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AmelHap: Leveraging drone whole-genome sequence data to create a honey bee HapMap

dc.contributor.authorParejo Feuz, Melanie
dc.contributor.authorTalenti, A.
dc.contributor.authorRichardson, M.
dc.contributor.authorVignal, A.
dc.contributor.authorBarnett, M.
dc.contributor.authorWragg, D.
dc.date.accessioned2023-05-15T17:04:20Z
dc.date.available2023-05-15T17:04:20Z
dc.date.issued2023-04
dc.identifier.citationScientific Data 10(1) : (2023) // Article ID 198es_ES
dc.identifier.issn2052-4463
dc.identifier.urihttp://hdl.handle.net/10810/61123
dc.description.abstractHoney bee, Apis mellifera, drones are typically haploid, developing from an unfertilized egg, inheriting only their queen’s alleles and none from the many drones she mated with. Thus the ordered combination or ‘phase’ of alleles is known, making drones a valuable haplotype resource. We collated whole-genome sequence data for 1,407 drones, including 45 newly sequenced Scottish drones, collectively representing 19 countries, 8 subspecies and various hybrids. Following alignment to Amel_HAv3.1, variant calling and quality filtering, we retained 17.4 M high quality variants across 1,328 samples with a genotyping rate of 98.7%. We demonstrate the utility of this haplotype resource, AmelHap, for genotype imputation, returning >95% concordance when up to 61% of data is missing in haploids and up to 12% of data is missing in diploids. AmelHap will serve as a useful resource for the community for imputation from low-depth sequencing or SNP chip data, accurate phasing of diploids for association studies, and as a comprehensive reference panel for population genetic and evolutionary analyses.es_ES
dc.description.sponsorshipFor the purpose of open access, the author has applied a Creative Commons Attribution (CC BY) licence to any Author Accepted Manuscript version arising from this submission. This work was supported by a grant from the CB Dennis British Beekeepers’ Research Trust awarded to MB and DW, and through strategic investment funding to the Roslin Institute from the Biotechnology and Biological Sciences Research Council (BBS/E/D/30002276). MP was supported by a Basque Government grant (IT1233-19).es_ES
dc.language.isoenges_ES
dc.publisherNaturees_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.titleAmelHap: Leveraging drone whole-genome sequence data to create a honey bee HapMapes_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.holder© The Author(s) 2023. This 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 Cre- ative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not per- mitted 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 license, visit http://creativecommons.org/licenses/by/4.0/.es_ES
dc.rights.holderAtribución 3.0 España*
dc.relation.publisherversionhttps://www.nature.com/articles/s41597-023-02097-zes_ES
dc.identifier.doi10.1038/s41597-023-02097-z
dc.departamentoesGenética, antropología física y fisiología animales_ES
dc.departamentoeuGenetika,antropologia fisikoa eta animalien fisiologiaes_ES


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© The Author(s) 2023. This 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 Cre- ative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not per- mitted 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 license, visit http://creativecommons.org/licenses/by/4.0/.
Except where otherwise noted, this item's license is described as © The Author(s) 2023. This 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 Cre- ative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not per- mitted 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 license, visit http://creativecommons.org/licenses/by/4.0/.