320-6 QTL Mapping for Oleic and Linolenic Acids In Soybean.

Poster Number 633

See more from this Division: C01 Crop Breeding & Genetics
See more from this Session: Molecular, Statistical and Breeding Tools to Improve Selection Efficiency
Wednesday, October 19, 2011
Henry Gonzalez Convention Center, Hall C
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Guo-liang Jiang1, Xianzhi Wang1, Marci Green1, Roy Scott1, David Hyten2 and Perry Cregan2, (1)South Dakota State University, Brookings, SD
(2)U.S. Dep. of Agriculture, Beltsville, MD
QTL Mapping for Oleic and Linolenic Acids in Soybean Guo-Liang Jiang*, Xianzhi Wang, Marci Green, Roy Scott Plant Science Department, South Dakota State University, Brookings, SD 57007 David Hyten, Perry Cregan USDA/ARS, 10300 Baltimore Ave, Beltsville, MD 20705 * Corresponding author: Guo-Liang.Jiang@sdstate.edu ABSTRACT Soybean [Glycine max (L.) Merr.] is the leading oilseed crop in the United States in terms of gross vegetable oil production and economic importance. Increased oleic and decreased linolenic acids are desirable for human consumption. For better understanding of the genetic basis of differences in fatty acids and improve breeding efficiency, QTL mapping for oleic and linolenic acids was performed with a recombinant inbred line (RIL) population. A total of 87 F5 RILs derived from the cross of SD02-4-59 A02-381100 were evaluated for fatty acids in six environments over 4 years. Genotypic data with about 800 polymorphic DNA markers were used to construct the linkage map, and QTL analysis was performed in WinQTLCart version 2.5. For oleic acid, two major QTLs on linkage groups E and G were consistently detected, explaining 11.61-19.61% and 9.47-22.72% of the variance, respectively. For linolenic acid, two major QTLs on linkage groups D1b and G were consistently detected, accounting for 30.52-38.69% and 7.43-13.14% of the total variance, respectively. A combination of two favorable QTL alleles significantly increased oleic acid or decrease linolenic acid. 1
See more from this Division: C01 Crop Breeding & Genetics
See more from this Session: Molecular, Statistical and Breeding Tools to Improve Selection Efficiency