Linking traits based on their shared molecular mechanisms

Elife. 2015 Mar 17;4:e04346. doi: 10.7554/eLife.04346.

Abstract

There is growing recognition that co-morbidity and co-occurrence of disease traits are often determined by shared genetic and molecular mechanisms. In most cases, however, the specific mechanisms that lead to such trait-trait relationships are yet unknown. Here we present an analysis of a broad spectrum of behavioral and physiological traits together with gene-expression measurements across genetically diverse mouse strains. We develop an unbiased methodology that constructs potentially overlapping groups of traits and resolves their underlying combination of genetic loci and molecular mechanisms. For example, our method predicts that genetic variation in the Klf7 gene may influence gene transcripts in bone marrow-derived myeloid cells, which in turn affect 17 behavioral traits following morphine injection; this predicted effect of Klf7 is consistent with an in vitro perturbation of Klf7 in bone marrow cells. Our analysis demonstrates the utility of studying hidden causative mechanisms that lead to relationships between complex traits.

Keywords: causative networks; computational biology; evolutionary biology; genomics; mouse; phenome connections; recombinant inbred mouse strains.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Animals
  • Computational Biology / methods*
  • Gene Expression Regulation
  • Genetic Variation*
  • Humans
  • Kruppel-Like Transcription Factors
  • Mice, Inbred C57BL
  • Mice, Inbred DBA
  • Mice, Inbred Strains
  • Models, Genetic
  • Myeloid Cells / metabolism
  • Phenotype
  • Quantitative Trait Loci / genetics*
  • Reproducibility of Results

Substances

  • KLF7 protein, human
  • Kruppel-Like Transcription Factors

Grant support

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.