Please use this identifier to cite or link to this item: http://hdl.handle.net/10261/236068
Share/Export:
logo share SHARE BASE
Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL | DATACITE
Title

A fully integrated machine learning scan of selection in the chimpanzee genome

AuthorsNye, Jessica; Mondal, Mayukh CSIC ORCID; Bertranpetit, Jaume CSIC ORCID ; Laayouni, Hafid CSIC ORCID
Issue Date3-Sep-2020
PublisherOxford University Press
CitationNAR Genomics and Bioinformatics 2(3): lqaa061 (2020)
AbstractAfter diverging, each chimpanzee subspecies has been the target of unique selective pressures. Here, we employ a machine learning approach to classify regions as under positive selection or neutrality genome-wide. The regions determined to be under selection reflect the unique demographic and adaptive history of each subspecies. The results indicate that effective population size is important for determining the proportion of the genome under positive selection. The chimpanzee subspecies share signals of selection in genes associated with immunity and gene regulation. With these results, we have created a selection map for each population that can be displayed in a genome browser (www.hsb.upf.edu/chimp_browser). This study is the first to use a detailed demographic history and machine learning to map selection genome-wide in chimpanzee. The chimpanzee selection map will improve our understanding of the impact of selection on closely related subspecies and will empower future studies of chimpanzee.
Publisher version (URL)http://dx.doi.org/10.1093/nargab/lqaa061
URIhttp://hdl.handle.net/10261/236068
Identifiersdoi: 10.1093/nargab/lqaa061
e-issn: 2631-9268
Appears in Collections:(IBE) Artículos

Files in This Item:
File Description SizeFormat
lqaa061.pdf1,54 MBAdobe PDFThumbnail
View/Open
Show full item record
Review this work

Page view(s)

44
checked on May 16, 2022

Download(s)

49
checked on May 16, 2022

Google ScholarTM

Check


WARNING: Items in Digital.CSIC are protected by copyright, with all rights reserved, unless otherwise indicated.