Mapping eQTLs with RNA-seq reveals novel susceptibility genes, non-coding RNAs and alternative-splicing events in systemic lupus erythematosus

Abstract

Studies attempting to functionally interpret complex-disease susceptibility loci by GWAS and eQTL integration have predominantly employed microarrays to quantify gene-expression. RNA-Seq has the potential to discover a more comprehensive set of eQTLs and illuminate the underlying molecular consequence. We examine the functional outcome of 39 variants associated with Systemic Lupus Erythematosus (SLE) through the integration of GWAS and eQTL data from the TwinsUK microarray and RNA-Seq cohort in lymphoblastoid cell lines. We use conditional analysis and a Bayesian colocalisation method to provide evidence of a shared causal-variant, then compare the ability of each quantification type to detect disease relevant eQTLs and eGenes. We discovered the greatest frequency of candidate-causal eQTLs using exon-level RNA-Seq, and identified novel SLE susceptibility genes (e.g. NADSYN1 and TCF7) that were concealed using microarrays, including four non-coding RNAs. Many of these eQTLs were found to influence the expression of several genes, supporting the notion that risk haplotypes may harbour multiple functional effects. Novel SLE associated splicing events were identified in the T-reg restricted transcription factor, IKZF2, and other candidate genes (e.g. WDFY4) through asQTL mapping using the Geuvadis cohort. We have significantly increased our understanding of the genetic control of gene-expression in SLE by maximising the leverage of RNA-Seq and performing integrative GWAS-eQTL analysis against gene, exon, and splice-junction quantifications. We conclude that to better understand the true functional consequence of regulatory variants, quantification by RNA-Seq should be performed at the exon-level as a minimum, and run in parallel with gene and splice-junction level quantification.

Splicing variant of WDFY4 augments MDA5 signalling and the risk of clinically amyopathic dermatomyositis

“…A recent study reported that the SLE risk variant (rs2663052) also had a splicing QTL effect on WDFY4. 44 However, rs2663052 is not in tight LD with the CADM risk variant (rs7919656, r 2 =0.46 in the Asian samples), and rs2663052 displayed a weaker association signal in CADM in the present study (P=0.0012). A missense variant (rs7097397), which is in moderate LD with rs7919656 (r 2 =0.58 in the Asian samples), may be another candidate causal variant in SLE,42 but the association in CADM was moderate (P=0.0022).…”

Lessons learned from twins in autoimmune and chronic inflammatory diseases

“…DNA demethylation has been found in SLE CD4 þ T cells, but not in either CD8þT cells or other mononuclear white blood cells [71,72]. Moreover, an impaired DNA methylation of the inactive X-chromosome was suggested to explain, at least in part, the female prevalence of the disease micro-and long non-coding RNA expression are though to contribute to the pathogenesis of SLE [73]. Since SLE, as most autoimmune diseases, is characterized by a female predominance, the X chromosome was hypothesized to be involved in the disease pathogenesis, as in other autoimmune diseases [74,75].…”

Pathogenesis of Human Systemic Lupus Erythematosus: A Cellular Perspective

“…Although the number of patients in both studies was not large, an analysis of these groups over time might enable the development of personalized therapies for SLE patients [22]. Furthermore, the emergence of next-generation sequencing technologies such as RNA sequencing has provided higher resolution in gene expression measurements together with identification of alternative splicing events, noncoding RNAs, and novel loci in SLE [23]. Technological advances including deep sequencing have offered novel high-throughput platforms that will help to decipher the molecular pathways contributing to SLE pathogenesis.…”