ArticlePLoS genetics2012
Use of pleiotropy to model genetic interactions in a population.
Article in PLoS genetics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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.
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.
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Who cites it
19 citing papers in PubMed, 27 citations in OpenAlex.
- Pleiotropy, epistasis and the genetic architecture of quantitative traits.Nature reviews. Genetics · 2024Review
- Genomic determinants, architecture, and constraints in drought-related traits in Corymbia calophylla.BMC genomics · 2024Article
- Differences in lipid metabolism in acquired versus preexisting glucose intolerance during gestation: role of free fatty acids and sphingosine-1-phosphate.Lipids in health and disease · 2022Article
- Effects of kinship correction on inflation of genetic interaction statistics in commonly used mouse populations.G3 (Bethesda, Md.) · 2021Article
- A Multilayer Interactome Network Constructed in a Forest Poplar Population Mediates the Pleiotropic Control of Complex Traits.Frontiers in genetics · 2021Article
- Genetic Interactions Affect Lung Function in Patients with Systemic Sclerosis.G3 (Bethesda, Md.) · 2020Article
- Comparing phenotypic variation between inbred and outbred mice.Nature methods · 2018Article
- Epistatic Networks Jointly Influence Phenotypes Related to Metabolic Disease and Gene Expression in Diversity Outbred Mice.Genetics · 2017Article
- Mapping of quantitative trait loci for grain yield and its components in a US popular winter wheat TAM 111 using 90K SNPs.PloS one · 2017Article
- Past Roadblocks and New Opportunities in Transcription Factor Network Mapping.Trends in genetics : TIG · 2016Review
- Functional Regression Models for Epistasis Analysis of Multiple Quantitative Traits.PLoS genetics · 2016Article
- Weak Epistasis Generally Stabilizes Phenotypes in a Mouse Intercross.PLoS genetics · 2016Article
- A genetic interaction network model of a complex neurological disease.Genes, brain, and behavior · 2014Article
- Detecting epistasis in human complex traits.Nature reviews. Genetics · 2014Review
- Regularized machine learning in the genetic prediction of complex traits.PLoS genetics · 2014Article
- Two-stage genome-wide search for epistasis with implementation to Recombinant Inbred Lines (RIL) populations.PloS one · 2014Article
- Dissection of complex gene expression using the combined analysis of pleiotropy and epistasis.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2014Article
- CAPE: an R package for combined analysis of pleiotropy and epistasis.PLoS computational biology · 2013Article
- Inferring gene function and network organization in Drosophila signaling by combined analysis of pleiotropy and epistasis.G3 (Bethesda, Md.) · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
Systems-level genetic studies in humans and model systems increasingly involve both high-resolution genotyping and multi-dimensional quantitative phenotyping. We present a novel method to infer and interpret genetic interactions that exploits the complementary information in multiple phenotypes. We applied this approach to a population of yeast strains with randomly assorted perturbations of five genes involved in mating. We quantified pheromone response at the molecular level and overall mating efficiency. These phenotypes were jointly analyzed to derive a network of genetic interactions that mapped mating-pathway relationships. To determine the distinct biological processes driving the phenotypic complementarity, we analyzed patterns of gene expression to find that the pheromone response phenotype is specific to cellular fusion, whereas mating efficiency was a combined measure of cellular fusion, cell cycle arrest, and modifications in cellular metabolism. We applied our novel method to global gene expression patterns to derive an expression-specific interaction network and demonstrate applicability to global transcript data. Our approach provides a basis for interpretation of genetic interactions and the generation of specific hypotheses from populations assayed for multiple phenotypes.
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What OpenQuestion holds
Registered trials
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.