Evidence map›Paper›PMID 20500215›Full record

ArticleEvolution; international journal of organic evolution2010

Integrating evolutionary and functional approaches to infer adaptation at specific loci.

Jay F Storz, Christopher W Wheat

Abstract read
In one paragraph

Article in Evolution; international journal of organic evolution, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers.

0numbers the graph read from it
0cells of the map it votes in
50citing 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

50 citing papers in PubMed.

  1. Article
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  6. Highly Replicated Evolution of Parapatric Ecotypes.Molecular biology and evolution · 2021
    Article
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  12. Review
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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

2 authors.

Jay F StorzSchool of Biological Sciences, University of Nebraska, Lincoln, NE 68588, USA. jstorz2@unl.edu
Christopher W Wheat

Funding

Mutational Pleiotropy, Epistasis, and the Adaptive Evolution of Hemoglobin FunctionR01HL087216 · NHLBI · UNIVERSITY OF NEBRASKA LINCOLN · PI STORZ, JAY · 2008 to 2021
$4.5M
NHLBI NIH HHS R01 HL087216
6 · The paper itself

Abstract

Inferences about adaptation at specific loci are often exclusively based on the static analysis of DNA sequence variation. Ideally,population-genetic evidence for positive selection serves as a stepping-off point for experimental studies to elucidate the functional significance of the putatively adaptive variation. We argue that inferences about adaptation at specific loci are best achieved by integrating the indirect, retrospective insights provided by population-genetic analyses with the more direct, mechanistic insights provided by functional experiments. Integrative studies of adaptive genetic variation may sometimes be motivated by experimental insights into molecular function, which then provide the impetus to perform population genetic tests to evaluate whether the functional variation is of adaptive significance. In other cases, studies may be initiated by genome scans of DNA variation to identify candidate loci for recent adaptation. Results of such analyses can then motivate experimental efforts to test whether the identified candidate loci do in fact contribute to functional variation in some fitness-related phenotype. Functional studies can provide corroborative evidence for positive selection at particular loci, and can potentially reveal specific molecular mechanisms of adaptation.

Indexed as

Adaptation, BiologicalEvolution, MolecularGenetic LociGenetic VariationAnimalsButterfliesDNA Mutational AnalysisFish ProteinsGene FrequencyGenomicsGenotypeHemoglobinsInsect ProteinsPeromyscusPhenotypeSelection, GeneticFish ProteinsHemoglobinsInsect Proteins

Identifiers

PMID20500215
PMCPMC2981648

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.