Evidence map›Paper›PMID 38187753›Full record

ArticlebioRxiv : the preprint server for biology2023

Genome evolution is surprisingly predictable after initial hybridization.

Quinn K Langdon, Jeffrey S Groh, Stepfanie M Aguillon, Daniel L Powell, Theresa Gunn, Cheyenne Payne, John J Baczenas, Alex Donny, Tristram O Dodge, Kang Du and 5 more

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

15 authors.

Quinn K LangdonDepartment of Biology, Stanford University.
Jeffrey S GrohCenter for Population Biology and Department of Evolution and Ecology, University of California, Davis.
Stepfanie M AguillonDepartment of Biology, Stanford University.
Daniel L PowellDepartment of Biology, Stanford University.
Theresa GunnDepartment of Biology, Stanford University.
Cheyenne PayneDepartment of Biology, Stanford University.
John J BaczenasDepartment of Biology, Stanford University.
Alex DonnyDepartment of Biology, Stanford University.
Tristram O DodgeDepartment of Biology, Stanford University.
Kang DuXiphophorus Genetic Stock Center, Texas State University San Marcos.
Manfred SchartlXiphophorus Genetic Stock Center, Texas State University San Marcos.
Oscar Ríos-CárdenasRed de Biología Evolutiva, Instituto de Ecología, A.C.
Carla Gutierrez-RodríguezRed de Biología Evolutiva, Instituto de Ecología, A.C.
Molly MorrisDepartment of Biology, Ohio University.
Molly SchumerDepartment of Biology, Stanford University.ORCID 0000-0002-2075-5668

Funding

The population genomics of hybridization: from genetic incompatibilities to genome evolutionR35GM133774 · NIGMS · STANFORD UNIVERSITY · PI Molly Schumer · 2019 to 2026
$3.3M
NIGMS NIH HHS R35 GM133774
6 · The paper itself

Abstract

Over the past two decades, evolutionary biologists have come to appreciate that hybridization, or genetic exchange between distinct lineages, is remarkably common - not just in particular lineages but in taxonomic groups across the tree of life. As a result, the genomes of many modern species harbor regions inherited from related species. This observation has raised fundamental questions about the degree to which the genomic outcomes of hybridization are repeatable and the degree to which natural selection drives such repeatability. However, a lack of appropriate systems to answer these questions has limited empirical progress in this area. Here, we leverage independently formed hybrid populations between the swordtail fish

Identifiers

PMID38187753
PMCPMC10769416

What OpenQuestion holds

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LicenceCC BY
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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.