Project description:This dataset consists of in situ HiC-seq data from human monocytes, monocyte-derived dendritic cells as well as monocyte-derived cells that were subjected to siRNA treatment targeting CTCF or RAD21. In total, the data set includes 42 samples.
Project description:CTCF is an organizer of higher-order chromatin structure, and regulates gene expression. Genetic studies have implicated mutations in CTCF in intellectual disabilities. However, there is no knowledge of the role of CTCF-mediated chromatin structure in learning and memory. We show that depletion of CTCF in postmitotic neurons, or depletion in the hippocampus of adult mice through viral-mediated knockout, induces deficits in learning and memory. These deficits in learning and memory at the beginning of adulthood are correlated with impaired long term potentiation and reduced spine density, with no changes in basal synaptic transmission and dendritic morphogenesis and arborization. Cognitive disabilities are associated with downregulation of cadherin and learning-related genes. In addition, CTCF knockdown attenuates fear conditioning-induced hippocampal gene expression of key learning genes and loss of long-range interactions at the BDNF and Arc loci. This study identifies CTCF-dependent gene expression regulation and DNA structure as regulators of learning and memory.
Project description:CTCF is a highly conserved and ubiquitously expressed protein involved in several fundamental processes such as fine-tuning gene expression, imprinting, X-chromosome inactivation and 3D chromatin organisation. To understand the impact of differences in the concentration of CTCF abundance on these processes, we exploit a CTCF hemizygous mouse model with a stable reduction in the concentration of this protein. We derived twelve independent primary lines of mouse embryonic fibroblasts (MEFs) from six wildtype and six CTCF-hemizygous mouse E13.5 embryos. Total RNA from each MEF line was purified using QIAzol Lysis Reagent (Qiagen); DNase treatment and removal was performed using the TURBO DNA-freeTM Kit (Ambion, Life Technologies). Libraries were prepared using the TruSeq Stranded Total RNA Library Prep Kit with Ribo-Zero Gold (Illumina) and sequenced in an Illumna HiSeq4000 to produce 150bp paired-end reads. On the same MEF lines we have performed ChIPseq for CTCF, H3K4me3 and H3K27ac and HiC.
Project description:The transcription factor CTCF appears indispensable in defining topologically associated domain boundaries and maintaining chromatin loop structures within these domains, supported by numerous functional studies. However, acute depletion of CTCF globally reduces chromatin interactions but does not significantly alter transcription. Here we systematically integrated multi-omics data including ATAC-seq, RNA-seq, WGBS, Hi-C, Cut&Run, CRISPR-Cas9 survival dropout screening, time-solved deep proteomic and phosphoproteomic analyses in cells carrying auxin-induced degron at endogenous CTCF locus. Acute CTCF protein degradation markedly rewired genome-wide chromatin accessibility. Increased accessible chromatin regions were largely located adjacent to CTCF-binding sites at promoter regions and insulator sites and were associated with enhanced transcription of nearby genes. In addition, we used CTCF-associated multi-omics data to establish a combinatorial data analysis pipeline to discover CTCF co-regulatory partners in regulating downstream gene expression. We successfully identified 40 candidates, including multiple established partners (i.e., MYC) supported by all layers of evidence. Interestingly, many CTCF co-regulators (e.g., YY1, ZBTB7A) that have evident alterations of respective downstream gene expression do not show changes at their expression levels across the multi-omics measurements upon acute CTCF loss, highlighting the strength of our system to discover hidden co-regulatory partners associated with CTCF-mediated transcription. This study highlights CTCF loss rewires genome-wide chromatin accessibility, which plays a critical role in transcriptional regulation
Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare NGS-derived liver transcriptome profiling (RNA-seq) to microarray and quantitative reverse transcription polymerase chain reaction (qRT–PCR) methods and to evaluate protocols for optimal high-throughput data analysis Methods: Liver mRNA profiles of 8-week-old wild-type (WT) and liver specific conditional CTCF KO (CTCF cKO) mice were generated by deep sequencing, in quadruplet, using Illumina GAIIx. The sequence reads that passed quality filters were analyzed at the transcript isoform level with two methods: Burrows–Wheeler Aligner (BWA) followed by ANOVA (ANOVA) and TopHat followed by Cufflinks. qRT–PCR validation was performed using TaqMan and SYBR Green assays Results: Using an optimized data analysis workflow, we mapped about 30 million sequence reads per sample to the mouse genome (build mm9) and identified 16,014 transcripts in the retinas of WT and Nrl−/− mice with BWA workflow and 34,115 transcripts with TopHat workflow. RNA-seq data confirmed stable expression of 25 known housekeeping genes, and 12 of these were validated with qRT–PCR. RNA-seq data had a linear relationship with qRT–PCR for more than four orders of magnitude and a goodness of fit (R2) of 0.8798. Approximately 10% of the transcripts showed differential expression between the WT and Nrl−/− retina, with a fold change ≥1.5 and p value <0.05. Altered expression of 25 genes was confirmed with qRT–PCR, demonstrating the high degree of sensitivity of the RNA-seq method. Hierarchical clustering of differentially expressed genes uncovered several as yet uncharacterized genes that may contribute to retinal function. Data analysis with BWA and TopHat workflows revealed a significant overlap yet provided complementary insights in transcriptome profiling. Conclusions: Our study represents the first detailed analysis of retinal transcriptomes, with biologic replicates, generated by RNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles. Our results show that NGS offers a comprehensive and more accurate quantitative and qualitative evaluation of mRNA content within a cell or tissue. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions.
Project description:CTCF is a highly conserved and ubiquitously expressed protein involved in several fundamental processes such as fine-tuning gene expression, imprinting, X-chromosome inactivation and 3D chromatin organisation. To understand the impact of differences in the concentration of CTCF abundance on these processes, we exploit a CTCF hemizygous mouse model with a stable reduction in the concentration of this protein. We derived independent primary lines of mouse embryonic fibroblasts (MEFs) from wildtype and CTCF-hemizygous mouse E13.5 embryos. For three biological replicates, cells were fixed in DMEM containing 2% fresh formaldehyde and incubated at room temperature for 10 min, quenched with 1M glycine for 5 min, and washed twice with ice cold PBS, before being flash-frozen at -80°C. Cross-linked cells were lysed, followed by chromatin HindIII digestion, biotinylataion, ligation, proteinase K treatment, DNA purification, sonication, end repair, biotin pull-down, adapter ligation, and PCR amplification. Pooled indexed libraries were sequenced on an Illumina HiSeq4000 to produce paired-end 150bp reads. On the same MEF lines we have performed RNAseq and ChIPseq for CTCF, H3K4me3 and H3K27ac.