Lapp Zena, Yoon Hyejin, Foley Brian, Leitner Thomas
Theoretical Biology and Biophysics Group, Los Alamos National Laboratory, Los Alamos, NM 87545, USA.
bioRxiv. 2024 Oct 29:2024.10.24.620069. doi: 10.1101/2024.10.24.620069.
The detection of APOBEC3F- and APOBEC3G-induced mutations in virus sequences is useful for identifying hypermutated sequences. These sequences are not representative of viral evolution and can therefore alter the results of downstream sequence analyses if included. We previously published the software Hypermut, which detects hypermutation events in sequences relative to a reference. Two versions of this method are available as a webtool. Neither of these methods consider multistate characters or gaps in the sequence alignment. Here, we present an updated, user-friendly web and command-line version of Hypermut with functionality to handle multistate characters and gaps in the sequence alignment. This tool allows for straightforward integration of hypermutation detection into sequence analysis pipelines. As with the previous tool, while the main purpose is to identify G to A hypermutation events, any mutational pattern and context can be specified.
检测病毒序列中由载脂蛋白B mRNA编辑酶催化多肽样蛋白3F（APOBEC3F）和载脂蛋白B mRNA编辑酶催化多肽样蛋白3G（APOBEC3G）诱导的突变，对于识别高度突变序列很有用。这些序列不代表病毒进化，如果包含在内，可能会改变下游序列分析的结果。我们之前发表了软件Hypermut，它可以检测相对于参考序列的序列中的高度突变事件。该方法的两个版本可作为网络工具使用。这两种方法都不考虑多态性特征或序列比对中的缺口。在这里，我们展示了一个更新的、用户友好的网络和命令行版本的Hypermut，它具有处理多态性特征和序列比对中缺口的功能。该工具允许将高度突变检测直接集成到序列分析流程中。与之前的工具一样，虽然主要目的是识别从鸟嘌呤（G）到腺嘌呤（A）的高度突变事件，但可以指定任何突变模式和背景。
