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New Phytologist
Article . 2013 . Peer-reviewed
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New Phytologist
Article
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PubMed Central
Other literature type . 2014
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New Phytologist
Article . 2014
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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

Authors: John Clifton-Brown; Elaine Jensen; Gancho T. Slavov; Rick Nipper; Paul Robson; Kerrie Farrar; Maurice Bosch; +2 Authors

Genome‐wide association studies and prediction of 17 traits related to phenology, biomass and cell wall composition in the energy grass Miscanthus sinensis

Abstract

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 (GWASs) 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 (SNVs) by sequencing restriction site‐associated DNA (RAD) tags in 138 Micanthus sinensis genotypes, and related SNVs 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.

Related Organizations
Keywords

Genetic Markers, Principal Component Analysis, DNA, Plant, Genotype, Geography, Research, Population Dynamics, Restriction Mapping, Sequence Analysis, DNA, Poaceae, Polymorphism, Single Nucleotide, Phenotype, Quantitative Trait, Heritable, Cell Wall, Biomass, Genome, Plant, Genome-Wide Association Study

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    94
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
94
Top 10%
Top 10%
Top 10%
Green
hybrid