Deconvoluting global cytokine signaling networks in natural killer cells [ATAC-Seq]

UID: 10808

Author(s): Lau, Colleen M.*, Sun, Joseph C.* * MSK affiliated

Description: Summary from the GEO: "Cytokine signaling via signal transducer and activator of transcription (STAT) proteins is crucial for optimal antiviral responses of natural killer (NK) cells. However, the pleiotropic effects of both cytokine and STAT signaling preclude the ability to precisely attribute molecular changes to either source. In this study, we employ a multi-“omics” approach to deconstruct and rebuild the complex interaction of three major STAT signaling pathways in NK cells. We uncover a global STAT4-STAT5 cooperative axis that is distinct and sometimes antagonistic to the STAT1 axis. We generate a network of STAT targets that highlights an integrated negative feedback loop, and demonstrate distinct STAT modes of epigenetic regulation. Finally, we identify shared signatures between mouse in vitro profiles and profiles from viral infection and humans, highlighting clinically translatable targets. Overall, we begin to unravel the intricate crosstalk between cytokine signaling pathways, and offer a valuable resource for improving cellular immunotherapy."

Overall design from the GEO: "ATAC-seq was performed on ex-vivo NK cells stimulated with various cytokine combinations."

Subject of Study

Subject(s)

Access via GEO
BED and BIGWIG files of genome binding/occupancy profiling by high throughput sequencing
Accession #: GSE140033

Access via SRA
ATAC Sequencing of 22 samples
Accession #: SRP228806

Access via BioProject
Additional information about the overall inititative.
Accession #: PRJNA588063
Access Restrictions: Free to All
Access Instructions: The NCBI Gene Expression Omnibus, SRA, and BioProject databases provide open access to these files. The SRA Run Selector link at the bottom of the page is a processing tool for raw data.
Associated Publications: Wiedemann G, Santosa E, Grassmann S, et al. Deconvoluting global cytokine signaling networks in natural killer cells. Nature Immunology. 2021; 22(5):627-638.
Data Type: Genomic
Equipment Used: Illumina HiSeq 4000
High throughput gene sequencing system
Software Used: SRA Toolkit
The NCBI SRA Toolkit enables reading ("dumping") of sequencing files from the SRA database and writing ("loading") files into the .sra format.
Dataset Format(s): SRA, TAR, BED, BIGWIG
Data Tool(s): ATAC Seq
Dataset Size: 7.7 Gb (TAR of BW), 430.8 Kb (BED), 27.8 Gb (SRA)

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