scholarly journals VEP-G2P: A Tool for Efficient, Flexible and Scalable Diagnostic Filtering of Genomic Variants

2018 ◽  
Author(s):  
Anja Thormann ◽  
Mihail Halachev ◽  
William McLaren ◽  
David J Moore ◽  
Victoria Svinti ◽  
...  
Keyword(s):  
Developmental Disorders ◽  
Large Scale ◽  
De Novo ◽  
Genetic Research ◽  
Evidence Based ◽  
Large Numbers ◽  
Whole Exome ◽  
Variant Filtering ◽  
And Control ◽  
Exome Sequence

AbstractPurposeWe aimed to develop an efficient, flexible, scalable and evidence-based approach to sequence-based diagnostic analysis/re-analysis of conditions with very large numbers of different causative genes. We then wished to define the expected rate of plausibly causative variants coming through strict filtering in control in comparison to disease populations to quantify background diagnostic “noise”.MethodsWe developed G2P (www.ebi.ac.uk/gene2phenotype) as an online system to facilitate the development, validation, curation and distribution of large-scale, evidence-based datasets for use in diagnostic variant filtering. Each locus-genotype-mechanism-disease-evidence thread (LGMDET) associates an allelic requirement and a mutational consequence at a defined locus with a disease entity and a confidence level and evidence links. We then developed an extension to Ensembl Variant Effect Predictor (VEP), VEP-G2P, which can filter based on G2P other widely used gene panel curation systems. We compared the output of disease-associated and control whole exome sequence (WES) using Developmental Disorders G2P (G2PDD; 2044 LGMDETs) and constitutional cancer predisposition G2P (G2PCancer; 128 LGMDETs).ResultsWe have shown a sensitivity/precision of 97.3%/33% and 81.6%/22.7% for causative de novo and inherited variants respectively using VEP-G2PDD in DDD study probands WES. Many of the apparently diagnostic genotypes “missed” are likely false-positive reports with lower minor allele frequencies and more severe predicted consequences being diagnostically-discriminative features.ConclusionCase:control comparisons using VEP-G2PDD established an observed:expected ratio of 1:30,000 plausibly causative variants in proband WES to ~1:40,000 reportable but presumed-benign variants in controls. At least half the filtered variants in probands represent background “noise”. Supporting phenotypic evidence is, therefore, necessary in genetically-heterogeneous disorders. G2P and VEP-G2P provides a practical approach to optimize disease-specific filtering parameters in diagnostic genetic research.

Advances in identification of genes involved in autosomal recessive intellectual disability: a brief review

2019 ◽  
Vol 56 (9) ◽  
pp. 567-573 ◽  
Author(s):  
Yaser Rafiq Mir ◽  
Raja Amir Hassan Kuchay
Keyword(s):  
Intellectual Disability ◽  
Large Scale ◽  
Autosomal Recessive ◽  
Biological Processes ◽  
Autozygosity Mapping ◽  
Whole Exome ◽  
Recessive Disorders ◽  
And Control ◽  
Very High ◽  
Dominant Genes

Intellectual disability (ID) is a clinically and genetically heterogeneous disorder, affecting 1%–3% of the general population. The number of ID-causing genes is high. Many X-linked genes have been implicated in ID. Autosomal dominant genes have recently been the focus of several large-scale studies. The total number of autosomal recessive ID (ARID) genes is estimated to be very high, and most are still unknown. Although research into the genetic causes of ID has recently gained momentum, identification of pathogenic mutations that cause ARID has lagged behind, predominantly due to non-availability of sizeable families. A commonly used approach to identify genetic loci for recessive disorders in consanguineous families is autozygosity mapping and whole-exome sequencing. Combination of these two approaches has recently led to identification of many genes involved in ID. These genes have diverse function and control various biological processes. In this review, we will present an update regarding genes that have been recently implicated in ID with focus on ARID.

scholarly journals Low load for disruptive mutations in autism genes and their biased transmission

2015 ◽  
Vol 112 (41) ◽  
pp. E5600-E5607 ◽  
Author(s):  
Ivan Iossifov ◽  
Dan Levy ◽  
Jeremy Allen ◽  
Kenny Ye ◽  
Michael Ronemus ◽  
...  
Keyword(s):  
Negative Selection ◽  
De Novo ◽  
Children With Autism ◽  
Autism Spectrum ◽  
Mutational Load ◽  
Whole Exome ◽  
Strong Negative Selection ◽  
Low Load ◽  
Spectrum Disorders ◽  
Exome Sequence

We previously computed that genes with de novo (DN) likely gene-disruptive (LGD) mutations in children with autism spectrum disorders (ASD) have high vulnerability: disruptive mutations in many of these genes, the vulnerable autism genes, will have a high likelihood of resulting in ASD. Because individuals with ASD have lower fecundity, such mutations in autism genes would be under strong negative selection pressure. An immediate prediction is that these genes will have a lower LGD load than typical genes in the human gene pool. We confirm this hypothesis in an explicit test by measuring the load of disruptive mutations in whole-exome sequence databases from two cohorts. We use information about mutational load to show that lower and higher intelligence quotients (IQ) affected individuals can be distinguished by the mutational load in their respective gene targets, as well as to help prioritize gene targets by their likelihood of being autism genes. Moreover, we demonstrate that transmission of rare disruptions in genes with a lower LGD load occurs more often to affected offspring; we show transmission originates most often from the mother, and transmission of such variants is seen more often in offspring with lower IQ. A surprising proportion of transmission of these rare events comes from genes expressed in the embryonic brain that show sharply reduced expression shortly after birth.

scholarly journals Rare loss-of-function variants in KMT2F are associated with schizophrenia and developmental disorders

2016 ◽  
Author(s):  
Tarjinder Singh ◽  
Mitja I. Kurki ◽  
David Curtis ◽  
Shaun M. Purcell ◽  
Lucy Crooks ◽  
...  
Keyword(s):  
Developmental Disorders ◽  
De Novo ◽  
Learning Difficulties ◽  
Loss Of Function ◽  
H3k4 Methylation ◽  
Methylation Pathway ◽  
Genome Wide ◽  
Whole Exome ◽  
A Genome ◽  
Histone H3k4

Schizophrenia is a common, debilitating psychiatric disorder with a substantial genetic component. By analysing the whole-exome sequences of 4,264 schizophrenia cases, 9,343 controls, and 1,077 parent-proband trios, we identified a genome-wide significant association between rare loss-of-function (LoF) variants in KMT2F and risk for schizophrenia. In this dataset, we observed three de novo LoF mutations, seven LoF variants in cases, and none in controls (P=3.3x10^(-9)). To search for LoF variants in KMT2F in individuals without a known neuropsychiatric diagnosis, we examined the exomes of 45,376 individuals in the ExAC database and found only two heterozygous LoF variants, showing that KMT2F is significantly depleted of LoF variants in the general population. Seven of the ten individuals with schizophrenia carrying KMT2F LoF variants also had varying degrees of learning difficulties. We further identified four KMT2F LoF carriers among 4,281 children with diverse, severe, undiagnosed developmental disorders, and two additional carriers in an independent sample of 5,720 Finnish exomes, both with notable neuropsychiatric phenotypes. Together, our observations show that LoF variants in KMT2F cause a range of neurodevelopmental disorders, including schizophrenia. Combined with previous common variant evidence, we more generally implicate epigenetic dysregulation, specifically in the histone H3K4 methylation pathway, as an important mechanism in the pathogenesis of schizophrenia.

A systematic comparison of two new releases of exome sequencing products: the aim of use determines the choice of product

2016 ◽  
Vol 397 (8) ◽  
pp. 791-801 ◽  
Author(s):  
Janine Altmüller ◽  
Susanne Motameny ◽  
Christian Becker ◽  
Holger Thiele ◽  
Sreyoshi Chatterjee ◽  
...  
Keyword(s):  
Exome Sequencing ◽  
Developmental Disorders ◽  
Large Scale ◽  
Data Sets ◽  
Early Access ◽  
Whole Exome ◽  
Agilent Sureselect ◽  
Disease Associated Genes ◽  
Diagnostic Setting ◽  
Better Than

Abstract We received early access to the newest releases of exome sequencing products, namely Agilent SureSelect v6 (Agilent, Santa Clara, CA, USA) and NimbleGen MedExome (Roche NimbleGen, Basel, Switzerland), and we conducted whole exome sequencing (WES) of several DNA samples with each of these products in order to assess their performance. Here, we provide a detailed evaluation of the original, normalized (with respect to the different target sizes), and trimmed data sets and compare them in terms of the amount of duplicates, the reads on target, and the enrichment evenness. In addition to these general statistics, we performed a detailed analysis of the frequently mutated and newly described genes found in ‘The Deciphering Developmental Disorders Study’ published very recently (Fitzgerald, T.W., Gerety, S.S., Jones, W.D., van Kogelenberg, M., King, D.A., McRae, J., Morley, K.I., Parthiban, V., Al-Turki, S., Ambridge, K., et al. (2015). Large-scale discovery of novel genetic causes of developmental disorders. Nature 519, 223–228.). In our comparison, the Agilent v6 exome performs better than the NimbleGen’s MedExome both in terms of efficiency and evenness of coverage distribution. With its larger target size, it is also more comprehensive, and therefore the better choice in research projects that aim to identify novel disease-associated genes. In contrast, if the exomes are mainly used in a diagnostic setting, we see advantages for the new NimbleGen MedExome. We find a superior coverage here in those genes of high clinical relevance that likely allows for a better detection of relevant, disease-causing mutations.

scholarly journals Comparison of the frequencies of ENU-induced point mutations in male germ cells and inherited germline mutations in their offspring

2021 ◽  
Vol 43 (1) ◽  
Author(s):  
Kenichi Masumura ◽  
Tomoko Ando ◽  
Naomi Toyoda-Hokaiwado ◽  
Akiko Ukai ◽  
Takehiko Nohmi ◽  
...  
Keyword(s):  
Germ Cells ◽  
De Novo ◽  
Genetic Diseases ◽  
Point Mutations ◽  
Gene Mutations ◽  
Next Generation ◽  
Male Germ Cells ◽  
Gene Coding ◽  
Whole Exome ◽  
And Control

Abstract Background Gene mutations induced in germ cells may be transmitted to the next generation and cause adverse effects such as genetic diseases. Certain mutations may result in infertility or death in early development. Thus, the mutations may not be inheritable. However, the extent to which point mutations in male germ cells are transmitted to the next generation or eliminated during transmission is largely unknown. This study compared mutation frequencies (MFs) in sperm of N-ethyl-N-nitrosourea (ENU)-treated gpt delta mice and de novo MFs in the whole exome/genome of their offspring. Results Male gpt delta mice were treated with 10, 30, and 85 mg/kg of ENU (i.p., weekly × 2) and mated with untreated females to generate offspring. We previously reported a dose-dependent increase in de novo MFs in the offspring estimated by whole exome sequencing (WES) (Mutat. Res., 810, 30–39, 2016). In this study, gpt MFs in the sperm of ENU-treated mice were estimated, and the MFs per reporter gene were converted to MFs per base pair. The inherited de novo MFs in the offspring (9, 26 and 133 × 10− 8/bp for 10, 30, and 85 mg/kg ENU-treated groups, respectively) were comparable to those of the converted gpt MFs in the sperm of ENU-treated fathers (6, 16, and 69 × 10− 8/bp). It indicated that the gpt MFs in the ENU-treated father’s sperm were comparable to the inherited de novo MFs in the offspring as estimated by WES. In addition, de novo MFs in the offspring of 10 mg/kg ENU-treated and control fathers were estimated by whole genome sequencing (WGS), because WES was not sufficiently sensitive to detect low background MF. The de novo MF in the offspring of the ENU-treated fathers was 6 × 10− 8/bp and significantly higher than that of the control (2 × 10− 8/bp). There were no significant differences in de novo MFs between gene-coding and non-coding regions. WGS analysis was able to detect ENU-induced characteristic de novo base substitutions at a low dose group. Conclusions Despite a difference between exome/genome and exogenous reporter genes, the results indicated that ENU-induced point mutations in male germ cells could be transmitted to the next generation without severe selection.

scholarly journals Neurological disorder-associated genetic variants in individuals with psychogenic nonepileptic seizures

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Costin Leu ◽  
Jocelyn F. Bautista ◽  
Monica Sudarsanam ◽  
Lisa-Marie Niestroj ◽  
Arthur Stefanski ◽  
...  
Keyword(s):  
Psychiatric Disorders ◽  
Genetic Variants ◽  
Large Scale ◽  
Genetic Factors ◽  
Tertiary Care ◽  
Genetic Research ◽  
Genetic Investigation ◽  
Psychogenic Nonepileptic Seizures ◽  
Whole Exome ◽  
Nonepileptic Seizures

Abstract Psychogenic nonepileptic seizures (PNES) are diagnosed in approximately 30% of patients referred to tertiary care epilepsy centers. Little is known about the molecular pathology of PNES, much less about possible underlying genetic factors. We generated whole-exome sequencing and whole-genome genotyping data to identify rare, pathogenic (P) or likely pathogenic (LP) variants in 102 individuals with PNES and 448 individuals with focal (FE) or generalized (GE) epilepsy. Variants were classified for all individuals based on the ACMG-AMP 2015 guidelines. For research purposes only, we considered genes associated with neurological or psychiatric disorders as candidate genes for PNES. We observe in this first genetic investigation of PNES that six (5.88%) individuals with PNES without coexistent epilepsy carry P/LP variants (deletions at 10q11.22-q11.23, 10q23.1-q23.2, distal 16p11.2, and 17p13.3, and nonsynonymous variants in NSD1 and GABRA5). Notably, the burden of P/LP variants among the individuals with PNES was similar and not significantly different to the burden observed in the individuals with FE (3.05%) or GE (1.82%) (PNES vs. FE vs. GE (3 × 2 χ2), P = 0.30; PNES vs. epilepsy (2 × 2 χ2), P = 0.14). The presence of variants in genes associated with monogenic forms of neurological and psychiatric disorders in individuals with PNES shows that genetic factors are likely to play a role in PNES or its comorbidities in a subset of individuals. Future large-scale genetic research studies are needed to further corroborate these interesting findings in PNES.

scholarly journals exomeSuite: Whole exome sequence variant filtering tool for rapid identification of putative disease causing SNVs/indels

Genomics ◽  
2014 ◽  
Vol 103 (2-3) ◽  
pp. 169-176 ◽  
Author(s):  
B. Maranhao ◽  
P. Biswas ◽  
J.L. Duncan ◽  
K.E. Branham ◽  
G.A. Silva ◽  
...  
Keyword(s):  
Rapid Identification ◽  
Sequence Variant ◽  
Whole Exome ◽  
Variant Filtering ◽  
Exome Sequence

Collaboration, Power, Participation and Control on a Large Scale Research Team: Multiple Perspectives from the Oxford House Research Project

2001 ◽  
Author(s):  
Bradley Olson ◽  
Leonard Jason ◽  
Joseph R. Ferrari ◽  
Leon Venable ◽  
Bertel F. Williams ◽  
...  
Keyword(s):  
Large Scale ◽  
Research Team ◽  
Multiple Perspectives ◽  
Research Project ◽  
Oxford House ◽  
And Control

Computer Analyses in Preventive Health Research

1967 ◽  
Vol 06 (01) ◽  
pp. 8-14 ◽  
Author(s):  
M. F. Collen
Keyword(s):  
Medical Research ◽  
Preventive Medicine ◽  
Health Research ◽  
Large Scale ◽  
Preventive Health ◽  
New Era ◽  
Large Numbers ◽  
Normal Test ◽  
Computer Analyses

The utilization of an automated multitest laboratory as a data acquisition center and of a computer for trie data processing and analysis permits large scale preventive medical research previously not feasible. Normal test values are easily generated for the particular population studied. Long-term epidemiological research on large numbers of persons becomes practical. It is our belief that the advent of automation and computers has introduced a new era of preventive medicine.

Interference mitigation in point to point wireless sensor networks using LSP protocol and time division multiplexing approach

2020 ◽  
Vol 39 (4) ◽  
pp. 5449-5458
Author(s):  
A. Arokiaraj Jovith ◽  
S.V. Kasmir Raja ◽  
A. Razia Sulthana
Keyword(s):  
Energy Consumption ◽  
Large Scale ◽  
Control Parameter ◽  
Interference Mitigation ◽  
Wireless Sensor ◽  
Point To Point ◽  
A Minor ◽  
Two Stages ◽  
Time Division ◽  
And Control

Interference in Wireless Sensor Network (WSN) predominantly affects the performance of the WSN. Energy consumption in WSN is one of the greatest concerns in the current generation. This work presents an approach for interference measurement and interference mitigation in point to point network. The nodes are distributed in the network and interference is measured by grouping the nodes in the region of a specific diameter. Hence this approach is scalable and isextended to large scale WSN. Interference is measured in two stages. In the first stage, interference is overcome by allocating time slots to the node stations in Time Division Multiple Access (TDMA) fashion. The node area is split into larger regions and smaller regions. The time slots are allocated to smaller regions in TDMA fashion. A TDMA based time slot allocation algorithm is proposed in this paper to enable reuse of timeslots with minimal interference between smaller regions. In the second stage, the network density and control parameter is introduced to reduce interference in a minor level within smaller node regions. The algorithm issimulated and the system is tested with varying control parameter. The node-level interference and the energy dissipation at nodes are captured by varying the node density of the network. The results indicate that the proposed approach measures the interference and mitigates with minimal energy consumption at nodes and with less overhead transmission.

Sign in / Sign up

Export Citation Format

Share Document