Genome-wide association studies and prediction of 17 traits related to phenology, biomass and cell wall composition in the energy grass Miscanthus sinensis
Article first published online: 6 DEC 2013
© 2013 The Authors. New Phytologist © 2013 New Phytologist Trust
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Volume 201, Issue 4, pages 1227–1239, March 2014
How to Cite
Slavov, G. T., Nipper, R., Robson, P., Farrar, K., Allison, G. G., Bosch, M., Clifton-Brown, J. C., Donnison, I. S. and Jensen, E. (2014), Genome-wide association studies and prediction of 17 traits related to phenology, biomass and cell wall composition in the energy grass Miscanthus sinensis. New Phytologist, 201: 1227–1239. doi: 10.1111/nph.12621
- Issue published online: 3 FEB 2014
- Article first published online: 6 DEC 2013
- Manuscript Accepted: 28 OCT 2013
- Manuscript Received: 16 AUG 2013
- Biosciences, Environment and Agriculture Alliance
- UK Biotechnology and Biological Sciences Research Council (BBSRC). Grant Numbers: BB/J0042/1, BB/K01711X/1
- genomic selection;
- genome-wide association studies (GWAS);
- Miscanthus sinensis ;
- molecular markers;
- single-nucleotide variants
- 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.