Genetic architecture and major genes for backfat thickness in pig lines of diverse genetic backgrounds

Background: Backfat thickness is an important carcass composition trait for pork production and is commonly included in swine breeding programmes. In this paper, we report the results of a large genome-wide association study for backfat thickness using data from eight lines of diverse genetic backgr...

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Autores: Gozalo-Marcilla, Miguel, Buntjer, Jaap, Johnsson, Martin, Batista, Lorena, Diez, Federico, Werner, Christian R., Chen, Ching-Yi, Gorjanc, Gregor, Mellanby, Richard J., Hickey, John M., Ros Freixedes, Roger
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2021
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10459.1/71973
Acceso en línea:https://doi.org/10.1186/s12711-021-00671-w
http://hdl.handle.net/10459.1/71973
Access Level:acceso abierto
Palabra clave:Porcs
Genètica animal
Genètica veterinària
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spelling Genetic architecture and major genes for backfat thickness in pig lines of diverse genetic backgroundsGozalo-Marcilla, MiguelBuntjer, JaapJohnsson, MartinBatista, LorenaDiez, FedericoWerner, Christian R.Chen, Ching-YiGorjanc, GregorMellanby, Richard J.Hickey, John M.Ros Freixedes, RogerPorcsGenètica animalGenètica veterinàriaBackground: Backfat thickness is an important carcass composition trait for pork production and is commonly included in swine breeding programmes. In this paper, we report the results of a large genome-wide association study for backfat thickness using data from eight lines of diverse genetic backgrounds. Methods: Data comprised 275,590 pigs from eight lines with diverse genetic backgrounds (breeds included Large White, Landrace, Pietrain, Hampshire, Duroc, and synthetic lines) genotyped and imputed for 71,324 single-nucleotide polymorphisms (SNPs). For each line, we estimated SNP associations using a univariate linear mixed model that accounted for genomic relationships. SNPs with significant associations were identified using a threshold of p < 10-6 and used to define genomic regions of interest. The proportion of genetic variance explained by a genomic region was estimated using a ridge regression model. Results: We found significant associations with backfat thickness for 264 SNPs across 27 genomic regions. Six genomic regions were detected in three or more lines. The average estimate of the SNP-based heritability was 0.48, with estimates by line ranging from 0.30 to 0.58. The genomic regions jointly explained from 3.2 to 19.5% of the additive genetic variance of backfat thickness within a line. Individual genomic regions explained up to 8.0% of the additive genetic variance of backfat thickness within a line. Some of these 27 genomic regions also explained up to 1.6% of the additive genetic variance in lines for which the genomic region was not statistically significant. We identified 64 candidate genes with annotated functions that can be related to fat metabolism, including well-studied genes such as MC4R, IGF2, and LEPR, and more novel candidate genes such as DHCR7, FGF23, MEDAG, DGKI, and PTN. Conclusions: Our results confirm the polygenic architecture of backfat thickness and the role of genes involved in energy homeostasis, adipogenesis, fatty acid metabolism, and insulin signalling pathways for fat deposition in pigs. The results also suggest that several less well-understood metabolic pathways contribute to backfat development, such as those of phosphate, calcium, and vitamin D homeostasis.The authors acknowledge the financial support from the BBSRC ISPG to The Roslin Institute (BBS/E/D/30002275), from Genus plc, Innovate UK (grant 102271), and from grant numbers BB/N004736/1, BB/N015339/1, BB/ L020467/1, and BB/M009254/1. MJ acknowledges financial support from the Swedish Research Council for Sustainable Development Formas Dnr 2016-01386.BMC2021202120212021info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://doi.org/10.1186/s12711-021-00671-whttp://hdl.handle.net/10459.1/71973http://hdl.handle.net/10459.1/71973reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésReproducció del document publicat a: https://doi.org/10.1186/s12711-021-00671-wGenetics Selection Evolution, 2021, article núm. 76cc-by (c) Gozalo-Marcilla, Miguel et al., 2021info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/3.0/esoai:recercat.cat:10459.1/719732026-05-29T05:05:01Z
dc.title.none.fl_str_mv Genetic architecture and major genes for backfat thickness in pig lines of diverse genetic backgrounds
title Genetic architecture and major genes for backfat thickness in pig lines of diverse genetic backgrounds
spellingShingle Genetic architecture and major genes for backfat thickness in pig lines of diverse genetic backgrounds
Gozalo-Marcilla, Miguel
Porcs
Genètica animal
Genètica veterinària
title_short Genetic architecture and major genes for backfat thickness in pig lines of diverse genetic backgrounds
title_full Genetic architecture and major genes for backfat thickness in pig lines of diverse genetic backgrounds
title_fullStr Genetic architecture and major genes for backfat thickness in pig lines of diverse genetic backgrounds
title_full_unstemmed Genetic architecture and major genes for backfat thickness in pig lines of diverse genetic backgrounds
title_sort Genetic architecture and major genes for backfat thickness in pig lines of diverse genetic backgrounds
dc.creator.none.fl_str_mv Gozalo-Marcilla, Miguel
Buntjer, Jaap
Johnsson, Martin
Batista, Lorena
Diez, Federico
Werner, Christian R.
Chen, Ching-Yi
Gorjanc, Gregor
Mellanby, Richard J.
Hickey, John M.
Ros Freixedes, Roger
author Gozalo-Marcilla, Miguel
author_facet Gozalo-Marcilla, Miguel
Buntjer, Jaap
Johnsson, Martin
Batista, Lorena
Diez, Federico
Werner, Christian R.
Chen, Ching-Yi
Gorjanc, Gregor
Mellanby, Richard J.
Hickey, John M.
Ros Freixedes, Roger
author_role author
author2 Buntjer, Jaap
Johnsson, Martin
Batista, Lorena
Diez, Federico
Werner, Christian R.
Chen, Ching-Yi
Gorjanc, Gregor
Mellanby, Richard J.
Hickey, John M.
Ros Freixedes, Roger
author2_role author
author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Porcs
Genètica animal
Genètica veterinària
topic Porcs
Genètica animal
Genètica veterinària
description Background: Backfat thickness is an important carcass composition trait for pork production and is commonly included in swine breeding programmes. In this paper, we report the results of a large genome-wide association study for backfat thickness using data from eight lines of diverse genetic backgrounds. Methods: Data comprised 275,590 pigs from eight lines with diverse genetic backgrounds (breeds included Large White, Landrace, Pietrain, Hampshire, Duroc, and synthetic lines) genotyped and imputed for 71,324 single-nucleotide polymorphisms (SNPs). For each line, we estimated SNP associations using a univariate linear mixed model that accounted for genomic relationships. SNPs with significant associations were identified using a threshold of p < 10-6 and used to define genomic regions of interest. The proportion of genetic variance explained by a genomic region was estimated using a ridge regression model. Results: We found significant associations with backfat thickness for 264 SNPs across 27 genomic regions. Six genomic regions were detected in three or more lines. The average estimate of the SNP-based heritability was 0.48, with estimates by line ranging from 0.30 to 0.58. The genomic regions jointly explained from 3.2 to 19.5% of the additive genetic variance of backfat thickness within a line. Individual genomic regions explained up to 8.0% of the additive genetic variance of backfat thickness within a line. Some of these 27 genomic regions also explained up to 1.6% of the additive genetic variance in lines for which the genomic region was not statistically significant. We identified 64 candidate genes with annotated functions that can be related to fat metabolism, including well-studied genes such as MC4R, IGF2, and LEPR, and more novel candidate genes such as DHCR7, FGF23, MEDAG, DGKI, and PTN. Conclusions: Our results confirm the polygenic architecture of backfat thickness and the role of genes involved in energy homeostasis, adipogenesis, fatty acid metabolism, and insulin signalling pathways for fat deposition in pigs. The results also suggest that several less well-understood metabolic pathways contribute to backfat development, such as those of phosphate, calcium, and vitamin D homeostasis.
publishDate 2021
dc.date.none.fl_str_mv 2021
2021
2021
2021
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://doi.org/10.1186/s12711-021-00671-w
http://hdl.handle.net/10459.1/71973
http://hdl.handle.net/10459.1/71973
url https://doi.org/10.1186/s12711-021-00671-w
http://hdl.handle.net/10459.1/71973
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Reproducció del document publicat a: https://doi.org/10.1186/s12711-021-00671-w
Genetics Selection Evolution, 2021, article núm. 76
dc.rights.none.fl_str_mv cc-by (c) Gozalo-Marcilla, Miguel et al., 2021
info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/3.0/es
rights_invalid_str_mv cc-by (c) Gozalo-Marcilla, Miguel et al., 2021
http://creativecommons.org/licenses/by/3.0/es
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv BMC
publisher.none.fl_str_mv BMC
dc.source.none.fl_str_mv reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
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collection Recercat. Dipósit de la Recerca de Catalunya
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