BioRxiv
bioRxiv Subject Collection: Systems Biology
This feed contains articles for bioRxiv Subject Collection "Systems Biology"
Identifying Spatial Co-occurrence in Healthy and InflAmed tissues (ISCHIA)
Spatial transcriptomics (ST) techniques are able to chart the distribution and localization of cell types and RNA molecules across a tissue. Sequencing-based methods allow unbiased capturing of RNA molecules at barcoded spots. While the coarse resolution of these techniquee is considered a disadvantage, we argue that the inherent proximity of transcriptomes captured on spots can be leveraged to reconstruct cellular networks. To this end, we developed ISCHIA (Identifying Spatial Co-occurrence in Healthy and InflAmed tissues), a computational framework to analyze the spatial co-occurrence of cell types and transcript species in the tissue environment. Co-occurrence analysis is complementary to differential gene expression, as it does not depend on the abundance of a given cell type or the transcript expression levels, but rather on their spatial arrangement in the tissue. We applied ISCHIA to analyze co-occurrence of cell types, ligands and receptors in a sequencing-based ST dataset of human ulcerative colitis, and validated our findings on matched hybridization-based data. We uncover inflammation-induced cellular networks involving M-cell and fibroblasts, as well as ligand-receptor interactions enriched in the inflamed human colon, and their associated gene signatures. Our results highlight the hypothesis-generating power and broad applicability of co-occurrence analysis on spatial transcriptomics data.
Lafzi, A., Borrelli, C., Bach, K., Kretz, J. A., Handler, K., Regan-Komito, D., Ficht, X., Frei, A. P., Moor, A. E.
February 16, 2023
http://biorxiv.org/cgi/content/short/2023.02.13.526554v1?rss=1