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Identification of Tissue-Specific Protein-Coding and Noncoding Transcripts across 14 Human Tissues Using RNA-seq

Many diseases and adverse drug reactions exhibit tissue specificity. To better understand the tissue-specific expression characteristics of transcripts in different human tissues, we deeply sequenced RNA samples from 14 different human tissues. After filtering many lowly expressed transcripts, 24,72...

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Autores principales: Zhu, Jinhang, Chen, Geng, Zhu, Sibo, Li, Suqing, Wen, Zhuo, Bin Li, Zheng, Yuanting, Shi, Leming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4916594/
https://www.ncbi.nlm.nih.gov/pubmed/27329541
http://dx.doi.org/10.1038/srep28400
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author Zhu, Jinhang
Chen, Geng
Zhu, Sibo
Li, Suqing
Wen, Zhuo
Bin Li,
Zheng, Yuanting
Shi, Leming
author_facet Zhu, Jinhang
Chen, Geng
Zhu, Sibo
Li, Suqing
Wen, Zhuo
Bin Li,
Zheng, Yuanting
Shi, Leming
author_sort Zhu, Jinhang
collection PubMed
description Many diseases and adverse drug reactions exhibit tissue specificity. To better understand the tissue-specific expression characteristics of transcripts in different human tissues, we deeply sequenced RNA samples from 14 different human tissues. After filtering many lowly expressed transcripts, 24,729 protein-coding transcripts and 1,653 noncoding transcripts were identified. By analyzing highly expressed tissue-specific protein-coding transcripts (TSCTs) and noncoding transcripts (TSNTs), we found that testis expressed the highest numbers of TSCTs and TSNTs. Brain, monocytes, ovary, and heart expressed more TSCTs than the rest tissues, whereas brain, placenta, heart, and monocytes expressed more TSNTs than other tissues. Co-expression network constructed based on the TSCTs and TSNTs showed that each hub TSNT was co-expressed with several TSCTs, allowing functional annotation of TSNTs. Important biological processes and KEGG pathways highly related to the specific functions or diseases of each tissue were enriched with the corresponding TSCTs. These TSCTs and TSNTs may participate in the tissue-specific physiological or pathological processes. Our study provided a unique data set and systematic analysis of expression characteristics and functions of both TSCTs and TSNTs based on 14 distinct human tissues, and could facilitate future investigation of the mechanisms behind tissue-specific diseases and adverse drug reactions.
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spelling pubmed-49165942016-06-27 Identification of Tissue-Specific Protein-Coding and Noncoding Transcripts across 14 Human Tissues Using RNA-seq Zhu, Jinhang Chen, Geng Zhu, Sibo Li, Suqing Wen, Zhuo Bin Li, Zheng, Yuanting Shi, Leming Sci Rep Article Many diseases and adverse drug reactions exhibit tissue specificity. To better understand the tissue-specific expression characteristics of transcripts in different human tissues, we deeply sequenced RNA samples from 14 different human tissues. After filtering many lowly expressed transcripts, 24,729 protein-coding transcripts and 1,653 noncoding transcripts were identified. By analyzing highly expressed tissue-specific protein-coding transcripts (TSCTs) and noncoding transcripts (TSNTs), we found that testis expressed the highest numbers of TSCTs and TSNTs. Brain, monocytes, ovary, and heart expressed more TSCTs than the rest tissues, whereas brain, placenta, heart, and monocytes expressed more TSNTs than other tissues. Co-expression network constructed based on the TSCTs and TSNTs showed that each hub TSNT was co-expressed with several TSCTs, allowing functional annotation of TSNTs. Important biological processes and KEGG pathways highly related to the specific functions or diseases of each tissue were enriched with the corresponding TSCTs. These TSCTs and TSNTs may participate in the tissue-specific physiological or pathological processes. Our study provided a unique data set and systematic analysis of expression characteristics and functions of both TSCTs and TSNTs based on 14 distinct human tissues, and could facilitate future investigation of the mechanisms behind tissue-specific diseases and adverse drug reactions. Nature Publishing Group 2016-06-22 /pmc/articles/PMC4916594/ /pubmed/27329541 http://dx.doi.org/10.1038/srep28400 Text en Copyright © 2016, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Zhu, Jinhang
Chen, Geng
Zhu, Sibo
Li, Suqing
Wen, Zhuo
Bin Li,
Zheng, Yuanting
Shi, Leming
Identification of Tissue-Specific Protein-Coding and Noncoding Transcripts across 14 Human Tissues Using RNA-seq
title Identification of Tissue-Specific Protein-Coding and Noncoding Transcripts across 14 Human Tissues Using RNA-seq
title_full Identification of Tissue-Specific Protein-Coding and Noncoding Transcripts across 14 Human Tissues Using RNA-seq
title_fullStr Identification of Tissue-Specific Protein-Coding and Noncoding Transcripts across 14 Human Tissues Using RNA-seq
title_full_unstemmed Identification of Tissue-Specific Protein-Coding and Noncoding Transcripts across 14 Human Tissues Using RNA-seq
title_short Identification of Tissue-Specific Protein-Coding and Noncoding Transcripts across 14 Human Tissues Using RNA-seq
title_sort identification of tissue-specific protein-coding and noncoding transcripts across 14 human tissues using rna-seq
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4916594/
https://www.ncbi.nlm.nih.gov/pubmed/27329541
http://dx.doi.org/10.1038/srep28400
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