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CC BY-NC V4.0, Open Access
Journal article
Inference of gorilla demographic and selective history from whole-genome sequence data
Molecular biology and evolution, Vol.32(3), pp.600-612
03/2015
Handle:
https://hdl.handle.net/2376/113652
PMCID: PMC4327160
PMID: 25534031
Abstract
Although population-level genomic sequence data have been gathered extensively for humans, similar data from our closest living relatives are just beginning to emerge. Examination of genomic variation within great apes offers many opportunities to increase our understanding of the forces that have differentially shaped the evolutionary history of hominid taxa. Here, we expand upon the work of the Great Ape Genome Project by analyzing medium to high coverage whole-genome sequences from 14 western lowland gorillas (Gorilla gorilla gorilla), 2 eastern lowland gorillas (G. beringei graueri), and a single Cross River individual (G. gorilla diehli). We infer that the ancestors of western and eastern lowland gorillas diverged from a common ancestor approximately 261 ka, and that the ancestors of the Cross River population diverged from the western lowland gorilla lineage approximately 68 ka. Using a diffusion approximation approach to model the genome-wide site frequency spectrum, we infer a history of western lowland gorillas that includes an ancestral population expansion of 1.4-fold around 970 ka and a recent 5.6-fold contraction in population size 23 ka. The latter may correspond to a major reduction in African equatorial forests around the Last Glacial Maximum. We also analyze patterns of variation among western lowland gorillas to identify several genomic regions with strong signatures of recent selective sweeps. We find that processes related to taste, pancreatic and saliva secretion, sodium ion transmembrane transport, and cardiac muscle function are overrepresented in genomic regions predicted to have experienced recent positive selection.
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Details
- Title
- Inference of gorilla demographic and selective history from whole-genome sequence data
- Creators
- Kimberly F McManus - Department of Biology, Stanford University Department of Biomedical Informatics, Stanford UniversityJoanna L Kelley - Department of Genetics, Stanford University School of Biological Sciences, Washington State UniversityShiya Song - Department of Computational Medicine & Bioinformatics, University of MichiganKrishna R Veeramah - ARL Division of Biotechnology, University of ArizonaAugust E Woerner - ARL Division of Biotechnology, University of ArizonaLaurie S Stevison - Institute for Human Genetics, University of California San FranciscoOliver A Ryder - San Diego Zoo Institute for Conservation Research, San Diego Zoo Global, Escondido, CAGreat Ape Genome Project - Department of Epidemiology & Biostatistics, University of California San FranciscoJeffrey M Kidd - Department of Computational Medicine & Bioinformatics, University of Michigan Department of Human Genetics, University of Michigan jmkidd@med.umich.edu mfh@email.arizona.eduJeffrey D Wall - Institute for Human Genetics, University of California San FranciscoCarlos D Bustamante - Department of Genetics, Stanford UniversityMichael F Hammer - ARL Division of Biotechnology, University of Arizona jmkidd@med.umich.edu mfh@email.arizona.edu
- Publication Details
- Molecular biology and evolution, Vol.32(3), pp.600-612
- Academic Unit
- Kelley Lab; Biological Sciences, School of
- Publisher
- Oxford Univ Press; United States
- Number of pages
- 13
- Grant note
- T32 HG000044 / NHGRI NIH HHS T32 GM007276 / NIGMS NIH HHS
- Identifiers
- 99900547639201842
- Language
- English
- Resource Type
- Journal article