Cargando…
Quantifying the contribution of sequence variants with regulatory and evolutionary significance to 34 bovine complex traits
Many genome variants shaping mammalian phenotype are hypothesized to regulate gene transcription and/or to be under selection. However, most of the evidence to support this hypothesis comes from human studies. Systematic evidence for regulatory and evolutionary signals contributing to complex traits...
Autores principales: | , , , , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
National Academy of Sciences
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6765237/ https://www.ncbi.nlm.nih.gov/pubmed/31501319 http://dx.doi.org/10.1073/pnas.1904159116 |
_version_ | 1783454526449123328 |
---|---|
author | Xiang, Ruidong van den Berg, Irene MacLeod, Iona M. Hayes, Benjamin J. Prowse-Wilkins, Claire P. Wang, Min Bolormaa, Sunduimijid Liu, Zhiqian Rochfort, Simone J. Reich, Coralie M. Mason, Brett A. Vander Jagt, Christy J. Daetwyler, Hans D. Lund, Mogens S. Chamberlain, Amanda J. Goddard, Michael E. |
author_facet | Xiang, Ruidong van den Berg, Irene MacLeod, Iona M. Hayes, Benjamin J. Prowse-Wilkins, Claire P. Wang, Min Bolormaa, Sunduimijid Liu, Zhiqian Rochfort, Simone J. Reich, Coralie M. Mason, Brett A. Vander Jagt, Christy J. Daetwyler, Hans D. Lund, Mogens S. Chamberlain, Amanda J. Goddard, Michael E. |
author_sort | Xiang, Ruidong |
collection | PubMed |
description | Many genome variants shaping mammalian phenotype are hypothesized to regulate gene transcription and/or to be under selection. However, most of the evidence to support this hypothesis comes from human studies. Systematic evidence for regulatory and evolutionary signals contributing to complex traits in a different mammalian model is needed. Sequence variants associated with gene expression (expression quantitative trait loci [eQTLs]) and concentration of metabolites (metabolic quantitative trait loci [mQTLs]) and under histone-modification marks in several tissues were discovered from multiomics data of over 400 cattle. Variants under selection and evolutionary constraint were identified using genome databases of multiple species. These analyses defined 30 sets of variants, and for each set, we estimated the genetic variance the set explained across 34 complex traits in 11,923 bulls and 32,347 cows with 17,669,372 imputed variants. The per-variant trait heritability of these sets across traits was highly consistent (r > 0.94) between bulls and cows. Based on the per-variant heritability, conserved sites across 100 vertebrate species and mQTLs ranked the highest, followed by eQTLs, young variants, those under histone-modification marks, and selection signatures. From these results, we defined a Functional-And-Evolutionary Trait Heritability (FAETH) score indicating the functionality and predicted heritability of each variant. In additional 7,551 cattle, the high FAETH-ranking variants had significantly increased genetic variances and genomic prediction accuracies in 3 production traits compared to the low FAETH-ranking variants. The FAETH framework combines the information of gene regulation, evolution, and trait heritability to rank variants, and the publicly available FAETH data provide a set of biological priors for cattle genomic selection worldwide. |
format | Online Article Text |
id | pubmed-6765237 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | National Academy of Sciences |
record_format | MEDLINE/PubMed |
spelling | pubmed-67652372019-10-02 Quantifying the contribution of sequence variants with regulatory and evolutionary significance to 34 bovine complex traits Xiang, Ruidong van den Berg, Irene MacLeod, Iona M. Hayes, Benjamin J. Prowse-Wilkins, Claire P. Wang, Min Bolormaa, Sunduimijid Liu, Zhiqian Rochfort, Simone J. Reich, Coralie M. Mason, Brett A. Vander Jagt, Christy J. Daetwyler, Hans D. Lund, Mogens S. Chamberlain, Amanda J. Goddard, Michael E. Proc Natl Acad Sci U S A PNAS Plus Many genome variants shaping mammalian phenotype are hypothesized to regulate gene transcription and/or to be under selection. However, most of the evidence to support this hypothesis comes from human studies. Systematic evidence for regulatory and evolutionary signals contributing to complex traits in a different mammalian model is needed. Sequence variants associated with gene expression (expression quantitative trait loci [eQTLs]) and concentration of metabolites (metabolic quantitative trait loci [mQTLs]) and under histone-modification marks in several tissues were discovered from multiomics data of over 400 cattle. Variants under selection and evolutionary constraint were identified using genome databases of multiple species. These analyses defined 30 sets of variants, and for each set, we estimated the genetic variance the set explained across 34 complex traits in 11,923 bulls and 32,347 cows with 17,669,372 imputed variants. The per-variant trait heritability of these sets across traits was highly consistent (r > 0.94) between bulls and cows. Based on the per-variant heritability, conserved sites across 100 vertebrate species and mQTLs ranked the highest, followed by eQTLs, young variants, those under histone-modification marks, and selection signatures. From these results, we defined a Functional-And-Evolutionary Trait Heritability (FAETH) score indicating the functionality and predicted heritability of each variant. In additional 7,551 cattle, the high FAETH-ranking variants had significantly increased genetic variances and genomic prediction accuracies in 3 production traits compared to the low FAETH-ranking variants. The FAETH framework combines the information of gene regulation, evolution, and trait heritability to rank variants, and the publicly available FAETH data provide a set of biological priors for cattle genomic selection worldwide. National Academy of Sciences 2019-09-24 2019-09-09 /pmc/articles/PMC6765237/ /pubmed/31501319 http://dx.doi.org/10.1073/pnas.1904159116 Text en Copyright © 2019 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/ https://creativecommons.org/licenses/by-nc-nd/4.0/This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | PNAS Plus Xiang, Ruidong van den Berg, Irene MacLeod, Iona M. Hayes, Benjamin J. Prowse-Wilkins, Claire P. Wang, Min Bolormaa, Sunduimijid Liu, Zhiqian Rochfort, Simone J. Reich, Coralie M. Mason, Brett A. Vander Jagt, Christy J. Daetwyler, Hans D. Lund, Mogens S. Chamberlain, Amanda J. Goddard, Michael E. Quantifying the contribution of sequence variants with regulatory and evolutionary significance to 34 bovine complex traits |
title | Quantifying the contribution of sequence variants with regulatory and evolutionary significance to 34 bovine complex traits |
title_full | Quantifying the contribution of sequence variants with regulatory and evolutionary significance to 34 bovine complex traits |
title_fullStr | Quantifying the contribution of sequence variants with regulatory and evolutionary significance to 34 bovine complex traits |
title_full_unstemmed | Quantifying the contribution of sequence variants with regulatory and evolutionary significance to 34 bovine complex traits |
title_short | Quantifying the contribution of sequence variants with regulatory and evolutionary significance to 34 bovine complex traits |
title_sort | quantifying the contribution of sequence variants with regulatory and evolutionary significance to 34 bovine complex traits |
topic | PNAS Plus |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6765237/ https://www.ncbi.nlm.nih.gov/pubmed/31501319 http://dx.doi.org/10.1073/pnas.1904159116 |
work_keys_str_mv | AT xiangruidong quantifyingthecontributionofsequencevariantswithregulatoryandevolutionarysignificanceto34bovinecomplextraits AT vandenbergirene quantifyingthecontributionofsequencevariantswithregulatoryandevolutionarysignificanceto34bovinecomplextraits AT macleodionam quantifyingthecontributionofsequencevariantswithregulatoryandevolutionarysignificanceto34bovinecomplextraits AT hayesbenjaminj quantifyingthecontributionofsequencevariantswithregulatoryandevolutionarysignificanceto34bovinecomplextraits AT prowsewilkinsclairep quantifyingthecontributionofsequencevariantswithregulatoryandevolutionarysignificanceto34bovinecomplextraits AT wangmin quantifyingthecontributionofsequencevariantswithregulatoryandevolutionarysignificanceto34bovinecomplextraits AT bolormaasunduimijid quantifyingthecontributionofsequencevariantswithregulatoryandevolutionarysignificanceto34bovinecomplextraits AT liuzhiqian quantifyingthecontributionofsequencevariantswithregulatoryandevolutionarysignificanceto34bovinecomplextraits AT rochfortsimonej quantifyingthecontributionofsequencevariantswithregulatoryandevolutionarysignificanceto34bovinecomplextraits AT reichcoraliem quantifyingthecontributionofsequencevariantswithregulatoryandevolutionarysignificanceto34bovinecomplextraits AT masonbretta quantifyingthecontributionofsequencevariantswithregulatoryandevolutionarysignificanceto34bovinecomplextraits AT vanderjagtchristyj quantifyingthecontributionofsequencevariantswithregulatoryandevolutionarysignificanceto34bovinecomplextraits AT daetwylerhansd quantifyingthecontributionofsequencevariantswithregulatoryandevolutionarysignificanceto34bovinecomplextraits AT lundmogenss quantifyingthecontributionofsequencevariantswithregulatoryandevolutionarysignificanceto34bovinecomplextraits AT chamberlainamandaj quantifyingthecontributionofsequencevariantswithregulatoryandevolutionarysignificanceto34bovinecomplextraits AT goddardmichaele quantifyingthecontributionofsequencevariantswithregulatoryandevolutionarysignificanceto34bovinecomplextraits |