The underpinnings of cancer metastasis remain poorly understood, in part due to a lack of tools for probing their emergence at high resolution. Here we present macsGESTALT, an inducible CRISPR-Cas9-based lineage recorder with highly efficient single-cell capture of both transcriptional and phylogenetic information. Applying macsGESTALT to a mouse model of metastatic pancreatic cancer, we recover ∼380,000 CRISPR target sites and reconstruct dissemination of ∼28,000 single cells across multiple metastatic sites. We find that cells occupy a continuum of epithelial-to-mesenchymal transition (EMT) states. Metastatic potential peaks in rare, late-hybrid EMT states, which are aggressively selected from a predominately epithelial ancestral pool. The gene signatures of these late-hybrid EMT states are predictive of reduced survival in both human pancreatic and lung cancer patients, highlighting their relevance to clinical disease progression. Finally, we observe evidence for in vivo propagation of S100 family gene expression across clonally distinct metastatic subpopulations. Display omitted •macsGESTALT is an inducible lineage recorder with efficient capture in single cells•Despite genetic competency, most cancer clones are not metastatic•Metastatic aggression peaks at specific late-hybrid EMT states•Expression of S100 genes is propagated across distinct metastatic subpopulations Simeonov et al. develop an inducible lineage recorder, enabling simultaneous capture of lineages and transcriptomes from single cells. Lineage reconstruction in a metastatic pancreatic cancer model reveals extensive bottlenecking and subpopulation signaling, as well as specific transcriptional states associated with metastatic aggression and predictive of worse outcomes in human cancer.