Rapid identification and interpretation of gene-environment associations using the new R.SamBada landscape genomics pipeline.


Journal

Molecular ecology resources
ISSN: 1755-0998
Titre abrégé: Mol Ecol Resour
Pays: England
ID NLM: 101465604

Informations de publication

Date de publication:
Sep 2019
Historique:
received: 20 03 2019
revised: 10 05 2019
accepted: 13 05 2019
pubmed: 29 5 2019
medline: 18 1 2020
entrez: 29 5 2019
Statut: ppublish

Résumé

samβada is a genome-environment association software, designed to search for signatures of local adaptation. However, pre- and postprocessing of data can be labour-intensive, preventing wider uptake of the method. We have now developed R.SamBada, an r-package providing a pipeline for landscape genomic analysis based on samβada, spanning from the retrieval of environmental conditions at sampling locations to gene annotation using the Ensembl genome browser. As a result, R.SamBada standardizes the landscape genomics pipeline and eases the search for candidate genes of local adaptation, enhancing reproducibility of landscape genomic studies. The efficiency and power of the pipeline is illustrated using two examples: sheep populations from Morocco with no evident population structure and Lidia cattle from Spain displaying population substructuring. In both cases, R.SamBada enabled rapid identification and interpretation of candidate genes, which are further discussed in the light of local adaptation. The package is available in the r CRAN package repository and on GitHub (github.com/SolangeD/R.SamBada).

Identifiants

pubmed: 31136078
doi: 10.1111/1755-0998.13044
pmc: PMC6790591
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1355-1365

Subventions

Organisme : FACCE ERA-NET Plus
ID : ANR-14-JFAC-0002-01
Organisme : H2020 Marie Skłodowska-Curie Actions
ID : DLV-655100
Organisme : Biotechnology and Biological Sciences Research Council
ID : BB/M019276/1
Pays : United Kingdom
Organisme : FP7 Food, Agriculture and Fisheries, Biotechnology
ID : 244356

Commentaires et corrections

Type : CommentIn

Informations de copyright

© 2019 The Authors. Molecular Ecology Resources Published by John Wiley & Sons Ltd.

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Auteurs

Solange Duruz (S)

Laboratory of Geographic Information Systems (LASIG), School of Architecture, Civil and Environmental Engineering (ENAC), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.

Natalia Sevane (N)

Departamento de Producción Animal, Facultad de Veterinaria, Universidad Complutense de Madrid, Madrid, Spain.

Oliver Selmoni (O)

Laboratory of Geographic Information Systems (LASIG), School of Architecture, Civil and Environmental Engineering (ENAC), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.

Elia Vajana (E)

Laboratory of Geographic Information Systems (LASIG), School of Architecture, Civil and Environmental Engineering (ENAC), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.

Kevin Leempoel (K)

Department of Biology, Stanford University, Stanford, California.

Sylvie Stucki (S)

Laboratory of Geographic Information Systems (LASIG), School of Architecture, Civil and Environmental Engineering (ENAC), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.

Pablo Orozco-terWengel (P)

School of Biosciences, Cardiff University, Cardiff, Wales, UK.

Estelle Rochat (E)

Laboratory of Geographic Information Systems (LASIG), School of Architecture, Civil and Environmental Engineering (ENAC), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.

Susana Dunner (S)

Departamento de Producción Animal, Facultad de Veterinaria, Universidad Complutense de Madrid, Madrid, Spain.

Michael W Bruford (MW)

School of Biosciences, Cardiff University, Cardiff, Wales, UK.

Stéphane Joost (S)

Laboratory of Geographic Information Systems (LASIG), School of Architecture, Civil and Environmental Engineering (ENAC), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.

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Classifications MeSH