Immunological Genome Project

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Immunological Genome Project
Organismsimmune cells in the mouse.
Laboratoryvarious labs in US

The Immunological Genome Project (ImmGen) is a collaborative scientific research project that is currently building a gene-expression database for all characterized immune cells in the mouse. The overarching goal of the project is to computationally reconstruct the gene regulatory network in immune cells

.[1] All data generated as part of ImmGen are made freely and publicly available at the ImmGen portal [1].

The ImmGen project began in 2008, as a collaboration between several immunology and computational biology laboratories across the United States, and will be completing its second phase on 2017. Currently, raw data and specialized data browsers from the first and second phases are on



A true understanding of cell differentiation in the immune system will require a general perspective on the transcriptional profile of each cell type of the adaptive and innate immune systems, and how these profiles evolve through cell differentiation or activation by immunogenic or tolerogenic ligands. The ImmGen project aims to establish the roadmap of these transcriptional states.

Gene-expression compendium[edit]

The first aim of ImmGen is to generate a compendium of whole-genome transcriptional profiles (initially by microarray, now mostly by RNA-sequencing) for nearly all characterized cell populations of the adaptive and innate immune systems in the mouse, at major stages of differentiation and activation. This effort is being carried out by a group of collaborating immunology research laboratories across the U.S. Each of the laboratories brings a unique expertise in a particular cell lineage, and all are employing standardized procedures for cell sorting. The compendium of microarray data currently include over 250 immunologically relevant cell types, from all lymphoid organs and other tissues which are monitored by immune cells.


A series of ImmGen reports was published as the compendium accumulated. Some lineage specific reports described hematopoietic stem cells,[2] natural killer cells,[3] neutrophiles,[4] B and T cells,[5] natural killer cells,[6] macrophage,[7] dendritic cells,[8] alpha beta T cells,[9] gamma delta T cells,[10] activated CD8 T cells,[11] innate lymphoid cells,[12] and lymph node stromal cells.[13] Though most of the transcriptional profiling was done on B6 mice, the effect of genetic variation was also studied.[14] The second phase of ImmGen started profiling activated immune cells. The interferon response was used as a test case.[15]

Bioinformatic gene regulatory network model[edit]

Several groups of collaborating computational biologists (Regev & Koller) used the data to reverse-engineer the genetic regulatory network in immune cells,[16] and compare it to the human immune system [17] An initial survey of differential splicing across immune lineages was carried out using both microarrays and RNA-sequencing.[18]

Visual representation of data[edit]

Project participants from Brown University's Computer Sciences Department are also exploring novel representation modes for the ImmGen data, developing and curating the public representation.


Participating Immunology laboratories include the Brenner (NKT, BWH, Boston), Goldrath (Activated CD8 T cells, UCSD, San Diego), Kang (gamma delta T cells, U. Mass, Worcester), Lanier (NK, UCSF, San Francisco), Mathis/Benoist (alpha beta T cells, HMS, Boston), Merad and Randolph (monocytes & macrophages, Mount Sinai, New York and Washington University, Saint Louis), Rossi (HSC, Children's, Boston), Turley (DC, DFCI, Boston), and Wagers (HSC, Joslin, Boston) labs.

Tragically, Richard (Randy) Hardy (Fox Chase, Philadelphia), who was an ImmGen member since its initiation, passed away on June 2016.

Current status[edit]

As of August 2016, Immgen has profiled more than 250 naive cell populations in the mouse using microarrays, and several dozens of activated cell types using RNA-sequencing.

Data access[edit]

The project's status and detailed information can be seen at (ImmGen). This site also includes a dedicated data browser, with which users can interactively explore the expression profiles for particular genes, networks of co-regulated genes, and genes that best distinguish different cell types. Raw data are available at the NCBI's Gene Expression Omnibus [2]

See also[edit]


  1. ^ Heng, T. S., M. W. Painter and C. Immunological Genome Project (2008). "The Immunological Genome Project: networks of gene expression in immune cells." Nat Immunol 9(10): 1091-1094.
  2. ^ Gazit, R., B. S. Garrison, T. N. Rao, T. Shay, J. Costello, J. Ericson, F. Kim, J. J. Collins, A. Regev, A. J. Wagers, D. J. Rossi and C. Immunological Genome Project (2013). "Transcriptome analysis identifies regulators of hematopoietic stem and progenitor cells." Stem Cell Reports 1(3): 266-280.
  3. ^ Cohen, N. R., P. J. Brennan, T. Shay, G. F. Watts, M. Brigl, J. Kang, M. B. Brenner and C. ImmGen Project (2013). "Shared and distinct transcriptional programs underlie the hybrid nature of iNKT cells." Nat Immunol 14(1): 90-99.
  4. ^ Ericson, J. A., P. Duffau, K. Yasuda, A. Ortiz-Lopez, K. Rothamel, I. R. Rifkin, P. A. Monach and C. ImmGen (2014). "Gene expression during the generation and activation of mouse neutrophils: implication of novel functional and regulatory pathways." PLoS One 9(10): e108553.
  5. ^ Painter, M. W., S. Davis, R. R. Hardy, D. Mathis, C. Benoist and C. Immunological Genome Project (2011). "Transcriptomes of the B and T lineages compared by multiplatform microarray profiling." J Immunol 186(5): 3047-3057.
  6. ^ Bezman, N. A., C. C. Kim, J. C. Sun, G. Min-Oo, D. W. Hendricks, Y. Kamimura, J. A. Best, A. W. Goldrath, L. L. Lanier and C. Immunological Genome Project (2012).
  7. ^ Gautier, E. L., T. Shay, J. Miller, M. Greter, C. Jakubzick, S. Ivanov, J. Helft, A. Chow, K. G. Elpek, S. Gordonov, A. R. Mazloom, A. Ma'ayan, W. J. Chua, T. H. Hansen, S. J. Turley, M. Merad, G. J. Randolph and C. Immunological Genome (2012). "Gene-expression profiles and transcriptional regulatory pathways that underlie the identity and diversity of mouse tissue macrophages." Nat Immunol 13(11): 1118-1128.
  8. ^ Miller, J. C., B. D. Brown, T. Shay, E. L. Gautier, V. Jojic, A. Cohain, G. Pandey, M. Leboeuf, K. G. Elpek, J. Helft, D. Hashimoto, A. Chow, J. Price, M. Greter, M. Bogunovic, A. Bellemare-Pelletier, P. S. Frenette, G. J. Randolph, S. J. Turley, M. Merad and C. Immunological Genome (2012). "Deciphering the transcriptional network of the dendritic cell lineage." Nat Immunol 13(9): 888-899.
  9. ^ Mingueneau, M., T. Kreslavsky, D. Gray, T. Heng, R. Cruse, J. Ericson, S. Bendall, M. H. Spitzer, G. P. Nolan, K. Kobayashi, H. von Boehmer, D. Mathis, C. Benoist, C. Immunological Genome, A. J. Best, J. Knell, A. Goldrath, V. Joic, D. Koller, T. Shay, A. Regev, N. Cohen, P. Brennan, M. Brenner, F. Kim, T. Nageswara Rao, A. Wagers, T. Heng, J. Ericson, K. Rothamel, A. Ortiz-Lopez, D. Mathis, C. Benoist, N. A. Bezman, J. C. Sun, G. Min-Oo, C. C. Kim, L. L. Lanier, J. Miller, B. Brown, M. Merad, E. L. Gautier, C. Jakubzick, G. J. Randolph, P. Monach, D. A. Blair, M. L. Dustin, S. A. Shinton, R. R. Hardy, D. Laidlaw, J. Collins, R. Gazit, D. J. Rossi, N. Malhotra, K. Sylvia, J. Kang, T. Kreslavsky, A. Fletcher, K. Elpek, A. Bellemare-Pelletier, D. Malhotra and S. Turley (2013). "The transcriptional landscape of alphabeta T cell differentiation." Nat Immunol 14(6): 619-632.
  10. ^ Narayan, K., K. E. Sylvia, N. Malhotra, C. C. Yin, G. Martens, T. Vallerskog, H. Kornfeld, N. Xiong, N. R. Cohen, M. B. Brenner, L. J. Berg, J. Kang and C. Immunological Genome Project (2012). "Intrathymic programming of effector fates in three molecularly distinct gammadelta T cell subtypes." Nat Immunol 13(5): 511-518.
  11. ^ Best, J. A., D. A. Blair, J. Knell, E. Yang, V. Mayya, A. Doedens, M. L. Dustin, A. W. Goldrath and C. Immunological Genome Project (2013). "Transcriptional insights into the CD8(+) T cell response to infection and memory T cell formation." Nat Immunol 14(4): 404-412.
  12. ^ Malhotra, N., K. Narayan, O. H. Cho, K. E. Sylvia, C. Yin, H. Melichar, M. Rashighi, V. Lefebvre, J. E. Harris, L. J. Berg, J. Kang and C. Immunological Genome Project (2013). "A network of high-mobility group box transcription factors programs innate interleukin-17 production." Immunity 38(4): 681-693.
  13. ^ Malhotra, D., A. L. Fletcher, J. Astarita, V. Lukacs-Kornek, P. Tayalia, S. F. Gonzalez, K. G. Elpek, S. K. Chang, K. Knoblich, M. E. Hemler, M. B. Brenner, M. C. Carroll, D. J. Mooney, S. J. Turley and C. Immunological Genome Project (2012). "Transcriptional profiling of stroma from inflamed and resting lymph nodes defines immunological hallmarks." Nat Immunol 13(5): 499-510.
  14. ^ Mostafavi, S., A. Ortiz-Lopez, M. A. Bogue, K. Hattori, C. Pop, D. Koller, D. Mathis, C. Benoist and C. Immunological Genome (2014). "Variation and genetic control of gene expression in primary immunocytes across inbred mouse strains." J Immunol 193(9): 4485-4496.
  15. ^ Mostafavi, S., H. Yoshida, D. Moodley, H. LeBoite, K. Rothamel, T. Raj, C. J. Ye, N. Chevrier, S. Y. Zhang, T. Feng, M. Lee, J. L. Casanova, J. D. Clark, M. Hegen, J. B. Telliez, N. Hacohen, P. L. De Jager, A. Regev, D. Mathis, C. Benoist and C. Immunological Genome Project (2016). "Parsing the Interferon Transcriptional Network and Its Disease Associations." Cell 164(3): 564-578.
  16. ^ Jojic, V., T. Shay, K. Sylvia, O. Zuk, X. Sun, J. Kang, A. Regev and D. Koller (2013). "Identification of transcriptional regulators in the mouse immune system." Nat Immunol 14(6): 633-643.
  17. ^ Shay, T., V. Jojic, O. Zuk, K. Rothamel, D. Puyraimond-Zemmour, T. Feng, E. Wakamatsu, C. Benoist, D. Koller, A. Regev and t. I. Consortium (2013). "Conservation and divergence in the transcriptional programs of the human and mouse immune systems." Proceedings of the National Academy of Sciences 110(8): 2946-2951.
  18. ^ Ergun, A., G. Doran, J. C. Costello, H. H. Paik, J. J. Collins, D. Mathis, C. Benoist and C. ImmGen (2013). "Differential splicing across immune system lineages." Proc Natl Acad Sci U S A 110(35): 14324-14329.