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Large-scale association study on daily weight gain in pigs reveals overlap of genetic factors for growth in humans

BACKGROUND: Imputation from genotyping array to whole-genome sequence variants using resequencing of representative reference populations enhances our ability to map genetic factors affecting complex phenotypes in livestock species. The accumulation of knowledge about gene function in human and labo...

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Autores principales: Cai, Zexi, Christensen, Ole Fredslund, Lund, Mogens Sandø, Ostersen, Tage, Sahana, Goutam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8845347/
https://www.ncbi.nlm.nih.gov/pubmed/35168569
http://dx.doi.org/10.1186/s12864-022-08373-3
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author Cai, Zexi
Christensen, Ole Fredslund
Lund, Mogens Sandø
Ostersen, Tage
Sahana, Goutam
author_facet Cai, Zexi
Christensen, Ole Fredslund
Lund, Mogens Sandø
Ostersen, Tage
Sahana, Goutam
author_sort Cai, Zexi
collection PubMed
description BACKGROUND: Imputation from genotyping array to whole-genome sequence variants using resequencing of representative reference populations enhances our ability to map genetic factors affecting complex phenotypes in livestock species. The accumulation of knowledge about gene function in human and laboratory animals can provide substantial advantage for genomic research in livestock species. RESULTS: In this study, 201,388 pigs from three commercial Danish breeds genotyped with low to medium (8.5k to 70k) SNP arrays were imputed to whole genome sequence variants using a two-step approach. Both imputation steps achieved high accuracies, and in total this yielded 26,447,434 markers on 18 autosomes. The average estimated imputation accuracy of markers with minor allele frequency ≥ 0.05 was 0.94. To overcome the memory consumption of running genome-wide association study (GWAS) for each breed, we performed within-breed subpopulation GWAS then within-breed meta-analysis for average daily weight gain (ADG), followed by a multi-breed meta-analysis of GWAS summary statistics. We identified 15 quantitative trait loci (QTL). Our post-GWAS analysis strategy to prioritize of candidate genes including information like gene ontology, mammalian phenotype database, differential expression gene analysis of high and low feed efficiency pig and human GWAS catalog for height, obesity, and body mass index, we proposed MRAP2, LEPROT, PMAIP1, ENSSSCG00000036234, BMP2, ELFN1, LIG4 and FAM155A as the candidate genes with biological support for ADG in pigs. CONCLUSION: Our post-GWAS analysis strategy helped to identify candidate genes not just by distance to the lead SNP but also by multiple sources of biological evidence. Besides, the identified QTL overlap with genes which are known for their association with human growth-related traits. The GWAS with this large data set showed the power to map the genetic factors associated with ADG in pigs and have added to our understanding of the genetics of growth across mammalian species. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12864-022-08373-3.
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spelling pubmed-88453472022-02-16 Large-scale association study on daily weight gain in pigs reveals overlap of genetic factors for growth in humans Cai, Zexi Christensen, Ole Fredslund Lund, Mogens Sandø Ostersen, Tage Sahana, Goutam BMC Genomics Research BACKGROUND: Imputation from genotyping array to whole-genome sequence variants using resequencing of representative reference populations enhances our ability to map genetic factors affecting complex phenotypes in livestock species. The accumulation of knowledge about gene function in human and laboratory animals can provide substantial advantage for genomic research in livestock species. RESULTS: In this study, 201,388 pigs from three commercial Danish breeds genotyped with low to medium (8.5k to 70k) SNP arrays were imputed to whole genome sequence variants using a two-step approach. Both imputation steps achieved high accuracies, and in total this yielded 26,447,434 markers on 18 autosomes. The average estimated imputation accuracy of markers with minor allele frequency ≥ 0.05 was 0.94. To overcome the memory consumption of running genome-wide association study (GWAS) for each breed, we performed within-breed subpopulation GWAS then within-breed meta-analysis for average daily weight gain (ADG), followed by a multi-breed meta-analysis of GWAS summary statistics. We identified 15 quantitative trait loci (QTL). Our post-GWAS analysis strategy to prioritize of candidate genes including information like gene ontology, mammalian phenotype database, differential expression gene analysis of high and low feed efficiency pig and human GWAS catalog for height, obesity, and body mass index, we proposed MRAP2, LEPROT, PMAIP1, ENSSSCG00000036234, BMP2, ELFN1, LIG4 and FAM155A as the candidate genes with biological support for ADG in pigs. CONCLUSION: Our post-GWAS analysis strategy helped to identify candidate genes not just by distance to the lead SNP but also by multiple sources of biological evidence. Besides, the identified QTL overlap with genes which are known for their association with human growth-related traits. The GWAS with this large data set showed the power to map the genetic factors associated with ADG in pigs and have added to our understanding of the genetics of growth across mammalian species. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12864-022-08373-3. BioMed Central 2022-02-15 /pmc/articles/PMC8845347/ /pubmed/35168569 http://dx.doi.org/10.1186/s12864-022-08373-3 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Cai, Zexi
Christensen, Ole Fredslund
Lund, Mogens Sandø
Ostersen, Tage
Sahana, Goutam
Large-scale association study on daily weight gain in pigs reveals overlap of genetic factors for growth in humans
title Large-scale association study on daily weight gain in pigs reveals overlap of genetic factors for growth in humans
title_full Large-scale association study on daily weight gain in pigs reveals overlap of genetic factors for growth in humans
title_fullStr Large-scale association study on daily weight gain in pigs reveals overlap of genetic factors for growth in humans
title_full_unstemmed Large-scale association study on daily weight gain in pigs reveals overlap of genetic factors for growth in humans
title_short Large-scale association study on daily weight gain in pigs reveals overlap of genetic factors for growth in humans
title_sort large-scale association study on daily weight gain in pigs reveals overlap of genetic factors for growth in humans
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8845347/
https://www.ncbi.nlm.nih.gov/pubmed/35168569
http://dx.doi.org/10.1186/s12864-022-08373-3
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