Detection of Soybean Amino Acid QTLs and Seed Yield QTLs Using Selective Genotyping

Author

Benjamin David FallenFollow

Date of Award

12-2012

Degree Type

Dissertation

Degree Name

Doctor of Philosophy

Major

Plant Sciences

Major Professor

Vincent Pantalone

Committee Members

Fred L. Allen, Dean A. Kopsell, Arnold Saxton

Abstract

The U.S. Census Bureau projects the world’s population will top more than nine billion by 2050. Today, soybeans account for 56 % of the world oilseed production and 68 % of the world protein meal consumption, with U.S. soybean production accounting for 33 % of the world soybean production. So, to meet the demand of the world’s growing population and of the livestock industry improvements in both the composition and the yield of soybean is essential.

The primary objective of this project was to use molecular markers to identify genomic regions associated with amino acid composition and yield in soybean. For amino acid quantitative trait loci (QTL) detection 282 F_5:9 recombinant inbred lines (RIL) developed from a cross between Essex and Williams 82 were used. The Universal Soy Linkage Panel (USLP) 1.0 of 1536 single nucleotide polymorphic markers (SNPs) was used to identify 480 polymorphic molecular genetic markers and to genotype the 282 RILs. A total of ten QTL were detected on chromosomes 5, 7, 9, 10, 13 and 20 that explained 5 to 14 % of the total phenotypic variation for a particular amino acid.

To detect yield QTL 875 F_5:9 RIL developed from a cross between Essex and Williams 82 were used. The 875 RILs were divided into four groups based on maturity and each group was grown in Knoxville, TN and one other location of adaptability. Each RIL was genotyped with >50,000 SNPs of which 17,232 were polymorphic across the population. A total of forty-six yield QTLs were detected in this study, explaining 4.5 % to 11.9% of the phenotypic variation for yield. In addition, marker assisted selections (MAS) were made using only additive effects and using a yield prediction model (YPM) in each environment and across environments for each group. By including additive by additive effects in addition to additive effects into the YPM, more top yielding lines were selected than by just using only additive effects. This study provides new information concerning amino acid research in soybean and may offer some important insights into using an YPM that includes epistasis in soybean.

Recommended Citation

Fallen, Benjamin David, "Detection of Soybean Amino Acid QTLs and Seed Yield QTLs Using Selective Genotyping. " PhD diss., University of Tennessee, 2012.
https://trace.tennessee.edu/utk_graddiss/1523