News

November 2023: : ImmGen is powered by ChatGPT.
ChatGPT and Immgenlogocombined
(In a small part)
Artificial Intelligence now informs ImmGen’s databrowsers. Not the expression profiles or epigenomic data, which are still experimentally-determined. But, in an effort to increase the information served about genes or gene clusters and what they might mean, OpenAI’s ChatGPT 3.5 will be used to query the function of a gene, or relationships between genes in the databrowsers, with answers that can be more immediately intuitive and integrated than those delivered by the usual tools.
Disclaimer: ChatGPT’s answers are not always completely true (and it may plead ignorance in some cases).
So “caveat emptor”, but these functions represent the start of ImmGen’s interest in including AI and Machine Learning to enhance the knowledge it serves.



August 2023: New transcriptional signatures to inflammatory Cytokines.
cyto
In the latest installment of ImmGen’s goal of systematically determining the transcriptional signatures of all cytokines across all immunologic lineages, Juliana Lee has generated gene expression profiles (RNAseq on carefully sorted cell populations) of the responses to key inflammatory cytokines (IL1-beta, Il6, and TNF-alpha) across the ImmGen standard 14-cell-set.

Use the Skyline databrowser to display cytokine-induced expression profiles across the ImmGen immunological cell-types for a selected gene, or download signature sets for each cytokine.








June 2023: Human data in the ImmGen app
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ImmGen developer Jeff Ericson has updated the ImmGen Mobile app, adding a Human RNAseq datagroup. The new release of the app displays human RNAseq data from the main populations of human PBMCs, in addition to the previous mouse data. Search for a Gene Symbol, and the app displays gene expression levels in different lineages of the immune system, toggle between human and mouse. Updated Gene Summaries from NCBI have been added. Download the new Version from the Apple iTunes Store or the Google Play store using the keyword “ImmGen”. This update is automatically applied on existing installs.





The ImmGen “Populations” list is ever growing !
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Immune cell types have been isolated and added to ImmGen’s already long population collection of flow-purified.
The new additions include B cells (Julie Tellier, Nutt Lab), activated and memory CD8 T (Ty Crowl, Goldrath lab), MAIT (Mallory Paynich, Kronenberg lab) and more Mast cells than most Immunologists ever knew existed (Tamara Salloum, Dwyer lab).

You can now browse and compare their expression profiles with ImmGen’s most popular databrowsers : Gene Skyline, Population Comparison and MyGeneSet.




“AlwaysOpen” ImmGen
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ImmGen is now launching a new “AlwaysOpen” initiative, to open its workhorse low-input RNAseq pipeline to any qualified laboratory interested in helping to generate RNAseq datasets that fit their own interests, while contributing to the compendium displayed on the ImmGen website and mobile apps.
Yes, free profiling.
That being said, ImmGen is not turning into a core facility. Proposals needs to meet criteria of general interest, and sample preparation will need to follow obsessively the ImmGen SOP.
More details



Dec 2022: Our ImmGen app gets a new feature!

ImmGen developer Jeff Ericson has updated the ImmGen Mobile up, bringing the datasets to speed and adding a mobile version of the Gene Constellation databrowser.

Appupdate As in previous ImmGen app versions, search for a Gene Symbol, and the app displays gene expression levels in different lineages of the mouse immune system, either as 2-D barcode view for all lineages or as detailed histograms for specific lineages. The new constellation feature allows users to visualize correlation networks for a chosen gene, showing the genes whose expression within a selected lineage of immunocytes is most related to the queried gene (and, on rainy afternoons, can iteratively look for genes most related one of those genes, and so on)


Deployed simultaneously on both Android and IOS apps, the new release of the app displays RNAseq data as well as previous microarray data, easily switched through a toggle button. Download Version 3.1.0 from the Apple iTunes Store or the Google Play store using the keyword “ImmGen”. Future updates will be applied automatically on existing apps.





May 2022: ImmGen launches a new Open Source Project!

Umouse
Per the recent Correspondence in NatImm, ImmGen launches a new Open Source Project! After the success of the OpenSource MNP, when myeloid cells had their day, time for the real deal: T cells! They have been named killers, helpers. But who are they really?

The goal is to coordinate wide community participation (beyond the core Immgen labs) around a simple project goal: to profile every T cell, in every body location of the mouse, and in every state that immunologic challenges push T cells into. You name it and we’ll sequence it (TM)!

• T cells across body locations (e.g. lymphoid and parenchymal organs): check
• bacterial, fungal, viral and parasitic infections, autoimmune and inflammatory lesions, tumors, pharmacological intervention: check
• Over time, sex and genetic background: check

Profiling will be performed at the single-cell level, with the combined measurement of mRNA, surface protein (CITE-seq/TotalSeq) expression, and TCR-V sequencing (both chains, real clonotypes). The ImmGen core team collaborated with BioLegend to define, test and optimize a panel of DNA-coded antibodies to proteins on the surfaces of T cells. These will allow a direct connection between RNA and protein content, resolving cell-types/states from both the RNA and protein side (jointly displayed on the Rosetta viewer).

This OpenSource Project is open to all labs. If you have an idea, a specific know-how, a model of T cell function/challenge that you feel is in scope (see Forum), and whose workup you would like to be actively involved in, please consider participating by submitting a short proposal and justification.




December 2021: Immgen Gene of the Year Announced

IL7r

The ImmGen team has tallied the number of times each GeneSymbol was requested during 2021 on the skyline databrowser.
The winner is Il7r, requested 300 times over the course of the year, followed by 3 very close contenders: Itgax (228 times), Il2ra (227 times) and Tcf7 (226 times).

Best wishes for a Happy New Year to all ImmGen users!



















December 2021: Immgen Annual workshop


The annual Immgen workshop took place on December 10, 2021.

Contrary to tradition, no one had to brave the Boston winter this year. As for the traditional dinner at the MFA, here's a reminder from 2 years ago:




MFA1MFA1



September 2021: New transcriptional signatures to CGC Cytokines.

Rosetta
In keeping with ImmGen mission, Kumba Seddu, Alev Baysoy and Felicia Chen have generated gene expression profiles of the immediate responses to cytokines of the Common-Gamma-Chan family (IL2, IL4, IL7, IL9, Il15 and IL21), this across all immunological lineages represented in the ImmGen standard 14-cell-set. All responses were induced in vivo by systemic injection of free cytokine or of cytokine/Ab complexes, and responses profiled by RNAseq 2 hours pi (timepoint chosen to focus mostly on direct effects).
A deep analysis of the data (which revealed several unexpected facets of the CGC family) is being performed by an ImmGen data analysis team. As usual, the curated data are available pre-publication using the immGen databrowsers: Display cytokine-induced expression profiles across the ImmGen immunological cell-types for a selected single gene, or explore changes in your own set of genes through an interactive heatmap.

Specific signature sets (induced or repressed, relative to PBS control) are also available for download.



August 2021: Brand new ways to look at single cell data…


Rosetta*, the RNA/Protein Mirror Viewer for single-cell data.


Rosetta
This interactive tool, developed by Brinda Vijaykumar, provides integrated representations of Protein and RNA expression in single-cell profiling data (CITEseq technology).

Two different visualizations modes are offered:

On the Heatmap tab, cells are grouped by dimensionality reduction onto two UMAP plots generated from either the RNA or protein data. They can be colored according to cell lineage or standard clustering. Selecting groups of cells on either the Protein or RNA UMAP will display their position on the other map, and also bring up new heatmaps that display the proteins and genes whose expression best characterizes the selected cells.
More data will be curated into the site soon.

The FACS-style tab displays three scatter plots familiar to immunologists, in which cells are displayed according to expression of two chosen protein markers. A selection tool is used to gate cells in the first panel(s), and these gates can be applied to show the position of the selected cells in the subsequent panels, and on the RNA and Protein UMAPs below.
The data shown in this first release represent whole mouse splenocytes (major immunocyte lineages are included). It was generated with 97 DNA-tagged antibodies against cell surface markers (TotalSeqC panel designed in collaboration with BioLegend). More soon…

*Named after the Rosetta stone, which also showed the same text in different languages.













April 2021: Humans are back!

human
The ImmGen databrowsers are now used to portray externally-generated transcriptome data from human immunocytes.
The site has now been updated to include RNAseq data from the sister-project “Immune Cell Atlas”. Either as population RNAseq on the usual Skyline viewer (Angela Magnuson) or as scRNAseq (Michal Slyper, Julia Waldman, Angela Magnuson and Jerome Martin).
More data will be curated into the site soon.





Thank you to all ImmGen users for having been a part of the ImmGen story for the last 15 years.

Best wishes to all for a Happy(ier) New Year!


ImmGen15



September 2020: New and improved Constellation Databrowser


Liang Yang has completely reworked the classic ImmGen Gene constellation browser, which shows the genes whose expression is most closely related to a query gene. Many many additional features and links. And yes in a non-Flash environment (for those who wondered… the ImmGen site is now officially Flash-free!)

Constellation The Constellation databrowser presents the genes most closely correlated to a chosen gene, within ImmGen expression data. As in the original instance, users can jump from one gene to the next caution, can be addictive). The distance from the center representing the tightness of this relationship. Users can choose to organized these correlated genes by secondary correlation, or according to chromosomal location. The correlation can be calculated across the entire set of lineages (will tend to return lineage-specific transcripts) or within a lineage (more specific information). An interactive graph displays the actual expression values across the selected populations.

The new Constellation browser includes two important expansions for complementary followup analyses on the set of correlated genes:
- An interaction network visualization, thanks to the String database
- A rich search of GeneOntology, Pathway enrichment, regulatory connections, etc, thanks to the Enrichr project.

Additionally, the Constellation page connects directly to a range of ImmGen databrowsers looking at the data from various angles (expression, Open Chromatin Regions/ Enhancer analysis, human Cell Atlas).

Please be aware of small discrepancies that may occur while comparing to previously downloaded data or figures. Changes are minimal for most genes, but M25 differs from M16 by introducing around 2400 new genes and 8000 new transcripts (for a total of 55401 total genes, of which 21859 are recognized as protein-coding). Many of them are microRNA precursors, others correspond to better distinguished members of gene families. The most significant “newcomers” are Vps28, Tmem179b, and Itprip (primarily expressed in Mast cells, Macrophages and Granulocytes, respectively).



15 years!
15



ImmGen at 15
Immunological Genome Project.
Nat Immunol. 2020 Jul;21(7):700-703.




July 2020: GENCODE update

Gencode
ImmGen is updating the gene/transcript reference framework used to map and assign RNAseq data. Liang Yang has performed the herculean task of re-processing all existing ULI RNAseq data against GENCODE Version M25, from the previously used M16. This update applies to data on the “RNAseq Skyline”, "Population Comparison (RNASeq)" and "MyGeneSet" databrowser pages.
In addition, Gene tables for datasets deposited at NCBI’s Gene Expression Omnibus (GSE109125, GSE122108, GSE122597) have been updated to M25, as have the raw count numbers and normalized tables found on the ImmGen Dataset page.

Please be aware of small discrepancies that may occur while comparing to previously downloaded data or figures. Changes are minimal for most genes, but M25 differs from M16 by introducing around 2400 new genes and 8000 new transcripts (for a total of 55401 total genes, of which 21859 are recognized as protein-coding). Many of them are microRNA precursors, others correspond to better distinguished members of gene families. The most significant “newcomers” are Vps28, Tmem179b, and Itprip (primarily expressed in Mast cells, Macrophages and Granulocytes, respectively).



June 2020: Flamboyant past

Flash
It is with mixed feelings that we announce the retirement of our beloved ImmGen Flash interface.

Over the years, Flash has jazzed up the ImmGen website, providing dynamic and colored displays to the early databrowsers. Flash is unfortunately being phased out. For those nostalgic ImmGen users, we have left a small taste of the good old Flash in the Constellation databrowser, but this will also come to pass, alas...




April 2020: COVID-19


During the pandemic, Immgen programs are naturally slowed down.
To support COVID-19 research worldwide, we are re-deploying here some of our visualization tools to display datasets related to SARS-CoV2, the pathology or the immune response it elicits.




December 2019 : ImmGen Annual Workshop

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Where to?


The Immunological Genome Project hosted its annual Workshop on Dec 6.
As usual, ImmGen Participants braved the Boston weather and came to meet new members, discuss recent findings and share their thoughts about the Consortium's possible future directions.
This year's T-shirt is sure to become a collector's item.




New ImmGen Enhancer networks databrowser to explore Open Chromatin Regions associated with a gene.

EnhancerA series of new tools, developed by Eunice Esomonu and Liang Yang are now available through the databrowser page.

This new online tool is an extension to the article “cis-Regulatory Atlas of the Mouse Immune System” published by Yoshida et al in the February issue of Cell, which describes a matched epigenome and transcriptome analysis in 86 primary cell-types spanning the mouse immune system.
This work resulted in the description of 512,595 Open Chromatin Regions accessible in one or more immune cell-types, and in strong predictions of the transcription factors likely (by presence of DNA motif and correlated expression) to control the activity of each OCR.

The Enhancer Networks portal supports the exploration of OCR accessibility for a particular gene using several paths:
1-The display of OCRs associated with this gene with their chromosome location.
2-The visualization of OCR accessibility in key immune cell-types.
3-Transcription factors predicted to bind these OCRs.
More features will be added in the future.



July 2019: ImmGen Computational Workshop:



Organized by Tal Shay and Sara Mostafavi, two days of exciting presentations on cutting edge approaches to understanding cells and their regulatory networks, brainstorming on how these could be applied to ImmGen data or questions, or how ImmGen could tailor some of its profiling to dovetail with computational needs.

#immgencomp2019






June 2019: Population comparison: The RNAseq version is OUT!:

Thank you to the patient ImmGen user (you know who you are) who pushed us to move this upgrade up the priority list.

As previously, the “Population Comparison” databrowser compares gene expression between cell-types and returns a table of the most differential genes. Can be used for a simple pairwise comparison (e.g. Follicular B vs GC B cells) or for comparison between groups of populations (e.g all CD4+ T vs all CD8+ T cells), and either the new RNAseq or the older microarray data can be consulted.