Computational analysis of cellular and subcellular spatial transcriptional heterogeneity.

Jean Fan, Johns Hopkins University, Johns Hopkins University
Host: Department of Computer Science

Recent technological advancements have enabled spatially-resolved transcriptomic measurements of hundreds to thousands of mRNA species with a throughput of hundreds to thousands of single cells per single day experiment. However, computational methods for statistical analysis capable of taking advantage of this new spatial dimension are still needed to connect transcriptional and spatial-contextual differences in single cells as well as identify putative subpopulations and patterns in their spatial organization from within a probabilistic framework. Here, we will demonstrate how we applied computational analysis of transcriptome-scale multiplexed error-robust FISH (MERFISH) data to identify RNA species enriched in different subcellular compartments, transcriptionally distinct cell states corresponding to different cell-cycle phases, and spatial patterning of transcriptionally distinct cells. We anticipate that such spatially resolved transcriptome profiling coupled with spatial computational analyses could help address a wide array of questions ranging from the regulation of gene expression in cells to the development of cell fate and organization in tissues.

Speaker Biography

I am an Assistant Professor in the Department of Biomedical Engineering at Johns Hopkins University. My lab is interested in understanding the molecular and spatial-contextual factors shaping cellular identity and heterogeneity, particularly in the context of cancer and how this heterogeneity impacts tumor progression, therapeutic resistance, and ultimately clinical prognosis. We develop new open-source computational software for analyzing single-cell multi-omic and imaging data that can be tailored and applied to diverse cancer types and biological systems. I was previously an NCI F99/K00 post-doctoral fellow in the lab of Dr. Xiaowei Zhuang at Harvard University. I received my PhD in Bioinformatics and Integrative Genomics at Harvard under the mentorship of Dr. Peter Kharchenko at the Department of Biomedical Informatics and in close collaboration with Dr. Catherine Wu at the Dana-Farber Cancer Institute.