scholarly journals Whole Genome Sequencing and Rare Variant Analysis in Essential Tremor Families

2018 ◽  
Author(s):  
Zagaa Odgerel ◽  
Nora Hernandez ◽  
Jemin Park ◽  
Ruth Ottman ◽  
Elan D. Louis ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Essential Tremor ◽  
Candidate Genes ◽  
Genome Sequencing ◽  
Rare Variant ◽  
Complex Disease ◽  
Mixed Model ◽  
Whole Genome ◽  
Inheritance Patterns ◽  
Disease Inheritance

ABSTRACTEssential tremor (ET) is one of the most common movement disorders. The etiology of ET remains largely unexplained. Whole genome sequencing (WGS) is likely to be of value in understanding a large proportion of ET with Mendelian and complex disease inheritance patterns. In ET families with Mendelian inheritance patterns, WGS may lead to gene identification where WES analysis failed to identify the causative variant due to incomplete coverage of the entire coding region of the genome. Alternatively, in ET families with complex disease inheritance patterns with gene x gene and gene x environment interactions enrichment of functional rare coding and non-coding variants may explain the heritability of ET. We performed WGS in eight ET families (n=40 individuals) enrolled in the Family Study of Essential Tremor. The analysis included filtering WGS data based on allele frequency in population databases, rare variant classification and association testing using the Mixed-Model Kernel Based Adaptive Cluster (MM-KBAC) test and prioritization of candidate genes identified within families using phenolyzer. WGS analysis identified candidate genes for ET in 5/8 (62.5%) of the families analyzed. WES analysis in a subset of these families in our previously published study failed to identify candidate genes. In one family, we identified a deleterious and damaging variant (c.1367G>A, p.(Arg456Gln)) in the candidate gene, CACNA1G, which encodes the pore forming subunit of T-type Ca(2+) channels, CaV3.1, and is expressed in various motor pathways and has been previously implicated in neuronal autorhythmicity and ET. Other candidate genes identified include SLIT3 (family D), which encodes an axon guidance molecule and in three families, phenolyzer prioritized genes that are associated with hereditary neuropathies (family A, KARS, family B, KIF5A and family F, NTRK1). This work has identified candidate genes and pathways for ET that can now be prioritized for functional studies.

scholarly journals Whole genome sequencing and rare variant analysis in essential tremor families

PLoS ONE ◽  
2019 ◽  
Vol 14 (8) ◽  
pp. e0220512 ◽  
Author(s):  
Zagaa Odgerel ◽  
Shilpa Sonti ◽  
Nora Hernandez ◽  
Jemin Park ◽  
Ruth Ottman ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Essential Tremor ◽  
Genome Sequencing ◽  
Rare Variant ◽  
Whole Genome ◽  
Rare Variant Analysis ◽  
Variant Analysis

scholarly journals Dynamic Scan Procedure for Detecting Rare-Variant Association Regions in Whole Genome Sequencing Studies

2019 ◽  
Author(s):  
Zilin Li ◽  
Xihao Li ◽  
Yaowu Liu ◽  
Jincheng Shen ◽  
Han Chen ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Rare Variant ◽  
Type I Error ◽  
Rare Variants ◽  
Error Rates ◽  
Type I ◽  
Whole Genome ◽  
Rare Variant Association ◽  
Dynamic Scan

AbstractWhole genome sequencing (WGS) studies are being widely conducted to identify rare variants associated with human diseases and disease-related traits. Classical single-marker association analyses for rare variants have limited power, and variant-set based analyses are commonly used to analyze rare variants. However, existing variant-set based approaches need to pre-specify genetic regions for analysis, and hence are not directly applicable to WGS data due to the large number of intergenic and intron regions that consist of a massive number of non-coding variants. The commonly used sliding window method requires pre-specifying fixed window sizes, which are often unknown as a priori, are difficult to specify in practice and are subject to limitations given genetic association region sizes are likely to vary across the genome and phenotypes. We propose a computationally-efficient and dynamic scan statistic method (Scan the Genome (SCANG)) for analyzing WGS data that flexibly detects the sizes and the locations of rare-variants association regions without the need of specifying a prior fixed window size. The proposed method controls the genome-wise type I error rate and accounts for the linkage disequilibrium among genetic variants. It allows the detected rare variants association region sizes to vary across the genome. Through extensive simulated studies that consider a wide variety of scenarios, we show that SCANG substantially outperforms several alternative rare-variant association detection methods while controlling for the genome-wise type I error rates. We illustrate SCANG by analyzing the WGS lipids data from the Atherosclerosis Risk in Communities (ARIC) study.

scholarly journals An oligogenic risk model for Gilles de la Tourette syndrome based on whole-genome sequencing data

2021 ◽  
Author(s):  
Malgorzata Borczyk ◽  
Jakup P Fichna ◽  
Marcin Piechota ◽  
Sławomir Gołda ◽  
Michał Korostyński ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Candidate Genes ◽  
Tourette Syndrome ◽  
Genome Sequencing ◽  
Risk Model ◽  
Neurodevelopmental Disorder ◽  
Tic Disorders ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Pathogenic Variants

Gilles de la Tourette syndrome (GTS) is a neurodevelopmental disorder from the spectrum of tic disorders (TDs). GTS and other TDs have a substantial genetic component with the heritability estimated at between 60 and 80%. Here we propose an oligogenic risk model of GTS and other TDs using whole-genome sequencing (WGS) data from a group of Polish GTS patients and their families (n=185). The model is based on the overrepresentation of putatively pathogenic coding and non-coding genetic variants in genes selected from a set of 86 genes previously suggested to be associated with GTS. Based on the variant overrepresentation (SKAT test results) between unrelated GTS patients and controls based on gnomAD database allele frequencies five genes (HDC, CHADL, MAOA, NAA11, and PCDH10) were selected for the risk model. Putatively pathogenic variants (n = 98) with the median allele frequency of ~0.04 in and near these genes were used to build an additive classifier which was then validated on the GTS patients and their families. This risk model successfully assigned individuals from 22 families to either healthy or GTS groups (AUC-ROC = 0.6, p < 0.00001). These results were additionally validated using the GTS GWAS data from the Psychiatric Genomic Consortium. To investigate the GTS genetics further we identified 32 genes from the list of 86 genes as candidate genes in 14 multiplex families, including NEGR1 and NRXN with variants overrepresented in multiple families. WGS data allowed the construction of an oligogenic risk model of GTS based on possibly pathogenic variants likely contributing to the risk of GTS and TDs. The model includes putatively deleterious rare and non-coding variants in and near GTS candidate genes that may cooperatively contribute to GTS etiology and provides a novel approach to the analysis of clinical WGS data.

scholarly journals Efficient Variant Set Mixed Model Association Tests for Continuous and Binary Traits in Large-Scale Whole-Genome Sequencing Studies

2019 ◽  
Vol 104 (2) ◽  
pp. 260-274 ◽  
Author(s):  
Han Chen ◽  
Jennifer E. Huffman ◽  
Jennifer A. Brody ◽  
Chaolong Wang ◽  
Seunggeun Lee ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Large Scale ◽  
Mixed Model ◽  
Whole Genome ◽  
Association Tests ◽  
Binary Traits ◽  
Sequencing Studies

scholarly journals Rare variant discovery by deep whole-genome sequencing of 1,070 Japanese individuals

2015 ◽  
Vol 6 (1) ◽  
Author(s):  
Masao Nagasaki ◽  
◽  
Jun Yasuda ◽  
Fumiki Katsuoka ◽  
Naoki Nariai ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Rare Variant ◽  
Whole Genome ◽  
Variant Discovery

scholarly journals Comprehensive whole-genome sequencing of an early-stage primary myelofibrosis patient defines low mutational burden and non-recurrent candidate genes

Haematologica ◽  
2013 ◽  
Vol 98 (11) ◽  
pp. 1689-1696 ◽  
Author(s):  
J. D. Merker ◽  
K. M. Roskin ◽  
D. Ng ◽  
C. Pan ◽  
D. G. Fisk ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Candidate Genes ◽  
Genome Sequencing ◽  
Early Stage ◽  
Primary Myelofibrosis ◽  
Whole Genome ◽  
Mutational Burden

Identification of candidate genes in rice for resistance to sheath blight disease by whole genome sequencing

2011 ◽  
Vol 124 (1) ◽  
pp. 63-74 ◽  
Author(s):  
James Silva ◽  
Brian Scheffler ◽  
Yamid Sanabria ◽  
Christian De Guzman ◽  
Dominique Galam ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Candidate Genes ◽  
Genome Sequencing ◽  
Sheath Blight ◽  
Whole Genome ◽  
Sheath Blight Disease ◽  
Blight Disease

scholarly journals Dynamic Scan Procedure for Detecting Rare-Variant Association Regions in Whole-Genome Sequencing Studies

2019 ◽  
Vol 104 (5) ◽  
pp. 802-814 ◽  
Author(s):  
Zilin Li ◽  
Xihao Li ◽  
Yaowu Liu ◽  
Jincheng Shen ◽  
Han Chen ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Rare Variant ◽  
Whole Genome ◽  
Rare Variant Association ◽  
Sequencing Studies ◽  
Dynamic Scan
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