# ImmGen: Gene Expression and Regulation in Immune Cells > **NIH NIH R24** · HARVARD MEDICAL SCHOOL · 2022 · $1,676,072 ## Abstract ImmGen is a collaborative group of 19 Immunology and Computational Biology laboratories who perform, under standardized conditions, a thorough dissection of gene expression and its regulation in the immune system of the mouse. Shared SOPs, data generation and processing pipelines have made for cross- comparable gene expression and epigenetic data that serve as frequently consulted public resource and reference. Machine learning approaches have been developed to infer underlying genetic regulatory networks. These main themes will be continued: 1, Charting Transcriptomes. We will continue to evolve the ImmGen gene expression compendium, combining population RNAseq with single-cell RNAseq/CITEseq to chart the landscape of immunocytes across lymphoid and parenchymal organs, lineage co-adaptation to organismal locations, infectious/autoimmune challenges, or genetic or sex-specific variation. We will expand the ongoing catalog of cytokines signatures in all the major lineages. To chart the “dark transcriptome” (unrecognized transcripts or splice variants missing from standard references), long-read direct RNA sequencing will be applied, at baseline or after strong activation. 2, Charting Immunogenomic Regulatory Networks. We will further ImmGen’s epigenomic charting: (i) ongoing highly granular mapping of the histone post-translational modification code will be expanded to non-standard PTMs that reveal subtle aspects of the code’s implementation; (ii) we will generate genomewide methylome profiles across lineages; (iii) multimodal strategies that match chromatin accessibility and mRNA across single-cells (SHAREseq) will be applied in “buckets” of cells of a given lineage (T, B, ILC, myeloid) that encompass the range of phenotypic variation within a lineage, internally validated by using F1 intercross mice as donors, relating genetic variation in TF- binding motifs with chromatin activation. These multilayered data will serve as input for ongoing Artificial Intelligence decoding of regulatory networks underlying immunocyte differentiation. 3: From Data to Public Reference. The role that ImmGen data serve as a community reference will be broadened. The interactive databrowsers on the ImmGen web and smartphone app will be expanded and optimized (cell-type centered querying, RNA-protein match). With the leitmotiv of reference data homogeneity, we will import and harmonize a collection of multimodal immunogenomic datasets, complementing those produced internally. This homogenous resource will be served for facilitated public browsing, and will support: (i) definitions of immune cell-types based on statistically objective distance- and continuity-based criteria (ii) Reference Maps (cross- organ or cross-lineages) for public use, against which new studies can be aligned by label transfer software, with a dedicated online service (iii) panels of expression signatures identifying cell-types or co-regulated gene modules. This reference work will solicit communit... ## Key facts - **NIH application ID:** 10411158 - **Project number:** 2R24AI072073-16 - **Recipient organization:** HARVARD MEDICAL SCHOOL - **Principal Investigator:** CHRISTOPHE O. BENOIST - **Activity code:** R24 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2022 - **Award amount:** $1,676,072 - **Award type:** 2 - **Project period:** 2007-09-18 → 2027-08-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10411158 ## Citation > US National Institutes of Health, RePORTER application 10411158, ImmGen: Gene Expression and Regulation in Immune Cells (2R24AI072073-16). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10411158. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*