Strategies for activity analysis of single nucleotide polymorphisms associated with human diseases. Issue 4 (25th December 2022)

• Record Type: Journal Article
• Authors: Ren, Naixia; Dai, Shangkun; Ma, Shumin; Yang, Fengtang
• Is Part Of: Clinical genetics. Volume 103:Issue 4(2023)
• Page Start: 392
• Page End: 400
• Publication Date: 2022-12-25
• Subjects: activity analysis -- GWAS -- human diseases -- personalized medicine -- SNPs; Medical genetics -- Periodicals; 616.0420
• DOI: 10.1111/cge.14282
• Languages: English
• ISSNs: 0009-9163

Abstract

Abstract: Genome‐wide association studies (GWAS) have identified a large number of single nucleotide polymorphism (SNP) sites associated with human diseases. In the annotation of human diseases, especially cancers, SNPs, as an important component of genetic factors, have gained increasing attention. Given that most of the SNPs are located in non‐coding regions, the functional verification of these SNPs is a great challenge. The key to functional annotation for risk SNPs is to screen SNPs with regulatory activity from thousands of disease associated‐SNPs. In this review, we systematically recapitulate the characteristics and functional roles of SNP sites, discuss three parallel reporter screening strategies in detail based on barcode tag classification, and recommend the common in silico strategies to help supplement the annotation of SNP sites with epigenetic activity analysis, prediction of target genes and trans‐acting factors. We hope that this review will contribute to this exuberant research field by providing robust activity analysis strategies that can facilitate the translation of GWAS results into personalized diagnosis and prevention measures for human diseases. Abstract : Causal single nucleotide polymorphisms (SNPs) associated with human diseases usually play a regulatory role. Analyzing strategies is an essential step before the regulatory mechanisms verification. This review systematically recapitulates different strategies for activity analysis of SNPs associated with human diseases.