Live-cell imaging of circadian clock protein dynamics in CRISPR-generated knock-in cells.
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ABSTRACT:
SUBMITTER: Gabriel CH
PROVIDER: S-EPMC8213786 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Purpose: Alteration in light dark cycle leads to changes in daily behavior in mammals. We have previously demonstrated that different light:dark cycle lengths result in dynamic changes in DNA methylation within the suprachiasmatic nuclei (SCN) that globally alter transcription of both clock genes and non-clock genes. The goal of this study was to re-examine DNA methylation in the SCN separately for dorsal and ventral regions. Method: Six-week-old wild-type mice (C57BL/6Cr1) were entrained to light:dark cycles either 22, 24, or 26 hours in length (T22, T24, or T26) for six weeks. After 6 weeks, we recorded wheel-running behavior in constant darkness. After 3 days in DD, we used Clocklab software to predict time of activity onset for each mouse. Brains were isolated at the circadian time CT4 and then sliced immediately using vibratome, one coronal SCN slice of ~250μM was collected from the middle part of the SCN. Using ophthalmic knife vSCN and dSCN sub-regions were separated. To get enough DNA, a pool of vSCN and dSCN was prepared twice from 5 mice from each T-cycle. Genomic DNA was extracted from SCN slices by overnight Proteinase K digestion, followed by phenol-chloroform and ethanol precipitation. After RNase treatment, genomic DNA was sonicated to generate small fragments (average of 300bp), using a Covaris sonicator (BioRuptor). DNA immunoprecipitation was performed using Epiquik™ MeDIP Ultra Kit (EPIGENTEK™), following manufacturer's instructions. The methylated enriched DNA was then used for library preparation using Accel-NGS™ DNA Library Kits (Swift Biosciences), following manufacturer's instructions. Quality check, library preparation and sequencing were performed by Fasteris (CH). Results: 13-21 x 10^6 reads were obtained from each meDIP library. Quality control was performed on the fasta raw sequence data using FastQC.MeDIP-seq data were aligned to the mm9 mouse genome build using the Burrows-Wheeler Alignment tool (BWA) (Li and Durbin, 2009). Mapped reads were than analyzed using the MEDIPS package (Lienhard et al., 2014). Methylation score was calculated for each region of 500bp across the genome. CpG density-dependent normalization was incorporated. Pairwise correlation analysis of the genome wide coverage profile between MEDIP replicate samples was performed using the MEDIPS.correlation function. Pearson correlation coefficient r varied between 0.85 and 0.92, indicating good reproducibility of MEDIP-seq signal. Differential methylation analysis was performed using MEDIPS in 500bp widows excluding regions with less than 8 unique mapped reads. DMR were than identified by filtering for a widows associated with a p ≤0.001. DMR were than mapped using the web based chip-seq tool “ChIPseek” (Chen et al., 2014). Different sets of genes showed methylation changes in dorsal vs. ventral regions. Interestingly, far greater changes were observed in vSCN than in dSCN.
2016-10-28 | GSE89255 | GEO