Klonowski Jonathan, Liang Qianqian, Coban-Akdemir Zeynep, Lo Cecilia, Kostka Dennis
Department of Developmental Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
Department of Epidemiology, Human Genetics and Environmental Sciences, University of Texas School of Public Health, Houston, TX, USA.
bioRxiv. 2023 Mar 21:2023.03.17.533185. doi: 10.1101/2023.03.17.533185.
DNA changes that cause premature termination codons (PTCs) represent a large fraction of clinically relevant pathogenic genomic variation. Typically, PTCs induce a transcript's degradation by nonsense-mediated mRNA decay (NMD) and render such changes loss-of-function alleles. However, certain PTC-containing transcripts escape NMD and can exert dominant-negative or gain-of-function (DN/GOF) effects. Therefore, systematic identification of human PTC-causing variants and their susceptibility to NMD contributes to the investigation of the role of DN/GOF alleles in human disease. Here we present aenmd, a software for annotating PTC-containing transcript-variant pairs for predicted escape from NMD. aenmd is user-friendly and self-contained. It offers functionality not currently available in other methods and is based on established and experimentally validated rules for NMD escape; the software is designed to work at scale, and to integrate seamlessly with existing analysis workflows. We applied aenmd to variants in the gnomAD, Clinvar, and GWAS catalog databases and report the prevalence of human PTC-causing variants in these databases, and the subset of these that could exert DN/GOF effects via NMD escape. Availability and implementation: aenmd is implemented in the R programming language. Code is available on GitHub as an R package (github.com/kostkalab/aenmd.git), and as a containerized command-line interface (github.com/kostkalab/aenmd_cli.git).
导致过早终止密码子(PTC)的DNA变化占临床相关致病基因组变异的很大一部分。通常,PTC会通过无义介导的mRNA衰变(NMD)诱导转录本降解,并使这些变化成为功能丧失等位基因。然而,某些含有PTC的转录本可逃避NMD,并可发挥显性负性或功能获得(DN/GOF)效应。因此,系统鉴定导致人类PTC的变异及其对NMD的敏感性,有助于研究DN/GOF等位基因在人类疾病中的作用。在此,我们展示了aenmd,这是一款用于注释含有PTC的转录本-变异对以预测其逃避NMD的软件。aenmd用户友好且独立运行。它提供了其他方法目前无法提供的功能,并且基于已确立且经过实验验证的NMD逃避规则;该软件旨在大规模运行,并与现有的分析工作流程无缝集成。我们将aenmd应用于gnomAD、Clinvar和GWAS目录数据库中的变异,并报告了这些数据库中导致人类PTC的变异的流行情况,以及其中可通过NMD逃避发挥DN/GOF效应的子集。可用性和实现方式:aenmd用R编程语言实现。代码可在GitHub上作为R包(github.com/kostkalab/aenmd.git)获取,也可作为容器化命令行界面(github.com/kostkalab/aenmd_cli.git)获取。