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This on-demand webinar discusses a project at the Broad Institute to use spatial profiling to understand the disease progression of COVID-19.

Sami Farhi of the Broad Institute shares details of the project, which performed transcriptomic and proteomic spatial analysis on lung parenchyma from rapid autopsies of patients succumbing to the disease. 

The team used NanoString GeoMx to perform whole-transcriptome, cancer transcriptome, and protein studies on 17 donor samples. More than 12 regions of interest were selected for each donor, guided by RNAScope against the SARS-CoV-2 S gene to identify regions of high and low viral load. 

Farhi and colleagues performed differential analyses of epithelial and non-epithelial compartments across different viral load, anatomical compartment, and inflammation status. Results matched conclusions from single-cell and bulk RNA sequencing data on the same samples. 

Dr. Farhi discusses how the study highlights the utility of RNAScope in guiding other spatial analysis methods as well as how the data set captures the intra- and inter-sample expression heterogeneity associated with COVID-19, highlighting both early response mechanisms to SARS-CoV-2 and subsequent late-stage responses to viral damage.

Key Learning Points:

Spatial variation of gene expression programs in COVID-19 tissues

Guiding Nanostring GeoMx experimental design with RNAScope measurements

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