Scalable methylome-transcriptome profiling resolves clonal organization in human hematopoiesis

Abstract

Understanding human tissue maintenance and remodeling requires linking clonal ancestry to molecular state, yet scalable joint measurement remains challenging. Here, we introduce Droplet-MT and an integrated computational workflow for joint transcriptome and methylome profiling at ~10,000 cells per library. Methylation epimutations enable mutation-independent clonal reconstruction from high-coverage methylomes, while reference-based label transfer assigns cells to established clones at ~0.2% CpG coverage, reducing sequencing cost. Clone-aggregated somatic variants provide genetic annotation without additional single-cell genotyping. Across ~21,000 paired profiles from healthy blood and longitudinal acute myeloid leukemia, we resolved small and expanded clones with heterogeneous lineage output. In leukemia, the framework distinguished changes in malignant clonal abundance, state remodeling within persistent clones, and recovery of healthy polyclonal hematopoiesis. Malignant monocytes remained transcriptionally and epigenetically distinct from healthy and recovery-associated cells despite treatment-associated remodeling. Droplet-MT enables scalable analysis of human tissues by linking clonal organization with molecular state and retrospective genetic annotation.