Lineage tracing on transcriptional landscapes links state to fate during differentiation

Abstract

A challenge in biology is to associate molecular differences among progenitor cells with their capacity to generate mature cell types. Here, we used expressed DNA barcodes to clonally trace transcriptomes over time and applied this to study fate determination in hematopoiesis. We identified states of primed fate potential and located them on a continuous transcriptional landscape. We identified two routes of monocyte differentiation that leave an imprint on mature cells. Analysis of sister cells also revealed cells to have intrinsic fate biases not detectable by single-cell RNA sequencing. Finally, we benchmarked computational methods of dynamic inference from single-cell snapshots, showing that fate choice occurs earlier than is detected by state-of the-art algorithms and that cells progress steadily through pseudotime with precise and consistent dynamics.

Single-cell time-series mapping of cell fate trajectories reveals an expanded developmental potential for human PSC-derived distal lung progenitors

“…We validated the parent-progeny relationships predicted by our model by using a combination of scRNA-seq and DNA barcoding (Weinreb et al, 2019). Genetic tagging of individual cells allowed tracing of their progeny during directed differentiation.…”

“…Second, our method was designed to detect multipotency and fate bifurcations rather than to quantify any lineage bias that may be present at each developmental stage. Others have published lentiviral barcoding over time that might be employed to more precisely quantify lineage bias at each stage in our protocol (Biddy et al, 2018;Weinreb et al, 2019). It should be pointed out that prior time series profiles have revealed fate convergence from distinct origins is detectable in the development of alternate germ layer derivatives (e.g.…”

“…To functionally test this prediction, we employed lentiviral barcoding to clonally trace the progeny of individual cells in the protocol followed by scRNA-seq profiling to assign them to paths in the model. On day 15 of differentiation PSC-derived NKX2-1 progenitors were sorted to purity and on day 17 a single cell suspension of these progenitors was infected with our lentiviral barcoding library for "Lineage and RNA Recovery" (LARRY) (Weinreb et al, 2019) which encodes for enhanced green fluorescent protein (eGFP) mRNA together with a 3'UTR carrying a unique inheritable barcode for each cell ( Figures 6A). This library has a complexity of 10 6 barcodes, sufficient to label 10 4 cells with <0.5% barcode overlap between clones (Weinreb et al, 2019).…”

“…On day 15 of differentiation PSC-derived NKX2-1 progenitors were sorted to purity and on day 17 a single cell suspension of these progenitors was infected with our lentiviral barcoding library for "Lineage and RNA Recovery" (LARRY) (Weinreb et al, 2019) which encodes for enhanced green fluorescent protein (eGFP) mRNA together with a 3'UTR carrying a unique inheritable barcode for each cell ( Figures 6A). This library has a complexity of 10 6 barcodes, sufficient to label 10 4 cells with <0.5% barcode overlap between clones (Weinreb et al, 2019). We first optimized this system to achieve a transduction efficiency in iPSC-derived lung progenitors of ~30% using a viral multiplicity of infection (MOI)=10.…”

“…Lineage tracing of individual cells was performed using a lentiviral barcode labeling system (Weinreb et al, 2019). Human BU3 NGST cells were differentiated, sorted on D15 for NKX2-1 GFP positive cells and grown as alveolospheres, as described above, until D17.…”