scholarly journals Large-scale targeted sequencing identifies risk genes for neurodevelopmental disorders

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Tianyun Wang ◽  
◽  
Kendra Hoekzema ◽  
Davide Vecchio ◽  
Huidan Wu ◽  
...  
Keyword(s):  
Neurodevelopmental Disorders ◽  
Large Scale ◽  
De Novo ◽  
Targeted Sequencing ◽  
Published Data ◽  
De Novo Mutations ◽  
Risk Genes ◽  
Mutation Burden ◽  
Number Of Patients ◽  
Significant Burden

Abstract Most genes associated with neurodevelopmental disorders (NDDs) were identified with an excess of de novo mutations (DNMs) but the significance in case–control mutation burden analysis is unestablished. Here, we sequence 63 genes in 16,294 NDD cases and an additional 62 genes in 6,211 NDD cases. By combining these with published data, we assess a total of 125 genes in over 16,000 NDD cases and compare the mutation burden to nonpsychiatric controls from ExAC. We identify 48 genes (25 newly reported) showing significant burden of ultra-rare (MAF < 0.01%) gene-disruptive mutations (FDR 5%), six of which reach family-wise error rate (FWER) significance (p < 1.25E−06). Among these 125 targeted genes, we also reevaluate DNM excess in 17,426 NDD trios with 6,499 new autism trios. We identify 90 genes enriched for DNMs (FDR 5%; e.g., GABRG2 and UIMC1); of which, 61 reach FWER significance (p < 3.64E−07; e.g., CASZ1). In addition to doubling the number of patients for many NDD risk genes, we present phenotype–genotype correlations for seven risk genes (CTCF, HNRNPU, KCNQ3, ZBTB18, TCF12, SPEN, and LEO1) based on this large-scale targeted sequencing effort.

scholarly journals Author Correction: Large-scale targeted sequencing identifies risk genes for neurodevelopmental disorders

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Tianyun Wang ◽  
◽  
Kendra Hoekzema ◽  
Davide Vecchio ◽  
Huidan Wu ◽  
...  
Keyword(s):  
Neurodevelopmental Disorders ◽  
Large Scale ◽  
Targeted Sequencing ◽  
Risk Genes

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

scholarly journals Profiling SARS-CoV-2 mutation fingerprints that range from the viral pangenome to individual infection quasispecies

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Billy T. Lau ◽  
Dmitri Pavlichin ◽  
Anna C. Hooker ◽  
Alison Almeda ◽  
Giwon Shin ◽  
...  
Keyword(s):  
De Novo ◽  
Targeted Sequencing ◽  
Contact Tracing ◽  
Clinical Samples ◽  
De Novo Mutations ◽  
Viral Mutation ◽  
Number Of Patients ◽  
Frequent Mutations ◽  
Virus Genomes ◽  
Viral Sequences

Abstract Background The genome of SARS-CoV-2 is susceptible to mutations during viral replication due to the errors generated by RNA-dependent RNA polymerases. These mutations enable the SARS-CoV-2 to evolve into new strains. Viral quasispecies emerge from de novo mutations that occur in individual patients. In combination, these sets of viral mutations provide distinct genetic fingerprints that reveal the patterns of transmission and have utility in contact tracing. Methods Leveraging thousands of sequenced SARS-CoV-2 genomes, we performed a viral pangenome analysis to identify conserved genomic sequences. We used a rapid and highly efficient computational approach that relies on k-mers, short tracts of sequence, instead of conventional sequence alignment. Using this method, we annotated viral mutation signatures that were associated with specific strains. Based on these highly conserved viral sequences, we developed a rapid and highly scalable targeted sequencing assay to identify mutations, detect quasispecies variants, and identify mutation signatures from patients. These results were compared to the pangenome genetic fingerprints. Results We built a k-mer index for thousands of SARS-CoV-2 genomes and identified conserved genomics regions and landscape of mutations across thousands of virus genomes. We delineated mutation profiles spanning common genetic fingerprints (the combination of mutations in a viral assembly) and a combination of mutations that appear in only a small number of patients. We developed a targeted sequencing assay by selecting primers from the conserved viral genome regions to flank frequent mutations. Using a cohort of 100 SARS-CoV-2 clinical samples, we identified genetic fingerprints consisting of strain-specific mutations seen across populations and de novo quasispecies mutations localized to individual infections. We compared the mutation profiles of viral samples undergoing analysis with the features of the pangenome. Conclusions We conducted an analysis for viral mutation profiles that provide the basis of genetic fingerprints. Our study linked pangenome analysis with targeted deep sequenced SARS-CoV-2 clinical samples. We identified quasispecies mutations occurring within individual patients and determined their general prevalence when compared to over 70,000 other strains. Analysis of these genetic fingerprints may provide a way of conducting molecular contact tracing.

scholarly journals Protein phosphatase 2A – structure, function and role in neurodevelopmental disorders

2021 ◽  
Vol 134 (13) ◽  
Author(s):  
Priyanka Sandal ◽  
Chian Ju Jong ◽  
Ronald A. Merrill ◽  
Jianing Song ◽  
Stefan Strack
Keyword(s):  
Neurodevelopmental Disorders ◽  
Protein Phosphatase ◽  
Mammalian Cells ◽  
Large Scale ◽  
De Novo ◽  
Protein Phosphatase 2A ◽  
Cell Types ◽  
De Novo Mutations ◽  
Sequencing Studies ◽  
Phosphatase 2A

ABSTRACT Neurodevelopmental disorders (NDDs), including intellectual disability (ID), autism and schizophrenia, have high socioeconomic impact, yet poorly understood etiologies. A recent surge of large-scale genome or exome sequencing studies has identified a multitude of mostly de novo mutations in subunits of the protein phosphatase 2A (PP2A) holoenzyme that are strongly associated with NDDs. PP2A is responsible for at least 50% of total Ser/Thr dephosphorylation in most cell types and is predominantly found as trimeric holoenzymes composed of catalytic (C), scaffolding (A) and variable regulatory (B) subunits. PP2A can exist in nearly 100 different subunit combinations in mammalian cells, dictating distinct localizations, substrates and regulatory mechanisms. PP2A is well established as a regulator of cell division, growth, and differentiation, and the roles of PP2A in cancer and various neurodegenerative disorders, such as Alzheimer's disease, have been reviewed in detail. This Review summarizes and discusses recent reports on NDDs associated with mutations of PP2A subunits and PP2A-associated proteins. We also discuss the potential impact of these mutations on the structure and function of the PP2A holoenzymes and the etiology of NDDs.

scholarly journals Identification and validation of novel candidate risk genes in endocytic vesicular trafficking associated with esophageal atresia and tracheoesophageal fistulas

2021 ◽  
Author(s):  
Guojie Zhong ◽  
Priyanka Ahimaz ◽  
Nicole A. Edwards ◽  
Jacob J. Hagen ◽  
Christophe Faure ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Congenital Anomalies ◽  
De Novo ◽  
Simulation Analysis ◽  
Loss Of Function ◽  
Developmental Defects ◽  
Risk Genes ◽  
Significant Burden ◽  
Background Mutation Rate ◽  
Complex Cases

Esophageal atresias/tracheoesophageal fistulas (EA/TEF) are rare congenital anomalies caused by aberrant development of the foregut. Previous studies indicate that rare or de novo genetic variants significantly contribute to EA/TEF risk, and most individuals with EA/TEF do not have pathogenic genetic variants in established risk genes. To identify novel genetic contributions to EA/TEF, we performed whole genome sequencing of 185 trios (probands and parents) with EA/TEF, including 59 isolated and 126 complex cases with additional congenital anomalies and/or neurodevelopmental disorders. There was a significant burden of protein altering de novo coding variants in complex cases (p=3.3e-4), especially in genes that are intolerant of loss of function variants in the population. We performed simulation analysis of pathway enrichment based on background mutation rate and identified a number of pathways related to endocytosis and intracellular trafficking that as a group have a significant burden of protein altering de novo variants. We assessed 18 variants for disease causality using CRISPR-Cas9 mutagenesis in Xenopus and confirmed 13 with tracheoesophageal phenotypes. Our results implicate disruption of endosome-mediated epithelial remodeling as a potential mechanism of foregut developmental defects. This research may have implications for the mechanisms of other rare congenital anomalies.

scholarly journals Inherited and multiple de novo mutations in autism/developmental delay risk genes suggest a multifactorial model

2018 ◽  
Vol 9 (1) ◽  
Author(s):  
Hui Guo ◽  
Tianyun Wang ◽  
Huidan Wu ◽  
Min Long ◽  
Bradley P. Coe ◽  
...  
Keyword(s):  
Developmental Delay ◽  
De Novo ◽  
De Novo Mutations ◽  
Risk Genes ◽  
Multifactorial Model

scholarly journals mTADA: a framework for analyzing de novo mutations in multiple traits

2018 ◽  
Author(s):  
Hoang T. Nguyen ◽  
Amanda Dobbyn ◽  
Joseph Buxbaum ◽  
Dalila Pinto ◽  
Shaun M Purcell ◽  
...  
Keyword(s):  
De Novo ◽  
Neuropsychiatric Disorders ◽  
Joint Analysis ◽  
Data Sets ◽  
Analysis Method ◽  
De Novo Mutations ◽  
Multiple Traits ◽  
Risk Genes ◽  
Trait Analysis ◽  
Chd Risk

AbstractJoint analysis of multiple traits can result in the identification of associations not found through the analysis of each trait in isolation. In addition, approaches that consider multiple traits can aid in the characterization of shared genetic etiology among those traits. In recent years, parent-offspring trio studies have reported an enrichment of de novo mutations (DNMs) in neuropsychiatric disorders. The analysis of DNM data in the context of neuropsychiatric disorders has implicated multiple putatively causal genes, and a number of reported genes are shared across disorders. However, a joint analysis method designed to integrate de novo mutation data from multiple studies has yet to be implemented. We here introduce multi pi e-trait TAD A (mTADA) which jointly analyzes two traits using DNMs from non-overlapping family samples. mTADA uses two single-trait analysis data sets to estimate the proportion of overlapping risk genes, and reports genes shared between and specific to the relevant disorders. We applied mTADA to >13,000 trios for six disorders: schizophrenia (SCZ), autism spectrum disorder (ASD), developmental disorders (DD), intellectual disability (ID), epilepsy (EPI), and congenital heart disease (CHD). We report the proportion of overlapping risk genes and the specific risk genes shared for each pair of disorders. A total of 153 genes were found to be shared in at least one pair of disorders. The largest percentages of shared risk genes were observed for pairs of DD, ID, ASD, and CHD (>20%) whereas SCZ, CHD, and EPI did not show strong overlaps In risk gene set between them. Furthermore, mTADA identified additional SCZ, EPI and CHD risk genes through integration with DD de novo mutation data. For CHD, using DD information, 31 risk genes with posterior probabilities > 0.8 were identified, and 20 of these 31 genes were not in the list of known CHD genes. We find evidence that most significant CHD risk genes are strongly expressed in prenatal stages of the human genes. Finally, we validated our findings for CHD and EPI in independent cohorts comprising 1241 CHD trios, 226 CHD singletons and 197 EPI trios. Multiple novel risk genes identified by mTADA also had de novo mutations in these independent data sets. The joint analysis method introduced here, mTADA, is able to identify risk genes shared by two traits as well as additional risk genes not found through single-trait analysis only. A number of risk genes reported by mTADA are identified only through joint analysis, specifically when ASD, DD, or ID are one of the two traits examined. This suggests that novel genes for the trait or a new trait might converge to a core gene list of the three traits.

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