Dataset Information

Genome-wide prediction methods in highly diverse and heterozygous species: proof-of-concept through simulation in grapevine.

ABSTRACT: Nowadays, genome-wide association studies (GWAS) and genomic selection (GS) methods which use genome-wide marker data for phenotype prediction are of much potential interest in plant breeding. However, to our knowledge, no studies have been performed yet on the predictive ability of these methods for structured traits when using training populations with high levels of genetic diversity. Such an example of a highly heterozygous, perennial species is grapevine. The present study compares the accuracy of models based on GWAS or GS alone, or in combination, for predicting simple or complex traits, linked or not with population structure. In order to explore the relevance of these methods in this context, we performed simulations using approx 90,000 SNPs on a population of 3,000 individuals structured into three groups and corresponding to published diversity grapevine data. To estimate the parameters of the prediction models, we defined four training populations of 1,000 individuals, corresponding to these three groups and a core collection. Finally, to estimate the accuracy of the models, we also simulated four breeding populations of 200 individuals. Although prediction accuracy was low when breeding populations were too distant from the training populations, high accuracy levels were obtained using the sole core-collection as training population. The highest prediction accuracy was obtained (up to 0.9) using the combined GWAS-GS model. We thus recommend using the combined prediction model and a core-collection as training population for grapevine breeding or for other important economic crops with the same characteristics.

SUBMITTER: Fodor A

PROVIDER: S-EPMC4217727 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Genome-wide prediction methods in highly diverse and heterozygous species: proof-of-concept through simulation in grapevine.

Fodor Agota A Segura Vincent V Denis Marie M Neuenschwander Samuel S Fournier-Level Alexandre A Chatelet Philippe P Homa Félix Abdel Aziz FA Lacombe Thierry T This Patrice P Le Cunff Loic L

PloS one 20141103 11

Nowadays, genome-wide association studies (GWAS) and genomic selection (GS) methods which use genome-wide marker data for phenotype prediction are of much potential interest in plant breeding. However, to our knowledge, no studies have been performed yet on the predictive ability of these methods for structured traits when using training populations with high levels of genetic diversity. Such an example of a highly heterozygous, perennial species is grapevine. The present study compares the accu ...[more]

PMID: 25365338

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Dataset Information

Genome-wide prediction methods in highly diverse and heterozygous species: proof-of-concept through simulation in grapevine.

Publications

Genome-wide prediction methods in highly diverse and heterozygous species: proof-of-concept through simulation in grapevine.

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