Abstract
BackgroundThe invention of high throughput sequencing technologies has led to the discoveries of hundreds of thousands of genetic variants associated with thousands of human diseases. Many of these genetic variants are located outside the protein coding regions, and as such, it is challenging to interpret the function of these genetic variants by traditional genetic approaches. Recent genome-wide functional genomics studies, such as FANTOM5 and ENCODE have uncovered a large number of regulatory elements across hundreds of different tissues or cell lines in the human genome. These findings provide an opportunity to study the interaction between regulatory elements and disease-associated genetic variants. Identifying these diseased-related regulatory elements will shed light on understanding the mechanisms of how these variants regulate gene expression and ultimately result in disease formation and progression.ResultsIn this study, we curated and categorized 27,558 Mendelian disease variants, 20,964 complex disease variants, 5,809 cancer predisposing germline variants, and 43,364 recurrent cancer somatic mutations. Compared against nine different types of regulatory regions from FANTOM5 and ENCODE projects, we found that different types of disease variants show distinctive propensity for particular regulatory elements. Mendelian disease variants and recurrent cancer somatic mutations are 22-fold and 10- fold significantly enriched in promoter regions respectively (q<0.001), compared with allele-frequency-matched genomic background. Separate from these two categories, cancer predisposing germline variants are 27-fold enriched in histone modification regions (q<0.001), 10-fold enriched in chromatin physical interaction regions (q<0.001), and 6-fold enriched in transcription promoters (q<0.001). Furthermore, Mendelian disease variants and recurrent cancer somatic mutations share very similar distribution across types of functional effects.We further found that regulatory regions are located within over 50% coding exon regions. Transcription promoters, methylation regions, and transcription insulators have the highest density of disease variants, with 472, 239, and 72 disease variants per one million base pairs, respectively.ConclusionsDisease-associated variants in different disease categories are preferentially located in particular regulatory elements. These results will be useful for an overall understanding about the differences among the pathogenic mechanisms of various disease-associated variants.
Highlights
The invention of high throughput sequencing technologies has led to the discoveries of hundreds of thousands of genetic variants associated with thousands of human diseases
A lot of well-annotated disease-variants have been collected in the Human Gene Mutation Database (HGMD) [6]; these variants are organized into three groups of significant functional disease SNPs, namely coding SNPs, splicing SNPs and regulatory SNPs, which account for ~86%, ~10% and ~3% of variants in HGMD respectively [6,7,8,9]
Compared with 5,809 cancer predisposing germline variants from HGMD professional database [6], 43,364 recurrent cancer somatic mutations were extracted from COSMIC [34]
Summary
The invention of high throughput sequencing technologies has led to the discoveries of hundreds of thousands of genetic variants associated with thousands of human diseases Many of these genetic variants are located outside the protein coding regions, and as such, it is challenging to interpret the function of these genetic variants by traditional genetic approaches. Recent genome-wide functional genomics studies, such as FANTOM5 and ENCODE have uncovered a large number of regulatory elements across hundreds of different tissues or cell lines in the human genome These findings provide an opportunity to study the interaction between regulatory elements and disease-associated genetic variants. Genome-wide association studies (GWAS) [10] identified over ten thousand variants associated with various diseases/traits, ~90% of which localize outside of known protein-coding regions This phenomenon highlights the substantial gap between the plethora of disease- or trait-associated noncoding variants and our understanding of how most of these variants contribute to diseases/traits. This phenomenon highlights the substantial gap between the plethora of disease- or trait-associated noncoding variants and our understanding of how most of these variants contribute to diseases/traits. (Figure S1)
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