Abstract
Genome-wide association studies (GWAS) is one of the most popular methods of studying the genetic control of traits. This methodology has been intensely performed on inbred genotypes to identify causal variants. Nonetheless, the lack of covariance between the phenotype of inbred lines and their offspring in cross-pollinated species (such as maize) raises questions on the applicability of these findings in a hybrid breeding context. To address this topic, we incorporated previously reported parental lines GWAS information into the prediction of a low heritability trait in hybrids. This was done by marker-assisted selection based on significant markers identified in the lines and by genomic prediction having these markers as fixed effects. Additive-dominance GWAS of hybrids, a non-conventional procedure, was also performed for comparison purposes. Our results suggest that incorporating information from parental inbred lines GWAS led to decreases in the predictive ability of hybrids. Correspondingly, inbred lines and hybrids-based GWAS yielded different results. These findings do not invalidate GWAS on inbred lines for selection purposes, but mean that it may not be directly useful for hybrid breeding.
Highlights
Marker Assisted Selection (MAS; [1]) is a commonly used technique in plant breeding
Two genotypes were removed based on the low nitrogen tolerance index (LNTI) values
The results indicate that integrating genomic prediction (GP) and MAS (MAS|GBLUP and MAS|RKHS) under the studied scenario did not lead to any prediction improvements
Summary
Marker Assisted Selection (MAS; [1]) is a commonly used technique in plant breeding. This methodology has been reported to be most effective for selecting genomic regions that account for a relevant amount of genotypic variation in a population, often identified by QTL mapping. The inability to select for small-effect QTL is an important limitation of MAS [2,3]. In this sense, genomic prediction (GP; [4]), a whole-genome-based selection methodology, was proposed with the intent of capturing as much genetic variation as possible, regardless of QTL identification.
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