ArticlePLoS genetics2009
Learning a prior on regulatory potential from eQTL data.
Article in PLoS genetics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 135 papers.
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Who cites it
135 citing papers in PubMed, 202 citations in OpenAlex.
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- The yeast Mkt1/Pbp1 complex promotes adaptive responses to respiratory growth.The Journal of cell biology · 2025Article
- High-resolution, genotype-free mapping of genetic variation with CRI-SPA-Map.bioRxiv : the preprint server for biology · 2025Article
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- Enhancing Gene Expression Predictions Using Deep Learning and Functional Annotations.Genetic epidemiology · 2025Article
- Distinct genetic liability profiles define clinically relevant patient strata across common diseases.Nature communications · 2024Article
- The fitness trade-off between growth and stress resistance determines the phenotypic landscape.BMC biology · 2024Article
- Enforcement of Postzygotic Species Boundaries in the Fungal Kingdom.Microbiology and molecular biology reviews : MMBR · 2022Review
- Dynamic regulatory module networks for inference of cell type-specific transcriptional networks.Genome research · 2022Article
- Interpreting Functional Impact of Genetic Variations by Network QTL for Genotype-Phenotype Association Study.Frontiers in cell and developmental biology · 2021Article
- Fully automated web-based tool for identifying regulatory hotspots.BMC genomics · 2020Article
- Genome-wide pQTL analysis of protein expression regulatory networks in the human liver.BMC biology · 2020Article
- The RNA-associated proteins MKT1 and MKT1L form alternative PBP1-containing complexes inThe Journal of biological chemistry · 2020Article
- CERENKOV3: Clustering and molecular network-derived features improve computational prediction of functional noncoding SNPs.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2020Article
- CERENKOV2: improved detection of functional noncoding SNPs using data-space geometric features.BMC bioinformatics · 2019Article
- Pbp1-Interacting Protein Mkt1 Regulates Virulence and Sexual Reproduction inFrontiers in cellular and infection microbiology · 2019Article
- A guide to deep learning in healthcare.Nature medicine · 2019Review
- Quantitative Trait Nucleotides Impacting the Technological Performances of IndustrialFrontiers in genetics · 2019Article
75 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
7 authors at 5 institutions in 1 country.
Funding
Abstract
Genome-wide RNA expression data provide a detailed view of an organism's biological state; hence, a dataset measuring expression variation between genetically diverse individuals (eQTL data) may provide important insights into the genetics of complex traits. However, with data from a relatively small number of individuals, it is difficult to distinguish true causal polymorphisms from the large number of possibilities. The problem is particularly challenging in populations with significant linkage disequilibrium, where traits are often linked to large chromosomal regions containing many genes. Here, we present a novel method, Lirnet, that automatically learns a regulatory potential for each sequence polymorphism, estimating how likely it is to have a significant effect on gene expression. This regulatory potential is defined in terms of "regulatory features"-including the function of the gene and the conservation, type, and position of genetic polymorphisms-that are available for any organism. The extent to which the different features influence the regulatory potential is learned automatically, making Lirnet readily applicable to different datasets, organisms, and feature sets. We apply Lirnet both to the human HapMap eQTL dataset and to a yeast eQTL dataset and provide statistical and biological results demonstrating that Lirnet produces significantly better regulatory programs than other recent approaches. We demonstrate in the yeast data that Lirnet can correctly suggest a specific causal sequence variation within a large, linked chromosomal region. In one example, Lirnet uncovered a novel, experimentally validated connection between Puf3-a sequence-specific RNA binding protein-and P-bodies-cytoplasmic structures that regulate translation and RNA stability-as well as the particular causative polymorphism, a SNP in Mkt1, that induces the variation in the pathway.
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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.