Project description:Sirt6, the NAD+-dependent deacetylase, has been described to deacetylate H3K9, H3K18, and H3K56. However, analysis of the acetylation status revealed that loss of Sirt6 caused a massive increase of histone H3K56ac levels but no detectable change of histone H3K9ac and H3K18ac, indicating that SIRT6 is the dominant deacetylase for H3K56ac in muscle stem cells (MuSCs). Further, we investigate genome-wide H3K56ac profiling in the absence of Sirt6 in MuSCs and mouse embryonic stem cells (mESCs) using high throughput sequencing (ChIP-seq).
Project description:Changes in cellular chromatin states fine-tune transcriptional output and ultimately lead to phenotypic changes. Here we propose a novel application of our reproducibility-optimized test statistics (ROTS) to detect differential chromatin states (ATAC-seq) or differential chromatin modification states (ChIP-seq) between conditions. We compare the performance of ROTS to existing and widely used methods for ATAC-seq and ChIP-seq data using both synthetic and real datasets. Our results show that ROTS outperformed other commonly used methods when analyzing ATAC-seq data. ROTS also displayed the most accurate detection of small differences when modeling with synthetic data. We observed that two-step methods that require the use of a separate peak caller often more accurately called enrichment borders, whereas one-step methods without a separate peak calling step were more versatile in calling sub-peaks. The top ranked differential regions detected by the methods had marked correlation with transcriptional differences of the closest genes. Overall, our study provides evidence that ROTS is a useful addition to the available differential peak detection methods to study chromatin and performs especially well when applied to study differential chromatin states in ATAC-seq data.
Project description:Activation of regulatory elements is thought to be inversely correlated with DNA methylation levels. However, it is difficult to determine whether DNA methylation is compatible with chromatin accessibility or transcription factor (TF) binding if assays are performed separately. We developed a fast, low-input, low sequencing depth method, EpiMethylTag, that combines ATAC-seq or ChIP-seq (M-ATAC or M-ChIP) with bisulfite conversion, to simultaneously examine accessibility/TF binding and methylation on the same DNA. Here we demonstrate that EpiMethylTag can be used to study the functional interplay between chromatin accessibility and TF binding (CTCF and KLF4) at methylated sites.
Project description:ChIP-Atlas (https://chip-atlas.org) is a web service providing both GUI- and API-based data-mining tools to reveal the architecture of the transcription regulatory landscape. ChIP-Atlas is powered by comprehensively integrating all data sets from high-throughput ChIP-seq and DNase-seq, a method for profiling chromatin regions accessible to DNase. In this update, we further collected all the ATAC-seq and whole-genome bisulfite-seq data for six model organisms (human, mouse, rat, fruit fly, nematode, and budding yeast) with the latest genome assemblies. These together with ChIP-seq data can be visualized with the Peak Browser tool and a genome browser to explore the epigenomic landscape of a query genomic locus, such as its chromatin accessibility, DNA methylation status, and protein-genome interactions. This epigenomic landscape can also be characterized for multiple genes and genomic loci by querying with the Enrichment Analysis tool, which, for example, revealed that inflammatory bowel disease-associated SNPs are the most significantly hypo-methylated in neutrophils. Therefore, ChIP-Atlas provides a panoramic view of the whole epigenomic landscape. All datasets are free to download via either a simple button on the web page or an API.
Project description:We present a modified approach of chromatin immuno-precipitation followed by sequencing (ChIP-Seq), which relies on the direct ligation of molecular barcodes to chromatin fragments, thereby permitting experimental scale-up. With Bar-ChIP now enabling the concurrent profiling of multiple DNA-protein interactions, we report the simultaneous generation of 90 ChIP-Seq datasets without any robotic instrumentation. We demonstrate that application of Bar-ChIP to a panel of Saccharomyces cerevisiae chromatin-associated mutants provides a rapid and accurate genome-wide overview of their chromatin status. Additionally, we validate the utility of this technology to derive novel biological insights by identifying a role for the Rpd3S complex in maintaining H3K14 hypo-acetylation in gene bodies. We also report an association between the presence of intragenic H3K4 tri-methylation and the emergence of cryptic transcription in a Set2 mutant. Finally, we uncover a crosstalk between H3K14 acetylation and H3K4 methylation in this mutant. These results show that Bar-ChIP enables biological discovery through rapid chromatin profiling at single-nucleosome resolution for various conditions and protein modifications at once.
