Description
Lymphoblastoid cell lines (LCLs), originally collected as renewable sources of DNA, are now being used as a model system to study genotype-phenotype relationships in human cells. These cell lines have been used to search for genetic variants that are associated with drug response as well as with more basic cellular traits such as RNA levels. In setting out to extend such studies by searching for genetic variants contributing to drug response, we observed that phenotypes in LCLs were, in our lab and others, significantly affected by experimental confounders (i.e. in vitro growth rate, metabolic state, and relative levels of the Epstein-Barr virus used to transform the cells). As we did not find any SNPs associated with genome-wide significance to drug response, we evaluated whether incorporating RNA expression levels (and eQTLs) in the analysis could increase power to detect such effects. As previously shown, cis-acting eQTLs were detectable for a sizeable fraction of RNAs and baseline levels of many RNAs predicted response to several drugs. However, we found only limited evidence that SNPs influenced drug response through their effect on expression of RNA. Efforts to use LCLs to map genes underlying cellular traits will require great care to control experimental confounders, unbiased methods for integrating and interpreting such multi-dimensional data, and much larger sample sizes than have been applied to date.