IF 5.8 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES Scientific Data Pub Date : 2025-02-07 DOI:10.1038/s41597-025-04548-1
Feiyang Xue, Yuqin Yan, Weiwei Jin, Haotian Zhu, Yanbo Yang, Zhanhui Yu, Xuewen Xu, Jing Gong, Xiaohui Niu
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摘要

作为一种主要的转录前机制,替代启动子(AP)事件可以启动不同的转录起始位点,从而产生不同的 mRNA 异构体并调控其表达。目前,在人体组织中已经发现了数十万个APs,相当多的APs已被证实与复杂的性状和疾病相关。最近的研究也证明了 APs 对动物的重要影响。然而,APs 在动物体内的分布尚未得到充分认识。在这项研究中,我们对来自 12 个物种 23,077 个样本的 102,349 个 AP 图谱进行了系统表征。我们进一步鉴定了组织特异性 APs,并调查了不同物种中与性状相关的启动子。此外,我们还分析了 AP 与增强子 RNA(eRNA)/转录因子(TF)之间的关联,以此来确定潜在的调控因子。综合这些发现,我们最终开发出了动物 APdb,这是一个用于搜索、浏览和下载动物 APs 相关信息的数据库。Animal-APdb有望成为探索动物APs功能和机制的宝贵资源。
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An Integrated Database for Exploring Alternative Promoters in Animals.

Alternative promoter (AP) events, as a major pre-transcriptional mechanism, can initiate different transcription start sites to generate distinct mRNA isoforms and regulate their expression. At present, hundreds of thousands of APs have been identified across human tissues, and a considerable number of APs have been demonstrated to be associated with complex traits and diseases. Recent researches have also proven important effects of APs on animals. However, the landscape of APs in animals has not been fully recognized. In this study, 102,349 AP profiles from 23,077 samples across 12 species were systematically characterized. We further identified tissue-specific APs and investigated trait-related promoters among various species. In addition, we analyzed the associations between APs and enhancer RNAs (eRNA)/transcription factors (TF) as a means of identifying potential regulatory factors. Integrating these findings, we finally developed Animal-APdb, a database for the searching, browsing, and downloading of information related to Animal APs. Animal-APdb is expected to serve as a valuable resource for exploring the functions and mechanisms of APs in animals.

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来源期刊
Scientific Data
Scientific Data Social Sciences-Education
CiteScore
11.20
自引率
4.10%
发文量
689
审稿时长
16 weeks
期刊介绍: Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data. The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.
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