A machine learning-based megakaryocyte identification system uncovers resident organs, markers, and functional diversity

The organ- and stage-specific diversity of megakaryocytes (MKs) has prompted a reassessment of their distribution and functions. By integrating single-cell transcriptomic data across multiple organs and developmental stages, we identified previously unreported MK and platelet markers, including Tnik , a key regulator of MK function and platelet production. Using these markers alongside established ones, we developed a machine learning-based MK identification system (MKIDS) that enables MK detection in the brain, heart, and placenta in mice and humans. Functional studies demonstrated that brain-resident MKs are essential for neural development, underscoring organ-specific roles of MKs in regulating tissue development and function. Transcriptomic integration of MKs across organs and stages, with functional validation, revealed a developmental shift in platelet production—from a mitochondria-low to a mitochondria-enriched subpopulation. Our findings offer a transformative perspective on the MK system, highlighting its cellular diversity, functional complexity, and developmental dynamics. • Identification of additional MK markers, such as TNIK • MKIDS enables detection of MKs across multiple organs not previously recognized • MKs in the embryonic brain support neural development • Two platelet-producing MK subsets (plt and mt) undergo a developmental transition Xia et al. integrate cross-organ and single-cell datasets to define megakaryocyte (MK) diversity, identify additional markers, and develop a machine learning-based identification system, MKIDS, to detect MKs in unrecognized organs. They show that MKs in the embryonic brain support neural development and reveal a developmental transition between platelet-producing MK subsets.