Evidence map›Paper›PMID 33410164›Full record

ArticleMolecular ecology2021

Can laboratory evolution experiments teach us about natural populations?

Mark A Phillips, Molly K Burke

Open access · bronzeAbstract readComment
PubMed Publisher
In one paragraph

Article in Molecular ecology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.7field-weighted citation impact, top 27% 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

5 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
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  5. Mutation inFrontiers in microbiology · 2022
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Mark A PhillipsDepartment of Integrative Biology, Oregon State University, Corvallis, OR, USA.ORCID 0000-0002-2319-7913
Molly K BurkeDepartment of Integrative Biology, Oregon State University, Corvallis, OR, USA.ORCID 0000-0002-4280-0247
Oregon State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The ability to predict how natural populations will evolve and adapt to major changes in environmental conditions has long been of interest to evolutionary biologists and ecologists alike. The reality of global climate change has also created a pressing need for advancement in this particular area of research, as species are increasingly faced with rapid shifts in abiotic and biotic conditions. Evolutionary genomics has the potential to be incredibly useful as we move forward in addressing this need and in particular, evolve and resequence (E&R) studies-where researchers combine experimental evolution with whole-genome sequencing-have an important role to play. However, while E&R studies have shown a great deal of promise in tackling fundamental questions regarding the genetics of adaptation (Long et al., 2015; Schlötterer et al., 2014), it is unclear whether results from laboratory experiments can be directly translated to natural populations. In a From the Cover article in this issue of Molecular Ecology, Hsu et al. (Mol Ecol, 29, 2020) explicitly contend with this issue by examining the overlap between genes implicated in thermal adaptation in a Drosophila melanogaster E&R study and genes identified by comparing natural populations from different latitudinal clines. They report significant correlations between the two sets of temperature-adaptive genes and ultimately conclude that E&R studies can indeed generate insights applicable to populations inhabiting complex natural environments. While more work is needed to assess the generality of these conclusions, Hsu and Belmouaden (Mol Ecol, 29, 2020) contribute an important precedent.

Indexed as

Drosophila melanogasterSelection, GeneticAnimalsGene ExpressionGenetics, PopulationLaboratoriesadaptationexperimental evolutiongene expression

Identifiers

PMID33410164
OpenAlexW3119938966

What OpenQuestion holds

Textmetadata
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.