With the gradual aging of the global population, the need to research and find the keys to healthy aging is ever more critical and takes on new urgency. Aging is a complex process, influenced by environmental factors, genetic and epigenetic regulations, post-translational modifications, metabolism, microbiome, lifestyle, and other factors. Recently, high-throughput omics technologies (including genomics, transcriptomics, epigenomics, metabolomics, proteomics, pharmacogenomics and metagenomics) have been widely applied to aging studies, facilitating large-scale profiling of aging-associated molecular changes and regulatory states. In addition, emerging methods have allowed us to probe aging at the single-cell resolution, providing integrated multi-dimensional data at an unprecedented scale and depth. To date, a growing volume of valuable aging-related data necessitates an open, integrative database to support new lines of aging research. Aging Atlas is a project that began in 2019 and aims to provide a wide range of life science researchers with valuable resources and allow access to large-scale gene expression and regulation datasets created by a range of high-throughput omics technologies.
Overview of Aging Atlas databases
Aging atlas is a curated biomedical database comprising a range of aging-related omics data (transcriptomics, epigenomics, proteomics and single-cell transcriptomics), as well as bioinformatics tools to query and visualize the data. This database aims to collect omics data spanning the entire spectrum of aging and longevity biology across different model organisms and species and curate data related to cellular senescence, age-related diseases, lifespan-extending strategies (such as exercise and caloric restriction) and geroprotective drug development. The dataset is classified according to the type of omics data. Currently, data in our Aging Atlas are manually curated from literature and retrieved from existing databases. Global users are readily able to upload their data to a specific data category with raw data deposited in the China National Center for Bioinformation (CNCB).
This database is searchable by gene name or DOI of the literature references and the results are displayed in the form of tables and interactive charts. Raw data can also be downloaded. In this way, Aging Atlas provides user-friendly functionalities to explore age-related changes in gene expression and help identify key regulatory networks during aging. The database is constantly updated to add high-quality aging omics data, and is open and freely available to the public. Therefore, it is a valuable resource for aging communities and life scientists.