scholarly journals VCF.Filter: interactive prioritization of disease-linked genetic variants from sequencing data

2017 ◽  
Vol 45 (W1) ◽  
pp. W567-W572 ◽  
Author(s):  
Heiko Müller ◽  
Raul Jimenez-Heredia ◽  
Ana Krolo ◽  
Tatjana Hirschmugl ◽  
Jasmin Dmytrus ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Sequencing Data

scholarly journals Rare genetic variants affecting urine metabolite levels link population variation to inborn errors of metabolism

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Yurong Cheng ◽  
◽  
Pascal Schlosser ◽  
Johannes Hertel ◽  
Peggy Sekula ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Inborn Errors Of Metabolism ◽  
Cell Types ◽  
Population Variation ◽  
Whole Body ◽  
Sequencing Data ◽  
Inborn Errors ◽  
Data Links ◽  
Liver And Kidney ◽  
Constraint Based Modeling

AbstractMetabolite levels in urine may provide insights into genetic mechanisms shaping their related pathways. We therefore investigate the cumulative contribution of rare, exonic genetic variants on urine levels of 1487 metabolites and 53,714 metabolite ratios among 4864 GCKD study participants. Here we report the detection of 128 significant associations involving 30 unique genes, 16 of which are known to underlie inborn errors of metabolism. The 30 genes are strongly enriched for shared expression in liver and kidney (odds ratio = 65, p-FDR = 3e−7), with hepatocytes and proximal tubule cells as driving cell types. Use of UK Biobank whole-exome sequencing data links genes to diseases connected to the identified metabolites. In silico constraint-based modeling of gene knockouts in a virtual whole-body, organ-resolved metabolic human correctly predicts the observed direction of metabolite changes, highlighting the potential of linking population genetics to modeling. Our study implicates candidate variants and genes for inborn errors of metabolism.

scholarly journals GSDMA drives the most replicated association with asthma in naïve CD4+ T cells

2019 ◽  
Author(s):  
Anne-Marie Madore ◽  
Lucile Pain ◽  
Anne-Marie Boucher-Lafleur ◽  
Jolyane Meloche ◽  
Andréanne Morin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
T Cells ◽  
Genetic Variants ◽  
Immune Cell ◽  
Cell Types ◽  
Sequencing Data ◽  
Opposite Pattern ◽  
Genetic Mechanisms ◽  
New Gene

AbstractBackgroundThe 17q12-21 locus is the most replicated association with asthma. However, no study had described the genetic mechanisms underlying this association considering all genes of the locus in immune cell samples isolated from asthmatic and non-asthmatic individuals.ObjectiveThis study takes benefit of samples from naïve CD4+ T cells and eosinophils isolated from the same 200 individuals to describe specific interactions between genetic variants, gene expression and DNA methylation levels for the 17q12-21 asthma locus.Methods and ResultsAfter isolation of naïve CD4+ T cells and eosinophils from blood samples, next generation sequencing was used to measure DNA methylation levels and gene expression counts. Genetic interactions were then evaluated considering genetic variants from imputed genotype data. In naïve CD4+ T cells but not eosinophils, 20 SNPs in the fourth and fifth haplotype blocks modulated both GSDMA expression and methylation levels, showing an opposite pattern of allele frequencies and expression counts in asthmatics compared to controls. Moreover, negative correlations have been measured between methylation levels of CpG sites located within the 1.5 kb region from the transcription start site of GSDMA and its expression counts.ConclusionAvailability of sequencing data from two key cell types isolated from asthmatic and non-asthmatic individuals allowed identifying a new gene in naïve CD4+ T cells that drives the association with the 17q12-21 locus, leading to a better understanding of the genetic mechanisms taking place in it.

Variant calling and quality control of large-scale human genome sequencing data

2019 ◽  
Vol 3 (4) ◽  
pp. 399-409 ◽  
Author(s):  
Brandon Jew ◽  
Jae Hoon Sul
Keyword(s):  
Quality Control ◽  
Genome Sequencing ◽  
Genetic Variants ◽  
Large Scale ◽  
Variant Calling ◽  
Sequencing Data ◽  
Computational Approaches ◽  
Sequencing Errors ◽  
Human Genome Sequencing ◽  
Number Of Individuals

Abstract Next-generation sequencing has allowed genetic studies to collect genome sequencing data from a large number of individuals. However, raw sequencing data are not usually interpretable due to fragmentation of the genome and technical biases; therefore, analysis of these data requires many computational approaches. First, for each sequenced individual, sequencing data are aligned and further processed to account for technical biases. Then, variant calling is performed to obtain information on the positions of genetic variants and their corresponding genotypes. Quality control (QC) is applied to identify individuals and genetic variants with sequencing errors. These procedures are necessary to generate accurate variant calls from sequencing data, and many computational approaches have been developed for these tasks. This review will focus on current widely used approaches for variant calling and QC.

scholarly journals Limitations of Detecting Genetic Variants from the RNA Sequencing Data in Tissue and Fine-Needle Aspiration Samples

Thyroid ◽  
2020 ◽  
Author(s):  
Cihan Kaya ◽  
Princesca Dorsaint ◽  
Stephanie Mercurio ◽  
Alexander M. Campbell ◽  
Kenneth Wha Eng ◽  
...  
Keyword(s):  
Rna Sequencing ◽  
Fine Needle Aspiration ◽  
Genetic Variants ◽  
Needle Aspiration ◽  
Sequencing Data ◽  
Fine Needle

scholarly journals Improved haplotype inference by exploiting long-range linking and allelic imbalance in RNA-seq datasets

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Emily Berger ◽  
Deniz Yorukoglu ◽  
Lillian Zhang ◽  
Sarah K. Nyquist ◽  
Alex K. Shalek ◽  
...  
Keyword(s):  
Long Range ◽  
Genetic Variants ◽  
Read Length ◽  
Rna Seq ◽  
Sequencing Data ◽  
Specific Expression ◽  
Integrative Framework ◽  
Whole Exome ◽  
Allele Specific ◽  
Diverse Data

Abstract Haplotype reconstruction of distant genetic variants remains an unsolved problem due to the short-read length of common sequencing data. Here, we introduce HapTree-X, a probabilistic framework that utilizes latent long-range information to reconstruct unspecified haplotypes in diploid and polyploid organisms. It introduces the observation that differential allele-specific expression can link genetic variants from the same physical chromosome, thus even enabling using reads that cover only individual variants. We demonstrate HapTree-X’s feasibility on in-house sequenced Genome in a Bottle RNA-seq and various whole exome, genome, and 10X Genomics datasets. HapTree-X produces more complete phases (up to 25%), even in clinically important genes, and phases more variants than other methods while maintaining similar or higher accuracy and being up to 10×  faster than other tools. The advantage of HapTree-X’s ability to use multiple lines of evidence, as well as to phase polyploid genomes in a single integrative framework, substantially grows as the amount of diverse data increases.

scholarly journals Detection of CYP2C19 Genetic Variants in Malaysian Orang Asli from Massively Parallel Sequencing Data

PLoS ONE ◽  
2016 ◽  
Vol 11 (10) ◽  
pp. e0164169 ◽  
Author(s):  
Geik Yong Ang ◽  
Choo Yee Yu ◽  
Vinothini Subramaniam ◽  
Mohd Ikhmal Hanif Abdul Khalid ◽  
Tuan Azlin Tuan Abdu Aziz ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Massively Parallel Sequencing ◽  
Massively Parallel ◽  
Sequencing Data ◽  
Parallel Sequencing ◽  
Orang Asli

scholarly journals Clinical and molecular relevance of genetic variants in the non-coding transcriptome of patients with cytogenetically normal acute myeloid leukemia

Haematologica ◽  
2021 ◽  
Author(s):  
Dimitrios Papaioannou ◽  
Hatice G. Ozer ◽  
Deedra Nicolet ◽  
Amog P. Urs ◽  
Tobias Herold ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Clinical Outcome ◽  
Rna Sequencing ◽  
Clinical Significance ◽  
Genetic Variants ◽  
Myeloid Leukemia ◽  
Sequencing Data ◽  
Younger Adults ◽  
Non Coding Rnas ◽  
Acute Myeloid

Expression levels of long non-coding RNAs (lncRNAs) have been shown to associate with clinical outcome of patients with cytogenetically normal acute myeloid leukemia (CN-AML). However, the frequency and clinical significance of genetic variants in the nucleotide sequences of lncRNAs in AML patients is unknown. Herein, we analyzed total RNA sequencing data of 377 younger adults (aged

Genetic Evidence for Congenital Vascular Disorders in Patients with VACTERL Association

2021 ◽  
Author(s):  
Jessica Ritter ◽  
Kristina Lisec ◽  
Martina Heinrich ◽  
Dietrich von Schweinitz ◽  
Roland Kappler ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Genetic Background ◽  
Vascular Diseases ◽  
Genetic Mutation ◽  
Analysis Tool ◽  
Cardiovascular Development ◽  
Vacterl Association ◽  
Sequencing Data ◽  
Vascular Disorders ◽  
Organ Systems

Abstract Introduction The VACTERL association is a rare malformation complex, showing at least three anomalies of the following organ systems: vertebra, anorectum, heart and vessels, trachea and esophagus, genitourinary tract, and limbs. In addition to a multifactorial event, congenital vascular disorders are also discussed as triggers for the VACTERL association. The aim of this study was to determine whether there is a genetic background for vascular disorders triggering VACTERL association. Materials and Methods We performed a functional analysis on whole exome sequencing data of 21 patients with VACTERL or VACTERL-like phenotype using the online analysis tool “Database for Annotation, Visualization and Integrated Discovery (DAVID) v6.8.” The study was approved by the institutional ethics committee (approval no. 026–13). Written informed consent was obtained from all patients or their parents. Results We identified a total of 86 genetic variants (in 75 genes) classified as damaging (including probably damaging missense, nonsense, and frameshift variants), which are associated to cardiovascular development. Each investigated patient showed at least one damaging variant in genes associated to cardiovascular development. These variants were further reduced by significance in cardiovascular development to 39 genetic variants (in 33 genes). Of note, a pair of siblings, both presenting with cardiac and renal defects, had the same damaging variant in two different genes. Conclusion Our results indicate a genetic background for congenital vascular disorders in patients with VACTERL association. In line with the literature, our data suggest that genetic mutation led to vascular diseases, which in turn may cause malformations similar to the VACTERL association.

scholarly journals A pooling-based approach to mapping genetic variants associated with DNA methylation

2015 ◽  
Author(s):  
Irene Miriam Kaplow ◽  
Julia L MacIsaac ◽  
Sarah M Mah ◽  
Lisa M McEwen ◽  
Michael S Kobor ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Genetic Variants ◽  
Statistical Power ◽  
Epigenetic Modification ◽  
Chromatin Accessibility ◽  
Ctcf Binding ◽  
Sequencing Data ◽  
Individual Level ◽  
Novel Approach ◽  
Genome Wide

DNA methylation is an epigenetic modification that plays a key role in gene regulation. Previous studies have investigated its genetic basis by mapping genetic variants that are associated with DNA methylation at specific sites, but these have been limited to microarrays that cover less than 2% of the genome and cannot account for allele-specific methylation (ASM). Other studies have performed whole-genome bisulfite sequencing on a few individuals, but these lack statistical power to identify variants associated with DNA methylation. We present a novel approach in which bisulfite-treated DNA from many individuals is sequenced together in a single pool, resulting in a truly genome-wide map of DNA methylation. Compared to methods that do not account for ASM, our approach increases statistical power to detect associations while sharply reducing cost, effort, and experimental variability. As a proof of concept, we generated deep sequencing data from a pool of 60 human cell lines; we evaluated almost twice as many CpGs as the largest microarray studies and identified over 2,000 genetic variants associated with DNA methylation. We found that these variants are highly enriched for associations with chromatin accessibility and CTCF binding but are less likely to be associated with traits indirectly linked to DNA, such as gene expression and disease phenotypes. In summary, our approach allows genome-wide mapping of genetic variants associated with DNA methylation in any tissue of any species, without the need for individual-level genotype or methylation data.

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