Systematic analysis of the effects of genetic variants on chromatin accessibility to decipher functional variants in non-coding regions

• Published in: Frontiers in oncology 2022-10, Vol.12, p.1035855-1035855
• Main Authors: Wang, Dongyang, Wu, Xiaohong, Jiang, Guanghui, Yang, Jianye, Yu, Zhanhui, Yang, Yanbo, Yang, Wenqian, Niu, Xiaohui, Tang, Ke, Gong, Jing
• Format: Article
• Language: English
• Subjects: Breast cancer; caQTL; Chromatin accessibility; Oncology; Quantitative trait locus; Single nucleotide polymorphism
• ISSN: 2234-943X; 2234-943X
• DOI: 10.3389/fonc.2022.1035855

Genome-wide association study (GWAS) has identified thousands of single nucleotide polymorphisms (SNPs) associated with complex diseases and traits. However, deciphering the functions of these SNPs still faces challenges. Recent studies have shown that SNPs could alter chromatin accessibility and result in differences in tumor susceptibility between individuals. Therefore, systematically analyzing the effects of SNPs on chromatin accessibility could help decipher the functions of SNPs, especially those in non-coding regions. Using data from The Cancer Genome Atlas (TCGA), chromatin accessibility quantitative trait locus (caQTL) analysis was conducted to estimate the associations between genetic variants and chromatin accessibility. We analyzed caQTLs in 23 human cancer types and identified 9,478 caQTLs in breast carcinoma (BRCA). In BRCA, these caQTLs tend to alter the binding affinity of transcription factors, and open chromatin regions regulated by these caQTLs are enriched in regulatory elements. By integrating with eQTL data, we identified 141 caQTLs showing a strong signal for colocalization with eQTLs. We also identified 173 caQTLs in genome-wide association studies (GWAS) loci and inferred several possible target genes of these caQTLs. By performing survival analysis, we found that ~10% caQTLs potentially influence the prognosis of patients. To facilitate access to relevant data, we developed a user-friendly data portal, BCaQTL ( http://gong_lab.hzau.edu.cn/caqtl_database ), for data searching and downloading. Our work may facilitate fine-map regulatory mechanisms underlying risk loci of cancer and discover the biomarkers or therapeutic targets for cancer prognosis. The BCaQTL database will be an important resource for genetic and epigenetic studies.