Genomics

Dataset Information

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Identification of Functional Lung Cancer Risk-Associated SNPs through Examination of Allele-Specific Effects [WGBS]


ABSTRACT: Lung cancer is the leading cause of cancer death. To date, many SNPs have been found associated with lung cancer risk through genome-wide association studies (GWAS). However, since most GWAS SNPs lie in non-coding regions and are co-inherited with hundreds of SNPs in linkage disequilibrium (LD), which SNP(s) play a causal role in the disease remains poorly understood. Here we aim to identify causal SNPs associated with lung cancer risk through investigating allele-specific effects (ASE). By integrating data from 374 sequencing experiments (including ChIP-seq, DNase-seq, ATAC-seq, and FAIRE-seq) performed in 71 lung-relevant cells, we found 30 lung cancer risk-associated SNPs that showed ASE. Of particular interest, seven SNPs from four loci (12p13.33, 5p15.33, 6p21.33, 22q12.22) were also found as the top-ranked SNPs in fine mapping studies, lending statistical support to our hypothesis that SNPs showing ASE are strong candidates for causal SNPs. Three SNPs, rs11571379, rs7725218, and rs3101018, showed allele-specific enhancer/promoter activities in luciferase reporter assays, supporting their causal roles. Predictions of transcription factor (TF) binding sites and target genes suggest that allele-specific binding of TFs to rs11571379, rs7725218, and rs3101018 regulates the expression of RAD52, TERT and C4A respectively, which could contribute to lung cancer risk through a variety of mechanisms. In conclusion, we have performed a comprehensive ASE evaluation of lung cancer risk-associated SNPs. Our findings highlight three potential causal SNPs and provide insights into the mechanism of by which these risk loci can contribute to lung cancer. This dataset contains the whole-genome bisulfite sequencing data from AECs used to call SNPtypes. Overall design: WGBS data from 3 individuals experiments were used to determine allele-specific effects of SNPs on functional epigenomes This dataset presents methylation domain calling data.

INSTRUMENT(S): Illumina HiSeq 2000 (Homo sapiens)

ORGANISM(S): Homo Sapiens

SUBMITTER: Crystal N Marconett 

PROVIDER: GSE92362 | GEO | 2019-12-31

REPOSITORIES: GEO