Single- and multiple-trait quantitative trait locus analysis for seed oil and protein contents of soybean populations with advanced breeding line background

Authors: HUYNH, TU - The Ohio State University; VAN, KYUJUNG - The Ohio State University; Mian, Rouf; MCHALE, LEAH - The Ohio State University

Submitted to: Molecular Breeding
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/24/2024
Publication Date: N/A
Citation: N/A

Interpretive Summary: Oil and protein are the two most valuable components in soybean seeds together accounting for more than 60% of its dry weight. Both components have high economic value, however, soybean seed oil and protein are negatively correlated, posing a challenge in breeding efforts to enhance both traits symultaneously. Previous studies have identified many oil and protein loci via the single-trait quantitative trait loci (QTL) analyses. Multiple-trait QTL methods for correlated traits were shown to improve detection power and mapping precision compared to single-trait methods but have not been applied to seed oil and protein contents. Our study conducted both single- and multiple-trait multiple interval mapping (ST-MIM and MT-MIM, respectively) for oil and protein contents using three recombinant inbred line populations derived from crosses between advanced breeding lines and tested in four environments. We detected seven ST-MIM QTLs on chromosomes 1, 8, 6, 15, 19, and two on 20, five of which were confirmed by MT-MIM. Using our original data as well as simulated data, our findings show the multiple-trait method did not outperform the single-trait approach for our traits of interest with high heritability (H2 > 0.84). All loci exerted opposite effects on oil and protein contents, but the protein-to-oil additive effect ratio varied (-0.6 to -48.8). We calculated the allelic effects on estimated processed values (EPV) using the National Oilseed Processors Association (NOPA) and High Yield + Quality (HY+Q) methods. Oil-increasing alleles of QTLs on chromosomes 6, 15, 19, and 20 increased both EPVNOPA and EPVHY+Q, while oil-increasing alleles of QTLs on chromosomes 1 and 8 increased EPVNOPA and decreased EPVHY+Q, which penalizes low protein meal. With the populations’ elite pedigree, selected lines can be used to determine the allelic effects on yield and directly integrated into breeding programs. The eestimated processed values (EPV) used in this study revealed the real economic value of a QTL allele.

Technical Abstract: Soybean seed oil and protein contents are negatively correlated, posing a challenge in breeding efforts to enhance both traits symultaneously. Previous studies have identified hundreds of oil and protein QTLs mainly via the single-trait QTL analyses. Multiple-trait QTL methods for correlated traits were shown to improve detection power and mapping precision compared to single-trait methods but have not been applied to seed oil and protein contents. Our study conducted both single- and multiple-trait multiple interval mapping (ST-MIM and MT-MIM, respectively) for oil and protein contents using three recombinant inbred line populations derived from crosses between advanced breeding lines and tested in four environments. We detected seven ST-MIM QTLs on chromosomes 1, 8, 6, 15, 19, and two on 20, five of which were confirmed by MT-MIM. Using our original data as well as simulated data, our findings show the multiple-trait method did not outperform the single-trait approach for our traits of interest with high heritability (H2 > 0.84). All loci exerted opposite effects on oil and protein contents, but the protein-to-oil additive effect ratio varied (-0.6 to -48.8). We calculated the allelic effects on estimated processed values (EPV) using the National Oilseed Processors Association (NOPA) and High Yield + Quality (HY+Q) methods. Oil-increasing alleles of QTLs on chromosomes 6, 15, 19, and 20 increased both EPVNOPA and EPVHY+Q, while oil-increasing alleles of QTLs on chromosomes 1 and 8 increased EPVNOPA and decreased EPVHY+Q, which penalizes low protein meal. With the populations’ elite pedigree, selected lines can be used to determine the allelic effects on yield and directly integrated into breeding programs.