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    Date Issued2018 (2)2016 (1)Author
    Zilionis, Rapolas (3)
    Hidalgo, Daniel (2)Hwang, Yung (2)Socolovsky, Merav (2)Waisman, Ari (2)View MoreUMass Chan AffiliationDepartment of Medicine (1)Department of Molecular, Cell and Cancer Biology (1)Division of Infectious Diseases and Immunology, Department of Medicine (1)Molecular, Cell and Cancer Biology (1)Pediatrics (1)View MoreDocument TypeJournal Article (2)Preprint (1)KeywordBiochemistry (1)Bioinformatics (1)Cell Biology (1)Cell biology (1)Cells (1)View MoreJournalbioRxiv (1)Genome research (1)Nature (1)

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    Population snapshots predict early haematopoietic and erythroid hierarchies

    Tusi, Betsabeh Khoramian; Wolock, Samuel L; Weinreb, Caleb; Hwang, Yung; Hidalgo, Daniel; Zilionis, Rapolas; Waisman, Ari; Huh, Jun R; Klein, Allon M; Socolovsky, Merav (2018-02-21)
    The formation of red blood cells begins with the differentiation of multipotent haematopoietic progenitors. Reconstructing the steps of this differentiation represents a general challenge in stem-cell biology. Here we used single-cell transcriptomics, fate assays and a theory that allows the prediction of cell fates from population snapshots to demonstrate that mouse haematopoietic progenitors differentiate through a continuous, hierarchical structure into seven blood lineages. We uncovered coupling between the erythroid and the basophil or mast cell fates, a global haematopoietic response to erythroid stress and novel growth factor receptors that regulate erythropoiesis. We defined a flow cytometry sorting strategy to purify early stages of erythroid differentiation, completely isolating classically defined burst-forming and colony-forming progenitors. We also found that the cell cycle is progressively remodelled during erythroid development and during a sharp transcriptional switch that ends the colony-forming progenitor stage and activates terminal differentiation. Our work showcases the utility of linking transcriptomic data to predictive fate models, and provides insights into lineage development in vivo.
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    Emergence of the erythroid lineage from multipotent hematopoiesis [preprint]

    Tusi, Betsabeh K.; Wolock, Samuel L.; Weinreb, Caleb; Hwang, Yung; Hidalgo, Daniel; Zilionis, Rapolas; Waisman, Ari; Huh, Jun R.; Klein, Allon M.; Socolovsky, Merav (2018-02-16)
    Red cell formation begins with the hematopoietic stem cell, but the manner by which it gives rise to erythroid progenitors, and their subsequent developmental path, remain unclear. Here we combined single-cell transcriptomics of murine hematopoietic tissues with fate potential assays to infer a continuous yet hierarchical structure for the hematopoietic network. We define the erythroid differentiation trajectory as it emerges from multipotency and diverges from 6 other blood lineages. With the aid of a new flow-cytometric sorting strategy, we validated predicted cell fate potentials at the single cell level, revealing a coupling between erythroid and basophil/mast cell fates. We uncovered novel growth factor receptor regulators of the erythroid trajectory, including the proinflammatory IL- 17RA, found to be a strong erythroid stimulator; and identified a global hematopoietic response to stress erythropoiesis. We further identified transcriptional and high-purity FACS gates for the complete isolation of all classically-defined erythroid burst-forming (BFU-e) and colony-forming progenitors (CFU-e), finding that they express a dedicated transcriptional program, distinct from that of terminally-differentiating erythroblasts. Intriguingly, profound remodeling of the cell cycle is intimately entwined with CFU-e developmental progression and with a sharp transcriptional switch that extinguishes the CFU-e stage and activates terminal differentiation. Underlying these results, our work showcases the utility of theoretic approaches linking transcriptomic data to predictive fate models, providing key insights into lineage development in vivo.
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    End Sequence Analysis Toolkit (ESAT) expands the extractable information from single-cell RNA-seq data

    Derr, Alan G.; Yang, Chaoxing; Zilionis, Rapolas; Sergushichev, Alexey; Blodgett, David; Redick, Sambra D.; Bortell, Rita; Luban, Jeremy; Harlan, David M.; Kadener, Sebastian; et al. (2016-10-01)
    RNA-seq protocols that focus on transcript termini are well suited for applications in which template quantity is limiting. Here we show that, when applied to end-sequencing data, analytical methods designed for global RNA-seq produce computational artifacts. To remedy this, we created the End Sequence Analysis Toolkit (ESAT). As a test, we first compared end-sequencing and bulk RNA-seq using RNA from dendritic cells stimulated with lipopolysaccharide (LPS). As predicted by the telescripting model for transcriptional bursts, ESAT detected an LPS-stimulated shift to shorter 3'-isoforms that was not evident by conventional computational methods. Then, droplet-based microfluidics was used to generate 1000 cDNA libraries, each from an individual pancreatic islet cell. ESAT identified nine distinct cell types, three distinct beta-cell types, and a complex interplay between hormone secretion and vascularization. ESAT, then, offers a much-needed and generally applicable computational pipeline for either bulk or single-cell RNA end-sequencing.
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