Evidence map›Paper›PMID 32884665›Full record

ArticleEcology and evolution2020

Investigating population-scale allelic differential expression in wild populations of

Romuald Laso-Jadart, Kevin Sugier, Emmanuelle Petit, Karine Labadie, Pierre Peterlongo, Christophe Ambroise, Patrick Wincker, Jean-Louis Jamet, Mohammed-Amin Madoui

Abstract read
In one paragraph

Article in Ecology and evolution, 2020. 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
–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

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
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  5. Article
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

9 authors.

Romuald Laso-JadartGénomique Métabolique, Genoscope Institut François Jacob, CEA, CNRS, Univ Evry Université Paris-Saclay Evry France.ORCID https://orcid.org/0000-0001-8410-1121
Kevin SugierGénomique Métabolique, Genoscope Institut François Jacob, CEA, CNRS, Univ Evry Université Paris-Saclay Evry France.
Emmanuelle PetitCEA, Genoscope Institut de Biologie François Jacob Université Paris-Saclay Evry France.
Karine LabadieCEA, Genoscope Institut de Biologie François Jacob Université Paris-Saclay Evry France.
Pierre PeterlongoCNRS, Inria, IRISA - UMR 6074 Univ Rennes Rennes France.
Christophe AmbroiseLaMME, CNRS Université Paris-Saclay Univ Evry Evry France.
Patrick WinckerGénomique Métabolique, Genoscope Institut François Jacob, CEA, CNRS, Univ Evry Université Paris-Saclay Evry France.
Jean-Louis JametMediterranean Institute of Oceanology (MIO) AMU-UTLN UM110 CNRS UMR7294, IRD UMR235 Equipe Ecologie Marine et Biodiversité (EMBIO) Université de Toulon Toulon Cedex 9 France.
Mohammed-Amin MadouiGénomique Métabolique, Genoscope Institut François Jacob, CEA, CNRS, Univ Evry Université Paris-Saclay Evry France.ORCID https://orcid.org/0000-0003-4809-2971

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acclimation allowed by variation in gene or allele expression in natural populations is increasingly understood as a decisive mechanism, as much as adaptation, for species evolution. However, for small eukaryotic organisms, as species from zooplankton, classical methods face numerous challenges. Here, we propose the concept of allelic differential expression at the population-scale (psADE) to investigate the variation in allele expression in natural populations. We developed a novel approach to detect psADE based on metagenomic and metatranscriptomic data from environmental samples. This approach was applied on the widespread marine copepod,

Indexed as

allelic expressionArctic seascopepodmetagenomicsmetatranscriptomicsselectionstructureTara OceansZooplankton

Identifiers

PMID32884665
PMCPMC7452778

What OpenQuestion holds

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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.