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Dryad

A new gene set identifies senescent cells and predicts senescence-associated pathways across tissues

Cite this dataset

Saul, Dominik (2022). A new gene set identifies senescent cells and predicts senescence-associated pathways across tissues [Dataset]. Dryad. https://doi.org/10.5061/dryad.j0zpc86gv

Abstract

Although cellular senescence drives multiple age-related co-morbidities through the senescence-associated secretory phenotype (SASP), in vivo senescent cell identification remains challenging. Here, we generated a gene set (SenMayo) and validated its enrichment in bone biopsies from two aged human cohorts. We further demonstrated reductions in SenMayo in bone following genetic clearance of senescent cells in mice and in adipose tissue from humans following pharmacological senescent cell clearance. We next used SenMayo to identify senescent hematopoietic or mesenchymal cells at the single cell level from human and murine bone marrow/bone scRNA-seq data. Thus, SenMayo identifies senescent cells across tissues and species with high fidelity. Using this senescence panel, we were able to characterize senescent cells at the single-cell level and identify key intercellular signaling pathways. SenMayo also represents a potentially clinically applicable panel for monitoring senescent cell burden with aging and other conditions as well as in studies of senolytic drugs.

Methods

Source Code

Raw counts

Funding

Deutsche Forschungsgemeinschaft, Award: 413501650

National Institute on Aging, Award: AG062413

National Institute on Aging, Award: AG065868

National Institute of Arthritis and Musculoskeletal and Skin Diseases, Award: AR070241

National Institute on Aging, Award: AG063707

National Institute on Aging, Award: R37 AG 013925

National Cancer Institute, Award: R33AG 61456