P0862
Identification and Validation of QTL for Yield Components under Contrasting Water Treatments in a Collection of Spring Wheat from North America

Junli Zhang , University of California, Davis, Davis, CA
Shiferaw Gizaw , Washington State University, Pullman, WA
Eligio Bossolini , Bayer CropScience, Gent, Belgium
Marco Maccaferri , DipSA - University of Bologna, Bologna, Italy
Joshua Hegarty , University of California, Davis, Davis, CA
Arron H. Carter , Washington State University, Pullman, WA
Shiaoman Chao , USDA-ARS, Fargo, ND
Eduard Akhunov , Kansas State University, Department of Plant Pathology, Manhattan, KS, Manhattan, KS
Jorge Dubcovsky , University of California, Davis, Davis, CA
Increasing grain yield is always a priority in wheat breeding. A genome-wide association study (GWAS) was conducted in 3 locations across 2 years under two irrigation regimes using 262 photoperiod non-sensitive spring wheat collection to identify quantitative trait loci (QTL) associated with yield and yield components. Significant marker-trait associations (MTAs) were identified in the GWAS and validated using 8 nested association mapping (NAMs) created by TriticeaeCAP (TCAP) for traits grain yield (GY), spikelet number per spike (SNS), kernel number per spike (KNS), and kernel weight (KW). After validation, 12 QTL for GY, 12 QTL for SNS, 1 QTL for KNS, and 20 QTL for KW were reported in the present study. Multiple QTL showed consistent high effects across environments without the confounding effects of heading date and plant height. These validated QTL are useful sources for improving wheat grain yield under diverse environments.