Cells are the unit building blocks of tissues and organs, thus, to understand the organization of tissues and organs, it is important to understand where different types of cells reside in the tissue. Here, we implement a newly invented technology called Slide-seq to characterize gene expression relationships in large tissue volumes at 10-micron resolution. First, we will develop tissue quality metrics, and modifications to the Slide- seq protocol, that optimize Slide-seq data quality across a range of tissues that are the focus of the HuBMAP consortium. Next, we will generate large-scale Slide-seq datasets from human colon and kidney, and compare and contrast the resulting data from spatial technologies being deployed by existing HuBMAP TMCs. Finally, we will scale the production of the Slide-seq arrays, and host training workshops, to enable the technology to be successfully adopted across the HuBMAP consortium. Together, we aim to make Slide-seq a routine and valuable measurement tool for the construction of comprehensive molecular maps of human tissues.
We will implement a new technology, Slide-seq, to measure gene expression relationships at high spatial resolution, across several human tissues that are currently the focus of the HuBMAP consortium. We will identify experimental parameters and characteristics of tissues that predict successful Slide-seq datasets, and use this information to optimize the quality of the data we acquire. We will then scale up production of Slide-seq arrays at the Broad Institute, to enable its routine and facile use across the HuBMAP consortium.
