Evidence map›Paper›PMID 22960214›Full record

ArticleGenetics2012

Limited evidence for classic selective sweeps in African populations.

Julie M Granka, Brenna M Henn, Christopher R Gignoux, Jeffrey M Kidd, Carlos D Bustamante, Marcus W Feldman

Abstract read
In one paragraph

Article in Genetics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
51citing papers in PubMed, 1 pooled it
–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

51 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Genomic evidence for shared common ancestry of East African hunting-gathering populations and insights into local adaptation.Proceedings of the National Academy of Sciences of the United States of America · 2019
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  9. Digital Image Processing to Detect Adaptive Evolution.Molecular biology and evolution · 2024
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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

6 authors.

Julie M GrankaDepartment of Biology, Stanford University, Stanford, California 94305, USA. jgranka@stanford.edu
Brenna M Henn
Christopher R Gignoux
Jeffrey M Kidd
Carlos D Bustamante
Marcus W Feldman

Funding

INSTITUTIONAL TRAINING GRANT IN GENOME SCIENCET32HG000044 · NHGRI · STANFORD UNIVERSITY · PI MICHAEL P. SNYDER · 1995 to 2026
$32.2M
PHARMACEUTICAL SCIENCES AND PHARMACOGENOMICST32GM007175 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI AHITUV, NADAV, KROETZ, DEANNA L · 1985 to 2021
$7.1M
Population Genetic Inferences From Dense Genotype DataR01HG003229 · NHGRI · CORNELL UNIVERSITY ITHACA · PI BUSTAMANTE, CARLOS DANIEL, CLARK, ANDREW G · 2004 to 2013
$4.8M
POPULATION GENETICS THEORYR01GM028016 · NIGMS · STANFORD UNIVERSITY · PI FELDMAN, MARCUS W · 1985 to 2010
$2.5M
NHGRI NIH HHS R01 HG003229NHGRI NIH HHS R01HG003229NHGRI NIH HHS T32 HG000044NHGRI NIH HHS T32HG000044NIGMS NIH HHS GM28016NIGMS NIH HHS R01 GM028016NIGMS NIH HHS T32 GM007175
6 · The paper itself

Abstract

While hundreds of loci have been identified as reflecting strong-positive selection in human populations, connections between candidate loci and specific selective pressures often remain obscure. This study investigates broader patterns of selection in African populations, which are underrepresented despite their potential to offer key insights into human adaptation. We scan for hard selective sweeps using several haplotype and allele-frequency statistics with a data set of nearly 500,000 genome-wide single-nucleotide polymorphisms in 12 highly diverged African populations that span a range of environments and subsistence strategies. We find that positive selection does not appear to be a strong determinant of allele-frequency differentiation among these African populations. Haplotype statistics do identify putatively selected regions that are shared across African populations. However, as assessed by extensive simulations, patterns of haplotype sharing between African populations follow neutral expectations and suggest that tails of the empirical distributions contain false-positive signals. After highlighting several genomic regions where positive selection can be inferred with higher confidence, we use a novel method to identify biological functions enriched among populations' empirical tail genomic windows, such as immune response in agricultural groups. In general, however, it seems that current methods for selection scans are poorly suited to populations that, like the African populations in this study, are affected by ascertainment bias and have low levels of linkage disequilibrium, possibly old selective sweeps, and potentially reduced phasing accuracy. Additionally, population history can confound the interpretation of selection statistics, suggesting that greater care is needed in attributing broad genetic patterns to human adaptation.

Indexed as

Selection, GeneticBlack PeopleCluster AnalysisComputer SimulationGenetics, PopulationHaplotypesHumansModels, GeneticPolymorphism, Single Nucleotide

Identifiers

PMID22960214
PMCPMC3522151

What OpenQuestion holds

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Registered trials

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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.