Abstract
Key message
We were able to obtain good prediction accuracy in genomic selection with ~ 2000 GBS-derived SNPs. SNPs in genic regions did not improve prediction accuracy compared to SNPs in intergenic regions.
Abstract
Since genotyping can represent an important cost in genomic selection, it is important to minimize it without compromising the accuracy of predictions. The objectives of the present study were to explore how a decrease in the unit cost of genotyping impacted: (1) the number of single nucleotide polymorphism (SNP) markers; (2) the accuracy of the resulting genotypic data; (3) the extent of coverage on both physical and genetic maps; and (4) the prediction accuracy (PA) for six important traits in barley. Variations on the genotyping by sequencing protocol were used to generate 16 SNP sets ranging from ~ 500 to ~ 35,000 SNPs. The accuracy of SNP genotypes fluctuated between 95 and 99%. Marker distribution on the physical map was highly skewed toward the terminal regions, whereas a fairly uniform coverage of the genetic map was achieved with all but the smallest set of SNPs. We estimated the PA using three statistical models capturing (or not) the epistatic effect; the one modeling both additivity and epistasis was selected as the best model. The PA obtained with the different SNP sets was measured and found to remain stable, except with the smallest set, where a significant decrease was observed. Finally, we examined if the localization of SNP loci (genic vs. intergenic) affected the PA. No gain in PA was observed using SNPs located in genic regions. In summary, we found that there is considerable scope for decreasing the cost of genotyping in barley (to capture ~ 2000 SNPs) without loss of PA.
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This study was funded jointly by the Natural Sciences and Engineering Research Council of Canada and by Céréla Inc. through a Collaborative Research and Development grant (RDCPJ 470998-14), The funders had no role in study design, data collection and analysis or preparation of the manuscript. We are grateful to Martin Lacroix, Suzanne Marchand and Eric Fournier (Université Laval), Annie Archambault and Samuel Ostiguy (Céréla) as well as the Biometrics and Statistics Unit (CIMMYT) for their assistance with various aspects of this work.
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Abed, A., Pérez-Rodríguez, P., Crossa, J. et al. When less can be better: How can we make genomic selection more cost-effective and accurate in barley?. Theor Appl Genet 131, 1873–1890 (2018). https://doi.org/10.1007/s00122-018-3120-8
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DOI: https://doi.org/10.1007/s00122-018-3120-8