AgeAnnoMO: a knowledgebase of multi-omics annotation for animal aging.
Kexin Huang, Xi Liu, Zhaocan Zhang, Tiangang Wang, Haixia Xu, Qingxuan Li, Yuhao Jia, Liyu Huang, Pora Kim, Xiaobo Zhou
Author Information
Kexin Huang: The Center of Gerontology and Geriatrics and West China Biomedical Big Data Centre, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, PR China.
Xi Liu: School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, PR China.
Zhaocan Zhang: School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, PR China.
Tiangang Wang: School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, PR China.
Haixia Xu: The Center of Gerontology and Geriatrics and West China Biomedical Big Data Centre, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, PR China.
Qingxuan Li: School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, PR China.
Yuhao Jia: School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, PR China.
Liyu Huang: School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, PR China. ORCID
Pora Kim: Center for Computational Systems Medicine, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA. ORCID
Xiaobo Zhou: Center for Computational Systems Medicine, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA. ORCID
Aging entails gradual functional decline influenced by interconnected factors. Multiple hallmarks proposed as common and conserved underlying denominators of aging on the molecular, cellular and systemic levels across multiple species. Thus, understanding the function of aging hallmarks and their relationships across species can facilitate the translation of anti-aging drug development from model organisms to humans. Here, we built AgeAnnoMO (https://relab.xidian.edu.cn/AgeAnnoMO/#/), a knowledgebase of multi-omics annotation for animal aging. AgeAnnoMO encompasses an extensive collection of 136 datasets from eight modalities, encompassing 8596 samples from 50 representative species, making it a comprehensive resource for aging and longevity research. AgeAnnoMO characterizes multiple aging regulators across species via multi-omics data, comprehensively annotating aging-related genes, proteins, metabolites, mitochondrial genes, microbiotas and age-specific TCR and BCR sequences tied to aging hallmarks for these species and tissues. AgeAnnoMO not only facilitates a deeper and more generalizable understanding of aging mechanisms, but also provides potential insights of the specificity across tissues and species in aging process, which is important to develop the effective anti-aging interventions for diverse populations. We anticipate that AgeAnnoMO will provide a valuable resource for comprehending and integrating the conserved driving hallmarks in aging biology and identifying the targetable biomarkers for aging research.
