Pan-genomic open reading frames: A potential supplement of single nucleotide polymorphisms in estimation of heritability and genomic prediction

Zhengcao Li and Henner Simianer

PLOS Genetics, 2020, vol. 16, issue 8, 1-19

Abstract: Pan-genomic open reading frames (ORFs) potentially carry protein-coding gene or coding variant information in a population. In this study, we suggest that pan-genomic ORFs are promising to be utilized in estimation of heritability and genomic prediction. A Saccharomyces cerevisiae dataset with whole-genome SNPs, pan-genomic ORFs, and the copy numbers of those ORFs is used to test the effectiveness of ORF data as a predictor in three prediction models for 35 traits. Our results show that the ORF-based heritability can capture more genetic effects than SNP-based heritability for all traits. Compared to SNP-based genomic prediction (GBLUP), pan-genomic ORF-based genomic prediction (OBLUP) is distinctly more accurate for all traits, and the predictive abilities on average are more than doubled across all traits. For four traits, the copy number of ORF-based prediction(CBLUP) is more accurate than OBLUP. When using different numbers of isolates in training sets in ORF-based prediction, the predictive abilities for all traits increased as more isolates are added in the training sets, suggesting that with very large training sets the prediction accuracy will be in the range of the square root of the heritability. We conclude that pan-genomic ORFs have the potential to be a supplement of single nucleotide polymorphisms in estimation of heritability and genomic prediction.Author summary: The properties of single nucleotide polymorphisms (SNPs) as a main source of genetic variability for estimation of heritability and genomic prediction have been widely studied over the past years. This data type remarkably accelerated the development of medical diagnosis in human genetics and prediction of breeding values in livestock and crop breeding field. However, due to the inherent pitfalls of SNP-based prediction, e.g. imperfect LD between markers and causal variants, seeking new genomic datasets of causal variants has become imperative. Our study point out some of the superiorities of pan-genomic open reading frames as independent variables in estimation of heritability and genomic prediction.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pgen00:1008995

DOI: 10.1371/journal.pgen.1008995

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