Evidence map›Paper›PMID 26205989›Full record

ArticleGenetics2015

Do Molecular Markers Inform About Pleiotropy?

Daniel Gianola, Gustavo de los Campos, Miguel A Toro, Hugo Naya, Chris-Carolin Schön, Daniel Sorensen

Abstract read
In one paragraph

Article in Genetics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 1 pooled it
–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

34 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Mapping pleiotropic loci using a fast-sequential testing algorithm.European journal of human genetics : EJHG · 2021
    Article
  11. Article
  12. Article
  13. Emerging issues in genomic selection.Journal of animal science · 2021
    Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Simultaneous selection for grain yield and protein content in genomics-assisted wheat breeding.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2019
    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

6 authors.

Daniel GianolaDepartments of Animal Sciences, Dairy Science, and Biostatistics and Medical Informatics, University of Wisconsin-Madison, Wisconsin 53706 Department of Plant Breeding, Technical University of Munich, Center for Life and Food Sciences, D-85354 Freising-Weihenstephan, Germany Institute of Advanced Study, Technical University of Munich, D-85748 Garching, Germany gianola@ansci.wisc.edu.
Gustavo de los CamposDepartment of Biostatistics, Michigan State University, East Lansing, Michigan 48824.
Miguel A ToroEscuela Técnica Superior de Ingenieros Agrónomos, Universidad Politécnica de Madrid, 20840 Madrid, Spain.
Hugo NayaInstitut Pasteur de Montevideo, Mataojo 2020, Montevideo 11400, Uruguay.
Chris-Carolin SchönDepartment of Plant Breeding, Technical University of Munich, Center for Life and Food Sciences, D-85354 Freising-Weihenstephan, Germany Institute of Advanced Study, Technical University of Munich, D-85748 Garching, Germany.
Daniel SorensenDepartment of Molecular Biology and Genetics, Aarhus University, DK-8000 Aarhus C, Denmark.

Funding

Statistical Tools for Whole-Genome Prediction of Complex Traits and DiseasesR01GM101219 · NIGMS · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI DE LOS CAMPOS, GUSTAVO · 2012 to 2017
$1.6M
Factors Affecting Prediction Accuracy of Complex Human Traits and DiseasesR01GM099992 · NIGMS · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI DE LOS CAMPOS, GUSTAVO · 2012 to 2015
$1.0M
NIGMS NIH HHS R01 GM099992NIGMS NIH HHS R01GM099992NIGMS NIH HHS R01 GM101219NIGMS NIH HHS R01GM101219
6 · The paper itself

Abstract

The availability of dense panels of common single-nucleotide polymorphisms and sequence variants has facilitated the study of statistical features of the genetic architecture of complex traits and diseases via whole-genome regressions (WGRs). At the onset, traits were analyzed trait by trait, but recently, WGRs have been extended for analysis of several traits jointly. The expectation is that such an approach would offer insight into mechanisms that cause trait associations, such as pleiotropy. We demonstrate that correlation parameters inferred using markers can give a distorted picture of the genetic correlation between traits. In the absence of knowledge of linkage disequilibrium relationships between quantitative or disease trait loci and markers, speculating about genetic correlation and its causes (e.g., pleiotropy) using genomic data is conjectural.

Indexed as

Genetic MarkersGenetic PleiotropyGenetic VariationAlgorithmsGenome, HumanHumansLinkage DisequilibriumModels, GeneticQuantitative Trait LociGenetic Markersgenetic correlationgenomic correlationgenomic heritabilitylinkage disequilibriumpleiotropy

Identifiers

PMID26205989
PMCPMC4566266

What OpenQuestion holds

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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.