Evidence map›Paper›PMID 35363317›Full record

ArticleMolecular biology and evolution2022

Detection of F1 Hybrids from Single-genome Data Reveals Frequent Hybridization in Hymenoptera and Particularly Ants.

Arthur Weyna, Lucille Bourouina, Nicolas Galtier, Jonathan Romiguier

Abstract read
In one paragraph

Article in Molecular biology and evolution, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. The "Chameleon Ant"Ecology and evolution · 2025
    Article
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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

4 authors.

Arthur WeynaInstitut des Sciences de l'Evolution (UMR 5554), University of Montpellier, CNRS Montpellier, France.
Lucille BourouinaInstitut des Sciences de l'Evolution (UMR 5554), University of Montpellier, CNRS Montpellier, France.
Nicolas GaltierInstitut des Sciences de l'Evolution (UMR 5554), University of Montpellier, CNRS Montpellier, France.ORCID 0000-0002-0479-4878
Jonathan RomiguierInstitut des Sciences de l'Evolution (UMR 5554), University of Montpellier, CNRS Montpellier, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hybridization occupies a central role in many fundamental evolutionary processes, such as speciation or adaptation. Yet, despite its pivotal importance in evolution, little is known about the actual prevalence and distribution of current hybridization across the tree of life. Here we develop and implement a new statistical method enabling the detection of F1 hybrids from single-individual genome sequencing data. Using simulations and sequencing data from known hybrid systems, we first demonstrate the specificity of the method, and identify its statistical limits. Next, we showcase the method by applying it to available sequencing data from more than 1,500 species of Arthropods, including Hymenoptera, Hemiptera, Coleoptera, Diptera, and Archnida. Among these taxa, we find Hymenoptera, and especially ants, to display the highest number of candidate F1 hybrids, suggesting higher rates of recent hybridization between previously isolated gene pools in these groups. The prevalence of F1 hybrids was heterogeneously distributed across ants, with taxa including many candidates tending to harbor specific ecological and life-history traits. This work shows how large-scale genomic comparative studies of recent hybridization can be implemented, uncovering the determinants of first-generation hybridization across whole taxa.

Indexed as

AntsAnimalsGene PoolGenomeGenomicsHybridization, GeneticantsarthropodscoalescentF1 hybrids detectionhybridizationhymenoptera

Identifiers

PMID35363317
PMCPMC9021736

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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.