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Genome graphs detect human polymorphisms in active epigenomic state during influenza infection [ChIP-seq]

ABSTRACT: Genome graphs detect human polymorphisms in active epigenomic state during influenza infection [ChIP-seq]

PROVIDER: PRJNA937199 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR23566219_1.fastq.gz	Fastqsanger.gz
	SRR23566219_2.fastq.gz	Fastqsanger.gz
	SRR23566220_1.fastq.gz	Fastqsanger.gz
	SRR23566220_2.fastq.gz	Fastqsanger.gz
	SRR23566221_1.fastq.gz	Fastqsanger.gz

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Genome graphs detect human polymorphisms in active epigenomic state during influenza infection

Project description:Genome graphs detect human polymorphisms in active epigenomic state during influenza infection

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Genome graphs detect human polymorphisms in active epigenomic state during influenza infection [ATAC-seq]

Project description:Genome graphs detect human polymorphisms in active epigenomic state during influenza infection [ATAC-seq]

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Genome graphs detect human polymorphisms in active epigenomic state during influenza infection [ChIP-seq]

Project description:Genetic variants, including mobile element insertions (MEIs), are known to impact the epigenome. We hypothesized that the use of a genome graph, which encapsulates genetic diversity, could reveal missing epigenomic signal. We tested this in a dataset obtained by sequencing the epigenome of monocyte-derived macrophages from 35 ancestrally diverse individuals before and after Influenza virus infection, which also allowed us to investigate the potential role of MEIs in immunity. After characterizing genetic variants in this cohort using linked-reads, including 5140 Alu, 316 L1, 94 SVAs and 48 ERVs, we incorporated them into a genome graph. Mapping epigenetic data to this graph revealed 2.5%, 3.0% and 2.3% novel peaks for H3K4me1 and H3K27ac ChIP-seq and ATAC-seq respectively. Notably, using a genome graph also modified quantitative trait loci estimates and we observed 375 polymorphic MEIs in active epigenomic state. For example, we found an AluYh3 polymorphism whose chromatin state changed after infection and that was associated with the expression of TRIM25, a gene that restricts influenza RNA synthesis. Our results demonstrate that graph genomes can reveal regulatory regions that would have been overlooked by other approaches.

2023-02-21 | GSE225706 | GEO

Genome graphs detect human polymorphisms in active epigenomic state during influenza infection [ATAC-seq]

2023-02-21 | GSE225704 | GEO

Genome graphs detect human polymorphisms in active epigenomic state during influenza infection.

Project description:Genetic variants, including mobile element insertions (MEIs), are known to impact the epigenome. We hypothesized that genome graphs, which encapsulate genetic diversity, could reveal missing epigenomic signals. To test this, we sequenced the epigenome of monocyte-derived macrophages from 35 ancestrally diverse individuals before and after influenza infection, allowing us to investigate the role of MEIs in immunity. We characterized genetic variants and MEIs using linked reads and built a genome graph. Mapping epigenetic data revealed 2.3%-3% novel peaks for H3K4me1, H3K27ac chromatin immunoprecipitation sequencing (ChIP-seq), and ATAC-seq. Additionally, the use of a genome graph modified some quantitative trait loci estimates and revealed 375 polymorphic MEIs in an active epigenomic state. Among these is an AluYh3 polymorphism whose chromatin state changed after infection and was associated with the expression of TRIM25, a gene that restricts influenza RNA synthesis. Our results demonstrate that graph genomes can reveal regulatory regions that would have been overlooked by other approaches.

| S-EPMC10203048 | biostudies-literature

Genome graphs detect human polymorphisms in active epigenomic state during influenza infection

Project description:This SuperSeries is composed of the SubSeries listed below.

2023-02-21 | GSE225708 | GEO

Detect-seq on transfected HEK293T cells [Detect-seq data]

Project description:Detect-seq on transfected HEK293T cells [Detect-seq data]

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Sox9 directs divergent epigenomic states in brain tumor subtypes

Project description:Epigenetic dysregulation is a universal feature of cancer that results in altered patterns of gene expression that drive malignancy. Brain tumors exhibit subtype-specific epigenetic alterations, however the molecular mechanisms responsible for these diverse epigenetic states remain unclear. Here we show that the developmental transcription factor Sox9 differentially regulates epigenomic states in high-grade glioma (HGG) and ependymoma (EPN). These contrasting roles for Sox9 correspond with protein interactions with histone deacetylating complexes in HGG, and association with the Rela oncofusion in EPN. Together, our studies demonstrate how epigenomic states are differentially regulated in distinct subtypes of brain tumors, while revealing divergent roles for Sox9 in HGG and EPN tumorigenesis.

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Epigenomic tomography for probing spatially-defined chromatin state in the brain

Project description:Here we demonstrate brain epigenomic tomography that is constructed via epigenomic profiling of mouse neocortex slices with sub-millimeter thickness using a low-input ChIP-seq technology. We profiled the variation in histone modification signal (H3K27me3 and H3K27ac) across these slices and grouped the spatial epigenomic features into clusters of various spatial variation patterns.

2023-10-18 | GSE215972 | GEO

Detect-seq on transfected HEK293T cells [Detect-seq data]

Project description:We used a new technology, named Detect-seq, to perform genome sequencing on transfected HEK293T cells to see DdCBEs' off-target mutations. Besides, targeted-amplicon sequencing and ATAC-seq data were applied to validate the results of Detect-seq.

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