Cargando…

Characterization of viral RNA splicing using whole-transcriptome datasets from host species

RNA alternative splicing (AS) is an important post-transcriptional mechanism enabling single genes to produce multiple proteins. It has been well demonstrated that viruses deploy host AS machinery for viral protein productions. However, knowledge on viral AS is limited to a few disease-causing virus...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhou, Chengran, Liu, Shanlin, Song, Wenhui, Luo, Shiqi, Meng, Guanliang, Yang, Chentao, Yang, Hua, Ma, Jinmin, Wang, Liang, Gao, Shan, Wang, Jian, Yang, Huanming, Zhao, Yun, Wang, Hui, Zhou, Xin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5818608/
https://www.ncbi.nlm.nih.gov/pubmed/29459752
http://dx.doi.org/10.1038/s41598-018-21190-7
_version_ 1783301059521806336
author Zhou, Chengran
Liu, Shanlin
Song, Wenhui
Luo, Shiqi
Meng, Guanliang
Yang, Chentao
Yang, Hua
Ma, Jinmin
Wang, Liang
Gao, Shan
Wang, Jian
Yang, Huanming
Zhao, Yun
Wang, Hui
Zhou, Xin
author_facet Zhou, Chengran
Liu, Shanlin
Song, Wenhui
Luo, Shiqi
Meng, Guanliang
Yang, Chentao
Yang, Hua
Ma, Jinmin
Wang, Liang
Gao, Shan
Wang, Jian
Yang, Huanming
Zhao, Yun
Wang, Hui
Zhou, Xin
author_sort Zhou, Chengran
collection PubMed
description RNA alternative splicing (AS) is an important post-transcriptional mechanism enabling single genes to produce multiple proteins. It has been well demonstrated that viruses deploy host AS machinery for viral protein productions. However, knowledge on viral AS is limited to a few disease-causing viruses in model species. Here we report a novel approach to characterizing viral AS using whole transcriptome dataset from host species. Two insect transcriptomes (Acheta domesticus and Planococcus citri) generated in the 1,000 Insect Transcriptome Evolution (1KITE) project were used as a proof of concept using the new pipeline. Two closely related densoviruses (Acheta domesticus densovirus, AdDNV, and Planococcus citri densovirus, PcDNV, Ambidensovirus, Densovirinae, Parvoviridae) were detected and analyzed for AS patterns. The results suggested that although the two viruses shared major AS features, dramatic AS divergences were observed. Detailed analysis of the splicing junctions showed clusters of AS events occurred in two regions of the virus genome, demonstrating that transcriptome analysis could gain valuable insights into viral splicing. When applied to large-scale transcriptomics projects with diverse taxonomic sampling, our new method is expected to rapidly expand our knowledge on RNA splicing mechanisms for a wide range of viruses.
format Online
Article
Text
id pubmed-5818608
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-58186082018-02-26 Characterization of viral RNA splicing using whole-transcriptome datasets from host species Zhou, Chengran Liu, Shanlin Song, Wenhui Luo, Shiqi Meng, Guanliang Yang, Chentao Yang, Hua Ma, Jinmin Wang, Liang Gao, Shan Wang, Jian Yang, Huanming Zhao, Yun Wang, Hui Zhou, Xin Sci Rep Article RNA alternative splicing (AS) is an important post-transcriptional mechanism enabling single genes to produce multiple proteins. It has been well demonstrated that viruses deploy host AS machinery for viral protein productions. However, knowledge on viral AS is limited to a few disease-causing viruses in model species. Here we report a novel approach to characterizing viral AS using whole transcriptome dataset from host species. Two insect transcriptomes (Acheta domesticus and Planococcus citri) generated in the 1,000 Insect Transcriptome Evolution (1KITE) project were used as a proof of concept using the new pipeline. Two closely related densoviruses (Acheta domesticus densovirus, AdDNV, and Planococcus citri densovirus, PcDNV, Ambidensovirus, Densovirinae, Parvoviridae) were detected and analyzed for AS patterns. The results suggested that although the two viruses shared major AS features, dramatic AS divergences were observed. Detailed analysis of the splicing junctions showed clusters of AS events occurred in two regions of the virus genome, demonstrating that transcriptome analysis could gain valuable insights into viral splicing. When applied to large-scale transcriptomics projects with diverse taxonomic sampling, our new method is expected to rapidly expand our knowledge on RNA splicing mechanisms for a wide range of viruses. Nature Publishing Group UK 2018-02-19 /pmc/articles/PMC5818608/ /pubmed/29459752 http://dx.doi.org/10.1038/s41598-018-21190-7 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Zhou, Chengran
Liu, Shanlin
Song, Wenhui
Luo, Shiqi
Meng, Guanliang
Yang, Chentao
Yang, Hua
Ma, Jinmin
Wang, Liang
Gao, Shan
Wang, Jian
Yang, Huanming
Zhao, Yun
Wang, Hui
Zhou, Xin
Characterization of viral RNA splicing using whole-transcriptome datasets from host species
title Characterization of viral RNA splicing using whole-transcriptome datasets from host species
title_full Characterization of viral RNA splicing using whole-transcriptome datasets from host species
title_fullStr Characterization of viral RNA splicing using whole-transcriptome datasets from host species
title_full_unstemmed Characterization of viral RNA splicing using whole-transcriptome datasets from host species
title_short Characterization of viral RNA splicing using whole-transcriptome datasets from host species
title_sort characterization of viral rna splicing using whole-transcriptome datasets from host species
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5818608/
https://www.ncbi.nlm.nih.gov/pubmed/29459752
http://dx.doi.org/10.1038/s41598-018-21190-7
work_keys_str_mv AT zhouchengran characterizationofviralrnasplicingusingwholetranscriptomedatasetsfromhostspecies
AT liushanlin characterizationofviralrnasplicingusingwholetranscriptomedatasetsfromhostspecies
AT songwenhui characterizationofviralrnasplicingusingwholetranscriptomedatasetsfromhostspecies
AT luoshiqi characterizationofviralrnasplicingusingwholetranscriptomedatasetsfromhostspecies
AT mengguanliang characterizationofviralrnasplicingusingwholetranscriptomedatasetsfromhostspecies
AT yangchentao characterizationofviralrnasplicingusingwholetranscriptomedatasetsfromhostspecies
AT yanghua characterizationofviralrnasplicingusingwholetranscriptomedatasetsfromhostspecies
AT majinmin characterizationofviralrnasplicingusingwholetranscriptomedatasetsfromhostspecies
AT wangliang characterizationofviralrnasplicingusingwholetranscriptomedatasetsfromhostspecies
AT gaoshan characterizationofviralrnasplicingusingwholetranscriptomedatasetsfromhostspecies
AT wangjian characterizationofviralrnasplicingusingwholetranscriptomedatasetsfromhostspecies
AT yanghuanming characterizationofviralrnasplicingusingwholetranscriptomedatasetsfromhostspecies
AT zhaoyun characterizationofviralrnasplicingusingwholetranscriptomedatasetsfromhostspecies
AT wanghui characterizationofviralrnasplicingusingwholetranscriptomedatasetsfromhostspecies
AT zhouxin characterizationofviralrnasplicingusingwholetranscriptomedatasetsfromhostspecies