Post-zygotic Point Mutations Are an Underrecognized Source of De Novo Genomic Variation

Acuña-Hidalgo, Rocío; Bo, Tan; Kwint, Michael; Vorst, Maartje van de; Pinelli, Michele; Veltman, Joris A.; Hoischen, Alexander; Vissers, Lisenka E.L.M.; Gilissen, Christian

doi:10.1016/j.ajhg.2015.05.008

Cited by 223 publications

(224 citation statements)

References 33 publications

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“…A number of recent reports have demonstrated that PMMs are relatively common in both healthy and neurodevelopmental disorder cohorts, including intellectual disability, ASD, or general developmental delays. 2,26,46,59,60 However, how frequent and widespread these events might be in early and/or late development and how much risk they contribute to complex disorders has yet to be fully elucidated. We found evidence for 11% of SNVs and 26% of indels previously reported as de novo mutations from the SSC Total number of genes differs from full lists as we used only genes that we were able to map to our gene symbol annotations and genes on sex chromosomes were excluded.…”

Section: Discussionmentioning

confidence: 99%

“…2 A similar analysis of de novo mutations identified from whole-genome sequencing of simplex ID trios validated 6.5% (7/107) as PMMs. 26 We reasoned that re-analyzing the WES data systematically with approaches tuned to detect PMMs would reveal novel mutations, especially those with lower AFs (<20%). We developed a SNV calling approach to detect PMMs without matched normal data but in the context of nuclear families ( Figure 1E).…”

Section: Discussionmentioning

confidence: 99%

“…2 A similar observation has been made from de novo mutations identified in wholegenome sequencing from simplex intellectual disability (ID) trios. 26 However, the mutation calling approaches used previously were tuned to detect GDMs. Here, we systematically evaluate the role of PMMs in ASD by leveraging a harmonized dataset 12 of existing whole-exome sequences (WES) from a well-characterized cohort of $2,300 families-the Simons Simplex Collection (SSC), including parents, probands, and unaffected siblings.…”

Section: Introductionmentioning

confidence: 99%

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Exonic Mosaic Mutations Contribute Risk for Autism Spectrum Disorder

Krupp

Barnard

Duffourd

et al. 2017

Preprint

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Genetic risk factors for autism spectrum disorder (ASD) have yet to be fully elucidated. Postzygotic mosaic mutations (PMMs) have been implicated in several neurodevelopmental disorders and overgrowth syndromes. By leveraging whole-exome sequencing data on a large family-based ASD cohort, the Simons Simplex Collection, we systematically evaluated the potential role of PMMs in autism risk. Initial re-evaluation of published single-nucleotide variant (SNV) de novo mutations showed evidence consistent with putative PMMs for 11% of mutations. We developed a robust and sensitive SNV PMM calling approach integrating complementary callers, logistic regression modeling, and additional heuristics. In our high-confidence call set, we identified 470 PMMs in children, increasing the proportion of mosaic SNVs to 22%. Probands have a significant burden of synonymous PMMs and these mutations are enriched for computationally predicted impacts on splicing. Evidence of increased missense PMM burden was not seen in the full cohort. However, missense burden signal increased in subcohorts of families where probands lacked nonsynonymous germline mutations, especially in genes intolerant to mutations. Parental mosaic mutations that were transmitted account for 6.8% of the presumed de novo mutations in the children. PMMs were identified in previously implicated high-confidence neurodevelopmental disorder risk genes, such as CHD2, CTNNB1, SCN2A, and SYNGAP1, as well as candidate risk genes with predicted functions in chromatin remodeling or neurodevelopment, including ACTL6B, BAZ2B, COL5A3, SSRP1, and UNC79. We estimate that PMMs potentially contribute risk to 3%-4% of simplex ASD case subjects and future studies of PMMs in ASD and related disorders are warranted.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Exonic Mosaic Mutations Contribute Risk for Autism Spectrum Disorder

Krupp

Barnard

Duffourd

et al. 2017

Preprint

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“…Nevertheless, it might be possible that siblings of affected individuals were included who share a DNM due to parental gonadal mosaicism. 34 Alternatively, DNMs might occur multiple times in disease cohorts as a consequence of a locally increased mutation rate. Examples of the latter might for instance incur a selective growth advantage (i.e., selfish mutations 35 ) and thereby result for FGFR2 (MIM 176943) mutations in Apert syndrome (MIM 101200).…”

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confidence: 99%

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

Lelieveld

Wiel

Venselaar

et al. 2017

The American Journal of Human Genetics

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101

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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

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“…An unknown proportion of mutations categorized as de novo may in fact result from unrecognized parental mosaicism 20. Asymptomatic parental somatic mosaicism has recently been identified by NGS and reported for a number of rare diseases such as Alport syndrome, tuberous sclerosis, and Dravet syndrome 22, 23, 24, 25.…”

Section: Discussionmentioning

confidence: 99%