Lei Sun, Jinwen Luan, Jinbiao Wang, Xiaoli Li, Wenqian Zhang, Xiaohui Ji, Longhua Liu, Ru Wang, Bingxiang Xu
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The metadata of each sample were manually curated. Data were uniformly processed and batch effects corrected. All the information was well organized in an easy-to-use website for free search, visualization, and download.</p><p><strong>Results: </strong>GEPREP now includes 69 RNA-seq datasets of pre- and post-exercise, comprising 26 human datasets (1120 samples) and 43 mouse datasets (1006 samples). Specifically, there were 977 (87.2 %) human samples of skeletal muscle and 143 (12.8 %) human samples of blood. There were also samples across 9 mice tissues with skeletal muscle (359, 35.7 %) and brain (280, 27.8 %) accounting for the main fractions. Metadata-including subject, exercise interventions, sampling sites, and post-processing methods-are also included. The metadata and gene expression profiles are freely accessible at http://www.geprep.org.cn/.</p><p><strong>Conclusion: </strong>GEPREP is a comprehensive data atlas of RNA-seq-based gene expression profiles responding to exercise. With its reliable annotations and user-friendly interfaces, it has the potential to deepen our understanding of exercise physiology.</p>","PeriodicalId":48897,"journal":{"name":"Journal of Sport and Health Science","volume":" ","pages":"100992"},"PeriodicalIF":9.7000,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"GEPREP: A comprehensive data atlas of RNA-seq-based gene expression profiles of exercise responses.\",\"authors\":\"Lei Sun, Jinwen Luan, Jinbiao Wang, Xiaoli Li, Wenqian Zhang, Xiaohui Ji, Longhua Liu, Ru Wang, Bingxiang Xu\",\"doi\":\"10.1016/j.jshs.2024.100992\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Physical activity can regulate and affect gene expression in multiple tissues and cells. Recently, with the development of next-generation sequencing, a large number of RNA-sequencing (RNA-seq)-based gene expression profiles about physical activity have been shared in public resources; however, they are poorly curated and underutilized. To tackle this problem, we developed a data atlas of such data through comprehensive data collection, curation, and organization.</p><p><strong>Methods: </strong>The data atlas, termed gene expression profiles of RNA-seq-based exercise responses (GEPREP), was built on a comprehensive collection of high-quality RNA-seq data on exercise responses. The metadata of each sample were manually curated. Data were uniformly processed and batch effects corrected. All the information was well organized in an easy-to-use website for free search, visualization, and download.</p><p><strong>Results: </strong>GEPREP now includes 69 RNA-seq datasets of pre- and post-exercise, comprising 26 human datasets (1120 samples) and 43 mouse datasets (1006 samples). Specifically, there were 977 (87.2 %) human samples of skeletal muscle and 143 (12.8 %) human samples of blood. There were also samples across 9 mice tissues with skeletal muscle (359, 35.7 %) and brain (280, 27.8 %) accounting for the main fractions. Metadata-including subject, exercise interventions, sampling sites, and post-processing methods-are also included. The metadata and gene expression profiles are freely accessible at http://www.geprep.org.cn/.</p><p><strong>Conclusion: </strong>GEPREP is a comprehensive data atlas of RNA-seq-based gene expression profiles responding to exercise. With its reliable annotations and user-friendly interfaces, it has the potential to deepen our understanding of exercise physiology.</p>\",\"PeriodicalId\":48897,\"journal\":{\"name\":\"Journal of Sport and Health Science\",\"volume\":\" \",\"pages\":\"100992\"},\"PeriodicalIF\":9.7000,\"publicationDate\":\"2024-09-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Sport and Health Science\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1016/j.jshs.2024.100992\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"HOSPITALITY, LEISURE, SPORT & TOURISM\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Sport and Health Science","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1016/j.jshs.2024.100992","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"HOSPITALITY, LEISURE, SPORT & TOURISM","Score":null,"Total":0}
GEPREP: A comprehensive data atlas of RNA-seq-based gene expression profiles of exercise responses.
Background: Physical activity can regulate and affect gene expression in multiple tissues and cells. Recently, with the development of next-generation sequencing, a large number of RNA-sequencing (RNA-seq)-based gene expression profiles about physical activity have been shared in public resources; however, they are poorly curated and underutilized. To tackle this problem, we developed a data atlas of such data through comprehensive data collection, curation, and organization.
Methods: The data atlas, termed gene expression profiles of RNA-seq-based exercise responses (GEPREP), was built on a comprehensive collection of high-quality RNA-seq data on exercise responses. The metadata of each sample were manually curated. Data were uniformly processed and batch effects corrected. All the information was well organized in an easy-to-use website for free search, visualization, and download.
Results: GEPREP now includes 69 RNA-seq datasets of pre- and post-exercise, comprising 26 human datasets (1120 samples) and 43 mouse datasets (1006 samples). Specifically, there were 977 (87.2 %) human samples of skeletal muscle and 143 (12.8 %) human samples of blood. There were also samples across 9 mice tissues with skeletal muscle (359, 35.7 %) and brain (280, 27.8 %) accounting for the main fractions. Metadata-including subject, exercise interventions, sampling sites, and post-processing methods-are also included. The metadata and gene expression profiles are freely accessible at http://www.geprep.org.cn/.
Conclusion: GEPREP is a comprehensive data atlas of RNA-seq-based gene expression profiles responding to exercise. With its reliable annotations and user-friendly interfaces, it has the potential to deepen our understanding of exercise physiology.
期刊介绍:
The Journal of Sport and Health Science (JSHS) is an international, multidisciplinary journal that aims to advance the fields of sport, exercise, physical activity, and health sciences. Published by Elsevier B.V. on behalf of Shanghai University of Sport, JSHS is dedicated to promoting original and impactful research, as well as topical reviews, editorials, opinions, and commentary papers.
With a focus on physical and mental health, injury and disease prevention, traditional Chinese exercise, and human performance, JSHS offers a platform for scholars and researchers to share their findings and contribute to the advancement of these fields. Our journal is peer-reviewed, ensuring that all published works meet the highest academic standards.
Supported by a carefully selected international editorial board, JSHS upholds impeccable integrity and provides an efficient publication platform. We invite submissions from scholars and researchers worldwide, and we are committed to disseminating insightful and influential research in the field of sport and health science.