Aging Atlas: a multi-omics database for aging biology

TLDR

Organismal aging is driven by interconnected molecular changes, and combinational multi‑omics analyses across genomics, epigenomics, transcriptomics, proteomics, metabolomics and pharmacogenomics at population or single‑cell levels enable a multi‑dimensional, integrated profile of the heterogeneous aging process, facilitating exploration of gene‑expression regulation and development of new interventions. The study establishes the Aging Atlas, an open, integrated database providing researchers access to large‑scale gene expression and regulation datasets from diverse high‑throughput omics technologies to support aging research. The database comprises five modules—RNA‑seq, scRNA‑seq, ChIP‑seq, protein‑protein interaction, and geroprotective compound pharmacogenomics—and offers user‑friendly tools to explore age‑related gene‑expression changes and download raw data. The Aging Atlas is freely available at https://bigd.big.ac.cn/aging/index.

Abstract

Organismal aging is driven by interconnected molecular changes encompassing internal and extracellular factors. Combinational analysis of high-throughput 'multi-omics' datasets (gathering information from genomics, epigenomics, transcriptomics, proteomics, metabolomics and pharmacogenomics), at either populational or single-cell levels, can provide a multi-dimensional, integrated profile of the heterogeneous aging process with unprecedented throughput and detail. These new strategies allow for the exploration of the molecular profile and regulatory status of gene expression during aging, and in turn, facilitate the development of new aging interventions. With a continually growing volume of valuable aging-related data, it is necessary to establish an open and integrated database to support a wide spectrum of aging research. The Aging Atlas database aims to provide a wide range of life science researchers with valuable resources that allow access to a large-scale of gene expression and regulation datasets created by various high-throughput omics technologies. The current implementation includes five modules: transcriptomics (RNA-seq), single-cell transcriptomics (scRNA-seq), epigenomics (ChIP-seq), proteomics (protein-protein interaction), and pharmacogenomics (geroprotective compounds). Aging Atlas provides user-friendly functionalities to explore age-related changes in gene expression, as well as raw data download services. Aging Atlas is freely available at https://bigd.big.ac.cn/aging/index.