Extended Data Fig. 1: FateMap reveals between-clone fate type diversity in treatment-naive cells, albeit to a lesser degree compared to resistant cells.

a. (left) UMAP of all barcoded treatment-naive cells. Total 16,432 cells (8,420 split A and 8,012 cells in split B) are colored by clusters determined using Seurat’s FindClusters command at a resolution of 0.6 (i.e. “Seurat clusters, resolution = 0.6”). (right) On the UMAP, we recolored each cell by its expression for a select subset of genes that were identified as differentially expressed in drug resistant cells via the Seurat pipeline (Cell counts available in Supplementary Table 11). b. Five representative examples demonstrate that a clone (cells sharing the same barcode) is constrained largely in a specific transcriptional cluster such that cells within a clone are more transcriptionally similar to each other than cells in other clones. c. Average pairwise correlation between cells within a clone was estimated based on the expression levels of the top 500 most variable genes. Each point represents the average value for Spearman’s correlation coefficient for all possible pairs of cells within a clone. For each clone, a paired control was created by randomly sampling an equivalent number of cells from the entire population. Higher average correlation coefficient in clones indicates higher transcriptional similarity among cells within a clone, as compared to cells that are not clones. Wilcoxon signed rank exact test (paired, two-sided) was used to compare the difference in average correlation coefficient. d. Fraction of variance explained by the experimental data and randomized data for the top 50 principal components (PCs). The number of PCs needed to explain the actual variance in data (indicated by the dotted line) is a measure of the degrees of freedom of variability of a given dataset. There was an increase (see Extended Data Fig. 1e for statistical testing) in the number of PCs needed to explain the variance in data from resistant cells (43 PCs) as compared to naive (30 PCs) and primed cells (23 PCs), suggesting that there is an increase in overall variability in samples when cells transition to becoming drug resistant. Primed cells were identified as cells where at least 40% of pre-resistant markers identified in (Emert et al. 2021) are higher than their average expression level. e. Average number of PCs needed to explain the variance in resistant, naive and pre-resistant cells. Error bars represent standard deviation over 100 simulations of randomized data. Mann-Whitney U-Test was used to estimate a p-value for pairwise difference in means. f. Comparison of Euclidean distances between clusters across resistant and naive populations of melanoma cells for varying numbers of clusters. We used the first 50 principal components to calculate the Euclidean distance between cells across clusters. We used Wilcoxon signed rank exact test (paired, two-sided) for statistical comparisons. g. Comparison between resistant and naive populations for total number of clusters, given fixed number of cells and shared nearest neighbor (snn) resolution. We used Wilcoxon signed rank exact test (paired, two-sided) for statistical comparisons of average number of clusters across resolutions. h. UMAPs of representative twin clones (sharing the same barcode) across the two splits A and B. The twins largely end up with the same transcriptional fate. This observation suggests that cells have similar transcriptional states prior to drug treatment.