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Exploring microproteins from various model organisms using the mip-mining database
Microproteins, prevalent across all kingdoms of life, play a crucial role in cell physiology and human health. Although global gene transcription is widely explored and abundantly available, our understanding of microprotein functions using transcriptome data is still limited. To mitigate this probl...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10623795/ https://www.ncbi.nlm.nih.gov/pubmed/37919660 http://dx.doi.org/10.1186/s12864-023-09735-1 |
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author | Zhao, Bowen Zhao, Jing Wang, Muyao Guo, Yangfan Mehmood, Aamir Wang, Weibin Xiong, Yi Luo, Shenggan Wei, Dong-Qing Zhao, Xin-Qing Wang, Yanjing |
author_facet | Zhao, Bowen Zhao, Jing Wang, Muyao Guo, Yangfan Mehmood, Aamir Wang, Weibin Xiong, Yi Luo, Shenggan Wei, Dong-Qing Zhao, Xin-Qing Wang, Yanjing |
author_sort | Zhao, Bowen |
collection | PubMed |
description | Microproteins, prevalent across all kingdoms of life, play a crucial role in cell physiology and human health. Although global gene transcription is widely explored and abundantly available, our understanding of microprotein functions using transcriptome data is still limited. To mitigate this problem, we present a database, Mip-mining (https://weilab.sjtu.edu.cn/mipmining/), underpinned by high-quality RNA-sequencing data exclusively aimed at analyzing microprotein functions. The Mip-mining hosts 336 sets of high-quality transcriptome data from 8626 samples and nine representative living organisms, including microorganisms, plants, animals, and humans, in our Mip-mining database. Our database specifically provides a focus on a range of diseases and environmental stress conditions, taking into account chemical, physical, biological, and diseases-related stresses. Comparatively, our platform enables customized analysis by inputting desired data sets with self-determined cutoff values. The practicality of Mip-mining is demonstrated by identifying essential microproteins in different species and revealing the importance of ATP15 in the acetic acid stress tolerance of budding yeast. We believe that Mip-mining will facilitate a greater understanding and application of microproteins in biotechnology. Moreover, it will be beneficial for designing therapeutic strategies under various biological conditions. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12864-023-09735-1. |
format | Online Article Text |
id | pubmed-10623795 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-106237952023-11-04 Exploring microproteins from various model organisms using the mip-mining database Zhao, Bowen Zhao, Jing Wang, Muyao Guo, Yangfan Mehmood, Aamir Wang, Weibin Xiong, Yi Luo, Shenggan Wei, Dong-Qing Zhao, Xin-Qing Wang, Yanjing BMC Genomics Database Microproteins, prevalent across all kingdoms of life, play a crucial role in cell physiology and human health. Although global gene transcription is widely explored and abundantly available, our understanding of microprotein functions using transcriptome data is still limited. To mitigate this problem, we present a database, Mip-mining (https://weilab.sjtu.edu.cn/mipmining/), underpinned by high-quality RNA-sequencing data exclusively aimed at analyzing microprotein functions. The Mip-mining hosts 336 sets of high-quality transcriptome data from 8626 samples and nine representative living organisms, including microorganisms, plants, animals, and humans, in our Mip-mining database. Our database specifically provides a focus on a range of diseases and environmental stress conditions, taking into account chemical, physical, biological, and diseases-related stresses. Comparatively, our platform enables customized analysis by inputting desired data sets with self-determined cutoff values. The practicality of Mip-mining is demonstrated by identifying essential microproteins in different species and revealing the importance of ATP15 in the acetic acid stress tolerance of budding yeast. We believe that Mip-mining will facilitate a greater understanding and application of microproteins in biotechnology. Moreover, it will be beneficial for designing therapeutic strategies under various biological conditions. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12864-023-09735-1. BioMed Central 2023-11-02 /pmc/articles/PMC10623795/ /pubmed/37919660 http://dx.doi.org/10.1186/s12864-023-09735-1 Text en © The Author(s) 2023 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/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Database Zhao, Bowen Zhao, Jing Wang, Muyao Guo, Yangfan Mehmood, Aamir Wang, Weibin Xiong, Yi Luo, Shenggan Wei, Dong-Qing Zhao, Xin-Qing Wang, Yanjing Exploring microproteins from various model organisms using the mip-mining database |
title | Exploring microproteins from various model organisms using the mip-mining database |
title_full | Exploring microproteins from various model organisms using the mip-mining database |
title_fullStr | Exploring microproteins from various model organisms using the mip-mining database |
title_full_unstemmed | Exploring microproteins from various model organisms using the mip-mining database |
title_short | Exploring microproteins from various model organisms using the mip-mining database |
title_sort | exploring microproteins from various model organisms using the mip-mining database |
topic | Database |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10623795/ https://www.ncbi.nlm.nih.gov/pubmed/37919660 http://dx.doi.org/10.1186/s12864-023-09735-1 |
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