Expression quantitative trait loci are highly sensitive to cellular differentiation state

PLoS Genet. 2009 Oct;5(10):e1000692. doi: 10.1371/journal.pgen.1000692. Epub 2009 Oct 16.


Genetical genomics is a strategy for mapping gene expression variation to expression quantitative trait loci (eQTLs). We performed a genetical genomics experiment in four functionally distinct but developmentally closely related hematopoietic cell populations isolated from the BXD panel of recombinant inbred mouse strains. This analysis allowed us to analyze eQTL robustness/sensitivity across different cellular differentiation states. Although we identified a large number (365) of "static" eQTLs that were consistently active in all four cell types, we found a much larger number (1,283) of "dynamic" eQTLs showing cell-type-dependence. Of these, 140, 45, 531, and 295 were preferentially active in stem, progenitor, erythroid, and myeloid cells, respectively. A detailed investigation of those dynamic eQTLs showed that in many cases the eQTL specificity was associated with expression changes in the target gene. We found no evidence for target genes that were regulated by distinct eQTLs in different cell types, suggesting that large-scale changes within functional regulatory networks are uncommon. Our results demonstrate that heritable differences in gene expression are highly sensitive to the developmental stage of the cell population under study. Therefore, future genetical genomics studies should aim at studying multiple well-defined and highly purified cell types in order to construct as comprehensive a picture of the changing functional regulatory relationships as possible.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Blood Cells / cytology*
  • Blood Cells / metabolism*
  • Cell Differentiation*
  • Female
  • Gene Expression Regulation, Developmental*
  • Genetic Markers
  • Mice
  • Oligonucleotide Array Sequence Analysis
  • Quantitative Trait Loci*


  • Genetic Markers