Cell states beyond transcriptomics: integrating structural organization and gene expression in hiPSC-derived cardiomyocytes

Gerbin, K. A.; Grancharova, T.; Donovan-Maiye, R.; Hendershott, M. C.; Brown, J.; Dinh, S. Q.; Gehring, J. L.; Hirano, M.; Johnson, G. R.; Nath, A.; Nelson, A.; Roco, C. M.; Rosenberg, A. B.; Sluzewski, M. F.; Viana, M. P.; Yan, C.; Zaunbrecher, R. J.; Cordes Metzler, K. R.; Menon, V.; Palecek, S. P.; Seelig, G.; Gaudreault, N.; Knijnenburg, T.; Rafelski, S. M.; Theriot, J. A.; Gunawardane, R. N.

doi:10.1101/2020.05.26.081083

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bioRxiv · 10.1101/2020.05.26.081083

Cell states beyond transcriptomics: integrating structural organization and gene expression in hiPSC-derived cardiomyocytes

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Abstract

We present a quantitative co-analysis of RNA abundance and sarcomere organization in single cells and an integrated framework to predict subcellular organization states from gene expression. We used human induced pluripotent stem cell (hiPSC)-derived cardiomyocytes expressing mEGFP-tagged alpha-actinin-2 to develop quantitative image analysis tools for systematic and automated classification of subcellular organization. This captured a wide range of sarcomeric organization states within cell populations that were previously difficult to quantify. We performed RNA FISH targeting genes identified by single cell RNA sequencing to simultaneously assess the relationship between transcript abundance and structural states in single cells. Co-analysis of gene expression and sarcomeric patterns in the same cells revealed biologically meaningful correlations that could be used to predict organizational states. This study establishes a framework for multi-dimensional analysis of single cells to study the relationships between gene expression and subcellular organization and to develop a more nuanced description of cell states. Graphical AbstractTranscriptional profiling and structural classification was performed on human induced pluripotent stem cell-derived cardiomyocytes to characterize the relationship between transcript abundance and subcellular organization. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=199 SRC="FIGDIR/small/081083v1_ufig1.gif" ALT="Figure 1"> View larger version (60K): org.highwire.dtl.DTLVardef@8f89c4org.highwire.dtl.DTLVardef@19dc813org.highwire.dtl.DTLVardef@1ba7c20org.highwire.dtl.DTLVardef@2b3daa_HPS_FORMAT_FIGEXP M_FIG C_FIG

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Gerbin, K. A., Grancharova, T., Donovan-Maiye, R., Hendershott, M. C., Brown, J., Dinh, S. Q., Gehring, J. L., Hirano, M., Johnson, G. R., Nath, A., Nelson, A., Roco, C. M., Rosenberg, A. B., Sluzewski, M. F., Viana, M. P., Yan, C., Zaunbrecher, R. J., Cordes Metzler, K. R., Menon, V., Palecek, S. P., Seelig, G., Gaudreault, N., Knijnenburg, T., Rafelski, S. M., Theriot, J. A., Gunawardane, R. N.. 2020-05-27. Cell states beyond transcriptomics: integrating structural organization and gene expression in hiPSC-derived cardiomyocytes. https://doi.org/10.1101/2020.05.26.081083

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