Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/31438
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dc.contributor.authorGutierrez, Alejandro Pen_UK
dc.contributor.authorMatika, Oswalden_UK
dc.contributor.authorBean, Tim Pen_UK
dc.contributor.authorHouston, Ross Den_UK
dc.date.accessioned2020-07-15T00:01:32Z-
dc.date.available2020-07-15T00:01:32Z-
dc.date.issued2018en_UK
dc.identifier.other391en_UK
dc.identifier.urihttp://hdl.handle.net/1893/31438-
dc.description.abstractPacific oysters are a key aquaculture species globally, and genetic improvement via selective breeding is a major target. Genomic selection has the potential to expedite genetic gain for key target traits of a breeding program, but has not yet been evaluated in oyster. The recent development of SNP arrays for Pacific oyster (Crassostrea gigas) raises the opportunity to test genomic selection strategies for polygenic traits. In this study, a population of 820 oysters (comprising 23 full-sibling families) were genotyped using a medium density SNP array (23 K informative SNPs), and the genetic architecture of growth-related traits [shell height (SH), shell length (SL), and wet weight (WW)] was evaluated. Heritability was estimated to be moderate for the three traits (0.26 ± 0.06 for SH, 0.23 ± 0.06 for SL and 0.35 ± 0.05 for WW), and results of a GWAS indicated that the underlying genetic architecture was polygenic. Genomic prediction approaches were used to estimate breeding values for growth, and compared to pedigree based approaches. The accuracy of the genomic prediction models (GBLUP) outperformed the traditional pedigree approach (PBLUP) by ∼25% for SL and WW, and ∼30% for SH. Further, reduction in SNP marker density had little impact on prediction accuracy, even when density was reduced to a few hundred SNPs. These results suggest that the use of genomic selection in oyster breeding could offer benefits for the selection of breeding candidates to improve complex economic traits at relatively modest cost.en_UK
dc.language.isoenen_UK
dc.publisherFrontiers Media SAen_UK
dc.relationGutierrez AP, Matika O, Bean TP & Houston RD (2018) Genomic Selection for Growth Traits in Pacific Oyster (Crassostrea gigas): Potential of Low-Density Marker Panels for Breeding Value Prediction. Frontiers in Genetics, 9, Art. No.: 391. https://doi.org/10.3389/fgene.2018.00391en_UK
dc.rights© 2018 Gutierrez, Matika, Bean and Houston. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.en_UK
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_UK
dc.subjectgenomic selectionen_UK
dc.subjectPacific oysteren_UK
dc.subjectgrowthen_UK
dc.subjectGBLUPen_UK
dc.subjectSNP arrayen_UK
dc.titleGenomic Selection for Growth Traits in Pacific Oyster (Crassostrea gigas): Potential of Low-Density Marker Panels for Breeding Value Predictionen_UK
dc.typeJournal Articleen_UK
dc.identifier.doi10.3389/fgene.2018.00391en_UK
dc.identifier.pmid30283494en_UK
dc.citation.jtitleFrontiers in Geneticsen_UK
dc.citation.issn1664-8021en_UK
dc.citation.volume9en_UK
dc.citation.publicationstatusPublisheden_UK
dc.citation.peerreviewedRefereeden_UK
dc.type.statusVoR - Version of Recorden_UK
dc.contributor.funderNatural Environment Research Councilen_UK
dc.contributor.funderBiotechnology and Biological Sciences Research Councilen_UK
dc.contributor.funderBiotechnology and Biological Sciences Research Councilen_UK
dc.contributor.funderBiotechnology and Biological Sciences Research Councilen_UK
dc.citation.date19/09/2018en_UK
dc.contributor.affiliationRoslin Instituteen_UK
dc.contributor.affiliationRoslin Instituteen_UK
dc.contributor.affiliationWeymouth Laboratoryen_UK
dc.contributor.affiliationRoslin Instituteen_UK
dc.identifier.isiWOS:000445068200001en_UK
dc.identifier.scopusid2-s2.0-85055143232en_UK
dc.identifier.wtid1643543en_UK
dc.date.accepted2018-08-29en_UK
dc.date.filedepositdate2020-07-14en_UK
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