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Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress
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Genome-wide co-expression analysis in multiple tissues.

Ian C Grieve1, Nicholas J Dickens, Michal Pravenec

  • 1MRC Clinical Sciences Centre, Imperial College, Hammersmith Hospital, London, United Kingdom.

Plos One
|December 30, 2008
PubMed
Summary
This summary is machine-generated.

This study reveals that while cis-acting expression quantitative trait loci (eQTLs) rarely show co-expression, trans-acting eQTLs frequently do, often within functional clusters. Genotypes significantly influence these co-expression patterns, particularly for trans-eQTLs.

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Area of Science:

  • Genomics
  • Systems Biology
  • Quantitative Genetics

Background:

  • Expression quantitative trait loci (eQTLs) regulate gene expression locally (cis) or distantly (trans).
  • Co-regulation patterns within trans-eQTL clusters and their link to genotypes are not fully understood.

Purpose of the Study:

  • To investigate genome-wide correlation structures in gene expression and genotypes across cis- and trans-eQTLs.
  • To elucidate the nature of co-regulation within eQTL datasets in four rat tissues.

Main Methods:

  • Mapping of thousands of cis- and trans-eQTLs in a rat recombinant inbred strain panel.
  • Genome-wide correlation analysis of eQTL transcript expression levels and underlying genotypes.
  • Functional enrichment analysis of identified trans-eQTL clusters.

Main Results:

  • Cis-regulated gene expression correlations were rare (<0.9%) and largely explained by genotype correlations.
  • Trans-regulated gene expression co-expression was more common (2.9%-14.9%), with high correlation within 81 identified trans-eQTL clusters.
  • Large trans-eQTL clusters showed significant functional enrichment, suggesting functional relatedness among co-expressed genes.

Conclusions:

  • eQTL genotypes significantly impact observed gene expression correlation patterns.
  • Co-expression in trans-eQTL clusters reflects functional relatedness of genes.
  • An integrative approach effectively reveals underlying genetic and co-expression structures.