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Genomic prediction using low-coverage portable Nanopore sequencing
Most traits in livestock, crops and humans are polygenic, that is, a large number of loci contribute to genetic variation. Effects at these loci lie along a continuum ranging from common low-effect to rare high-effect variants that cumulatively contribute to the overall phenotype. Statistical method...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8673642/ https://www.ncbi.nlm.nih.gov/pubmed/34910782 http://dx.doi.org/10.1371/journal.pone.0261274 |
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author | Lamb, Harrison J. Hayes, Ben J. Randhawa, Imtiaz A. S. Nguyen, Loan T. Ross, Elizabeth M. |
author_facet | Lamb, Harrison J. Hayes, Ben J. Randhawa, Imtiaz A. S. Nguyen, Loan T. Ross, Elizabeth M. |
author_sort | Lamb, Harrison J. |
collection | PubMed |
description | Most traits in livestock, crops and humans are polygenic, that is, a large number of loci contribute to genetic variation. Effects at these loci lie along a continuum ranging from common low-effect to rare high-effect variants that cumulatively contribute to the overall phenotype. Statistical methods to calculate the effect of these loci have been developed and can be used to predict phenotypes in new individuals. In agriculture, these methods are used to select superior individuals using genomic breeding values; in humans these methods are used to quantitatively measure an individual’s disease risk, termed polygenic risk scores. Both fields typically use SNP array genotypes for the analysis. Recently, genotyping-by-sequencing has become popular, due to lower cost and greater genome coverage (including structural variants). Oxford Nanopore Technologies’ (ONT) portable sequencers have the potential to combine the benefits genotyping-by-sequencing with portability and decreased turn-around time. This introduces the potential for in-house clinical genetic disease risk screening in humans or calculating genomic breeding values on-farm in agriculture. Here we demonstrate the potential of the later by calculating genomic breeding values for four traits in cattle using low-coverage ONT sequence data and comparing these breeding values to breeding values calculated from SNP arrays. At sequencing coverages between 2X and 4X the correlation between ONT breeding values and SNP array-based breeding values was > 0.92 when imputation was used and > 0.88 when no imputation was used. With an average sequencing coverage of 0.5x the correlation between the two methods was between 0.85 and 0.92 using imputation, depending on the trait. This suggests that ONT sequencing has potential for in clinic or on-farm genomic prediction, however, further work to validate these findings in a larger population still remains. |
format | Online Article Text |
id | pubmed-8673642 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-86736422021-12-16 Genomic prediction using low-coverage portable Nanopore sequencing Lamb, Harrison J. Hayes, Ben J. Randhawa, Imtiaz A. S. Nguyen, Loan T. Ross, Elizabeth M. PLoS One Research Article Most traits in livestock, crops and humans are polygenic, that is, a large number of loci contribute to genetic variation. Effects at these loci lie along a continuum ranging from common low-effect to rare high-effect variants that cumulatively contribute to the overall phenotype. Statistical methods to calculate the effect of these loci have been developed and can be used to predict phenotypes in new individuals. In agriculture, these methods are used to select superior individuals using genomic breeding values; in humans these methods are used to quantitatively measure an individual’s disease risk, termed polygenic risk scores. Both fields typically use SNP array genotypes for the analysis. Recently, genotyping-by-sequencing has become popular, due to lower cost and greater genome coverage (including structural variants). Oxford Nanopore Technologies’ (ONT) portable sequencers have the potential to combine the benefits genotyping-by-sequencing with portability and decreased turn-around time. This introduces the potential for in-house clinical genetic disease risk screening in humans or calculating genomic breeding values on-farm in agriculture. Here we demonstrate the potential of the later by calculating genomic breeding values for four traits in cattle using low-coverage ONT sequence data and comparing these breeding values to breeding values calculated from SNP arrays. At sequencing coverages between 2X and 4X the correlation between ONT breeding values and SNP array-based breeding values was > 0.92 when imputation was used and > 0.88 when no imputation was used. With an average sequencing coverage of 0.5x the correlation between the two methods was between 0.85 and 0.92 using imputation, depending on the trait. This suggests that ONT sequencing has potential for in clinic or on-farm genomic prediction, however, further work to validate these findings in a larger population still remains. Public Library of Science 2021-12-15 /pmc/articles/PMC8673642/ /pubmed/34910782 http://dx.doi.org/10.1371/journal.pone.0261274 Text en © 2021 Lamb et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Lamb, Harrison J. Hayes, Ben J. Randhawa, Imtiaz A. S. Nguyen, Loan T. Ross, Elizabeth M. Genomic prediction using low-coverage portable Nanopore sequencing |
title | Genomic prediction using low-coverage portable Nanopore sequencing |
title_full | Genomic prediction using low-coverage portable Nanopore sequencing |
title_fullStr | Genomic prediction using low-coverage portable Nanopore sequencing |
title_full_unstemmed | Genomic prediction using low-coverage portable Nanopore sequencing |
title_short | Genomic prediction using low-coverage portable Nanopore sequencing |
title_sort | genomic prediction using low-coverage portable nanopore sequencing |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8673642/ https://www.ncbi.nlm.nih.gov/pubmed/34910782 http://dx.doi.org/10.1371/journal.pone.0261274 |
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