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Reposted by Yuri Pritykin

Waggoner Lab @labwaggoner.bsky.social · 14h

Temporal and context-dependent requirements for the transcription factor Foxp3 expression in regulatory T cells @natimmunol.nature.com @yuripritykin.bsky.social Rudensky @princetonupress.bsky.social @mskcancercenter.bsky.social www.nature.com/articles/s41...

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Yuri Pritykin @yuripritykin.bsky.social · 20h

Our paper is out today at @natimmunol.nature.com! Very timely!
We performed extensive exploration of Foxp3 in Treg cells, using inducible protein degradation in vivo.
Wonderful collaboration led by Sasha Rudensky and Wei Hu, computation led by talented Gabe Dolsten.
Read it here: rdcu.be/eJ0hH

Temporal and context-dependent requirements for the transcription factor Foxp3 expression in regulatory T cells - Nature Immunology

Rudensky and colleagues demonstrate a context-dependent differential requirement for Foxp3 for Treg cell transcriptional and functional programs.

www.nature.com

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Yuri Pritykin @yuripritykin.bsky.social · 1d

Extremely happy about the Nobel prize recognizing regulatory T cells! A fascinating concept with so many potential clinical applications.
Very lucky to have been working on the genomics of Treg cells in collaboration with the giant in the field, Sasha Rudensky @mskcc.bsky.social !

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Reposted by Yuri Pritykin

Yuri Pritykin @yuripritykin.bsky.social · 19d

Excited to share our new study:
Single-cell multiomics reveals archetypal regulatory programs shared across CD4 and CD8 T cell subsets in viral infection
bioRxiv: doi.org/10.1101/2025...

🧵 Key findings below 👇

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Reposted by Yuri Pritykin

bioRxiv Genomics @biorxiv-genomic.bsky.social · 17d

Metadomain and metaloop genome interactions in mammalian T cells https://www.biorxiv.org/content/10.1101/2025.09.19.677419v1

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Yuri Pritykin @yuripritykin.bsky.social · 19d

This work is a wonderful collaboration led by amazing Sarah Walker, with Joris van der Veeken and Sasha Rudensky.
More details in the preprint: doi.org/10.1101/2025...

Looking forward to any feedback! 🙌

Single-cell multiomics reveals archetypal regulatory programs shared across CD4 and CD8 T cell subsets in viral infection

T cells protect against pathogens and tumors and can differentiate into various functionally distinct subsets. While each subset exhibits a characteristic epigenomic and transcriptional profile, essen...

doi.org

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Yuri Pritykin @yuripritykin.bsky.social · 19d

In sum, we provide:
– A resource and framework for high-resolution T cell regulatory analysis.
– Archetypal regulatory decomposition of core T cell functions across lineages and infection contexts.
– Insights into shared regulatory logic of CD8 progenitors and CD4 Tfh cells.

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Yuri Pritykin @yuripritykin.bsky.social · 19d

A key challenge is to decompose regulatory programs driving overlapping core T cell functions e.g. self-renewal, expansion, cytotoxicity, cytokine production.
For this, we did archetypal analysis.
It revealed that CD8 progenitors combine CD8 exhaustion & CD4 Tfh archetypes.

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Yuri Pritykin @yuripritykin.bsky.social · 19d

Surprisingly, these progenitor CD8 T cells were transcriptionally & epigenomically most similar to CD4 Tfh (follicular helper) cells.
Despite distinct lineages, they shared activity of CXCR5, BCL6, TOX, TCF1, ID3 and PD-1.
This suggests converging cellular phenotypes.

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Yuri Pritykin @yuripritykin.bsky.social · 19d

Notably, fundamentally and translationally important Tcf1⁺ progenitor CD8 T cells formed a shared population across acute & chronic infection.
These results help reconcile recent studies of several related populations.

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Yuri Pritykin @yuripritykin.bsky.social · 19d

We profiled 31k+ T cells with scATAC+RNA-seq during acute & chronic viral infection and built a 285-sample ATAC-seq atlas.
This enabled robust identification of all major T cell states: naive, effector, memory, Treg, Tfh, exhausted & progenitor, shared across infection conditions.

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Yuri Pritykin @yuripritykin.bsky.social · 19d

Excited to share our new study:
Single-cell multiomics reveals archetypal regulatory programs shared across CD4 and CD8 T cell subsets in viral infection
bioRxiv: doi.org/10.1101/2025...

🧵 Key findings below 👇

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Reposted by Yuri Pritykin

bioRxiv Genomics @biorxiv-genomic.bsky.social · 21d

ArchVelo: Archetypal Velocity Modeling for Single-cell Multi-omic Trajectories https://www.biorxiv.org/content/10.1101/2025.09.14.676182v1

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Yuri Pritykin @yuripritykin.bsky.social · 21d

Thanks Lee! In short, I think it's possible, and Drosophila is a good system for this, but the outcome depends on the loop. We described several classes, now working on a more detailed classification.
Some perturbations have already been reported, e.g. for tethering elements etc. but not at scale

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Yuri Pritykin @yuripritykin.bsky.social · 22d

A wonderful collaboration with the Mike Levine &
Olga Troyanskaya labs!

More papers and preprints from the lab coming soon — stay tuned!

pritykinlab.github.io

Pritykin Lab

Pritykin Lab at the Lewis-Sigler Institute for Integrative Genomics and the Department of Computer Science at Princeton University.

pritykinlab.github.io

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Yuri Pritykin @yuripritykin.bsky.social · 22d

We find 3D chromatin structures earlier than previously thought — before zygotic genome activation — and persisting through mitosis. Developmental elements linked to GAF/Zelda act as conserved bookmarks for gene regulation.

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Yuri Pritykin @yuripritykin.bsky.social · 22d

Happy to share our new paper!

We present high-resolution Micro-C maps across Drosophila embryogenesis, integrated with 149 ChIP-seq datasets. This systematic analysis enabled clustering of loops & boundaries into 4 distinct classes with distinct regulatory roles.

www.cell.com/cell-genomic...

3D chromatin structures precede genome activation in Drosophila embryogenesis

Dolsten et al. map the 3D chromatin architecture across early Drosophila development using high-resolution Micro-C, and, by integrative analysis with 149 public ChIP-seq datasets, identify four classe...

www.cell.com

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Reposted by Yuri Pritykin

bioRxiv Immunology @biorxiv-immuno.bsky.social · 25d

Single-cell multiomics reveals archetypal regulatory programs shared across CD4 and CD8 T cell subsets in viral infection https://www.biorxiv.org/content/10.1101/2025.09.08.675014v1

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Yuri Pritykin @yuripritykin.bsky.social · Jul 23

Come talk to me at #ISMBECCB2025 this week if interested in this opportunity

Yuri Pritykin @yuripritykin.bsky.social · Jul 23

Comp bio postdoc positions available! Come work with us at Princeton University on computational method development and applications in regulatory genomics, genome editing, immunology and cancer, in mouse and human: pritykinlab.github.io#jobs
Please share among all those who may be interested!

Pritykin Lab

Pritykin Lab at the Lewis-Sigler Institute for Integrative Genomics and the Department of Computer Science at Princeton University.

pritykinlab.github.io

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Reposted by Yuri Pritykin

Ferhat Ay @ferhatay.bsky.social · Jul 21

After a long trip and a long sleep, i am ready to enjoy the rich scientific program at #ISMBECCB2025 in Liverpool. This is also the first year of our new COSI in Computational and System Immunology (CSI) happening on Tuesday. And of course looking forward RegSys, as usual with fantastic organizers

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Reposted by Yuri Pritykin

Ferhat Ay @ferhatay.bsky.social · Jul 21

For CSI COSI, I am very thankful to my co-chair Jishnu Das and steering committee @yuripritykin.bsky.social, Hatice Ulku Osmanbeyoglu, Aly Azeem Khan. And everyone who submitted their for consideration for this session www.iscb.org/ismbeccb2025...

CSI: Computational Systems Immunology

ISCB - International Society for Computational Biology

www.iscb.org

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Reposted by Yuri Pritykin

Yuri Pritykin @yuripritykin.bsky.social · Jul 8

A belated announcement about our GuideScan2 paper finally out in Genome Biology: doi.org/10.1186/s130...
GuideScan2 is a new flexible and efficient CRISPR gRNA design and analysis tool with command line and web interfaces. Please let us know what you think!

Genome-wide CRISPR guide RNA design and specificity analysis with GuideScan2 - Genome Biology

We present GuideScan2 for memory-efficient, parallelizable construction of high-specificity CRISPR guide RNA (gRNA) databases and user-friendly design and analysis of individual gRNAs and gRNA librari...

doi.org

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Yuri Pritykin @yuripritykin.bsky.social · Jul 8

Compared with the results from the preprint (x.com/YuriPritykin...), we added new analyses and experimental data, including comparisons with other methods, and new functionality. We will appreciate any feedback, bug reports and feature requests!

Yuri Pritykin on X: "Excited to present our new preprint "Genome-wide CRISPR guide RNA design and specificity analysis with GuideScan2": https://t.co/01Jufl5bVP" / X

Excited to present our new preprint "Genome-wide CRISPR guide RNA design and specificity analysis with GuideScan2": https://t.co/01Jufl5bVP

x.com

Yuri Pritykin @yuripritykin.bsky.social · Jul 8

This is an amazing computational work by
@henrismitch.bsky.social
and experiments by
@minsizhang.bsky.social , in collaboration with multiple great scientists.
GuideScan2 web interface for most of your needs: guidescan.com
Command line tool for advanced analysis:
github.com/pritykinlab/...

GuideScan2: CRISPR Guide Design

Web site created using create-react-app

guidescan.com

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