Back

The hidden predictors of human haematopoietic clonal fate

Tomei, S.; Zhang, S.; Lin, M.; Audiger, C.; Weber, T. S.; Naik, S.

2025-08-01 cell biology
10.1101/2025.07.28.667115 bioRxiv
Show abstract

Human haematopoietic stem and progenitor cells (HSPCs) exhibit heterogeneous lineage output, but the molecular programs underlying clonal fate remain poorly defined. To address this, we developed a human haematopoietic organoid supporting differentiation into 15 lineages and used it to track barcoded HSPC clones over time. By integrating single-cell transcriptomes, surface phenotypes, and clonal fate, we applied machine learning to identify clonal fate modules - gene and marker signatures predictive of lineage commitment. This approach uncovered hidden transcriptional and surface correlates of multipotency, including CD200, which marked a subset of HSCs with broad output capacity, which we leveraged to increase manufactured type 1 dendritic cell purity for immunotherapy applications. Our study provides a framework for decoding clonal fate decisions in human HSPCs and identifies molecular features that distinguish truly multipotent clones, advancing strategies for stem cell purification and therapeutic engineering.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.