AgeAnno: a knowledgebase of single-cell annotation of aging in human.

Journal: Nucleic acids research
Published Date: Jan 6, 2023

Abstract

Aging is a complex process that accompanied by molecular and cellular alterations. The identification of tissue-/cell type-specific biomarkers of aging and elucidation of the detailed biological mechanisms of aging-related genes at the single-cell level can help to understand the heterogeneous aging process and design targeted anti-aging therapeutics. Here, we built AgeAnno (https://relab.xidian.edu.cn/AgeAnno/#/), a knowledgebase of single cell annotation of aging in human, aiming to provide comprehensive characterizations for aging-related genes across diverse tissue-cell types in human by using single-cell RNA and ATAC sequencing data (scRNA and scATAC). The current version of AgeAnno houses 1 678 610 cells from 28 healthy tissue samples with ages ranging from 0 to 110 years. We collected 5580 aging-related genes from previous resources and performed dynamic functional annotations of the cellular context. For the scRNA data, we performed analyses include differential gene expression, gene variation coefficient, cell communication network, transcription factor (TF) regulatory network, and immune cell proportionc. AgeAnno also provides differential chromatin accessibility analysis, motif/TF enrichment and footprint analysis, and co-accessibility peak analysis for scATAC data. AgeAnno will be a unique resource to systematically characterize aging-related genes across diverse tissue-cell types in human, and it could facilitate antiaging and aging-related disease research.

Authors

  • Kexin Huang
    School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, PR China.
  • Hoaran Gong
    West China Biomedical Big Data Centre, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, P.R. China.
  • Jingjing Guan
    School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, P.R. China.
  • Lingxiao Zhang
    Department of Computer Science, Peking University, Beijing, China.
  • Changbao Hu
    School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, P.R. China.
  • Weiling Zhao
    Center for Systems Medicine, School of Biomedical Bioinformatics, University of Texas Health Science Center at Houston, TX 77030, USA.
  • Liyu Huang
    School of Life Science and Technology, Xidian University, Xi'an, 710071, Shaanxi, People's Republic of China. huangly@mail.xidian.edu.cn.
  • Wei Zhang
    The First Affiliated Hospital of Nanchang University, Nanchang, China.
  • Pora Kim
    Center for Computational Systems Medicine, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA.
  • Xiaobo Zhou
    Department of Diagnostic Radiology, Wake Forest Medical School, Winston-Salem, NC 27103, USA. Electronic address: xizhou@wakehealth.edu.

Keywords

External Resources

Popular Topics
Recent Journals