title: Genomic Prediction with Pedigree and Genotype × Environment Interaction in Spring Wheat Grown in South and West Asia, North Africa, and Mexico.
abstract: Developing genomic selection (GS) models is an important step in applying GS to accelerate the rate of genetic gain in grain yield in plant breeding. In this study, seven genomic prediction models under two cross-validation (CV) scenarios were tested on 287 advanced elite spring wheat lines phenotyped for grain yield (GY), thousand-grain weight (GW), grain number (GN), and thermal time for flowering (TTF) in 18 international environments (year-location combinations) in major wheat-producing countries in 2010 and 2011. Prediction models with genomic and pedigree information included main effects and interaction with environments. Two random CV schemes were applied to predict a subset of lines that were not observed in any of the 18 environments (CV1), and a subset of lines that were not observed in a set of the environments, but were observed in other environments (CV2). Genomic prediction models, including genotype × environment (G×E) interaction, had the highest average prediction ability under the CV1 scenario for GY (0.31), GN (0.32), GW (0.45), and TTF (0.27). For CV2, the average prediction ability of the model including the interaction terms was generally high for GY (0.38), GN (0.43), GW (0.63), and TTF (0.53). Wheat lines in site-year combinations in Mexico and India had relatively high prediction ability for GY and GW. Results indicated that prediction ability of lines not observed in certain environments could be relatively high for genomic selection when predicting G×E interaction in multi-environment trials.
authors.affiliation: Global Wheat Program, International Maize and Wheat Improvement Center (CIMMYT), El Batan, Texcoco CP 56237, Mexico.
authors.forename: Sivakumar
authors.identifier: 0000-0003-4088-4624
authors.initials: S
authors.lastname: Sukumaran
authors.affiliation: Biometrics and Statistics Unit, CIMMYT, El Batan, Texcoco CP 56237, Mexico j.crossa@cgiar.org.
authors.forename: Jose
authors.identifier: 0000-0001-9429-5855
authors.initials: J
authors.lastname: Crossa
authors.affiliation: Department of Agronomy and Horticulture, University of Nebraska, Lincoln, Nebraska 68583.
authors.forename: Diego
authors.initials: D
authors.lastname: Jarquin
authors.affiliation: Global Wheat Program, CIMMYT, Emex, 06511 Ankara, Turkey.
authors.forename: Marta
authors.identifier: 0000-0002-7698-6019
authors.initials: M
authors.lastname: Lopes
authors.affiliation: Global Wheat Program, International Maize and Wheat Improvement Center (CIMMYT), El Batan, Texcoco CP 56237, Mexico.
authors.forename: Matthew P
authors.identifier: 0000-0002-4291-4316
authors.initials: MP
authors.lastname: Reynolds
mesh_terms: D000352:Africa, Northern; D001208:Asia; D001947:Breeding; D059647:Gene-Environment Interaction; D018745:Genome, Plant; D023281:Genomics; D005838:Genotype; D008800:Mexico; D010375:Pedigree; D010641:Phenotype; D019655:Quantitative Trait, Heritable; D012621:Seasons; D012641:Selection, Genetic; D014908:Triticum / Q000235:genetics* / Q000254:growth & development
keywords: GBLUP; GenPred; Shared Data Resources; WAMI; genomic prediction; genomic selection; pedigree-based prediction; spring wheat