Profiling of gene expression with microarrays holds great potential for human health, for illuminating disease pathways or providing biomarkers to monitor disease or its resolution. Using high-throughput approaches for genotyping, immunophenotyping and gene expression analysis, the project will examine the basis for the control of gene expression in human immune cells, and how it is influenced by natural genetic variation or aging. In practice, the project will combine several cross-informative approaches: 1) Building on the established sample/data pipelines and robust protocols of the Immunological Genome (ImmGen) project, and on established cohorts of ethnically diverse healthy volunteers at hand, microarray techniques will be used to generate whole-genome expression profiles from purified na?ve CD4+ lymphocytes and monocytes from 600 healthy volunteers. A dense genetic map will be established for all donors. The results will elucidate how variation in the human genome affects the expression of immune genes, of key importance in understanding gene variants that bring susceptibility to immune or inflammatory disease. Computational analysis of these rich data will allow the reconstruction of regulatory connections between genes, helping to establish general modules and those specific of a given immune cell type. These data will be complemented by an orthogonal datagroup, generated from a restricted subset of 10 individuals, in which we will profile a larger set of 28 carefully delineated cell populations that exist in human blood. This work will also benefit from powerful interspecies comparison with similar experiments being performed in mice by ImmGen. 2) In addition, RNA from the same set of 28 defined cell populations will be probed with microarrays that explore other aspects of the transcriptome: i) microRNAs and other non-coding RNAs;ii) exon or splice junction arrays that will establish a map of differential splicing in human blood leukocyte. 3) The composition and reactivity of blood cells from the same donors will be established at the time of sample collection using high-throughput flow cytometry, correlating immune phenotypes with gene expression and genetic variation. 4) Genetic variability conditions the baseline levels of gene expression, but also the responsiveness to activating challenges. With samples from the same donors, Nanostring technology for transcript counting will be used to analyze the transcriptional response of defined gene sets, representing response signatures of T or dendritic cells, for a fine-grained dissection of responses to different triggers (different bacterial ligands for dendritic cells, different cytokine environment for T cells). In keeping with the resource aspect of this project, all data and interpretations will be made publicly available rapidly upon curation, allowing public querying and browsing of the data, by using and evolving the existing web architectures of the ImmGen project, of the Broad Institute, and of international repositories.
Exploration with DNA chips of the genome's expression microarrays holds great potential for human health, to better understand disease and to serve as diagnostic tools. Using a combination of high-throughput genomic techniques and computational biology, we will perform a broad exploration of gene expression in human blood cells across groups of African-American, Asian and European ancestry, asking how these profiles are affected by genetic variation or by age. These results will provide an invaluable reference benchmark for the interpretation of genetic and immunological studies.
| Ye, Chun Jimmie; Chen, Jenny; Villani, Alexandra-Chloé et al. (2018) Genetic analysis of isoform usage in the human anti-viral response reveals influenza-specific regulation of ERAP2 transcripts under balancing selection. Genome Res 28:1812-1825 |
| Mostafavi, Sara; Yoshida, Hideyuki; Moodley, Devapregasan et al. (2016) Parsing the Interferon Transcriptional Network and Its Disease Associations. Cell 164:564-78 |
| Chastre, Anne; Hafler, David A; O'Connor, Kevin C (2016) Evaluation of KIR4.1 as an Immune Target in Multiple Sclerosis. N Engl J Med 374:1495-6 |
| Hernandez, Amanda L; Kitz, Alexandra; Wu, Chuan et al. (2015) Sodium chloride inhibits the suppressive function of FOXP3+ regulatory T cells. J Clin Invest 125:4212-22 |
| Esposito, Federica; Sorosina, Melissa; Ottoboni, Linda et al. (2015) A pharmacogenetic study implicates SLC9a9 in multiple sclerosis disease activity. Ann Neurol 78:115-27 |
| Moutsianas, Loukas; Jostins, Luke; Beecham, Ashley H et al. (2015) Class II HLA interactions modulate genetic risk for multiple sclerosis. Nat Genet 47:1107-1113 |
| Housley, William J; Fernandez, Salvador D; Vera, Kenneth et al. (2015) Genetic variants associated with autoimmunity drive NF?B signaling and responses to inflammatory stimuli. Sci Transl Med 7:291ra93 |
| Isobe, Noriko; Madireddy, Lohith; Khankhanian, Pouya et al. (2015) An ImmunoChip study of multiple sclerosis risk in African Americans. Brain 138:1518-30 |
| Farh, Kyle Kai-How; Marson, Alexander; Zhu, Jiang et al. (2015) Genetic and epigenetic fine mapping of causal autoimmune disease variants. Nature 518:337-43 |
| Raj, Towfique; Rothamel, Katie; Mostafavi, Sara et al. (2014) Polarization of the effects of autoimmune and neurodegenerative risk alleles in leukocytes. Science 344:519-23 |
Showing the most recent 10 out of 29 publications
