Distinct epigenomic patterns are associated with haploinsufficiency and predict risk genes of developmental disorders

Han, Xing; Chen, Siying; Flynn, Elise D.; Wu, Shuang; Wintner, Dana; Shen, Yufeng

doi:10.1038/s41467-018-04552-7

Cited by 33 publications

(43 citation statements)

References 46 publications

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“…The updated version of the score of Huang et al (2010) was downloaded from the DECIPHER database (https: //decipher.sanger.ac.uk/files/download s/HI Predictions Version3.bed.gz; accessed November 2019). The scores of Steinberg et al (2015) and Han et al (2018) were downloaded from the supplemental materials of the respective publications. In our comparison we did not include HIPred (Shihab et al, 2017), since it only provides binary haploinsufficiency predictions for a small number of genes.…”

Section: Previously Published Lof-intolerance Predictionsmentioning

confidence: 99%

“…Therefore, the deleterious effects of LoF variants in these genes are often mediated through a reduction of the normal amount of mRNA used for protein production. This in turn, implies that studying the character- istics of regulatory elements controlling the expression of highly LoF-intolerant genes has the potential to yield two important benefits (Han et al, 2018;Wang, Goldstein, 2020). First, it can highlight the features of the most functionally important regulatory elements in the human genome.…”

Section: Introductionmentioning

confidence: 99%

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Promoter CpG density predicts downstream gene loss-of-function intolerance

Boukas

Björnsson

Hansen

2020

Preprint

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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 LoFintolerance 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 currently lack reliable LOEUF estimates -as highly LoF-intolerant or not. These predictions have the potential to aid in the interpretation of novel patient variants. 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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Section: Previously Published Lof-intolerance Predictionsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Promoter CpG density predicts downstream gene loss-of-function intolerance

Boukas

Björnsson

Hansen

2020

Preprint

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“…First, genome-wide metrics of pathogenicity, including those that measure haploinsufficiency (haploinsufficiency score [HI]; essentiality score; genome-wide haploinsufficiency score [GHIS], and EpiScore) [61–64] and resistance to variation (residual variance to intolerance score [RVIS], probability of loss-of-function intolerance [pLI], and maximum constrained coding region [CCR] scores) [65–67], provide evidence for several candidate genes within CNV regions for developmental disorders (Fig 2A, S3 Table). For example, 45 out of 152 genes (30%) within 12 variably expressive CNV regions are intolerant to variation with RVIS metrics in the top 20th genome-wide percentile, similar to that of known neurodevelopmental genes such as CHD8 , NRXN1 , and SCN2A , as well as genes responsible for major features of syndromic CNVs, such as RAI1 and NSD1 (S3 Table).…”

Section: A Case For a Multigenic Model Of Cnv Pathogenicitymentioning

confidence: 99%

An interaction-based model for neuropsychiatric features of copy-number variants

Jensen

Girirajan

2019

PLoS Genet

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Variably expressive copy-number variants (CNVs) are characterized by extensive phenotypic heterogeneity of neuropsychiatric phenotypes. Approaches to identify single causative genes for these phenotypes within each CNV have not been successful. Here, we posit using multiple lines of evidence, including pathogenicity metrics, functional assays of model organisms, and gene expression data, that multiple genes within each CNV region are likely responsible for the observed phenotypes. We propose that candidate genes within each region likely interact with each other through shared pathways to modulate the individual gene phenotypes, emphasizing the genetic complexity of CNV-associated neuropsychiatric features.

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“…Perhaps counter to intuition, long genes are relatively mutation intolerant [Sironi, Menozzi, Comi, Cagliani, et al, ; Han et al, ]. This propensity is partly mechanistic but also a reflection of gene function [Niu & Yang, ].…”

Section: Resultsmentioning

confidence: 99%

Autism risk genes are evolutionarily ancient and maintain a unique feature landscape that echoes their function

et al. 2019

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Previous research on autism risk (ASD), developmental regulatory (DevReg), and central nervous system (CNS) genes suggests they tend to be large in size, enriched in nested repeats, and mutation intolerant. The relevance of these genomic features is intriguing yet poorly understood. In this study, we investigated the feature landscape of these gene groups to discover structural themes useful in interpreting their function, developmental patterns, and evolutionary history. ASD, DevReg, CNS, housekeeping, and whole genome control (WGC) groups were compiled using various resources. Multiple gene features of interest were extracted from NCBI/UCSC Bioinformatics. Residual variation intolerance scores, Exome Aggregation Consortium pLI scores, and copy number variation data from Decipher were used to estimate variation intolerance. Gene age and protein-protein interactions (PPI) were estimated using Ensembl and EBI Intact databases, respectively. Compared to WGC: ASD, DevReg, and CNS genes are longer, produce larger proteins, maintain greater numbers/density of conserved noncoding elements and transposable elements, produce more transcript variants, and are comparatively variation intolerant. After controlling for gene size, mutation tolerance, and clinical association, ASD genes still retain many of these same features. In addition, we also found that ASD genes that are extremely mutation intolerant have larger PPI networks. These data support many of the recent findings within the field of autism genetics but also expand our understanding of the evolution of these broad gene groups, their potential regulatory complexity, and the extent to which they interact with the cellular network.Lay Summary: Autism risk genes are more ancient compared to other genes in the genome. As such, they exhibit physical features related to their age, including long gene and protein size and regulatory sequences that help to control gene expression. They share many of these same features with other genes that are expressed in the brain and/or are associated with prenatal development.

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Distinct epigenomic patterns are associated with haploinsufficiency and predict risk genes of developmental disorders

Cited by 33 publications

References 46 publications

Promoter CpG density predicts downstream gene loss-of-function intolerance

Promoter CpG density predicts downstream gene loss-of-function intolerance

An interaction-based model for neuropsychiatric features of copy-number variants

Autism risk genes are evolutionarily ancient and maintain a unique feature landscape that echoes their function

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