Evidence map›Paper›PMID 21218185›Full record

ArticleInternational journal of plant sciences2010

USING POPULATION GENOMICS TO DETECT SELECTION IN NATURAL POPULATIONS: KEY CONCEPTS AND METHODOLOGICAL CONSIDERATIONS.

Paul A Hohenlohe, Patrick C Phillips, William A Cresko

Abstract read
In one paragraph

Article in International journal of plant sciences, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 89 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
89citing 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

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

  1. Pooled it
  2. Article
  3. Genomic Insights into Adaptation ofPlants (Basel, Switzerland) · 2026
    Article
  4. Evaluating inbreeding and assessing the risk of outbreeding depression in genetic rescue using whole-genome sequence data.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
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29 more citing papers are in PubMed but not listed here.

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

3 authors.

Paul A HohenloheCenter for Ecology and Evolutionary Biology, University of Oregon, Eugene, Oregon 97403, U.S.A.
Patrick C Phillips
William A Cresko

Funding

THE MATHEMATICAL DEMOGRAPHY OF BIODEMOGRAPHYP01AG022500 · NIA · UNIVERSITY OF CALIFORNIA DAVIS · PI CAREY, JAMES R. · 2003 to 2010
$8.1M
Rapid and cost-efficient genotyping tools for stuides of threespine sticklebackR24GM079486 · NIGMS · UNIVERSITY OF OREGON · PI CRESKO, WILLIAM A · 2007 to 2010
$708k
NIA NIH HHS P01 AG022500NIGMS NIH HHS R24 GM079486
6 · The paper itself

Abstract

Natural selection shapes patterns of genetic variation among individuals, populations, and species, and it does so differentially across genomes. The field of population genomics provides a comprehensive genome-scale view of the action of selection, even beyond traditional model organisms. However, even with nearly complete genomic sequence information, our ability to detect the signature of selection on specific genomic regions depends on choosing experimental and analytical tools appropriate to the biological situation. For example, processes that occur at different timescales, such as sorting of standing genetic variation, mutation-selection balance, or fixed interspecific divergence, have different consequences for genomic patterns of variation. Inappropriate experimental or analytical approaches may fail to detect even strong selection or falsely identify a signature of selection. Here we outline the conceptual framework of population genomics, relate genomic patterns of variation to evolutionary processes, and identify major biological factors to be considered in studies of selection. As data-gathering technology continues to advance, our ability to understand selection in natural populations will be limited more by conceptual and analytical weaknesses than by the amount of molecular data. Our aim is to bring critical biological considerations to the fore in population genomics research and to spur the development and application of analytical tools appropriate to diverse biological systems.

Identifiers

PMID21218185
PMCPMC3016716

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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.