↓ Skip to main content

Single-cell transcriptomic reconstruction reveals cell cycle and multi-lineage differentiation defects in Bcl11a-deficient hematopoietic stem cells

Overview of attention for article published in Genome Biology, September 2015
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (83rd percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
11 X users
wikipedia
1 Wikipedia page

Citations

dimensions_citation
89 Dimensions

Readers on

mendeley
172 Mendeley
citeulike
2 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Single-cell transcriptomic reconstruction reveals cell cycle and multi-lineage differentiation defects in Bcl11a-deficient hematopoietic stem cells
Published in
Genome Biology, September 2015
DOI 10.1186/s13059-015-0739-5
Pubmed ID
Authors

Jason C. H. Tsang, Yong Yu, Shannon Burke, Florian Buettner, Cui Wang, Aleksandra A. Kolodziejczyk, Sarah A. Teichmann, Liming Lu, Pentao Liu

Abstract

Hematopoietic stem cells (HSCs) are a rare cell type with the ability of long-term self-renewal and multipotency to reconstitute all blood lineages. HSCs are typically purified from the bone marrow using cell surface markers. Recent studies have identified significant cellular heterogeneities in the HSC compartment with subsets of HSCs displaying lineage bias. We previously discovered that the transcription factor Bcl11a has critical functions in the lymphoid development of the HSC compartment. In this report, we employ single-cell transcriptomic analysis to dissect the molecular heterogeneities in HSCs. We profile the transcriptomes of 180 highly purified HSCs (Bcl11a (+/+) and Bcl11a (-/-)). Detailed analysis of the RNA-seq data identifies cell cycle activity as the major source of transcriptomic variation in the HSC compartment, which allows reconstruction of HSC cell cycle progression in silico. Single-cell RNA-seq profiling of Bcl11a (-/-) HSCs reveals abnormal proliferative phenotypes. Analysis of lineage gene expression suggests that the Bcl11a (-/-) HSCs are constituted of two distinct myeloerythroid-restricted subpopulations. Remarkably, similar myeloid-restricted cells could also be detected in the wild-type HSC compartment, suggesting selective elimination of lymphoid-competent HSCs after Bcl11a deletion. These defects are experimentally validated in serial transplantation experiments where Bcl11a (-/-) HSCs are myeloerythroid-restricted and defective in self-renewal. Our study demonstrates the power of single-cell transcriptomics in dissecting cellular process and lineage heterogeneities in stem cell compartments, and further reveals the molecular and cellular defects in the Bcl11a-deficient HSC compartment.

X Demographics

X Demographics

The data shown below were collected from the profiles of 11 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 172 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 1%
United States 2 1%
Finland 1 <1%
Denmark 1 <1%
Sweden 1 <1%
Unknown 165 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 41 24%
Student > Ph. D. Student 39 23%
Student > Bachelor 16 9%
Student > Master 14 8%
Other 13 8%
Other 31 18%
Unknown 18 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 56 33%
Biochemistry, Genetics and Molecular Biology 42 24%
Medicine and Dentistry 15 9%
Computer Science 9 5%
Engineering 7 4%
Other 19 11%
Unknown 24 14%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 30 April 2017.
All research outputs
#3,689,031
of 25,374,647 outputs
Outputs from Genome Biology
#2,522
of 4,467 outputs
Outputs of similar age
#47,792
of 285,680 outputs
Outputs of similar age from Genome Biology
#53
of 85 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,467 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one is in the 43rd percentile – i.e., 43% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 285,680 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 83% of its contemporaries.
We're also able to compare this research output to 85 others from the same source and published within six weeks on either side of this one. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.