Evidence map›Paper›PMID 30325920›Full record

ArticlePLoS genetics2018

Recovery of novel association loci in Arabidopsis thaliana and Drosophila melanogaster through leveraging INDELs association and integrated burden test.

Baoxing Song, Richard Mott, Xiangchao Gan

Abstract read
In one paragraph

Article in PLoS genetics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

13 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Predicting Gene Regulatory Interactions Using Natural Genetic Variation.Methods in molecular biology (Clifton, N.J.) · 2023
    Article
  10. Article
  11. Review
  12. uORFlight: a vehicle toward uORF-mediated translational regulation mechanisms in eukaryotes.Database : the journal of biological databases and curation · 2020
    Article
  13. 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

3 authors.

Baoxing SongMax Planck Institute for Plant Breeding Research, Köln, Germany.ORCID 0000-0003-1478-9228
Richard MottUCL Genetics Institute, University College London, London United Kingdom.ORCID 0000-0002-1022-9330
Xiangchao GanMax Planck Institute for Plant Breeding Research, Köln, Germany.ORCID 0000-0001-6398-5191

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Short insertions, deletions (INDELs) and larger structural variants have been increasingly employed in genetic association studies, but few improvements over SNP-based association have been reported. In order to understand why this might be the case, we analysed two publicly available datasets and observed that 63% of INDELs called in A. thaliana and 64% in D. melanogaster populations are misrepresented as multiple alleles with different functional annotations, i.e. where the same underlying variant is represented by inconsistent alignments leading to different variant calls. To address this issue, we have developed the software Irisas to reclassify and re-annotate these variants, which we then used for single-locus tests of association. We also integrated them to predict the functional impact of SNPs, INDELs, and structural variants for burden testing. Using both approaches, we re-analysed the genetic architecture of complex traits in A. thaliana and D. melanogaster. Heritability analysis using SNPs alone explained on average 27% and 19% of phenotypic variance for A. thaliana and D. melanogaster respectively. Our method explained an additional 11% and 3%, respectively. We also identified novel trait loci that previous SNP-based association studies failed to map, and which contain established candidate genes. Our study shows the value of the association test with INDELs and integrating multiple types of variants in association studies in plants and animals.

Indexed as

AnimalsArabidopsisDrosophila melanogasterGenetic Association StudiesGenotypeINDEL MutationPhenotypePolymorphism, Single NucleotideQuantitative Trait LociSequence Analysis, DNASoftware

Identifiers

PMID30325920
PMCPMC6203403

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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.