QTL for Genetic Improvement of Soybean Amino Acid Composition.

Soybean is utilized globally as the primary source of plant-derived protein feed for swine, poultry, and farm-raised fish. Current soybean meal nutritional profiles are limited in some essential and non-essential amino acid. The five most important amino acids to the meat industry are: cysteine, methionine, lysine, threonine and tryptophan. These amino acids are required for muscle and tissue development as well as metabolism. The utilization of phenotypic and MAS breeding methods show promise for making incremental improvements in soymeal amino acid composition. The purpose of this research was to create and test a model to identify QTL that individually or cumulatively affect the five abovementioned amino acids. A population of 939 recombinant inbred lines (RILs) of ‘Essex’ x ‘Williams 82’ were genotyped using > 50,000 SNPs markers and 17,232 polymorphic SNP loci were detected. To measure phenotypic traits, RIL representing each genotype were grown in one location the first year and data were subdivided according to relative maturity. Amino acid composition was determined by near infrared spectroscopy (NIR). In 2013, 302 RIL of MG V were grown in three environments and phenotypic analysis was conducted using NIR. Significant differences (p<0.05) for amino acids were found among the RIL for both years. The RIL genotypic and phenotypic data were analyzed using composite interval mapping and R/qtl software to detect QTL. QTL were successfully identified for the five amino acids in both years. QTL for cysteine located on Gm03, Gm09 and Gm13 accounted for 4.1-6.7% of the phenotypic variation. One of the QTL on Gm013 (R2 = 4.9%) was stable across multiple environments. Our present model showed that the presence or absence of a given QTL or QTL combination can produce measurable changes in amino acid composition. Utilization of such information may lead to genetic improvements for amino acid composition.