Title |
Dissecting hematopoietic and renal cell heterogeneity in adult zebrafish at single-cell resolution using RNA sequencing
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Published in |
The Journal of Experimental Medicine, September 2017
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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. |
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Geographical breakdown
Country | Count | As % |
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United States | 7 | 39% |
Ireland | 1 | 6% |
United Kingdom | 1 | 6% |
Italy | 1 | 6% |
Guinea | 1 | 6% |
Austria | 1 | 6% |
Unknown | 6 | 33% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 9 | 50% |
Scientists | 7 | 39% |
Science communicators (journalists, bloggers, editors) | 2 | 11% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 164 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 40 | 24% |
Researcher | 23 | 14% |
Student > Master | 19 | 12% |
Student > Bachelor | 11 | 7% |
Student > Doctoral Student | 8 | 5% |
Other | 26 | 16% |
Unknown | 37 | 23% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 62 | 38% |
Agricultural and Biological Sciences | 27 | 16% |
Medicine and Dentistry | 8 | 5% |
Immunology and Microbiology | 5 | 3% |
Neuroscience | 5 | 3% |
Other | 15 | 9% |
Unknown | 42 | 26% |