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dc.contributor.authorGozalo-Marcilla, Miguel
dc.contributor.authorBuntjer, Jaap
dc.contributor.authorJohnsson, Martin
dc.contributor.authorBatista, Lorena
dc.contributor.authorDiez, Federico
dc.contributor.authorWerner, Christian R.
dc.contributor.authorChen, Ching-Yi
dc.contributor.authorGorjanc, Gregor
dc.contributor.authorMellanby, Richard J.
dc.contributor.authorHickey, John M.
dc.contributor.authorRos Freixedes, Roger
dc.date.accessioned2021-10-01T09:04:17Z
dc.date.available2021-10-01T09:04:17Z
dc.date.issued2021-09-22
dc.identifier.issn0999-193X
dc.identifier.urihttp://hdl.handle.net/10459.1/71973
dc.description.abstractBackground: 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.
dc.description.sponsorshipThe 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.
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherBMC
dc.relation.isformatofReproducció del document publicat a: https://doi.org/10.1186/s12711-021-00671-w
dc.relation.ispartofGenetics Selection Evolution, 2021, article núm. 76
dc.rightscc-by (c) Gozalo-Marcilla, Miguel et al., 2021
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es
dc.subject.otherPorcs
dc.subject.otherGenètica animal
dc.subject.otherGenètica veterinària
dc.titleGenetic architecture and major genes for backfat thickness in pig lines of diverse genetic backgrounds
dc.typeinfo:eu-repo/semantics/article
dc.date.updated2021-10-01T09:04:17Z
dc.identifier.idgrec031598
dc.type.versioninfo:eu-repo/semantics/publishedVersion
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.identifier.doihttps://doi.org/10.1186/s12711-021-00671-w


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cc-by (c) Gozalo-Marcilla, Miguel et al., 2021
Except where otherwise noted, this item's license is described as cc-by (c) Gozalo-Marcilla, Miguel et al., 2021