Evidence map›Paper›PMID 25849546›Full record

ArticlePloS one2015

Detection of convergent genome-wide signals of adaptation to tropical forests in humans.

Carlos Eduardo G Amorim, Josephine T Daub, Francisco M Salzano, Matthieu Foll, Laurent Excoffier

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
3.5field-weighted citation impact, top 7% of its field
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

17 citing papers in PubMed, 37 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Social ties in the Congo Basin: insights into tropical forest adaptation from BaYaka and their neighbours.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2022
    Review
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Review
  17. 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

5 authors at 5 institutions in 3 countries.

Carlos Eduardo G AmorimComputational and Molecular Population Genetics Laboratory, Institute of Ecology and Evolution, Berne, Switzerland; Swiss Institute of Bioinformatics, Lausanne, Switzerland; Departamento de Genética, Instituto de Biociências, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil; CAPES Foundation, Ministry of Education of Brazil, Brasília, Distrito Federal, Brazil.
Josephine T DaubComputational and Molecular Population Genetics Laboratory, Institute of Ecology and Evolution, Berne, Switzerland; Swiss Institute of Bioinformatics, Lausanne, Switzerland.
Francisco M SalzanoDepartamento de Genética, Instituto de Biociências, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil.
Matthieu FollSwiss Institute of Bioinformatics, Lausanne, Switzerland; School of Life Science, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland; Genetic Cancer Susceptibility Group, International Agency for Research on Cancer, Lyon, France.
Laurent ExcoffierComputational and Molecular Population Genetics Laboratory, Institute of Ecology and Evolution, Berne, Switzerland; Swiss Institute of Bioinformatics, Lausanne, Switzerland.
École Polytechnique Fédérale de Lausanne · CHMinistry of Education · BRSIB Swiss Institute of Bioinformatics · CHUniversidade Federal do Rio Grande do Sul · BRUniversity of Bern · CH

Funding

World Health Organization 001
6 · The paper itself

Abstract

Tropical forests are believed to be very harsh environments for human life. It is unclear whether human beings would have ever subsisted in those environments without external resources. It is therefore possible that humans have developed recent biological adaptations in response to specific selective pressures to cope with this challenge. To understand such biological adaptations we analyzed genome-wide SNP data under a Bayesian statistics framework, looking for outlier markers with an overly large extent of differentiation between populations living in a tropical forest, as compared to genetically related populations living outside the forest in Africa and the Americas. The most significant positive selection signals were found in genes related to lipid metabolism, the immune system, body development, and RNA Polymerase III transcription initiation. The results are discussed in the light of putative tropical forest selective pressures, namely food scarcity, high prevalence of pathogens, difficulty to move, and inefficient thermoregulation. Agreement between our results and previous studies on the pygmy phenotype, a putative prototype of forest adaptation, were found, suggesting that a few genetic regions previously described as associated with short stature may be evolving under similar positive selection in Africa and the Americas. In general, convergent evolution was less pervasive than local adaptation in one single continent, suggesting that Africans and Amerindians may have followed different routes to adapt to similar environmental selective pressures.

Indexed as

Genome, HumanGenome-Wide Association StudyPolymorphism, Single NucleotideRainforestAdaptation, PhysiologicalFemaleHumansMale

Identifiers

PMID25849546
PMCPMC4388690
OpenAlexW2058702699

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.