Project Summary: Single-Cell and Spatial Transcriptomics (SCST) Core Single cell transcriptomics permits researchers to analyze tissue heterogeneity and complexity in disease states. These technologies add enormous value to research strategies aimed at discovering new disease-specific cell surface markers, drug targets, molecular subtypes of tumors, etc. However, common single cell-omics platforms are limited by high cost and access to robust computational analysis. The goals of the Single-Cell and Spatial Transcriptomics (SCST) Core are to lower barriers of entry to single cell and spatial transcriptomics technologies for CMTDD investigators and the broader UNMC community at a reasonable cost, offer consultations and technical assistance for training new users, enable users to analyze complex datasets, and remain adaptable to increase capacity and tools as needed from the UNMC community. The working hypothesis is that increased access to these emergent and powerful technologies will pay dividends on the back end in the form of more impactful publications and a higher rate of grant funding. To achieve these goals, we will provide users with sufficient low-cost equipment, consultations, and computational tools to analyze single cell and spatial transcriptomics data. Pioneering work in the Shalek group identified a lower cost solution to droplet based scRNA-seq called Seq-Well to generate high quality libraries. We have successfully implemented Seq-Well at UNMC and generated hiqh quality data with unique biological insights. Our core also will provide subsidized access to spatial transcriptomics (MERSCOPE). Thus, the SCST core will provide low-cost access to Seq-Well and MERSCOPE, allowing for a range of options for high resolution molecular profiling of tissue and cellular heterogeneity in complex systems. Implementation of these tools at UNMC will enable investigators to develop innovative new research areas. The SCST will ensure that cutting edge computational tools are available to users who want to conduct their own rigorous data analysis and anticipate and develop new low-cost “omics” technologies. By lowering the financial bar of access to these technologies, research program competitiveness will increase, enhancing publication impact factors, grant funding, patents, and faculty recruitment to UNMC.