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Immunity. 2016 Jan 19;44(1):194-206. doi: 10.1016/j.immuni.2015.12.006. Epub 2016 Jan 12.

Compendium of Immune Signatures Identifies Conserved and Species-Specific Biology in Response to Inflammation.

Author information

1
Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA; Department of Microbiology and Immunobiology, Harvard Medical School, Boston, MA 02115, USA.
2
Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Bioinformatics Program, Boston University, Boston, MA 02215, USA.
3
Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
4
Institute for Computational Health Science, University of California, San Francisco, San Francisco, CA 94158, USA.
5
Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Division of Hematology/Oncology, Children's Hospital, Harvard Medical School, Boston, MA 02115, USA. Electronic address: nicholas_haining@dfci.harvard.edu.

Abstract

Gene-expression profiling has become a mainstay in immunology, but subtle changes in gene networks related to biological processes are hard to discern when comparing various datasets. For instance, conservation of the transcriptional response to sepsis in mouse models and human disease remains controversial. To improve transcriptional analysis in immunology, we created ImmuneSigDB: a manually annotated compendium of ∼5,000 gene-sets from diverse cell states, experimental manipulations, and genetic perturbations in immunology. Analysis using ImmuneSigDB identified signatures induced in activated myeloid cells and differentiating lymphocytes that were highly conserved between humans and mice. Sepsis triggered conserved patterns of gene expression in humans and mouse models. However, we also identified species-specific biological processes in the sepsis transcriptional response: although both species upregulated phagocytosis-related genes, a mitosis signature was specific to humans. ImmuneSigDB enables granular analysis of transcriptomic data to improve biological understanding of immune processes of the human and mouse immune systems.

PMID:
26795250
PMCID:
PMC5330663
DOI:
10.1016/j.immuni.2015.12.006
[Indexed for MEDLINE]
Free PMC Article

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