ArticleAmerican journal of human genetics2020
Promoter CpG Density Predicts Downstream Gene Loss-of-Function Intolerance.
Article in American journal of human genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Federated learning for the pathogenicity annotation of genetic variants in multi-site clinical settings.Bioinformatics (Oxford, England) · 2025Article
- Epigenomic insights into common human disease pathology.Cellular and molecular life sciences : CMLS · 2024Review
- Bayesian estimation of gene constraint from an evolutionary model with gene features.bioRxiv : the preprint server for biology · 2024Article
- Epigenetic dynamics during capacitation of naïve human pluripotent stem cells.Science advances · 2023Article
- An unsupervised deep learning framework for predicting human essential genes from population and functional genomic data.BMC bioinformatics · 2023Article
- Bayesian estimation of gene constraint from an evolutionary model with gene features.Research square · 2023Article
- DNMT3B overexpression downregulates genes with CpG islands, common motifs, and transcription factor binding sites that interact with DNMT3B.Scientific reports · 2022Article
- Systematic analysis and prediction of genes associated with monogenic disorders on human chromosome X.Nature communications · 2022Article
- Prioritizing non-coding regions based on human genomic constraint and sequence context with deep learning.Nature communications · 2021Article
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3 authors.
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Abstract
The aggregation and joint analysis of large numbers of exome sequences has recently made it possible to derive estimates of intolerance to loss-of-function (LoF) variation for human genes. Here, we demonstrate strong and widespread coupling between genic LoF intolerance and promoter CpG density across the human genome. Genes downstream of the most CpG-rich promoters (top 10% CpG density) have a 67.2% probability of being highly LoF intolerant, using the LOEUF metric from gnomAD. This is in contrast to 7.4% of genes downstream of the most CpG-poor (bottom 10% CpG density) promoters. Combining promoter CpG density with exonic and promoter conservation explains 33.4% of the variation in LOEUF, and the contribution of CpG density exceeds the individual contributions of exonic and promoter conservation. We leverage this to train a simple and easily interpretable predictive model that outperforms other existing predictors and allows us to classify 1,760 genes-which are currently unascertained in gnomAD-as highly LoF intolerant or not. These predictions have the potential to aid in the interpretation of novel variants in the clinical setting. Moreover, our results reveal that high CpG density is not merely a generic feature of human promoters but is preferentially encountered at the promoters of the most selectively constrained genes, calling into question the prevailing view that CpG islands are not subject to selection.
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