Evidence map›Paper›PMID 25534031›Full record

ArticleMolecular biology and evolution2015

Inference of gorilla demographic and selective history from whole-genome sequence data.

Kimberly F McManus, Joanna L Kelley, Shiya Song, Krishna R Veeramah, August E Woerner, Laurie S Stevison, Oliver A Ryder, Great Ape Genome Project, Jeffrey M Kidd, Jeffrey D Wall and 2 more

Abstract read
In one paragraph

Article in Molecular biology and evolution, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

30 citing papers in PubMed.

  1. Article
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  3. Article
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  5. Article
  6. Complete sequencing of ape genomes.bioRxiv : the preprint server for biology · 2024
    Article
  7. Article
  8. Ghost admixture in eastern gorillas.Nature ecology & evolution · 2023
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Population Genomics in the Great Apes.Methods in molecular biology (Clifton, N.J.) · 2020
    Article
  14. Detecting Positive Selection in Populations Using Genetic Data.Methods in molecular biology (Clifton, N.J.) · 2020
    Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Kimberly F McManusDepartment of Biology, Stanford University Department of Biomedical Informatics, Stanford University.
Joanna L KelleyDepartment of Genetics, Stanford University School of Biological Sciences, Washington State University.
Shiya SongDepartment of Computational Medicine & Bioinformatics, University of Michigan.
Krishna R VeeramahARL Division of Biotechnology, University of Arizona.
August E WoernerARL Division of Biotechnology, University of Arizona.
Laurie S StevisonInstitute for Human Genetics, University of California San Francisco.
Oliver A RyderSan Diego Zoo Institute for Conservation Research, San Diego Zoo Global, Escondido, CA.
Great Ape Genome ProjectDepartment of Epidemiology & Biostatistics, University of California San Francisco.
Jeffrey M KiddDepartment of Computational Medicine & Bioinformatics, University of Michigan Department of Human Genetics, University of Michigan jmkidd@med.umich.edu mfh@email.arizona.edu.
Jeffrey D WallInstitute for Human Genetics, University of California San Francisco.
Carlos D BustamanteDepartment of Genetics, Stanford University.
Michael F HammerARL Division of Biotechnology, University of Arizona jmkidd@med.umich.edu mfh@email.arizona.edu.

Funding

Supplement to Enhance Wellness and Resiliency in the Graduate EnvironmentT32GM007276 · NIGMS · STANFORD UNIVERSITY · PI MORRISON, ASHBY J. · 1985 to 2023
$32.9M
INSTITUTIONAL TRAINING GRANT IN GENOME SCIENCET32HG000044 · NHGRI · STANFORD UNIVERSITY · PI MICHAEL P. SNYDER · 1995 to 2026
$32.2M
NHGRI NIH HHS T32 HG000044NIGMS NIH HHS T32 GM007276
6 · The paper itself

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.

Indexed as

AnimalsGenetic FitnessGenomeGenome, HumanGenomicsGorilla gorillaHumansMetagenomicsSelection, Geneticgenomicsgorillasgreat apesnatural selection

Identifiers

PMID25534031
PMCPMC4327160

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LicenceCC BY-NC
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.