2021
DOI: 10.1186/s12915-021-00955-z
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Single-cell RNA-seq reveals a concomitant delay in differentiation and cell cycle of aged hematopoietic stem cells

Abstract: Background Hematopoietic stem cells (HSCs) are the guarantor of the proper functioning of hematopoiesis due to their incredible diversity of potential. During aging, heterogeneity of HSCs changes, contributing to the deterioration of the immune system. In this study, we revisited mouse HSC compartment and its transcriptional plasticity during aging at unicellular scale. Results Through the analysis of 15,000 young and aged transcriptomes, we identi… Show more

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Cited by 35 publications
(78 citation statements)
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References 73 publications
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“…Consistently, PU.1-deficient HSCs displayed overexpressed cell cycle and protein synthesis genes [82]. Aged HSCs display cell cycle arrest [90,91], which is associated with replicative stress [90]. Further studies are needed to investigate to what extent the dormant status of aged HSCs is caused by chronic exposure to inflammation.…”
Section: Hscs Are Transiently Activated Under Chronic Inflammationmentioning
confidence: 97%
“…Consistently, PU.1-deficient HSCs displayed overexpressed cell cycle and protein synthesis genes [82]. Aged HSCs display cell cycle arrest [90,91], which is associated with replicative stress [90]. Further studies are needed to investigate to what extent the dormant status of aged HSCs is caused by chronic exposure to inflammation.…”
Section: Hscs Are Transiently Activated Under Chronic Inflammationmentioning
confidence: 97%
“…These results point to the age-related expansion of HSC clones with relative resistance to differentiation-instructing stimuli, and although these latent HSCs are essentially defined by transplantation experiments, it is possible that they may also be childless in the native hematopoiesis of aged organisms (Figure 2d). The heterogeneity of aged HSCs is also demonstrated in terms of transcriptome [53,[61][62][63],…”
Section: Hsc Clonal Behavior During Agingmentioning
confidence: 99%
“…We used the Single-Cell Regulatory Network Inference and Clustering (SCENIC) approach 19 to identify regulons, which are modules of one TF and its potential targets, and their activities. We ran SCENIC workflow using pySCENIC v1.10.0 with its command line implementation 21 as in our previous study regarding gene filtering, TF motifs (motifs-v9-nr.mgi-m0.001-o0.0), cis-target (+/-10 kb from TSS mm9-tss-centered-10 kb-7species.mc9nr) databases and command line options 1 . In this study we used the whole 1721 TFs with an available motif in the motif database as input.…”
Section: Regulon Analysismentioning
confidence: 99%
“… Abstract We previously analyzed 15 000 transcriptomes of mouse hematopoietic stem and progenitor cells (HSPCs) from young and aged mice and characterized the early differentiation of the hematopoietic stem cells (HSCs) according to age, thanks to cell clustering and pseudotime analysis 1 . In this study, we propose an original strategy to build a Boolean gene network explaining HSC priming and homeostasis based on our previous single cell data analysis and the actual knowledge of these biological processes (graphical abstract) .We first made an exhaustive analysis of the transcriptional network on selected HSPC states in the differentiation trajectory of HSCs by identifying regulons, modules formed by a transcription factor (TFs) and its targets, from the scRNA-seq data., From this global view of transcriptional regulation in early hematopoiesis, we chose to focus on 15 components, 13 selected TFs (Tal1, Fli1, Gata2, Gata1, Zfpm1, Egr1, Junb, Ikzf1, Myc, Cebpa, Bclaf1, Klf1, Spi1) and two complexes regulating the ability of HSC to cycle (CDK4/6 - Cyclines D and CIP/KIP).…”
mentioning
confidence: 99%