same SSR motif and detected candidate loci with redundant sequences. In this study, a total of 80 polymorphic EST-SSR markers of soybean were developed, 50 of them were exploited by this modified method which proved the higher speed and efficiency of this method. All the 80 polymorphic EST-SSRs were mapped on soybean physical map through in silico mapping and 15 markers were integrated on a genetic map constructed in previous study. A software named hpSSR (high polymorphic SSR) was programmed based on the concept of the up-built method for EST-SSR development. This method is not only pragmatic for EST-SSR exploitation in soybean, but also effective for the development of the marker in other species if the redundancy EST data is available.