DiseaseEnhancer: a resource of human disease-associated enhancer catalog

Zhang, Guanxiong; Shi, Jian; Zhu, Shiwei; Lan, Yujia; Xu, Liwen; Yuan, Huating; Liao, Gaoming; Liu, Xiaoqin; Zhang, Yunpeng; Xiao, Yun; Li, Xia

doi:10.1093/nar/gkx920

Cited by 74 publications

(59 citation statements)

References 36 publications

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“…To analyze the LoF-tolerance scores for different types of diseases, we extracted a set of disease-associated enhancers from the manually curated DiseaseEnhancer database [74]. This database contains a mixture of enhancers with disease associations and a subset with causal links to disease since the authors looked for multiple evidences, including mechanistic characterization of genetic alterations such as disruption of TF binding [74]. While keeping this limitation in mind, we examined the LoF-tolerance scores predicted by our model for the 90 disease enhancers matched in MegaNet (Methods).…”

Section: Predicted Low-lof-tolerance Enhancers and Disease Riskmentioning

confidence: 99%

Loss-of-function tolerance of enhancers in the human genome

Gökçümen

Khurana

2020

PLoS Genet

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Previous studies have surveyed the potential impact of loss-of-function (LoF) variants and identified LoF-tolerant protein-coding genes. However, the tolerance of human genomes to losing enhancers has not yet been evaluated. Here we present the catalog of LoF-tolerant enhancers using structural variants from whole-genome sequences. Using a conservative approach, we estimate that individual human genomes possess at least 28 LoF-tolerant enhancers on average. We assessed the properties of LoF-tolerant enhancers in a unified regulatory network constructed by integrating tissue-specific enhancers and gene-gene interactions. We find that LoF-tolerant enhancers tend to be more tissue-specific and regulate fewer and more dispensable genes relative to other enhancers. They are enriched in immune-related cells while enhancers with low LoF-tolerance are enriched in kidney and brain/neuronal stem cells. We developed a supervised learning approach to predict the LoFtolerance of all enhancers, which achieved an area under the receiver operating characteristics curve (AUROC) of 98%. We predict 3,519 more enhancers would be likely tolerant to LoF and 129 enhancers that would have low LoF-tolerance. Our predictions are supported by a known set of disease enhancers and novel deletions from PacBio sequencing. The LoF-tolerance scores provided here will serve as an important reference for disease studies. Author summaryEnhancers are elements where transcription factors bind and regulate the expression of protein-coding genes. Although multiple previous studies have focused on which genes can tolerate loss-of-function (LoF), none has systematically evaluated the tolerance of all enhancers in the human genome to LoF. Individual studies have shown a broad range of phenotypic effects of enhancer LoF. The phenotypic effects of enhancer LoF likely fall into a spectrum where deletion of LoF-tolerant enhancers would not elicit substantial phenotypic impact, while some enhancers are likely to cause fitness defects when deleted. Here PLOS GENETICSPLOS Genetics | https://doi.

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Section: Predicted Low-lof-tolerance Enhancers and Disease Riskmentioning

confidence: 99%

Loss-of-function tolerance of enhancers in the human genome

Gökçümen

Khurana

2020

PLoS Genet

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“…The positive set was compiled from the DiseaseEnhancer database (Version1.0.1) [7], which manually collected 847 disease-associated enhancers and their associated variants. Enhancers with multiple variants or indels were eliminated to restrict our set to single nucleotide substitutions.…”

Section: Experimental Datasetsmentioning

confidence: 99%

“…To highlight the usefulness and performance of IPEV, we reanalyzed the experimentally validated pathogenic enhancer-variant pairs in the updated DiseaseEnhancer (version 1.0.2) [7], which were not presented in the training set. Since the majority of enhancer-variant pairs in the updated DiseaseEnhancer were derived from breast cancer, we thus used these variants as independent test set.…”

Section: Ipev Could Predict Deleterious Regulatory Variants In Enhancersmentioning

confidence: 99%

IPEV: a web server for inferring pathogenic enhancers with variants

Zhang¹,

Xie²,

Bai³

et al. 2019

Preprint

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Background Enhancer has been recognized as an important driver whose genetic alterations contribute to disease progression. However, there is still no easy-to-use tools to identify pathogenic enhancers, allowing for deciphering functional influence of genetic variants on enhancer. Results We developed a user-friendly one-stop shop platform, named inferring pathogenic enhancer with variant (IPEV), only requiring variants as input, to quickly infer the pathogenic enhancers that harbor variants affecting their activities. Results of IPEV are explored in an interactive, user-friendly web environment, which is designed to highlight the most probable pathogenic enhancers and their target genes. Furthermore, IPEV provides intuitive visualizations of how a variant affects the corresponding enhancer activity by mediating TF binding changes. Conclusions IPEV is specially designed to prioritize the potentially pathogenic enhancers with genetic variants, and provides intuitive visualizations how a variant affects the corresponding enhancer activity by mediating which transcription factor binding changes. The use of IPEV does not require any specialized computer skills. We believe that IPEV will be useful in interpreting non-coding variants by the inferring pathogenic enhancers. It is freely available at http://biocc.hrbmu.edu.cn/IPEV/ or http://210.46.80.168/IPEV and supports recent versions of all major browsers.

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“…Disease enhancers were collected from Zhang et al (Zhang et al 2018). We intersected our enhancers with the 1,059 disease enhancers which defined in Zhang et al, if no overlap found then take the closest neighbored enhancer.…”

Section: Disease Enhancersmentioning

confidence: 99%

Loss-of-function tolerance of enhancers in the human genome

Gökçümen

Khurana

2019

Preprint

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AbstractPrevious studies have surveyed the potential impact of loss-of-function (LoF) variants and identified LoF-tolerant protein-coding genes. However, the tolerance of human genomes to losing enhancers has not yet been evaluated. Here we present the catalog of LoF-tolerant enhancers using structural variants from whole-genome sequences. Using a conservative approach, we estimate that each individual human genome possesses at least 28 LoF-tolerant enhancers on average. We assessed the properties of LoF-tolerant enhancers in a unified regulatory network constructed by integrating tissue-specific enhancers and gene-gene interactions. We find that LoF-tolerant enhancers are more tissue-specific and regulate fewer and more dispensable genes. They are enriched in immune-related cells while LoF-intolerant enhancers are enriched in kidney and brain/neuronal stem cells. We developed a supervised learning approach to predict the LoF-tolerance of enhancers, which achieved an AUROC of 96%. We predict 5,677 more enhancers would be likely tolerant to LoF and 75 enhancers that would be highly LoF-intolerant. Our predictions are supported by known set of disease enhancers and novel deletions from PacBio sequencing. The LoF-tolerance scores provided here will serve as an important reference for disease studies.

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DiseaseEnhancer: a resource of human disease-associated enhancer catalog

Cited by 74 publications

References 36 publications

Loss-of-function tolerance of enhancers in the human genome

Loss-of-function tolerance of enhancers in the human genome

IPEV: a web server for inferring pathogenic enhancers with variants

Loss-of-function tolerance of enhancers in the human genome

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