Accounting for Group-Specific Allele Effects and Admixture in Genomic Predictions: Theory and Experimental Evaluation in Maize.

Rio, Simon; Moreau, Laurence; Charcosset, Alain; Mary-Huard, Tristan

Populations structured into genetic groups may display group-specific linkage disequilibrium, mutations and/or interactions between quantitative trait loci and the genetic background. These factors lead to heterogeneous marker effects affecting the efficiency of genomic prediction, especially for admixed individuals. Such individuals have a genome that is a mosaic of chromosome blocks from different origins, and may be of interest to combine favorable group-specific characteristics. We developed two genomic prediction models adapted to the prediction of admixed individuals in presence of heterogeneous marker effects: Multi-group Admixed GBLUP Random Individual (MAGBLUP-RI) modeling the ancestry of alleles, and MAGBLUP Random Allele Effect (MAGBLUP-RAE) modeling group-specific distributions of allele effects. MAGBLUP-RI can estimate the segregation variance generated by admixture while MAGBLUP-RAE can disentangle the variability that is due to main allele effects from that due to group-specific deviation effects. Both models were evaluated for their genomic prediction accuracy using a maize panel including lines from the Dent and Flint groups, along with admixed individuals. Based on simulated traits, both models proved their efficiency to improve genomic prediction accuracy compared to standard GBLUP models. For real traits, a clear gain was observed at low marker densities whereas it became limited at high marker densities. The interest of including admixed individuals in multi-group training sets was confirmed using simulated traits, but was variable using real traits. Both MAGBLUP models and admixed individuals are of interest whenever there exist group-specific SNP allele effects.