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Genome‐wide association studies and prediction of 17 traits related to phenology, biomass and cell wall composition in the energy grass Miscanthus sinensis
Author(s) -
Slavov Gancho T.,
Nipper Rick,
Robson Paul,
Farrar Kerrie,
Allison Gordon G.,
Bosch Maurice,
CliftonBrown John C.,
Donnison Iain S.,
Jensen Elaine
Publication year - 2014
Publication title -
new phytologist
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.742
H-Index - 244
eISSN - 1469-8137
pISSN - 0028-646X
DOI - 10.1111/nph.12621
Subject(s) - biology , genome wide association study , population , genome , genetic association , genome size , miscanthus , phenotypic trait , selection (genetic algorithm) , genetics , single nucleotide polymorphism , computational biology , microbiology and biotechnology , genotype , phenotype , bioenergy , gene , biofuel , demography , sociology , artificial intelligence , computer science
Summary Increasing demands for food and energy require a step change in the effectiveness, speed and flexibility of crop breeding. Therefore, the aim of this study was to assess the potential of genome‐wide association studies ( GWAS s) and genomic selection (i.e. phenotype prediction from a genome‐wide set of markers) to guide fundamental plant science and to accelerate breeding in the energy grass Miscanthus . We generated over 100 000 single‐nucleotide variants ( SNV s) by sequencing restriction site‐associated DNA ( RAD ) tags in 138 Micanthus sinensis genotypes, and related SNV s to phenotypic data for 17 traits measured in a field trial. Confounding by population structure and relatedness was severe in naïve GWAS analyses, but mixed‐linear models robustly controlled for these effects and allowed us to detect multiple associations that reached genome‐wide significance. Genome‐wide prediction accuracies tended to be moderate to high (average of 0.57), but varied dramatically across traits. As expected, predictive abilities increased linearly with the size of the mapping population, but reached a plateau when the number of markers used for prediction exceeded 10 000–20 000, and tended to decline, but remain significant, when cross‐validations were performed across subpopulations. Our results suggest that the immediate implementation of genomic selection in Miscanthus breeding programs may be feasible.