Unbiased profiling of multipotency landscapes reveals spatial modulators of clonal fate biases

single-cell clonal lineage tracing of mouse embryos traced from neurulation until mid-gestation, combined with a machine learning tool that categorizes individual clones into lineages based on shared transcriptional context. This revealed a previously unrecognized continuous, embryo-wide gradient of clonal fate biases, in which anatomical position and clonal composition are mutually predictive. Comparing clonal lineages revealed gene regulatory networks underlying the dynamic biasing of cells towards specific fates by spatial transcription factor programs. However, mosaic combinatorial perturbations targeting the Hedgehog pathway generated clones in which positional identity was mismatched with clonal composition, demonstrating that extrinsic signals can override the axial patterning system underlying clonal fate biases. Altogether, our work demonstrates an effective practical approach for dissecting mechanisms of lineage specification and has implications for stem cell engineering.