Spatial Clustering of de Novo Missense Mutations Identifies Candidate Neurodevelopmental Disorder-Associated Genes

Abstract

SummaryHaploinsufficiency (HI) is the best characterized mechanism through which dominant mutations exert their effect and cause disease. Non-haploinsufficiency (NHI) mechanisms, such as gain-of-function and dominant-negative mechanisms, are often characterized by the spatial clustering of mutations, thereby affecting only particular regions or base pairs of a gene. Variants leading to haploinsufficency might occasionally cluster as well, for example in critical domains, but such clustering is on the whole less pronounced with mutations often spread throughout the gene. Here we exploit this property and develop a method to specifically identify genes with significant spatial clustering patterns of de novo mutations in large cohorts. We apply our method to a dataset of 4,061 de novo missense mutations from published exome studies of trios with intellectual disability and developmental disorders (ID/DD) and successfully identify 15 genes with clustering mutations, including 12 genes for which mutations are known to cause neurodevelopmental disorders. For 11 out of these 12, NHI mutation mechanisms have been reported. Additionally, we identify three candidate ID/DD-associated genes of which two have an established role in neuronal processes. We further observe a higher intolerance to normal genetic variation of the identified genes compared to known genes for which mutations lead to HI. Finally, 3D modeling of these mutations on their protein structures shows that 81% of the observed mutations are unlikely to affect the overall structural integrity and that they therefore most likely act through a mechanism other than HI.De novo mutations affecting protein-coding genes are a major cause of intellectual disability (ID) and other developmental disorders (DDs). We downloaded all DNMs occurring in individuals with ID/DD from de novo-db version 1.3 14 identified through WES and whole genome sequencing which were then reannotated with our in-house variant annotation pipeline. The de novo mutations included in the analysis were previously validated by a second independent method or showed a high validation rate for a subset of de novo mutations. In addition, we added 1,183 de novo variants identified in the exomes of an in-house ID cohort that was previously published. 8 To further reduce the risk of including sequencing artifacts and/or genotyping errors, we excluded all de novo variants that were present more than once in the ExAC dataset (Table S1). 15 These efforts resulted in 6,495 protein coding DNMs, including 4,061 missense mutations, in 5,302 individuals with ID/DD (Table S2). We set out to determine for any gene whether the observed de novo missense mutations cluster more than expected compared to random permutations. Hereto, we selected for each the longest representative transcript (i.e., part of the GENCODE basic set) 16 and calculated the geometric mean distance d g over all missense DNMs on

Okur‐Chung neurodevelopmental syndrome: Eight additional cases with implications on phenotype and genotype expansion

“…27 In addition, most of the reported variations are located on the surface of the molecule, and are associated with non-haploinsufficient mechanisms. 28 Two variants were found recurrently in both cohorts. First, the p. Both males and females are affected equally as it would be expected in an autosomal variation.…”

Causes and effects of haploinsufficiency

“…It has been argued that in cases where different alleles of the same gene may be HI or dominant negative, HI may be more common, due to a greater number of possible LOF mutations (such as a truncating mutation occurring in the gene) than dominant negative mutations, which appear to have a more limited distribution (Deciphering Developmental Disorders Study, ). HI mutations tend to be less clustered around particularly sensitive regions than dominant negative mutations (Lelieveld et al ., ).…”

Expanding the clinical spectrum associated with PACS2 mutations

“…Latest advances in genome analysis have significantly enabled the discovery of molecular defects underlying neurodevelopmental disorders (NDDs), a clinically heterogeneous group of rare diseases presenting with central nervous system (CNS) malformations often associated with developmental and epileptic encephalopathies (DEEs) . Among the genes that have recently been implicated in DEEs, PACS1 (phosphofurin acid cluster sortin protein 1, OMIM 607492), encoding a trans ‐Golgi‐membrane traffic regulator highly expressed during human embryonic brain development, has been implicated in Schuurs‐Hoeijmakers syndrome (OMIM 615009), a dominantly inherited DEE with recognizable gestalt and brain structural abnormalities .…”