Genetic fingerprinting of salmon louse (Lepeophtheirus salmonis) populations in the North-East Atlantic using a random forest classification approach

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dc.contributor.author Jacobs, A.
dc.contributor.author De Noia, M.
dc.contributor.author Praebel, K.
dc.contributor.author Kanstad-Hanssen, O.
dc.contributor.author Paterno, M.
dc.contributor.author Jackson, D.
dc.contributor.author McGinnity, Philip
dc.contributor.author Sturm, A.
dc.contributor.author Elmer, K. R.
dc.contributor.author Llewellyn, M. S.
dc.date.accessioned 2018-02-20T13:24:11Z
dc.date.available 2018-02-20T13:24:11Z
dc.date.issued 2018
dc.identifier.citation Jacobs, A., De Noia, M., Praebel, K., Kanstad-Hanssen, Ø., Paterno, M., Jackson, D., McGinnity, P., Sturm, A., Elmer, K. R. and Llewellyn, M. S. (2018) 'Genetic fingerprinting of salmon louse (Lepeophtheirus salmonis) populations in the North-East Atlantic using a random forest classification approach', Scientific Reports, 8, 1203 (9pp). doi: 10.1038/s41598-018-19323-z en
dc.identifier.volume 8
dc.identifier.startpage 1
dc.identifier.endpage 9
dc.identifier.issn 2045-2322
dc.identifier.uri http://hdl.handle.net/10468/5489
dc.identifier.doi 10.1038/s41598-018-19323-z
dc.description.abstract Caligid sea lice represent a significant threat to salmonid aquaculture worldwide. Population genetic analyses have consistently shown minimal population genetic structure in North Atlantic Lepeophtheirus salmonis, frustrating efforts to track louse populations and improve targeted control measures. The aim of this study was to test the power of reduced representation library sequencing (IIb-RAD sequencing) coupled with random forest machine learning algorithms to define markers for fine-scale discrimination of louse populations. We identified 1286 robustly supported SNPs among four L. salmonis populations from Ireland, Scotland and Northern Norway. Only weak global structure was observed based on the full SNP dataset. The application of a random forest machine-learning algorithm identified 98 discriminatory SNPs that dramatically improved population assignment, increased global genetic structure and resulted in significant genetic population differentiation. A large proportion of SNPs found to be under directional selection were also identified to be highly discriminatory. Our data suggest that it is possible to discriminate between nearby L. salmonis populations given suitable marker selection approaches, and that such differences might have an adaptive basis. We discuss these data in light of sea lice adaption to anthropogenic and environmental pressures as well as novel approaches to track and predict sea louse dispersal. en
dc.description.sponsorship Research Councils UK (BB/N024028/; BB/L022923/1)
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.publisher Nature Publishing Group: en
dc.relation.uri https://www.nature.com/articles/s41598-018-19323-z
dc.rights © 2018, the Authors. Open Access 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 Creative 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 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 license, visit http://creativecommons.org/licenses/by/4.0/. en
dc.rights.uri http://creativecommons.org/licenses/by/4.0/
dc.subject Eel en
dc.subject Anguilla-rostrata en
dc.subject Sea Lice en
dc.subject Life-history en
dc.subject Wild en
dc.subject Differentiation en
dc.subject Resistance en
dc.subject Salinity en
dc.subject Ireland en
dc.subject Markers en
dc.subject Coasts en
dc.title Genetic fingerprinting of salmon louse (Lepeophtheirus salmonis) populations in the North-East Atlantic using a random forest classification approach en
dc.type Article (peer-reviewed) en
dc.internal.authorcontactother Philip Mcginnity, Biological, Earth & Environmental Sciences, University College Cork, Cork, Ireland. +353-21-490-3000 Email: p.mcginnity@ucc.ie en
dc.internal.availability Full text available en
dc.description.version Published Version en
dc.internal.rssid 424082677
dc.internal.rssid 424082677
dc.internal.wokid WOS:000417591100099
dc.contributor.funder FP7 People: Marie-Curie Actions
dc.contributor.funder Research Councils UK
dc.description.status Peer reviewed en
dc.identifier.journaltitle Scientific Reports en
dc.internal.IRISemailaddress p.mcginnity@ucc.ie en
dc.identifier.articleid 1203
dc.relation.project info:eu-repo/grantAgreement/EC/FP7::SP3::PEOPLE/302503/EU/Metacommunity dynamics of the fish surface mircobiome in health and disease: pathogens and probiotics/FISHPROBIO


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© 2018, the Authors. Open Access 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 Creative 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 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 license, visit http://creativecommons.org/licenses/by/4.0/. Except where otherwise noted, this item's license is described as © 2018, the Authors. Open Access 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 Creative 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 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 license, visit http://creativecommons.org/licenses/by/4.0/.
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