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Dominant transcript expression profiles of human protein-coding genes interrogated with GTEx dataset

The discovery and quantification of mRNA transcripts using short-read next-generation sequencing (NGS) data is a complicated task. There are far more alternative mRNA transcripts expressed by human genes than can be identified from NGS transcriptome data and various bioinformatic pipelines, while th...

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Autores principales: Tung, Kuo-Feng, Pan, Chao-Yu, Lin, Wen-chang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9050722/
https://www.ncbi.nlm.nih.gov/pubmed/35484179
http://dx.doi.org/10.1038/s41598-022-10619-9
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author Tung, Kuo-Feng
Pan, Chao-Yu
Lin, Wen-chang
author_facet Tung, Kuo-Feng
Pan, Chao-Yu
Lin, Wen-chang
author_sort Tung, Kuo-Feng
collection PubMed
description The discovery and quantification of mRNA transcripts using short-read next-generation sequencing (NGS) data is a complicated task. There are far more alternative mRNA transcripts expressed by human genes than can be identified from NGS transcriptome data and various bioinformatic pipelines, while the numbers of annotated human protein-coding genes has gradually declined in recent years. It is essential to learn more about the thorough tissue expression profiles of alternative transcripts in order to obtain their molecular modulations and actual functional significance. In this report, we present a bioinformatic database for interrogating the representative tissue of human protein-coding transcripts. The database allows researchers to visually explore the top-ranked transcript expression profiles in particular tissue types. Most transcripts of protein-coding genes were found to have certain tissue expression patterns. This observation demonstrated that many alternative transcripts were particularly modulated in different cell types. This user-friendly tool visually represents transcript expression profiles in a tissue-specific manner. Identification of tissue specific protein-coding genes and transcripts is a substantial advance towards interpreting their biological functions and further functional genomics studies.
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spelling pubmed-90507222022-04-30 Dominant transcript expression profiles of human protein-coding genes interrogated with GTEx dataset Tung, Kuo-Feng Pan, Chao-Yu Lin, Wen-chang Sci Rep Article The discovery and quantification of mRNA transcripts using short-read next-generation sequencing (NGS) data is a complicated task. There are far more alternative mRNA transcripts expressed by human genes than can be identified from NGS transcriptome data and various bioinformatic pipelines, while the numbers of annotated human protein-coding genes has gradually declined in recent years. It is essential to learn more about the thorough tissue expression profiles of alternative transcripts in order to obtain their molecular modulations and actual functional significance. In this report, we present a bioinformatic database for interrogating the representative tissue of human protein-coding transcripts. The database allows researchers to visually explore the top-ranked transcript expression profiles in particular tissue types. Most transcripts of protein-coding genes were found to have certain tissue expression patterns. This observation demonstrated that many alternative transcripts were particularly modulated in different cell types. This user-friendly tool visually represents transcript expression profiles in a tissue-specific manner. Identification of tissue specific protein-coding genes and transcripts is a substantial advance towards interpreting their biological functions and further functional genomics studies. Nature Publishing Group UK 2022-04-28 /pmc/articles/PMC9050722/ /pubmed/35484179 http://dx.doi.org/10.1038/s41598-022-10619-9 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Tung, Kuo-Feng
Pan, Chao-Yu
Lin, Wen-chang
Dominant transcript expression profiles of human protein-coding genes interrogated with GTEx dataset
title Dominant transcript expression profiles of human protein-coding genes interrogated with GTEx dataset
title_full Dominant transcript expression profiles of human protein-coding genes interrogated with GTEx dataset
title_fullStr Dominant transcript expression profiles of human protein-coding genes interrogated with GTEx dataset
title_full_unstemmed Dominant transcript expression profiles of human protein-coding genes interrogated with GTEx dataset
title_short Dominant transcript expression profiles of human protein-coding genes interrogated with GTEx dataset
title_sort dominant transcript expression profiles of human protein-coding genes interrogated with gtex dataset
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9050722/
https://www.ncbi.nlm.nih.gov/pubmed/35484179
http://dx.doi.org/10.1038/s41598-022-10619-9
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