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Deep annotation of long noncoding RNAs by assembling RNA-seq and small RNA-seq data

Long noncoding RNAs (lncRNAs) are increasingly being recognized as modulators in various biological processes. However, due to their low expression, their systematic characterization is difficult to determine. Here, we performed transcript annotation by a newly developed computational pipeline, term...

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Autores principales: Zhang, Jiaming, Hou, Weibo, Zhao, Qi, Xiao, Songling, Linghu, Hongye, Zhang, Lixin, Du, Jiawei, Cui, Hongdi, Yang, Xu, Ling, Shukuan, Su, Jianzhong, Kong, Qingran
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society for Biochemistry and Molecular Biology 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10498003/
https://www.ncbi.nlm.nih.gov/pubmed/37543366
http://dx.doi.org/10.1016/j.jbc.2023.105130
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author Zhang, Jiaming
Hou, Weibo
Zhao, Qi
Xiao, Songling
Linghu, Hongye
Zhang, Lixin
Du, Jiawei
Cui, Hongdi
Yang, Xu
Ling, Shukuan
Su, Jianzhong
Kong, Qingran
author_facet Zhang, Jiaming
Hou, Weibo
Zhao, Qi
Xiao, Songling
Linghu, Hongye
Zhang, Lixin
Du, Jiawei
Cui, Hongdi
Yang, Xu
Ling, Shukuan
Su, Jianzhong
Kong, Qingran
author_sort Zhang, Jiaming
collection PubMed
description Long noncoding RNAs (lncRNAs) are increasingly being recognized as modulators in various biological processes. However, due to their low expression, their systematic characterization is difficult to determine. Here, we performed transcript annotation by a newly developed computational pipeline, termed RNA-seq and small RNA-seq combined strategy (RSCS), in a wide variety of cellular contexts. Thousands of high-confidence potential novel transcripts were identified by the RSCS, and the reliability of the transcriptome was verified by analysis of transcript structure, base composition, and sequence complexity. Evidenced by the length comparison, the frequency of the core promoter and the polyadenylation signal motifs, and the locations of transcription start and end sites, the transcripts appear to be full length. Furthermore, taking advantage of our strategy, we identified a large number of endogenous retrovirus-associated lncRNAs, and a novel endogenous retrovirus–lncRNA that was functionally involved in control of Yap1 expression and essential for early embryogenesis was identified. In summary, the RSCS can generate a more complete and precise transcriptome, and our findings greatly expanded the transcriptome annotation for the mammalian community.
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spelling pubmed-104980032023-09-14 Deep annotation of long noncoding RNAs by assembling RNA-seq and small RNA-seq data Zhang, Jiaming Hou, Weibo Zhao, Qi Xiao, Songling Linghu, Hongye Zhang, Lixin Du, Jiawei Cui, Hongdi Yang, Xu Ling, Shukuan Su, Jianzhong Kong, Qingran J Biol Chem Research Article Long noncoding RNAs (lncRNAs) are increasingly being recognized as modulators in various biological processes. However, due to their low expression, their systematic characterization is difficult to determine. Here, we performed transcript annotation by a newly developed computational pipeline, termed RNA-seq and small RNA-seq combined strategy (RSCS), in a wide variety of cellular contexts. Thousands of high-confidence potential novel transcripts were identified by the RSCS, and the reliability of the transcriptome was verified by analysis of transcript structure, base composition, and sequence complexity. Evidenced by the length comparison, the frequency of the core promoter and the polyadenylation signal motifs, and the locations of transcription start and end sites, the transcripts appear to be full length. Furthermore, taking advantage of our strategy, we identified a large number of endogenous retrovirus-associated lncRNAs, and a novel endogenous retrovirus–lncRNA that was functionally involved in control of Yap1 expression and essential for early embryogenesis was identified. In summary, the RSCS can generate a more complete and precise transcriptome, and our findings greatly expanded the transcriptome annotation for the mammalian community. American Society for Biochemistry and Molecular Biology 2023-08-04 /pmc/articles/PMC10498003/ /pubmed/37543366 http://dx.doi.org/10.1016/j.jbc.2023.105130 Text en © 2023 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Research Article
Zhang, Jiaming
Hou, Weibo
Zhao, Qi
Xiao, Songling
Linghu, Hongye
Zhang, Lixin
Du, Jiawei
Cui, Hongdi
Yang, Xu
Ling, Shukuan
Su, Jianzhong
Kong, Qingran
Deep annotation of long noncoding RNAs by assembling RNA-seq and small RNA-seq data
title Deep annotation of long noncoding RNAs by assembling RNA-seq and small RNA-seq data
title_full Deep annotation of long noncoding RNAs by assembling RNA-seq and small RNA-seq data
title_fullStr Deep annotation of long noncoding RNAs by assembling RNA-seq and small RNA-seq data
title_full_unstemmed Deep annotation of long noncoding RNAs by assembling RNA-seq and small RNA-seq data
title_short Deep annotation of long noncoding RNAs by assembling RNA-seq and small RNA-seq data
title_sort deep annotation of long noncoding rnas by assembling rna-seq and small rna-seq data
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10498003/
https://www.ncbi.nlm.nih.gov/pubmed/37543366
http://dx.doi.org/10.1016/j.jbc.2023.105130
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