Title |
Transcriptional programs define molecular characteristics of innate lymphoid cell classes and subsets
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Published in |
Nature Immunology, January 2015
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DOI | 10.1038/ni.3094 |
Pubmed ID | |
Authors |
Michelle L Robinette, Anja Fuchs, Victor S Cortez, Jacob S Lee, Yaming Wang, Scott K Durum, Susan Gilfillan, Marco Colonna |
Abstract |
The recognized diversity of innate lymphoid cells (ILCs) is rapidly expanding. Three ILC classes have emerged, ILC1, ILC2 and ILC3, with ILC1 and ILC3 including several subsets. The classification of some subsets is unclear, and it remains controversial whether natural killer (NK) cells and ILC1 cells are distinct cell types. To address these issues, we analyzed gene expression in ILCs and NK cells from mouse small intestine, spleen and liver, as part of the Immunological Genome Project. The results showed unique gene-expression patterns for some ILCs and overlapping patterns for ILC1 cells and NK cells, whereas other ILC subsets remained indistinguishable. We identified a transcriptional program shared by small intestine ILCs and a core ILC signature. We revealed and discuss transcripts that suggest previously unknown functions and developmental paths for ILCs. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United States | 2 | 29% |
Germany | 1 | 14% |
Unknown | 4 | 57% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 5 | 71% |
Scientists | 1 | 14% |
Practitioners (doctors, other healthcare professionals) | 1 | 14% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Netherlands | 3 | <1% |
United Kingdom | 2 | <1% |
Germany | 1 | <1% |
Italy | 1 | <1% |
Sweden | 1 | <1% |
Czechia | 1 | <1% |
Ireland | 1 | <1% |
Spain | 1 | <1% |
Japan | 1 | <1% |
Other | 2 | <1% |
Unknown | 557 | 98% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 144 | 25% |
Researcher | 113 | 20% |
Student > Master | 60 | 11% |
Student > Bachelor | 45 | 8% |
Student > Doctoral Student | 36 | 6% |
Other | 67 | 12% |
Unknown | 106 | 19% |
Readers by discipline | Count | As % |
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Agricultural and Biological Sciences | 154 | 27% |
Immunology and Microbiology | 154 | 27% |
Biochemistry, Genetics and Molecular Biology | 66 | 12% |
Medicine and Dentistry | 56 | 10% |
Neuroscience | 10 | 2% |
Other | 21 | 4% |
Unknown | 110 | 19% |