MethAgingDB:衰老生物学的全面DNA甲基化数据库。

IF 6.9 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Siyu Li, Songming Tang, Haocheng Ma, Haixin Wang, Shengquan Chen
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引用次数: 0

摘要

准确量化生物年龄对于理解衰老机制和制定有效的干预措施至关重要。分子衰老时钟,特别是表观遗传时钟,利用DNA甲基化数据来估计生物年龄,已经成为这一研究领域的重要工具。然而,缺乏一个全面的、可公开访问的数据库,其中包含不同年龄和组织的统一格式的DNA甲基化数据集,使表观遗传时钟的研究变得复杂。研究人员在定位相关数据集、从原始数据中获取关键信息以及管理不一致的数据格式和元数据注释方面面临着重大挑战。此外,缺乏与衰老相关的差异甲基化位点(dms,也称为差异甲基化位点或差异甲基化胞嘧啶)和区域(DMRs)的专门资源,这阻碍了对衰老表观遗传机制的理解。为了解决这些挑战,我们开发了MethAgingDB,一个全面的DNA甲基化数据库,用于衰老生物学。MethAgingDB包括93个数据集,包括来自13种不同人体组织的11474个图谱和来自9种不同小鼠组织的1361个图谱。该数据库以一致的矩阵格式提供预处理的DNA甲基化数据,以及组织特异性dms和DMRs,以基因为中心的衰老见解以及广泛的表观遗传时钟收集。MethAgingDB有望简化与衰老相关的表观遗传学研究,并支持开发强大的、生物学上知情的衰老生物标志物。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

MethAgingDB: a comprehensive DNA methylation database for aging biology.

MethAgingDB: a comprehensive DNA methylation database for aging biology.

MethAgingDB: a comprehensive DNA methylation database for aging biology.

MethAgingDB: a comprehensive DNA methylation database for aging biology.

Accurately quantifying biological age is crucial for understanding the mechanisms of aging and developing effective interventions. Molecular aging clocks, particularly epigenetic clocks that use DNA methylation data to estimate biological age, have become essential tools in this area of research. However, the lack of a comprehensive, publicly accessible database with uniformly formatted DNA methylation datasets across various ages and tissues complicates the investigation of epigenetic clocks. Researchers face significant challenges in locating relevant datasets, accessing key information from raw data, and managing inconsistent data formats and metadata annotations. Additionally, there is a lack of dedicated resources for aging-related differentially methylated sites (DMSs, also named differentially methylated positions or differentially methylated cytosines) and regions (DMRs), which hinders progress in understanding the epigenetic mechanisms of aging. To address these challenges, we developed MethAgingDB, a comprehensive DNA methylation database for aging biology. MethAgingDB includes 93 datasets, with 11474 profiles from 13 distinct human tissues and 1361 profiles from 9 distinct mouse tissues. The database provides preprocessed DNA methylation data in a consistent matrix format, along with tissue-specific DMSs and DMRs, gene-centric aging insights, and an extensive collection of epigenetic clocks. Together, MethAgingDB is expected to streamline aging-related epigenetic research and support the development of robust, biologically informed aging biomarkers.

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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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