Paths and pathways that generate cell-type heterogeneity and developmental progression in hematopoiesis
Abstract
Mechanistic studies of Drosophila lymph gland hematopoiesis are limited by the availability of cell-type specific markers. Using a combination of bulk RNA-Seq of FACS-sorted cells, single cell RNA-Seq, and genetic dissection, we identify new blood cell subpopulations along a developmental trajectory with multiple paths to mature cell types. This provides functional insights into key developmental processes and signaling pathways. We highlight metabolism as a driver of development, show that graded Pointed expression allows distinct roles in successive developmental steps, and that mature crystal cells specifically express an alternate isoform of Hypoxia-inducible factor (Hif/Sima). Mechanistically, the Musashi-regulated protein Numb facilitates Sima-dependent non-canonical, and inhibits canonical, Notch signaling. Broadly, we find that prior to making a fate choice, a progenitor selects between alternative, biologically relevant, transitory states allowing smooth transitions reflective of combinatorial expressions rather than stepwise binary decisions. Increasingly, this view is gaining support in mammalian hematopoiesis.
Data availability
Sequencing data have been deposited in GEO under Accession Code GSE168823Complete Source Data are provided
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Paths and Pathways that Generate Cell-Type Heterogeneity and Developmental Progression in HematopoiesisNCBI Gene Expression Omnibus GSE168823.
Article and author information
Author details
Funding
National Heart, Lung, and Blood Institute (R01-HL067395)
- Utpal Banerjee
National Cancer Institute (R01-CA217608)
- Utpal Banerjee
National Heart, Lung, and Blood Institute (T32-HL69766)
- Juliet R Girard
National Institute of General Medical Sciences (K12-GM106996)
- Juliet R Girard
National Cancer Institute (T32-CA009056)
- Lauren M Goins
National Heart, Lung, and Blood Institute (T32-HL863458)
- Carrie M Spratford
Center for Global Mentoring at UCLA-DOE Institute for Genomics & Proteomics
- Dung M Vuu
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Erika A Bach, New York University School of Medicine, United States
Version history
- Preprint posted: February 13, 2021 (view preprint)
- Received: February 13, 2021
- Accepted: October 22, 2021
- Accepted Manuscript published: October 29, 2021 (version 1)
- Version of Record published: November 23, 2021 (version 2)
Copyright
© 2021, Girard et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Further reading
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- Computational and Systems Biology
- Developmental Biology
Organisms utilize gene regulatory networks (GRN) to make fate decisions, but the regulatory mechanisms of transcription factors (TF) in GRNs are exceedingly intricate. A longstanding question in this field is how these tangled interactions synergistically contribute to decision-making procedures. To comprehensively understand the role of regulatory logic in cell fate decisions, we constructed a logic-incorporated GRN model and examined its behavior under two distinct driving forces (noise-driven and signal-driven). Under the noise-driven mode, we distilled the relationship among fate bias, regulatory logic, and noise profile. Under the signal-driven mode, we bridged regulatory logic and progression-accuracy trade-off, and uncovered distinctive trajectories of reprogramming influenced by logic motifs. In differentiation, we characterized a special logic-dependent priming stage by the solution landscape. Finally, we applied our findings to decipher three biological instances: hematopoiesis, embryogenesis, and trans-differentiation. Orthogonal to the classical analysis of expression profile, we harnessed noise patterns to construct the GRN corresponding to fate transition. Our work presents a generalizable framework for top-down fate-decision studies and a practical approach to the taxonomy of cell fate decisions.
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- Developmental Biology
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