Evidence map›Paper›PMID 34226672›Full record

ArticleHeredity2021

Revisiting a GWAS peak in Arabidopsis thaliana reveals possible confounding by genetic heterogeneity.

Eriko Sasaki, Thomas Köcher, Danièle L Filiault, Magnus Nordborg

Open access · bronzeAbstract read
In one paragraph

Article in Heredity, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.9field-weighted citation impact, top 9% 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

8 citing papers in PubMed, 23 citations in OpenAlex.

  1. Article
  2. Life-history trade-offs explain local adaptation inbioRxiv : the preprint server for biology · 2025
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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 at 3 institutions in 2 countries.

Eriko SasakiGregor Mendel Institute of Molecular Plant Biology, Austrian Academy of Sciences, Vienna BioCenter, Dr. Bohr-Gasse 3, Vienna, 1030, Austria.ORCID http://orcid.org/0000-0002-0878-364X
Thomas KöcherVienna BioCenter Core Facilities, Vienna BioCenter, Dr. Bohr-Gasse 3, Vienna, 1030, Austria.ORCID http://orcid.org/0000-0003-0827-1457
Danièle L FiliaultGregor Mendel Institute of Molecular Plant Biology, Austrian Academy of Sciences, Vienna BioCenter, Dr. Bohr-Gasse 3, Vienna, 1030, Austria.ORCID http://orcid.org/0000-0002-2938-3071
Magnus NordborgGregor Mendel Institute of Molecular Plant Biology, Austrian Academy of Sciences, Vienna BioCenter, Dr. Bohr-Gasse 3, Vienna, 1030, Austria. magnus.nordborg@gmi.oeaw.ac.at.ORCID http://orcid.org/0000-0001-7178-9748
Gregor Mendel Institute of Molecular Plant Biology · ATKyushu University · JPVienna Biocenter · AT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genome-wide association studies (GWAS) have become a standard approach for exploring the genetic basis of phenotypic variation. However, correlation is not causation, and only a tiny fraction of all associations have been experimentally confirmed. One practical problem is that a peak of association does not always pinpoint a causal gene, but may instead be tagging multiple causal variants. In this study, we reanalyze a previously reported peak associated with flowering time traits in Swedish Arabidopsis thaliana population. The peak appeared to pinpoint the AOP2/AOP3 cluster of glucosinolate biosynthesis genes, which is known to be responsible for natural variation in herbivore resistance. Here we propose an alternative hypothesis, by demonstrating that the AOP2/AOP3 flowering association can be wholly accounted for by allelic variation in two flanking genes with clear roles in regulating flowering: NDX1, a regulator of the main flowering time controller FLC, and GA1, which plays a central role in gibberellin synthesis and is required for flowering under some conditions. In other words, we propose that the AOP2/AOP3 flowering-time association may be yet another example of a spurious, "synthetic" association, arising from trying to fit a single-locus model in the presence of two statistically associated causative loci. We conclude that caution is needed when using GWAS for fine-mapping.

Indexed as

ArabidopsisArabidopsis ProteinsFlowersGenetic HeterogeneityGenome-Wide Association StudyArabidopsis Proteins

Identifiers

PMID34226672
PMCPMC8405673
OpenAlexW3181340892

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.