Into the Wild: GWAS Exploration of Non-coding RNAs

Abstract

Genome-wide association studies (GWAS) have proven a fundamental tool to identify common variants associated to complex traits, thus contributing to unveil the genetic components of human disease. Besides, the advent of GWAS contributed to expose unexpected findings that urged to redefine the framework of population genetics. First, loci identified by GWAS had small effect sizes and could only explain a fraction of the predicted heritability of the traits under study. Second, the majority of GWAS hits mapped within non-coding regions (such as intergenic or intronic regions) where new functional RNA species (such as lncRNAs or circRNAs) have started to emerge. Bigger cohorts, meta-analysis and technical improvements in genotyping allowed identification of an increased number of genetic variants associated to coronary artery disease (CAD) and cardiometabolic traits. The challenge remains to infer causal mechanisms by which these variants influence cardiovascular disease development. A tendency to assign potential causal variants preferentially to coding genes close to lead variants contributed to disregard the role of non-coding elements. In recent years, in parallel to an increased knowledge of the non-coding genome, new studies started to characterize disease-associated variants located within non-coding RNA regions. The upcoming of databases integrating single-nucleotide polymorphisms (SNPs) and non-coding RNAs together with novel technologies will hopefully facilitate the discovery of causal non-coding variants associated to disease. This review attempts to summarize the current knowledge of genetic variation within non-coding regions with a focus on long non-coding RNAs that have widespread impact in cardiometabolic diseases.

Zebrafish models of sarcopenia

“…As more teleost fish genomes are being sequenced, Clément et al (2020) were able to identify ∼1,300,000 human and ∼111,000 zebrafish CNEs relying on evolutionary sequence conservation, then to link them to target genes based on a synteny conservation score. As we pointed out in the GWAS section above, it is well recognized that ∼90% of disease-associated SNPs are mapped to non-coding intergenic or intronic regions and are not positioned within protein-coding genes, and therefore are likely to influence gene regulation (Buniello et al, 2019;Giral et al, 2018). In order to validate the function and connection to specific GWAS SNPs, researchers can use the CRISPR/Cas9 system to knock out or mutate conserved CNEs and study their functional role in the associated disease or trait (for example, see Madelaine et al, 2018).…”

STX18-AS1is a Long Noncoding RNA predisposing to Atrial Septal Defect via downregulation ofNKX2-5in differentiating cardiomyocytes

“…Among all disease-associated SNPs, 45% map to lncRNAs, suggesting an important role for these genes in complex disease susceptibility 30 . Relatively few annotated lncRNAs containing GWAS associated 11 SNPs for cardiovascular diseases have been investigated 31 . Recently, the human homolog of the mouse lncRNA Upperhand was found to be a control on expression of the cardiac transcription factor Hand2 and essential for mouse heart development 32 .…”

Two ecotype-related long non-coding RNAs in the environmental control of root growth

“…Moreover, recently, the human LincSNP 2.0 database, which contains 809451 unique disease associated SNPs, 11,6 million of linkage disequilibrium SNPs and 244 545 lncRNAs, identified approximately 45% of disease–associated human SNPs that mapped to non-coding regions of the genome [68]. Some lncRNAs containing SNPs have been recently associated to cardiometabolic traits [69]. Similarly, in plants, the comparison of SNPs observed in fruit transcripts of two tomato cultivars also corresponded to non-coding genomic regions or lncRNA genes [70].…”