ncRNA-eQTL: a database to systematically evaluate the effects of SNPs on non-coding RNA expression across cancer types

Abstract

Numerous studies indicate that non-coding RNAs (ncRNAs) have critical functions across biological processes, and single-nucleotide polymorphisms (SNPs) could contribute to diseases or traits through influencing ncRNA expression. However, the associations between SNPs and ncRNA expression are largely unknown. Therefore, genome-wide expression quantitative trait loci (eQTL) analysis to assess the effects of SNPs on ncRNA expression, especially in multiple cancer types, will help to understand how risk alleles contribute toward tumorigenesis and cancer development. Using genotype data and expression profiles of ncRNAs of >8700 samples from The Cancer Genome Atlas (TCGA), we developed a computational pipeline to systematically identify ncRNA-related eQTLs (ncRNA-eQTLs) across 33 cancer types. We identified a total of 6 133 278 and 721 122 eQTL-ncRNA pairs in cis-eQTL and trans-eQTL analyses, respectively. Further survival analyses identified 8312 eQTLs associated with patient survival times. Furthermore, we linked ncRNA-eQTLs to genome-wide association study (GWAS) data and found 262 332 ncRNA-eQTLs overlapping with known disease- and trait-associated loci. Finally, a user-friendly database, ncRNA-eQTL (http://ibi.hzau.edu.cn/ncRNA-eQTL), was developed for free searching, browsing and downloading of all ncRNA-eQTLs. We anticipate that such an integrative and comprehensive resource will improve our understanding of the mechanistic basis of human complex phenotypic variation, especially for ncRNA- and cancer-related studies.

Cis- and Trans-Acting Expression Quantitative Trait Loci of Long Non-Coding RNA in 2,549 Cancers With Potential Clinical and Therapeutic Implications

“…Such differences might be attributed to the different selection pressure in mammals (55) or different regulatory mechanisms underlying these two types of transcripts (56). Furthermore, the current data showed a significant higher enrichment of cancer risk loci in the eQTLs of lncRNAs than in those of mRNA in cancer, which is consistent with a previous study (26).…”

“…While mapping the eQTLs in cancer, we accounted for different confounding effects (such as PEERs, SCNA, DNA methylations). Thus, our model is more stringent than those reported previously (11,26), and the eQTLs directly interfered with the regulome of cancers. In addition, we demonstrated that the genomic landscape of cis-eQTLs of lncRNA was similar to that of the cis-eQTLs of mRNA.…”

“…These methods have yielded valuable associations between germline variants and gene expression in cancer. Recent studies have reported eQTLs for various non-coding transcripts (lncRNA and miRNA) in human cancers (11,26). Moreover, study of Xia et al demonstrated that lncRNAs are active participants in immune regulation in 33 cancer types (23).…”

Population variation in miRNAs and isomiRs and their impact on human immunity to infection

“…Studies of miRNA abundance across various cell types and tissues have allowed characterizing the extent of genetic regulation of miRNA expression variability, i.e., miRNA expression quantitative trait loci (miR-QTLs), and highlighted the role of genetic variants located in the promoter of the precursor transcript of the miRNA (pri-miRNAs) in shaping inter-individual differences in miRNA expression [8,[12][13][14][15][16][17][18][19]. In the context of immunity, despite increasing evidence that marked population differences exist in the mRNA response to immune challenges [20,21], the extent to which miRNA responses to infection vary across individuals of different ancestry remains largely unknown.…”

Population variation of miRNAs and isomiRs and their impact on human immunity to infection

“…Studies of miRNA abundance across various cell types and tissues have allowed the characterization of the extent of genetic regulation of miRNA expression variability, i.e., miRNA expression quantitative trait loci (miR-QTLs), and highlighted the role of genetic variants located in the promoter of the precursor transcript of the miRNA (pri-miRNAs) in shaping inter-individual differences in miRNA expression (Borel et al 2011;Gamazon et al 2012;Parts et al 2012;Lappalainen et al 2013;Siddle et al 2014;Huan et al 2015;Budach et al 2016;Gottmann et al 2018;Li et al 2020). In the context of immunity, despite increasing evidence that marked population differences exist in the mRNA response to immune challenges Quach et al 2016), the extent to which miRNA responses to infection vary across individuals of different ancestry remains largely unknown.…”