NeoRdRp: A comprehensive dataset for identifying RNA-dependent RNA polymerase of various RNA viruses from metatranscriptomic data
NeoRdRp: A comprehensive dataset for identifying RNA-dependent RNA polymerase of various RNA viruses from metatranscriptomic data
复制标题
NeoRdRp：用于从宏转录组数据中识别各种 RNA 病毒的 RNA 依赖性 RNA 聚合酶的综合数据集
DOI：
10.1101/2021.12.31.474423
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发表时间：
2022
期刊：
影响因子：
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通讯作者：
Nakagawa So
中科院分区：
文献类型：
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作者：
Sakaguchi Shoichi;Urayama Syun-ichi;Takaki Yoshihiro;Hirosuna Kensuke;Wu Hong;Suzuki Youichi;Nunoura Takuro;Nakano Takashi;Nakagawa So
RNA病毒分布在各种环境中，并且最近已经通过元转录组测序鉴定了大多数。然而，由于RNA病毒的高核苷酸多样性，从元转录组数据中鉴定新型RNA病毒仍然具有挑战性。为了克服这个问题，我们创建了一个RNA依赖性RNA聚合酶（RdRp）结构域的数据集，这些结构域对于所有属于奥氏病毒的RNA病毒都是必需的。基于氨基酸序列相似性将来自各种RNA病毒的具有RdRp结构域的基因聚类。为每个簇生成多序列比对，并且当序列的数目大于三时创建隐马尔可夫模型（HMM）概况。我们通过检测RefSeq RNA病毒序列进一步完善了426个HMM图谱，随后将命中序列与RdRp结构域组合。结果，从12，502个RdRp结构域序列中生成了1，182个HMM谱，并将数据集命名为NeoRdRp。大多数NeoRdRp HMM配置文件成功检测到RdRp结构域，特别是在UniProt数据集中。此外，我们将NeoRdRp数据集与先前报道的使用元转录组测序数据进行RNA病毒检测的两种方法进行了比较。我们的方法成功地识别了数据集中的大多数RNA病毒;然而，与其他两种方法类似，一些RNA病毒未被检测到。NeoRdRp可以通过添加新的RdRp序列来重复改进，并且适用于作为用于从不同的元转录组数据检测各种RNA病毒的系统。
RNA viruses are distributed throughout various environments, and most have recently been identified by metatranscriptome sequencing. However, due to the high nucleotide diversity of RNA viruses, it is still challenging to identify novel RNA viruses from metatranscriptome data. To overcome this issue, we created a dataset of RNA-dependent RNA polymerase (RdRp) domains that are essential for all RNA viruses belonging to Orthornavirae. Genes with RdRp domains from various RNA viruses were clustered based on amino acid sequence similarities. A multiple sequence alignment was generated for each cluster, and a hidden Markov model (HMM) profile was created when the number of sequences was greater than three. We further refined 426 HMM profiles by detecting RefSeq RNA virus sequences and subsequently combined the hit sequences with the RdRp domains. As a result, 1,182 HMM profiles were generated from 12,502 RdRp domain sequences, and the dataset was named NeoRdRp. The majority of NeoRdRp HMM profiles successfully detected RdRp domains, specifically in the UniProt dataset. Furthermore, we compared the NeoRdRp dataset with two previously reported methods for RNA virus detection using metatranscriptome sequencing data. Our methods successfully identified the majority of RNA viruses in the datasets; however, some RNA viruses were not detected, similar to the other two methods. NeoRdRp may be repeatedly improved by the addition of new RdRp sequences and is applicable as a system for detecting various RNA viruses from diverse metatranscriptome data.