Biology subjects

Povysil, G.

Publications and source records attributed to Povysil, G..

5 recordsLinked to original sources

bioRxiv2020

A broad exome study of the genetic architecture of asthma reveals novel patient subgroups

IntroductionAsthma risk is a complex interplay between genetic susceptibility and environment. Despite many significantly-associated common variants, the contribution of rarer variants with potentially greater effect sizes has not been as extensively studied. We present an exome-based study adopting 24,576 cases and 120,530 controls to assess the contribution of rare protein-coding variants to the risk of early-onset or all-comer asthma. MethodsWe performed case-control analyses on three genetic units: variant-, gene- and pathway-level, using sequence data from the Scandinavian Asthma Genetic Study and UK Biobank participants with asthma. Cases were defined as all-comer asthma (n=24,576) and early-onset asthma (n=5,962). Controls were 120,530 UK Biobank participants without reported history of respiratory illness. ResultsVariant-level analyses identified statistically significant variants at moderate-to-common allele frequency, including protein-truncating variants in FLG and IL33. Asthma risk was significantly increased not only by individual, common FLG protein-truncating variants, but also among the collection of rare-to-private FLG protein-truncating variants (p=6.8x10-7). This signal was driven by early-onset asthma and did not correlate with circulating eosinophil levels. In contrast, a single splice variant in IL33 was significantly protective (p=8.0x10-10), while the collection of remaining IL33 protein-truncating variants showed no class effect (p=0.54). A pathway-based analysis identified that protein-truncating variants in loss-of-function intolerant genes were significantly enriched among individuals with asthma. ConclusionsAccess to the full allele frequency spectrum of protein-coding variants provides additional clarity about the potential mechanisms of action for FLG and IL33. Beyond these two significant drivers, we detected a significant enrichment of protein-truncating variants in loss-of-function intolerant genes.

genomics↗

bioRxiv2020

ATAV - a comprehensive platform for population-scale genomic analyses

BackgroundA common approach for sequencing studies is to do joint-calling and store variants of all samples in a single file. If new samples keep being added or controls are re-used for several studies, the cost and time required to perform joint-calling for each analysis can become prohibitive. ResultsWe present ATAV, an analysis platform for large-scale whole-exome and whole-genome sequencing projects. ATAV stores variant and per site coverage data for all samples in a centralized database, which is efficiently queried by ATAV to support diagnostic analyses for trios and singletons, as well as rare-variant collapsing analyses for finding disease associations in complex diseases. Runtime logs ensure full reproducibility and the modularized ATAV framework makes it extensible to continuous development. Besides helping with the identification of disease-causing variants for a range of diseases, ATAV has also enabled the discovery of disease-genes by rare-variant collapsing on datasets containing more than 20,000 samples. Analyses to date have been performed on data of more than 110,000 individuals demonstrating the scalability of the framework. The ATAV data browser (http://atavdb.org/) is a web-based interface that allows users to easily access variant-level data directly from the database. Summary-level data for more than 40,000 samples can be queried by the general public representing a mix of cases and controls of diverse ancestries. Users have access to phenotype categories of variant carriers, as well as predicted ancestry, gender, and quality metrics. In contrast to many other platforms, the data browser is able to show data of newly-added samples in real-time and is therefore evolving rapidly as more and more samples are sequenced. ConclusionsSince all code is freely available on GitHub, ATAV can easily be used by other groups to build up their own platform, database, and user interface. In addition to that users can query one of the largest variant databases for patients sequenced at a tertiary care center and look up their own genes or variants of interest.

bioinformatics↗

bioRxiv2019

Increased yields of duplex sequencing data by a series of quality control tools

Duplex sequencing is currently the most reliable method to identify ultra-low frequency DNA variants by grouping sequence reads derived from the same DNA molecule into families with information on the forward and reverse strand. However, only a small proportion of reads are assembled into duplex consensus sequences, and reads with potentially valuable information are discarded at different steps of the bioinformatics pipeline, especially reads without a family. We developed a bioinformatics tool-set that analyses the tag and family composition with the purpose to understand data loss and implement modifications to maximize the data output for the variant calling. Specifically, our tools show that tags contain PCR and sequencing errors that contribute to data loss and lower DCS yields. Our tools also identified chimeras, which result in unpaired families that do not form DCS. Finally, we also developed a tool called Variant Analyzer that re-examines variant calls from raw reads and provides different summary data that categorizes the confidence level of a variant call by a tier-based system. We demonstrate that this tool identified false positive variants tagged by the tier-based classification. Furthermore, with this tool we can include reads without a family and check the reliability of the call, which increases substantially the sequencing depth for variant calling, a particular important advantage for low-input samples or low-coverage regions.

genomics↗

bioRxiv2018

Family reunion via error correction: An efficient analysis of duplex sequencing data

Duplex sequencing is the most accurate approach for identification of sequence variants present at very low frequencies. Its power comes from pooling together multiple descendants of both strands of original DNA molecules, which allows distinguishing true nucleotide substitutions from PCR amplification and sequencing artifacts. This strategy comes at a cost--sequencing the same molecule multiple times increases dynamic range but significantly diminishes coverage, making whole genome duplex sequencing prohibitively expensive. Furthermore, every duplex experiment produces a substantial proportion of singleton reads that cannot be used in the analysis and are, technically, thrown away. In this paper we demonstrate that a significant fraction of these reads contains PCR or sequencing errors within duplex tags. Correction of such errors allows \"reuniting\" these reads with their respective families increasing the output of the method and making it more cost effective. Additionally, we combine error correction strategy with a number of algorithmic improvements in a new version of the duplex analysis software, Du Novo 2.0, readily available through Galaxy, Bioconda, and as the source code.

bioinformatics↗

bioRxiv2018

Length asymmetry and heterozygosity strongly influences the evolution of poly-A microsatellites at meiotic recombination hotspots

Meiotic recombination has strong, but poorly understood, effects on short tandem repeat (STR) instability. Here, we screened thousands of single recombinant products to characterize the transmission and evolution of polymorphic poly-A repeats at a human recombination hotspot. We show that length asymmetry between heterozygous poly-As plays a key role in the recombination outcome and their transmission. A difference of 10 As (9A/19A) elevates the frequency of non-crossovers, complex recombination products, and long conversion tracts. Moreover, asymmetry also influences STR transmission: the shorter allele is transmitted more frequently (deletion bias) at the asymmetric STR (9A/19A), while the longer allele is favored (insertion bias) at the site with a small STR length difference (6A/7A). Finally, potentially due to this opposing insertion/deletion driven evolution, we find that poly-As are enriched at human recombination hotspots predominantly with short poly-As, possibly influencing open chromatin regions that in turn can activate hotspots.

evolutionary biology↗