Evidence map›Paper›PMID 38565962›Full record

ReviewNature reviews. Genetics2024

Pleiotropy, epistasis and the genetic architecture of quantitative traits.

Trudy F C Mackay, Robert R H Anholt

Abstract readReview
In one paragraph

Review in Nature reviews. Genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 75 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
75citing 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

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

  1. Pooled it
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  12. Genetic characteristics and agronomic traits in leafy head Chinese cabbage breeding.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026
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15 more citing papers are in PubMed but not listed here.

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.

Trudy F C MackayCenter for Human Genetics, Clemson University, Greenwood, SC, USA. tmackay@clemson.edu.ORCID 0000-0002-2312-7245
Robert R H AnholtCenter for Human Genetics, Clemson University, Greenwood, SC, USA. ranholt@clemson.edu.ORCID 0000-0001-7196-8324

Funding

Genetics of Cocaine Sensitivity in DrosophilaU01DA041613 · NIDA · NORTH CAROLINA STATE UNIVERSITY RALEIGH · PI Robert R. H Anholt, TRUDY F. MACKAY · 2017 to 2026
$4.9M
Genetic Basis of Lifespan and Healthspan Extension by ACE Inhibition in DrosophilaR01AG073181 · NIA · CLEMSON UNIVERSITY · PI Robert R. H Anholt, MARIA DE LUCA · 2022 to 2026
$2.4M
NIA NIH HHS R01 AG073181NIDA NIH HHS U01 DA041613
6 · The paper itself

Abstract

Pleiotropy (whereby one genetic polymorphism affects multiple traits) and epistasis (whereby non-linear interactions between genetic polymorphisms affect the same trait) are fundamental aspects of the genetic architecture of quantitative traits. Recent advances in the ability to characterize the effects of polymorphic variants on molecular and organismal phenotypes in human and model organism populations have revealed the prevalence of pleiotropy and unexpected shared molecular genetic bases among quantitative traits, including diseases. By contrast, epistasis is common between polymorphic loci associated with quantitative traits in model organisms, such that alleles at one locus have different effects in different genetic backgrounds, but is rarely observed for human quantitative traits and common diseases. Here, we review the concepts and recent inferences about pleiotropy and epistasis, and discuss factors that contribute to similarities and differences between the genetic architecture of quantitative traits in model organisms and humans.

Indexed as

Epistasis, GeneticGenetic PleiotropyQuantitative Trait LociAnimalsHumansModels, GeneticPhenotypePolymorphism, GeneticQuantitative Trait, Heritable

Identifiers

PMID38565962
PMCPMC11330371

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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.