The architecture of gene regulatory variation across multiple human tissues: the MuTHER study.
Nica AC., Parts L., Glass D., Nisbet J., Barrett A., Sekowska M., Travers M., Potter S., Grundberg E., Small K., Hedman AK., Bataille V., Tzenova Bell J., Surdulescu G., Dimas AS., Ingle C., Nestle FO., di Meglio P., Min JL., Wilk A., Hammond CJ., Hassanali N., Yang TP., Montgomery SB., O'Rahilly S., Lindgren CM., Zondervan KT., Soranzo N., Barroso I., Durbin R., Ahmadi K., Deloukas P., McCarthy MI., Dermitzakis ET., Spector TD., MuTHER Consortium None.
While there have been studies exploring regulatory variation in one or more tissues, the complexity of tissue-specificity in multiple primary tissues is not yet well understood. We explore in depth the role of cis-regulatory variation in three human tissues: lymphoblastoid cell lines (LCL), skin, and fat. The samples (156 LCL, 160 skin, 166 fat) were derived simultaneously from a subset of well-phenotyped healthy female twins of the MuTHER resource. We discover an abundance of cis-eQTLs in each tissue similar to previous estimates (858 or 4.7% of genes). In addition, we apply factor analysis (FA) to remove effects of latent variables, thus more than doubling the number of our discoveries (1,822 eQTL genes). The unique study design (Matched Co-Twin Analysis--MCTA) permits immediate replication of eQTLs using co-twins (93%-98%) and validation of the considerable gain in eQTL discovery after FA correction. We highlight the challenges of comparing eQTLs between tissues. After verifying previous significance threshold-based estimates of tissue-specificity, we show their limitations given their dependency on statistical power. We propose that continuous estimates of the proportion of tissue-shared signals and direct comparison of the magnitude of effect on the fold change in expression are essential properties that jointly provide a biologically realistic view of tissue-specificity. Under this framework we demonstrate that 30% of eQTLs are shared among the three tissues studied, while another 29% appear exclusively tissue-specific. However, even among the shared eQTLs, a substantial proportion (10%-20%) have significant differences in the magnitude of fold change between genotypic classes across tissues. Our results underline the need to account for the complexity of eQTL tissue-specificity in an effort to assess consequences of such variants for complex traits.