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Multi-strategic RNA-seq analysis reveals a high-resolution transcriptional landscape in cotton
Cotton is an important natural fiber crop, however, its comprehensive and high-resolution gene map is lacking. Here we integrate four complementary high-throughput techniques, including Pacbio long read Iso-seq, strand-specific RNA-seq, CAGE-seq, and PolyA-seq, to systematically explore the transcri...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6797763/ https://www.ncbi.nlm.nih.gov/pubmed/31624240 http://dx.doi.org/10.1038/s41467-019-12575-x |
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author | Wang, Kun Wang, Dehe Zheng, Xiaomin Qin, Ai Zhou, Jie Guo, Boyu Chen, Yanjun Wen, Xingpeng Ye, Wen Zhou, Yu Zhu, Yuxian |
author_facet | Wang, Kun Wang, Dehe Zheng, Xiaomin Qin, Ai Zhou, Jie Guo, Boyu Chen, Yanjun Wen, Xingpeng Ye, Wen Zhou, Yu Zhu, Yuxian |
author_sort | Wang, Kun |
collection | PubMed |
description | Cotton is an important natural fiber crop, however, its comprehensive and high-resolution gene map is lacking. Here we integrate four complementary high-throughput techniques, including Pacbio long read Iso-seq, strand-specific RNA-seq, CAGE-seq, and PolyA-seq, to systematically explore the transcription landscape across 16 tissues or different organ types in Gossypium arboreum. We devise a computational pipeline, named IGIA, to reconstruct accurate gene structures from the integrated data. Our results reveal a dynamic and diverse transcriptional map in cotton: tissue-specific gene expression, alternative usage of TSSs and polyadenylation sites, hotspot of alternative splicing, and transcriptional read-through. These regulated events affect many genes in various aspects such as gain or loss of functional RNA motifs and protein domains, fine-tuning of DNA binding activity, and co-regulation for genes in the same complex or pathway. The methods and findings provide valuable resources for further functional genomic studies such as understanding natural SNP variations for plant community. |
format | Online Article Text |
id | pubmed-6797763 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-67977632019-10-21 Multi-strategic RNA-seq analysis reveals a high-resolution transcriptional landscape in cotton Wang, Kun Wang, Dehe Zheng, Xiaomin Qin, Ai Zhou, Jie Guo, Boyu Chen, Yanjun Wen, Xingpeng Ye, Wen Zhou, Yu Zhu, Yuxian Nat Commun Article Cotton is an important natural fiber crop, however, its comprehensive and high-resolution gene map is lacking. Here we integrate four complementary high-throughput techniques, including Pacbio long read Iso-seq, strand-specific RNA-seq, CAGE-seq, and PolyA-seq, to systematically explore the transcription landscape across 16 tissues or different organ types in Gossypium arboreum. We devise a computational pipeline, named IGIA, to reconstruct accurate gene structures from the integrated data. Our results reveal a dynamic and diverse transcriptional map in cotton: tissue-specific gene expression, alternative usage of TSSs and polyadenylation sites, hotspot of alternative splicing, and transcriptional read-through. These regulated events affect many genes in various aspects such as gain or loss of functional RNA motifs and protein domains, fine-tuning of DNA binding activity, and co-regulation for genes in the same complex or pathway. The methods and findings provide valuable resources for further functional genomic studies such as understanding natural SNP variations for plant community. Nature Publishing Group UK 2019-10-17 /pmc/articles/PMC6797763/ /pubmed/31624240 http://dx.doi.org/10.1038/s41467-019-12575-x Text en © The Author(s) 2019 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 Wang, Kun Wang, Dehe Zheng, Xiaomin Qin, Ai Zhou, Jie Guo, Boyu Chen, Yanjun Wen, Xingpeng Ye, Wen Zhou, Yu Zhu, Yuxian Multi-strategic RNA-seq analysis reveals a high-resolution transcriptional landscape in cotton |
title | Multi-strategic RNA-seq analysis reveals a high-resolution transcriptional landscape in cotton |
title_full | Multi-strategic RNA-seq analysis reveals a high-resolution transcriptional landscape in cotton |
title_fullStr | Multi-strategic RNA-seq analysis reveals a high-resolution transcriptional landscape in cotton |
title_full_unstemmed | Multi-strategic RNA-seq analysis reveals a high-resolution transcriptional landscape in cotton |
title_short | Multi-strategic RNA-seq analysis reveals a high-resolution transcriptional landscape in cotton |
title_sort | multi-strategic rna-seq analysis reveals a high-resolution transcriptional landscape in cotton |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6797763/ https://www.ncbi.nlm.nih.gov/pubmed/31624240 http://dx.doi.org/10.1038/s41467-019-12575-x |
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