Evidence map›Paper›PMID 37603463›Full record

ArticleMolecular biology and evolution2023

Genetic Architecture of Flowering Time Differs Between Populations With Contrasting Demographic and Selective Histories.

Célia Neto, Angela Hancock

Abstract read
In one paragraph

Article in Molecular biology and evolution, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

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3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Article
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  3. Article
  4. Review
  5. Article
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  8. Review
  9. Genetic architecture of the response ofFrontiers in plant science · 2023
    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

2 authors.

Célia NetoMolecular Basis of Adaptation Research Group, Max Planck Institute for Plant Breeding Research, Cologne, Germany.ORCID 0000-0003-3256-5228
Angela HancockMolecular Basis of Adaptation Research Group, Max Planck Institute for Plant Breeding Research, Cologne, Germany.ORCID 0000-0002-4768-3377

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding the evolutionary factors that impact the genetic architecture of traits is a central goal of evolutionary genetics. Here, we investigate how quantitative trait variation accumulated over time in populations that colonized a novel environment. We compare the genetic architecture of flowering time in Arabidopsis populations from the drought-prone Cape Verde Islands and their closest outgroup population from North Africa. We find that trait polygenicity is severely reduced in the island populations compared to the continental North African population. Further, trait architectures and reconstructed allelic histories best fit a model of strong directional selection in the islands in accord with a Fisher-Orr adaptive walk. Consistent with this, we find that large-effect variants that disrupt major flowering time genes (FRI and FLC) arose first, followed by smaller effect variants, including ATX2 L125F, which is associated with a 4-day reduction in flowering time. The most recently arising flowering time-associated loci are not known to be directly involved in flowering time, consistent with an omnigenic signature developing as the population approaches its trait optimum. Surprisingly, we find no effect in the natural population of EDI-Cvi-0 (CRY2 V367M), an allele for which an effect was previously validated by introgression into a Eurasian line. Instead, our results suggest the previously observed effect of the EDI-Cvi-0 allele on flowering time likely depends on genetic background, due to an epistatic interaction. Altogether, our results provide an empirical example of the effects demographic history and selection has on trait architecture.

Indexed as

ArabidopsisArabidopsis ProteinsAfrica, NorthernAllelesBiological EvolutionDemographyArabidopsis ProteinsFRI protein, Arabidopsisadaptive walk‌complex traitsdirectional selectionFisher–Orr geometric modelflowering time

Identifiers

PMID37603463
PMCPMC10461413

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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.