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Genetic relatedness and the ratio of subpopulation‐common alleles are related in genomic prediction across structured subpopulations in maize
Authors:Dongdong Li  Pingxi Wang  Riliang Gu  Junjie Fu  Zhenxiang Xu  Demar Lyle  Yunling Peng  Guoying Wang  Hongwei Zhang
Abstract:Genomic prediction (GP), which could predict the breeding value of crop plants genotyped with molecular markers, has been carried out in multiple species. Prediction accuracy (PA) of GP depends on various factors, including genetic relatedness and genetic basis. In this study, we examined the rationale for the low PA of GP when the training and validation populations were distinct using 170 temperate inbred lines and 210 tropical and subtropical inbred lines, respectively. All inbred lines were evaluated for 17 traits and genotyped with 550K high‐density markers. The results show that: (a) the influences of heritability and marker number on PA reflected variations in phenotypic variance captured by the genetic information; (b) the low PA of GP when the training and validation populations represent structured subpopulation is related to the ratio of subpopulation‐common alleles (RSCA) and the genetic relatedness between the two subpopulations; (c) RSCA and PA increased with the increase of genetic relatedness, suggesting that these three factors were related. Our findings would provide references when performing GP, and guidance when designing breeding populations.
Keywords:genetic relatedness  genomic best linear unbiased prediction  genomic prediction  prediction accuracy  subpopulation‐common allele
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