Identifying causal regulatory SNPs in ChIP-seq enhancers

被引：31

作者：

Huang, Di ^{[1
]}

Ovcharenko, Ivan ^{[1
]}

机构：

[1] Natl Lib Med, Computat Biol Branch, Natl Ctr Biotechnol Informat, NIH, Bethesda, MD 20892 USA

来源：

NUCLEIC ACIDS RESEARCH | 2015年 / 43卷 / 01期

基金：

美国国家卫生研究院;

关键词：

TRANSCRIPTION FACTOR-BINDING; GENOME-WIDE ASSOCIATION; COMMON HUMAN DISORDERS; LONG-RANGE ENHANCERS; HEPATOCELLULAR-CARCINOMA; COLORECTAL-CANCER; ALPHA-FETOPROTEIN; PROSTATE-CANCER; CELL-TYPES; VARIANTS;

D O I：

10.1093/nar/gku1318

中图分类号：

Q5 [生物化学]; Q7 [分子生物学];

学科分类号：

071010 ; 081704 ;

摘要：

Thousands of non-coding SNPs have been linked to human diseases in the past. The identification of causal alleles within this pool of disease-associated non-coding SNPs is largely impossible due to the inability to accurately quantify the impact of non-coding variation. To overcome this challenge, we developed a computational model that uses ChIP-seq intensity variation in response to non-coding allelic change as a proxy to the quantification of the biological role of non-coding SNPs. We applied this model to HepG2 enhancers and detected 4796 enhancer SNPs capable of disrupting enhancer activity upon allelic change. These SNPs are significantly over-represented in the binding sites of HNF4 and FOXA families of liver transcription factors and liver eQTLs. In addition, these SNPs are strongly associated with liver GWAS traits, including type I diabetes, and are linked to the abnormal levels of HDL and LDL cholesterol. Our model is directly applicable to any enhancer set for mapping causal regulatory SNPs.

引用

页码：225 / 236

页数：12

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