Mapping cis- and trans-regulatory effects across multiple tissues in twins

By E. Grundberg, K. Small, Å. Hedman, Alexandra C. Nica, A. Buil, S. Keildson, Jordana T. Bell, Tsun-Po Yang, Eshwar Meduri, Amy Barrett and 41 more. Nature Genetics, 2012

807 citations recorded by the source corpus.

Sequence-based variation in gene expression is a key driver of disease risk. Common variants regulating expression in cis have been mapped in many expression quantitative trait locus (eQTL) studies, typically in single tissues from unrelated individuals. Here, we present a comprehensive analysis of gene expression across multiple tissues conducted in a large set of mono- and dizygotic twins that allows systematic dissection of genetic (cis and trans) and non-genetic effects on gene expression. Using identity-by-descent estimates, we show that at least 40% of the total heritable cis effect on expression cannot be accounted for by common cis variants, a finding that reveals the contribution of low-frequency and rare regulatory variants with respect to both transcriptional regulation and complex trait susceptibility. We show that a substantial proportion of gene expression heritability is trans to the structural gene, and we identify several replicating trans variants that act predominantly in a tissue-restricted manner and may regulate the transcription of many genes.

Subfields: Genetics, Public Health, Environmental and Occupational Health

View Paper: https://www.semanticscholar.org/paper/406f2845ee8de02ac8b72069e8a6fe1376c88278

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Citations in the corpus

• A comprehensive 1000 Genomes-based genome-wide association meta-analysis of coronary artery disease (2015, neutral): “…with SNP rs93138 showing strong association with CAD ( P = 5.5 × 10 −8 ) and being a cis eQTL for SWAP70 in naive and challenged monocytes 28 , fat 29 , skin 29 and lung 22 ( Supplementary Table 14 ); three of the linked SNPs (rs93138, rs173396 and rs472109) are intronic and lie within ENCODE…”
• RNA Sequencing and Analysis (2015, neutral): “For instance, several studies have performed eQTL analysis across multiple tissues, indicating that genetic regulatory elements can have tissue-specific effects (Petretto et al. 2006; Schadt et al. 2008; Dimas et al. 2009; Kwan et al. 2009; Grundberg et al. 2012; Flutre et al. 2013).”
• Innate Immune Activity Conditions the Effect of Regulatory Variants upon Monocyte Gene Expression (2014, background): “The resolution of trans-acting genetic factors and associated gene networks is recognized to be highly informative but challenging (19, 28, 53).”
• An atlas of genetic influences on human blood metabolites (2014, neutral): “20 GADL1 (25) SLC6A20 (26) TKT (27) SUCLG2 (28)”
• Modelling local gene networks increases power to detect trans-acting genetic effects on gene expression (2016, methodology): “Despite these limitations to map trans eQTLs, heritability estimates suggest that collectively trans genetic effects explain a substantial proportion of the overall gene expression variance [15, 19], which cannot be explained by cis eQTLs.”