Project description:These ATAC-seq data were generated to correlate with genomic interaction data in a related Hi-C analysis. Analysis of ATAC-seq data revealed series of overlapping or specific open chromatin peaks in ATRA treated and control cells. Those specific peaks showed fewer overlapping with gene promoters than the overlapping peaks. Key transcription factor for blood cell differentiation GATA2 was found only bind in control specific peaks.
Project description:Purpose: Assay for Transposase Accessible Chromatin with high-throughput sequencing (ATAC-seq) is a method for mapping chromatin accessibility genome-wide. The goals of this study are to investigate chromatin accessibility of C57BL/6J mice through ATAC-seq. Results: ATAC-seq reads were aligned to the UCSC mm10 reference genome with BWA-MEM. ATAC-seq peaks were called through MACS2 . Peaks were annotated and known transcription factor binding motifs were further analyzed in the ATAC-seq peaks by HOMER.
Project description:Purpose: Zinc Finger MIZ-Type Containing 1 (Zmiz1) is a member of the PIAS family of protein and function as a transcriptional coactivator of Notch, Androgen Receptor (AR), p53, Estrogen Receptor (ER), and Smad3/4 . Despite Zmiz1 critical role in angiogenesis, its role in lymphatic vasculature is unknown. Here, we use HDLECs cell line to profileepigenetic changes upon Zmiz1 knockdown using siRNA. Methods: ATAC sequencing library was prepared as per manufacturer instruction (Active Motif, 53150). Briefly, intact nuclei were isolated from control and Zmiz1 siRNA transfected HDLECs. Samples were treated with a hyperactive Tn5 transposase which tag the target DNA with sequencing adapters and fragment the DNA simultaneously. Library was then quantified using Qubit dsDNA High Sensitivity Assay Kit (Thermo Fisher Scientific, Q32851) and verified using the Bioanalyzer DNA High Sensitivity Assay Kit (Agilent, 5067-4626). Validated samples were sequenced using the NextSeq1000/2000 P2 Reagents (100 Cycles) v3 (Illumina, 20046811) on a Nextseq1000/2000. Resulting sequencing data were analyzed using basepairtech ATAC-Seq pipeline (www.basepairtech.com). Briefly, sequenced reads were aligned to the human (hg19) reference genome using Bowtie2. ATAC-Seq peaks and differentially accessible regions were quantified using MACS2 and DESeq2. Results: ATAC seq peaks analysis using MACS2 identified 576 peaks of which are mostly located in intergenic regions followed by introns. We found significantly reduced open chromatin near Prox1 loci upol loss of Zmiz1. Conclusions: We identify Zmiz1 regulates chromatin accessibility near Prox1 genomic loci in lymphatic endothelial cells
Project description:We have studied the impact of T2D on open chromatin in human pancreatic islets. We used assay for transposase-accessible chromatin using sequencing (ATAC-seq) to profile open chromatin in islets from T2D and non-diabetic donors. We identified ATAC-seq peaks representing open chromatin regions in islets of non-diabetic and diabetic donors. The majority of ATAC-seq peaks mapped near transcription start sites. Additionally, peaks were enriched in enhancer regions and in regions where islet-specific TFs bind. Islet ATAC-seq peaks overlap with SNPs associated with T2D and with additional SNPs in LD with known T2D SNPs. There was enrichment of open chromatin regions near highly expressed genes in human islets.
Project description:For ATAC-seq data processing, we used the ENCODE ATAC-seq pipeline (https://www.encodeproject.org/atac-seq/). In detail, for each sample, ATAC-seq reads were first checked for adaptor contamination. Then, adaptor trimmed reads were aligned to hg19 using Bowtie2 under paired-end mode with parameter “-X2000”, which permits 2000 bp for the maximum allowable insert size between two paired ends of each read. Using the ENCODE ATAC-seq pipeline, duplicated reads were properly filtered out. ATAC-seq enriched peaks were called using MACS2 (Zhang et al., 2008) based on remaining unique reads with parameters “-f BAMPE -q 0.05 --nomodel”. In total, we collected 45,569 peaks for the ARID1AWT sample and 27,480 peaks for the ARID1AKO sample.
Project description:ATAC-seq was performed for T-cell blasts for the following study groups: healthy controls (HC, n=6) and patients with AIOLOS E82K (n=6) and Q402X (n=1). ATAC-Seq was performed using the Active Motif ATAC-Seq Kit following the manufacturer’s protocol and sequenced using the Illumina NextSeq 2000 with 42-bp paired end reads. Using Basepair bioinformatics tools and pipelines (https://www.basepairtech.com/), reads were aligned using Bowtie2, and peaks were called with MACS2 and annotated using Homer. Differential testing, annotation, and visualization were performed using R (v.4.3.1) and the following Bioconductor R packages (https://bioconductor.org/): DESeq2 (v.1.40.2), DiffBind (v.3.10.1), ChIPQC (v.1.36.1), ChIPseeker (v.1.36.0), clusterProfiler (v.4.8.2), and goseq (v.1.52.0).
Project description:The "Assay for Transposase Accessible Chromatin sequencing" (ATAC-seq) is an efficient and easy to implement protocol to measure chromatin accessibility that has been widely used in multiple applications studying gene regulation. While several modifications or variants of the protocol have been published since it was first described, there has not yet been an extensive evaluation of the effects of specific protocol choices head-to-head in a consistent experimental setting. In this study, we tested multiple protocol options for major ATAC-seq components (including three reaction buffers, two reaction temperatures, two enzyme sources, and the use of either native or fixed nuclei) in a well-characterized cell line. In addition, the native conditions were tested in a primary sample type (mouse lung tissue) with two different input amounts. In general, native samples yielded more peaks (particularly at loci not overlapping transcription start sites) than fixed samples, and the temperature at which the enzymatic reaction was carried out had a major impact on data quality metrics for both fixed and native nuclei. However, the effect of various conditions tested was not always consistent between the native and fixed samples. For example, the Nextera and Omni buffers were largely interchangeable across all other conditions, while the THS buffer resulted in markedly different profiles in native samples. In-house and commercial enzymes performed similarly. We found that the relationship between commonly used measures of library quality differed across temperature and fixation, and so evaluating multiple metrics in assessing the quality of a sample is recommended. Notably, we also found that these choices can bias the functional class of elements profiled and so we recommend evaluating several formulations in any new experiments. Finally, we hope the ATAC-seq workflow formulated in this study on crosslinked samples will help to profile archival clinical specimens.
Project description:To understand the precise mechanism that guide the formation of multisubunit complexes is of key importance. Nascent proteins can find and bind their interaction partners during their translation, leading to co-translational assembly. Here we demonstrate that the distinct modules of ATAC (ADA Two A Containing) and SAGA (SPT ADA GCN5 Acetyltransferase), two lysine acetyl transferase-containing transcription coactivator complexes, assemble co-translationally in the cytoplasm of mammalian cells. Fully assembled SAGA complex forms in the cytoplasm of mammalian cells and cytoplasmic SAGA acetylates non-histones proteins, before imported in the nucleus. In contrast, ATAC has no cytoplasmic functions as it cannot be detected in the cytoplasm of mammalian cells. However, fully assembled endogenous ATAC complex containing two functional modules forms and functions in the nucleus. Thus, the two related co-activators, ATAC and SAGA, assemble by using co-translational pathways, but their subcellular localization, cytoplasmic detectability and functions are distinct.
Project description:We present ATAC-seq combined with direction RNA seq data for eight time points across the intraerythorcytic development cycle of Plasmodium falciparum 3D7. ATAC peaks were called by MACS2 using ATAC-seq libraries generated with genomic DNA as a control. The majority of identified ATAC peaks were located in intergenic regions and captured most (95%) of previously identified binding sites of the transcription factor required for the expression of most invasion-related genes PfAP2-I (Santos et al., 2017). The robustness of the ATAC-seq dataset was confirmed with a second biological replicate both in terms of peak location and relative peak accessibility pattern. Peaks were assigned to the closest gene and the majority of peaks showed a clear positive correlation between chromatin accessibility pattern and relative mRNA abundance (Pearson correlation > 0.6). In addition, they were sufficient to drive the stage-specific expression of a reporter gene, demonstrating their functionality. Motif searches restricted to accessible regions showed enrichment of several predicted Plasmodium motifs while also predicting several novel regulatory elements.