A new lymphoid-primed progenitor marked by Dach1 downregulation identified with single cell multi-omics

Amann‐Zalcenstein, Daniela; Tian, Luyi; Schreuder, Jaring; Tomei, Sara; Lin, Dawn; Fairfax, Kirsten; Bolden, Jessica E.; McKenzie, Mark; Jarratt, Andrew; Hilton, Adrienne; Jackson, Jacob T.; Rago, Ladina Di; McCormack, Matthew P.; Graaf, Carolyn A. de; Stonehouse, Olivia; Taoudi, Samir; Alexander, Warren S.; Nutt, Stephen L.; Ritchie, Matthew E.; Ng, Ashley P.; Naik, Shalin H.

doi:10.1038/s41590-020-0799-x

Cited by 23 publications

(21 citation statements)

References 52 publications

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“…Finally, Group 1 (Figure 4F) TFs exhibit unique patterns of expression with peaks at different stages, all of which ultimately decaying as late neutrophil markers appear. These contain multiple TFs associated with specific lineages such as: Irf8 (Monocyte/DC fate (Olsson et al, 2016)), Aff3 (lymphoid/B cells (Ma and Staudt, 1996)), Dach1 (myeloid (Amann-Zalcenstein et al, 2020)), Hmga2 (myeloid, erythroid, megakaryocytic (Kumar et al, 2019), Pou2f2 (lymphoid/B cells (Novershtern et al, 2011) or are important for HSPC self-renewal, including Ikzf2 (Park et al, 2019) or Ssbp2 (Li et al, 2014). Thus, our analysis indicates that progenitors exhibit transient expression of major lineage determinants at specific differentiation stages on their way to becoming neutrophils (see Gfi1 , Flt3 , Irf8 in Figure S9D,E).…”

Section: Resultsmentioning

confidence: 99%

A time and single-cell resolved model of hematopoiesis

Kuciński

Campos

Barile

et al. 2022

Preprint

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The paradigmatic tree model of hematopoiesis is increasingly recognized to be limited as it is based on heterogeneous populations and largely inferred from non-homeostatic cell fate assays. Here, we combine persistent labeling with time-series single-cell RNA-Seq to build the first real-time, quantitative model of in vivo tissue dynamics for any mammalian organ. We couple cascading single-cell expression patterns with dynamic changes in differentiation and growth speeds. The resulting explicit linkage between single cell molecular states and cellular behavior reveals widely varying self-renewal and differentiation properties across distinct lineages. Transplanted stem cells show strong acceleration of neutrophil differentiation, illustrating how the new model can quantify the impact of perturbations. Our reconstruction of dynamic behavior from snapshot measurements is akin to how a Kinetoscope allows sequential images to merge into a movie. We posit that this approach is broadly applicable to empower single cell genomics to reveal important tissue scale dynamics information.

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Section: Resultsmentioning

confidence: 99%

A time and single-cell resolved model of hematopoiesis

Kuciński

Campos

Barile

et al. 2022

Preprint

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“…ScRNAseq consists in obtaining gene expression profiling at a single-cell resolution, putting in evidence the different cellular states and molecular dynamics of even the rarer subpopulations. This novel technology has been used successfully in several organs-for example, to study Prominin 1+ liver progenitors [114], Dach1-downregulated lymphoid progenitors [115] and KTR5+ lung progenitors in COVID-19 patients [116]. Within the past few years, an increasing number of research groups have applied this strategy to define the cell populations of the kidneys in mice and humans [117][118][119][120].…”

Section: Regulators Of Tubular Progenitors In Pathology: a Cacophonus Choirmentioning

confidence: 99%

Molecular Mechanisms of Renal Progenitor Regulation: How Many Pieces in the Puzzle?

Peired¹,

Melica²,

Molli³

et al. 2020

Preprint

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Kidneys of mice, rats and humans possess progenitors that maintain daily homeostasis and take part in endogenous regenerative processes following injury, owing to their capacity to proliferate and differentiate. In the glomerular and tubular compartments of the nephron, consistent studies demonstrated that well-characterized, distinct populations of progenitor cells, localized in the parietal epithelium of Bowman capsule and scattered in the proximal and distal tubules, could generate segment-specific cells in physiological conditions and following tissue injury. However, defective or abnormal regenerative responses of these progenitors can contribute to pathologic conditions. The molecular characteristics of renal progenitors have been extensively studied, revealing that numerous classical and evolutionarily conserved pathways, such as Notch or Wnt/β-catenin, play a major role in cell regulation. Others, such as retinoic acid, renin-angiotensin-aldosterone system, TLR2 (Toll-Like Receptor 2) and leptin, are also important in this process. In this review, we summarize the plethora of molecular mechanisms directing renal progenitor responses during homeostasis and following kidney injury. Finally, we will explore how single cell RNA sequencing could bring the characterization of renal progenitors to the next level, while knowing their molecular signature is gaining relevance in the clinic.

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“…Microarrays studies have provided useful insights into HSC and MPP biology [5][6][7]. Similarly, single-cell RNA (scRNA) sequencing has helped advance our understanding of the fate of hematopoietic cells [8][9][10][11][12]. However, the limited sensitivity of currently available scRNA approaches, capturing only the expression of a few thousand genes per cell, does not allow quantification of the entire protein-coding and non-coding transcriptomes.…”

Section: Introductionmentioning

confidence: 99%

Temporal Gene Expression Profiles Reflect the Dynamics of Lymphoid Differentiation

Chalabi

Legrand

Michaels

et al. 2022

IJMS

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Understanding the emergence of lymphoid committed cells from multipotent progenitors (MPP) is a great challenge in hematopoiesis. To gain deeper insight into the dynamic expression changes associated with these transitions, we report the quantitative transcriptome of two MPP subsets and the common lymphoid progenitor (CLP). While the transcriptome is rather stable between MPP2 and MPP3, expression changes increase with differentiation. Among those, we found that pioneer lymphoid genes such as Rag1, Mpeg1, and Dntt are expressed continuously from MPP2. Others, such as CD93, are CLP specific, suggesting their potential use as new markers to improve purification of lymphoid populations. Notably, a six-transcription factor network orchestrates the lymphoid differentiation program. Additionally, we pinpointed 24 long intergenic-non-coding RNA (lincRNA) differentially expressed through commitment and further identified seven novel forms. Collectively, our approach provides a comprehensive landscape of coding and non-coding transcriptomes expressed during lymphoid commitment.

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A new lymphoid-primed progenitor marked by Dach1 downregulation identified with single cell multi-omics

Cited by 23 publications

References 52 publications

A time and single-cell resolved model of hematopoiesis

A time and single-cell resolved model of hematopoiesis

Molecular Mechanisms of Renal Progenitor Regulation: How Many Pieces in the Puzzle?

Temporal Gene Expression Profiles Reflect the Dynamics of Lymphoid Differentiation

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