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Dissecting hematopoietic and renal cell heterogeneity in adult zebrafish at single-cell resolution using RNA sequencing

Overview of attention for article published in The Journal of Experimental Medicine, September 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (82nd percentile)
  • Average Attention Score compared to outputs of the same age and source

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18 X users
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1 Facebook page

Citations

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158 Dimensions

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167 Mendeley
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Title
Dissecting hematopoietic and renal cell heterogeneity in adult zebrafish at single-cell resolution using RNA sequencing
Published in
The Journal of Experimental Medicine, September 2017
DOI 10.1084/jem.20170976
Pubmed ID
Authors

Qin Tang, Sowmya Iyer, Riadh Lobbardi, John C. Moore, Huidong Chen, Caleb Lareau, Christine Hebert, McKenzie L. Shaw, Cyril Neftel, Mario L. Suva, Craig J. Ceol, Andre Bernards, Martin Aryee, Luca Pinello, Iain A. Drummond, David M. Langenau

Abstract

Recent advances in single-cell, transcriptomic profiling have provided unprecedented access to investigate cell heterogeneity during tissue and organ development. In this study, we used massively parallel, single-cell RNA sequencing to define cell heterogeneity within the zebrafish kidney marrow, constructing a comprehensive molecular atlas of definitive hematopoiesis and functionally distinct renal cells found in adult zebrafish. Because our method analyzed blood and kidney cells in an unbiased manner, our approach was useful in characterizing immune-cell deficiencies within DNA-protein kinase catalytic subunit (prkdc), interleukin-2 receptor γ a (il2rga), and double-homozygous-mutant fish, identifying blood cell losses in T, B, and natural killer cells within specific genetic mutants. Our analysis also uncovered novel cell types, including two classes of natural killer immune cells, classically defined and erythroid-primed hematopoietic stem and progenitor cells, mucin-secreting kidney cells, and kidney stem/progenitor cells. In total, our work provides the first, comprehensive, single-cell, transcriptomic analysis of kidney and marrow cells in the adult zebrafish.

X Demographics

X Demographics

The data shown below were collected from the profiles of 18 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 167 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 167 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 40 24%
Researcher 23 14%
Student > Master 19 11%
Student > Bachelor 11 7%
Student > Doctoral Student 8 5%
Other 29 17%
Unknown 37 22%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 62 37%
Agricultural and Biological Sciences 27 16%
Medicine and Dentistry 8 5%
Immunology and Microbiology 5 3%
Neuroscience 5 3%
Other 18 11%
Unknown 42 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 22 September 2017.
All research outputs
#3,268,722
of 25,461,852 outputs
Outputs from The Journal of Experimental Medicine
#2,309
of 11,616 outputs
Outputs of similar age
#56,900
of 323,419 outputs
Outputs of similar age from The Journal of Experimental Medicine
#38
of 58 outputs
Altmetric has tracked 25,461,852 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,616 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.4. This one has done well, scoring higher than 80% of its peers.
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 323,419 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 82% of its contemporaries.
We're also able to compare this research output to 58 others from the same source and published within six weeks on either side of this one. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.