Constraints on eQTL Fine Mapping in the Presence of Multisite Local Regulation of Gene Expression
| Autor: | Andres Metspalu, Joseph E. Powell, Greg Gibson, Arshed A. Quyyumi, Alexander Holloway, Urko M. Marigorta, Tõnu Esko, Jian Yang, Kenneth L. Brigham, Peter M. Visscher, Luke R. Lloyd-Jones, Grant W. Montgomery, Biao Zeng, Youssef Idaghdour |
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| Rok vydání: | 2017 |
| Předmět: |
0301 basic medicine
Linkage disequilibrium Quantitative Trait Loci Bayesian probability Computational biology Investigations QH426-470 Quantitative trait locus Biology Polymorphism Single Nucleotide colocalization 03 medical and health sciences Bayes' theorem Genetics Humans Computer Simulation Allele Molecular Biology Alleles Genetics (clinical) Linkage (software) Models Genetic multivariable regression Physical Chromosome Mapping Bayes Theorem 030104 developmental biology Gene Expression Regulation fine mapping Expression quantitative trait loci gene regulation linkage disequilibrium |
| Zdroj: | G3: Genes, Genomes, Genetics, Vol 7, Iss 8, Pp 2533-2544 (2017) G3: Genes|Genomes|Genetics |
| ISSN: | 2160-1836 |
| Popis: | Expression quantitative trait locus (eQTL) detection has emerged as an important tool for unraveling of the relationship between genetic risk factors and disease or clinical phenotypes. Most studies use single marker linear regression to discover primary signals, followed by sequential conditional modeling to detect secondary genetic variants affecting gene expression. However, this approach assumes that functional variants are sparsely distributed and that close linkage between them has little impact on estimation of their precise location and the magnitude of effects. We describe a series of simulation studies designed to evaluate the impact of linkage disequilibrium (LD) on the fine mapping of causal variants with typical eQTL effect sizes. In the presence of multisite regulation, even though between 80 and 90% of modeled eSNPs associate with normally distributed traits, up to 10% of all secondary signals could be statistical artifacts, and at least 5% but up to one-quarter of credible intervals of SNPs within r2 > 0.8 of the peak may not even include a causal site. The Bayesian methods eCAVIAR and DAP (Deterministic Approximation of Posteriors) provide only modest improvement in resolution. Given the strong empirical evidence that gene expression is commonly regulated by more than one variant, we conclude that the fine mapping of causal variants needs to be adjusted for multisite influences, as conditional estimates can be highly biased by interference among linked sites, but ultimately experimental verification of individual effects is needed. Presumably similar conclusions apply not just to eQTL mapping, but to multisite influences on fine mapping of most types of quantitative trait. |
| Databáze: | OpenAIRE |
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