Genetic Analysis of Human Traits In Vitro: Drug Response and Gene Expression in Lymphoblastoid Cell Lines

Edwin Choy,Jacqueline M Slavik,Richa Saxena,Chris Cotsapas,Robert M Plenge,Emmanouil T Dermitzakis,Roman Yelensky,Philip L De Jager,David Altshuler,Cara S Wolfish,Stanley Y Shaw,Elliott Kieff,Ellen Cahir-Mcfarland,Manuel Rivas,Mark J Daly,Sasha Bonakdar,David Hafler

doi:10.1371/journal.pgen.1000287

Abstract

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, including searches for QTLs influencing levels of individual mRNAs and responses to drugs and radiation. In the course of attempting to map genes for drug response using 269 LCLs from the International HapMap Project, we evaluated the extent to which biological noise and non-genetic confounders contribute to trait variability in LCLs. While drug responses could be technically well measured on a given day, we observed significant day-to-day variability and substantial correlation to non-genetic confounders, such as baseline growth rates and metabolic state in culture. After correcting for these confounders, we were unable to detect any QTLs with genome-wide significance for drug response. A much higher proportion of variance in mRNA levels may be attributed to non-genetic factors (intra-individual variance—i.e., biological noise, levels of the EBV virus used to transform the cells, ATP levels) than to detectable eQTLs. Finally, in an attempt to improve power, we focused analysis on those genes that had both detectable eQTLs and correlation to drug response; we were unable to detect evidence that eQTL SNPs are convincingly associated with drug response in the model. While LCLs are a promising model for pharmacogenetic experiments, biological noise and in vitro artifacts may reduce power and have the potential to create spurious association due to confounding.

Highlights

Genetic mapping offers an unbiased approach to discover genes and pathways influencing disease traits and responses to drugs and environmental exposures [1]
The use of lymphoblastoid cell lines (LCLs) has evolved from a renewable source of DNA to an in vitro model system to study the genetics of gene expression, drug response, and other traits in a controlled laboratory setting
We found that responses to at least some drugs and levels of many mRNAs can be technically well measured, but vary both across experiments and with nongenetic confounders such as growth rates, EBV levels, and ATP levels

Summary

Introduction

Genetic mapping offers an unbiased approach to discover genes and pathways influencing disease traits and responses to drugs and environmental exposures [1]. There would be great value in a human in vitro model that faithfully reflects both in vivo genetics and physiology while allowing for systematic perturbation and characterization in high throughput Such a model would be useful to study the function of sequence variants mapped by whole genome association studies of common human diseases that do not fall in obvious coding sequences [2,3,4,5,6], many of which are presumed to influence disease traits through subtle effects on gene regulation. LCLs derived from genotyped CEPH pedigrees [14] and HapMap participants [15] were used to identify genomic regions linked to and associated with inter-individual variation in mRNA transcript levels

Methods

Results

Discussion

Conclusion