Inferring Clonal Dynamics in Blood using Single-Cell Measurements

Abstract

In this work, we uniquely tag hematopoietic (blood) stem cells with genetic barcodes and follow their progeny over time to ask whether clonally related cells in myeloproliferative neoplasms (MPNs) favor particular blood cell fates. Myeloproliferative neoplasms are clonal disorders driven most frequently by the JAK2-V617F mutation, which arises in a single hematopoietic stem cell (HSC) and ultimately dominates the normal process of blood cell production. Although all patients carry the same driver mutation, they still branch into three distinct disease forms—essential thrombocythemia (ET), polycythemia vera (PV), or primary myelofibrosis (PMF)—and the reason for this variation remains unknown. One compelling hypothesis is that the JAK2-V617F mutation may arise in HSC subsets with intrinsic biases toward platlet-producing cells (as in ET) or red blood cell precursors (PV). To investigate this question, we analyzed bone-marrow cKit⁺ cells from mice engineered for inducible MPN disease and CRISPR array repair lineage tracing (CARLIN), using single-cell RNA sequencing. Our gene expression analysis shows that the mutation keeps key signaling and stress-response genes switched on and boosts growth-promoting enzymes, collectively pushing blood production toward the myeloid line. At the resolution of individual CARLIN clones (i.e. cells grouped by a shared progenitor), however, we observe no robust mutation-induced lineage bias—an outcome attributable to limited clone recovery and inter-mouse variability. Crucially, this work establishes a scalable analysis pipeline for future, higher-yield CARLIN experiments. Enhancing lineage-tracing sensitivity, barcode diversity, and biological replication will be essential to test whether these interferon-/stress-response and kinase programs manifest as subtle, clone-level fate biases in JAK2-driven MPN.