Title |
An atlas of mouse CD4+ T cell transcriptomes
|
---|---|
Published in |
Biology Direct, April 2015
|
DOI | 10.1186/s13062-015-0045-x |
Pubmed ID | |
Authors |
Michael JT Stubbington, Bidesh Mahata, Valentine Svensson, Andrew Deonarine, Jesper K Nissen, Alexander G Betz, Sarah A Teichmann |
Abstract |
CD4(+) T cells are key regulators of the adaptive immune system and can be divided into T helper (Th) cells and regulatory T (Treg) cells. During an immune response Th cells mature from a naive state into one of several effector subtypes that exhibit distinct functions. The transcriptional mechanisms that underlie the specific functional identity of CD4(+) T cells are not fully understood. To assist investigations into the transcriptional identity and regulatory processes of these cells we performed mRNA-sequencing on three murine T helper subtypes (Th1, Th2 and Th17) as well as on splenic Treg cells and induced Treg (iTreg) cells. Our integrated analysis of this dataset revealed the gene expression changes associated with these related but distinct cellular identities. Each cell subtype differentially expresses a wealth of 'subtype upregulated' genes, some of which are well known whilst others promise new insights into signalling processes and transcriptional regulation. We show that hundreds of genes are regulated purely by alternative splicing to extend our knowledge of the role of post-transcriptional regulation in cell differentiation. This CD4(+) transcriptome atlas provides a valuable resource for the study of CD4(+) T cell populations. To facilitate its use by others, we have made the data available in an easily accessible online resource at www.th-express.org . This article was reviewed by Wayne Hancock, Christine Wells and Erik van Nimwegen. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 2 | 40% |
United Kingdom | 1 | 20% |
Australia | 1 | 20% |
Unknown | 1 | 20% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 3 | 60% |
Scientists | 2 | 40% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 2 | 1% |
Japan | 1 | <1% |
United Kingdom | 1 | <1% |
Luxembourg | 1 | <1% |
Unknown | 173 | 97% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 45 | 25% |
Researcher | 34 | 19% |
Student > Master | 27 | 15% |
Student > Bachelor | 13 | 7% |
Student > Doctoral Student | 12 | 7% |
Other | 18 | 10% |
Unknown | 29 | 16% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 44 | 25% |
Immunology and Microbiology | 37 | 21% |
Biochemistry, Genetics and Molecular Biology | 36 | 20% |
Medicine and Dentistry | 11 | 6% |
Neuroscience | 6 | 3% |
Other | 16 | 9% |
Unknown | 28 | 16% |