BIOLOGICAL ANALYSIS CORE - PROJECT SUMMARY This Buck Institute Tissue Mapping Center (TMC) proposes to map senescent cells in three human somatic and reproductive tissues; ovaries, breast tissue and skeletal muscle. A major gap in the field has been to define specific cellular senescence markers for distinct cells and tissue types. We propose to fill this gap by defining markers of cellular senescence in the context of aging in human tissues. The capabilities of this core include a deep knowledge of multiple aspects of senescence encompassing the SASP, novel senolytics, and preliminary data defining senescent cells in human muscle tissue. Tissues received in the Biospecimen Core will be conveyed to the Biological Analysis Core and subjected to multiple procedures designed to identify senescent cell signatures (either protein or mRNA) in nuclei or biofluids, and confirmed in tissue sections. The results from the Biological Analysis Core will be conveyed to the Data Analysis Core, and coordinated through the Administrative Core. The Biological Analysis Core will spatially map and determine the signatures of cellular senescence in healthy human ovaries, breast, and muscle in both sexes across an aging continuum through four specific aims. 1) Determine the unique transcriptional signature of large senescent cells. We will determine the transcriptional signatures of large senescent cells, which are lost during conventional single cell workflows and use this data to determine the prevalence of such signatures in the breast, ovary, and muscle. 2) Determine senescent protein signatures of the breast, ovary, and skeletal muscle. We will comprehensively analyze secreted senescence-associated secretory phenotype (SASP) proteins from bio fluids, and cell culture systems from muscle, breast, and ovaries using different senescence inducers and senolytics. 3) Determine senescent transcriptional signatures of the breast, ovary, and skeletal muscle. We will use a bootstrapping strategy on key cell types from the tissues in this aim, to determine unique single cell senescent signatures derived from a range of senescent inducers on prototypical cell cultures from each tissue. We will use these data to map similar signatures back to complex fully profiled data sets derived from intact tissues using snRNA‐seq, cell assignment, and expression analysis. 4) Determine spatial relationship and frequencies of senescent cells in tissue sections. We will take advantage of emerging technologies from Nanostring (Digital Spatial Profiling), and 10X technologies (Visium) to build on our knowledge discovered in the first three aims to better understand frequency and subtypes of senescent cells within tissue sections from tissue sections. In conjunction with other cores we expect to create a comprehensive spatial map and signatures of senescence in reproductive tissues (breast and ovary) and also the sex-specific and longitudinal differences in muscle, a somatic tissue, with age.