iFORM/eQTL: An ultrahigh-dimensional platform for inferring the global genetic architecture of gene transcripts

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Abstract

Knowledge about how changes in gene expression are encoded by expression quantitative trait loci (eQTLs) is a key to construct the genotype-phenotype map for complex traits or diseases. Traditional eQTL mapping is to associate one transcript with a single marker at a time, thereby limiting our inference about a complete picture of the genetic architecture of gene expression. Here, we implemented an ultrahigh-dimensional variable selection model to build a computing platform that can systematically scan main effects and interaction effects among all possible loci and identify a set of significant eQTLs modulating differentiation and function of gene expression. This platform, named iFORM/eQTL, was assembled by forward-selection-based procedures to tackle complex covariance structures of gene-gene interactions. iFORM/eQTL can particularly discern the role of cis-QTLs, trans-QTLs and their epistatic interactions in gene expression. Results from the reanalysis of a published genetic and genomic data set through iFORM/eQTL gain new discoveries on the genetic origin of gene expression differentiation in Caenorhabditis elegans, which could not be detected by a traditional one-locus/one-transcript analysis approach.

Original languageEnglish (US)
Pages (from-to)250-259
Number of pages10
JournalBriefings in Bioinformatics
Volume18
Issue number2
DOIs
StatePublished - Jan 1 2017

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Quantitative Trait Loci
Gene expression
Genes
Gene Expression
Caenorhabditis elegans
Genotype
Phenotype

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Molecular Biology

Cite this

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title = "iFORM/eQTL: An ultrahigh-dimensional platform for inferring the global genetic architecture of gene transcripts",
abstract = "Knowledge about how changes in gene expression are encoded by expression quantitative trait loci (eQTLs) is a key to construct the genotype-phenotype map for complex traits or diseases. Traditional eQTL mapping is to associate one transcript with a single marker at a time, thereby limiting our inference about a complete picture of the genetic architecture of gene expression. Here, we implemented an ultrahigh-dimensional variable selection model to build a computing platform that can systematically scan main effects and interaction effects among all possible loci and identify a set of significant eQTLs modulating differentiation and function of gene expression. This platform, named iFORM/eQTL, was assembled by forward-selection-based procedures to tackle complex covariance structures of gene-gene interactions. iFORM/eQTL can particularly discern the role of cis-QTLs, trans-QTLs and their epistatic interactions in gene expression. Results from the reanalysis of a published genetic and genomic data set through iFORM/eQTL gain new discoveries on the genetic origin of gene expression differentiation in Caenorhabditis elegans, which could not be detected by a traditional one-locus/one-transcript analysis approach.",
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AU - Wu, Rongling

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