Evidence map›Paper›PMID 38523316›Full record

ArticleGenome biology2024

Next-Gen GWAS: full 2D epistatic interaction maps retrieve part of missing heritability and improve phenotypic prediction.

Clément Carré, Jean Baptiste Carluer, Christian Chaux, Chad Estoup-Streiff, Nicolas Roche, Eric Hosy, André Mas, Gabriel Krouk

Abstract read
In one paragraph

Article in Genome biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Article
  2. Harnessing artificial intelligence in plant breeding: innovations in digital phenotyping and breeding methodologies.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026
    Review
  3. Article
  4. Article
  5. Article
  6. Identification of miR171a-International journal of molecular sciences · 2025
    Article
  7. Article
  8. Article
  9. Review
  10. Review
  11. Article
  12. Review
  13. 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

8 authors.

Clément Carré *BionomeeX, Montpellier, France. clement.carre@bionomeex.com.
Jean Baptiste Carluer *IMAG, Univ. Montpellier, CNRS, Montpellier, France.
Christian ChauxBionomeeX, Montpellier, France.
Chad Estoup-StreiffBionomeeX, Montpellier, France.
Nicolas RocheBionomeeX, Montpellier, France.
Eric HosyInterdisciplinary Institute for Neuroscience, University of Bordeaux, CNRS, Bordeaux, France.
André MasBionomeeX, Montpellier, France. andre.mas@umontpellier.fr.
Gabriel KroukBionomeeX, Montpellier, France. gkrouk@gmail.com.ORCID 0000-0003-3693-6735

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The problem of missing heritability requires the consideration of genetic interactions among different loci, called epistasis. Current GWAS statistical models require years to assess the entire combinatorial epistatic space for a single phenotype. We propose Next-Gen GWAS (NGG) that evaluates over 60 billion single nucleotide polymorphism combinatorial first-order interactions within hours. We apply NGG to Arabidopsis thaliana providing two-dimensional epistatic maps at gene resolution. We demonstrate on several phenotypes that a large proportion of the missing heritability can be retrieved, that it indeed lies in epistatic interactions, and that it can be used to improve phenotype prediction.

Indexed as

Epistasis, GeneticGenome-Wide Association StudyModels, StatisticalPhenotypePolymorphism, Single Nucleotide

Identifiers

PMID38523316
PMCPMC10962106

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.