Evidence map›Paper›PMID 21705473›Full record

ArticleGenome biology and evolution2011

Characterizing the influence of effective population size on the rate of adaptation: Gillespie's Darwin domain.

Jeffrey D Jensen, Doris Bachtrog

Abstract read
In one paragraph

Article in Genome biology and evolution, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

35 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

2 authors.

Jeffrey D JensenSchool of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland. jeffrey.jensen@epfl.ch
Doris Bachtrog

Funding

The evolution of dosage compensation in DrosophilaR01GM076007 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI BACHTROG, DORIS · 2006 to 2020
$3.6M
NIGMS NIH HHS GM076007NIGMS NIH HHS R01 GM076007
6 · The paper itself

Abstract

Characterizing the role of effective population size in dictating the rate of adaptive evolution remains a major challenge in evolutionary biology. Depending on the underlying distribution of fitness effects of new mutations, populations of different sizes may differ vastly in their rate of adaptation. Here, we collect polymorphism data at over 100 loci for two closely related Drosophila species with different current effective population sizes (N(e)), Drosophila miranda and D. pseudoobscura, to evaluate the prevalence of adaptive evolution versus genetic drift in molecular evolution. Utilizing these large and consistently sampled data sets, we obtain greatly improved estimates of the demographic histories of both species. Specifically, although current N(e) differs between these species, their ancestral sizes were much more similar. We find that statistical approaches capturing recent adaptive evolution (using patterns of polymorphisms) detect higher rates of adaptive evolution in the larger D. pseudoobscura population. In contrast, methods aimed at detecting selection over longer time periods (i.e., those relying on divergence data) estimate more similar rates of adaptation between the two species. Thus, our results suggest an important role of effective population size in dictating rates of adaptation and highlight how complicated population histories--as is probably the case for most species--can effect rates of adaptation. Additionally, we also show how different methodologies to detect positive selection can reveal information about different timescales of adaptive evolution.

Indexed as

Adaptation, BiologicalAnimalsBiological EvolutionDrosophilaEvolution, MolecularGenetic DriftModels, TheoreticalPolymorphism, GeneticPopulation DensitySelection, Genetic

Identifiers

PMID21705473
PMCPMC3157839

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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.