Characterising and Predicting Haploinsufficiency in the Human Genome

By N. Huang, Insuk Lee, Edward M. Marcotte, Matthew E. Hurles. PLoS Genetics, 2010

627 citations recorded by the source corpus.

Haploinsufficiency, wherein a single functional copy of a gene is insufficient to maintain normal function, is a major cause of dominant disease. Human disease studies have identified several hundred haploinsufficient (HI) genes. We have compiled a map of 1,079 haplosufficient (HS) genes by systematic identification of genes unambiguously and repeatedly compromised by copy number variation among 8,458 apparently healthy individuals and contrasted the genomic, evolutionary, functional, and network properties between these HS genes and known HI genes. We found that HI genes are typically longer and have more conserved coding sequences and promoters than HS genes. HI genes exhibit higher levels of expression during early development and greater tissue specificity. Moreover, within a probabilistic human functional interaction network HI genes have more interaction partners and greater network proximity to other known HI genes. We built a predictive model on the basis of these differences and annotated 12,443 genes with their predicted probability of being haploinsufficient. We validated these predictions of haploinsufficiency by demonstrating that genes with a high predicted probability of exhibiting haploinsufficiency are enriched among genes implicated in human dominant diseases and among genes causing abnormal phenotypes in heterozygous knockout mice. We have transformed these gene-based haploinsufficiency predictions into haploinsufficiency scores for genic deletions, which we demonstrate to better discriminate between pathogenic and benign deletions than consideration of the deletion size or numbers of genes deleted. These robust predictions of haploinsufficiency support clinical interpretation of novel loss-of-function variants and prioritization of variants and genes for follow-up studies.

Subfields: Water Science and Technology

View Paper: https://www.semanticscholar.org/paper/f613fb44d93d9c108f3ef45d8a709a6b5af8c3e8

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Citations in the corpus

The Intolerance of Regulatory Sequence to Genetic Variation Predicts Gene Dosage Sensitivity (2015, background): “Inversely, genes that tolerate CNVs in the general population are unlikely to be dosage sensitive [21].”
dbNSFP v2.0: A Database of Human Non-synonymous SNVs and Their Functional Predictions and Annotations (2013, methodology): “…(Su et al. 2002) gene expression data from BioMart (Guberman et al. 2011); gene interaction data from IntAct (Kerrien et al. 2011) and BioGRID (Chatr-aryamontri et al. 2012); and estimated probability that the gene is haploinsufficient (Huang et al. 2010) and recessive (MacArthur et al. 2012).”
Mutation severity spectrum of rare alleles in the human genome is predictive of disease type (2019, background): “The 17 gene-level features include three numbers of protein-protein interactions (IntAct, BioGrid, and ConsensusPathDB) [111–113], four experimental measures of gene essentiality [64, 65, 114, 115], four scores of estimated haploinsufficiency (P(HI), HIPred_score and GHIS) [26, 29, 116] or gene esse”