Jiang, C. L. | bioRxiv Science

bioRxiv2022

ClonoCluster: a method for using clonal origin to inform transcriptome clustering

Clustering cells based on their high dimensional profiles is an important data reduction process by which researchers infer distinct categories of cellular state. The advent of cellular barcoding, however, provides an alternative means by which to group cells: by their clonal origin. We developed ClonoCluster, a computational method that combines both clone and transcriptome information to create hybrid clusters that weight both kinds of data with a tunable parameter. We generated hybrid clusters across six independent datasets and found that ClonoCluster generated qualitatively different clusters in all cases. The markers of these hybrid clusters were different but had equivalent fidelity to transcriptome-only clusters. The genes most strongly associated with the rearrangements in hybrid clusters were ribosomal function and extracellular matrix genes. We also developed the complementary tool Warp Factor that incorporates clone information in popular 2D visualization techniques like UMAP. Integrating ClonoCluster and Warp Factor revealed biologically relevant markers of cell identity.

bioinformatics↗

bioRxiv2021

Cell type determination for cardiac differentiation occurs soon after seeding of human induced pluripotent stem cells

Cardiac directed differentiation of human induced pluripotent stem cells consistently produces a mixed population of cardiomyocytes and non-cardiac cell types even when using very well-characterized protocols. We wondered whether differentiated cell types might result from intrinsic differences in hiPS cells prior to the onset of differentiation. By associating individual differentiated cells that share a common hiPS cell precursor, we were able to test whether expression variability in differentiated cells was pre-determined from the hiPS cell state. Although within a single experiment, differentiated cells that share an hiPS cell progenitor were more transcriptionally similar to each other than to other cells in the differentiated population, when the same hiPS cells were differentiated in parallel, we did not observe high transcriptional similarity across differentiations. Additionally, we found that substantial cell death occurred during differentiation in a manner that suggested that all cells were equally likely to survive or die, suggesting that there was no intrinsic selection bias for cells descended from particular hiPS cell progenitors. These results led us to wonder about how cells grow out spatially during the directed differentiation process. Labeling cells by their expression of a few canonical cell type marker genes, we showed that cells expressing the same marker tended to occur in patches observable by visual inspection, suggesting that cell type determination across multiple cell types, once initiated, is maintained in a cell-autonomous manner for multiple divisions. Altogether, our results show that while there is substantial heterogeneity in the initial hiPS cell population, that heterogeneity is not responsible for heterogeneous outcomes, and that the window during which cell type specification occurs is likely to begin shortly after the seeding of hiPS cells for differentiation.

genomics↗