Project description:To investigate the enrichment of SMARCA4-R1157W mutation on downstream target gene promoters, we performed CUT&Tag experiments in HCT116 cells.
Project description:HIF2A(EPAS1) geenome_wide localization by Cut & Tag in MRC5 human fibroblasts ectopically expressing HIF2A in the pBabe vector, and in control MRC5 human fibroblasts containing only the pBabe vector. 2 biological replicates were done for the MRC5-HIF2A cells. Cut & Tag with an anti-H3-K27me3 Ab was done as a positive control for the Cut & Tag experiments.
Project description:Cleavage Under Targets & Tagmentation (CUT&Tag) is a versatile method for measuring genomic occupancy of chromatin-associated proteins with high sensitivity and specificity. CUT&Tag has low sequencing requirements and is therefore suitable for highly multiplexed experiments, but methods to process samples at throughput without specialized equipment are lacking. Here we present a method for simultaneous parallel processing of 96 CUT&Tag samples in a standard microplate. Plate-CUT&Tag can be carried out in a similar time frame to benchtop CUT&Tag and yields data of comparable quality. We present data from cell culture and patient leukemia samples processed with Plate-CUT&Tag to illustrate its utility in large-scale preclinical and translational studies.
Project description:Precise profiling of epigenomes, including histone modifications and transcription factor binding sites, is essential for better understanding gene regulatory mechanisms. Cleavage Under Targets & Tagmentation (CUT&Tag) is an easy and low-cost epigenomic profiling method that can be performed on a low number of cells and at the single-cell level. A large number of CUT&Tag datasets have been generated in various biological systems, providing a valuable resource. CUT&Tag experiments use the hyperactive transposase Tn5 for tagmentation. We found that the preference of Tn5 captured reads toward accessible chromatin regions can influence the distribution of CUT&Tag reads and cause open chromatin biases, further confounding the analysis of CUT&Tag data. The high sparsity of single-cell sequencing data makes the open chromatin biases more substantial than in bulk sequencing data. Here, we present a comprehensive computational method, PATTY (Propensity Analyzer for Tn5 Transposase Yielded bias), to mitigate the open chromatin bias inherent in CUT&Tag data at both bulk and single-cell levels. By integrating existing transcriptome and epigenome data using machine learning and comprehensive modeling, we demonstrate that PATTY yields more accurate and robust detection of occupancy sites for both active and repressive histone marks than existing methods, with experimental validation. We further designed a single-cell CUT&Tag analysis framework by utilizing this model and showing improved cell clustering from bias-corrected single-cell CUT&Tag data compared to using raw data. This model paved the way for further development of computational tools for improving bulk and single-cell CUT&Tag data analysis.
Project description:CUT&Tag was performed to identify the effect of DIS3 depletion on DNA:RNA hybrids genome-wide. DIS3-AID HCT116 cells were treated with either Auxin (for rapid depletion of DIS3) or DMSO (control). CUT&Tag was performed targeting DNA:RNA hybrids using the CUT&Tag-IT® R-loop Assay Kit (Active Motive) with the S9.6 antibody.
Project description:CUT&Tag experiments were used to analyze DNA-binding of MYC protein in the vector or POH1-Flag expressed mouse pancreatic cancer cells.