 |
 |
GEO help: Mouse over screen elements for information. |
|
| Status |
Public on Jul 08, 2020 |
| Title |
FoxO1 ChIP-Seq Iso |
| Sample type |
SRA |
| |
|
| Source name |
Heart Tissue
|
| Organism |
Mus musculus |
| Characteristics |
tissue: heart
genotype: Wild Type
surgical procedure: Hypertrophied Heart: 12 wk old, male mice were subjected to subcutaneous isoproterenol injections (3 mg/kg/day) for 7 days
days post surgery: 7
strain: C57BL/6
antibody: Anti-FoxO1 (Santa Cruz Biotechnology- sc-11350)
Sex: male
|
| Treatment protocol |
12 wk old, wild type C57BL/6 male mice were subjected to vehicle injection/sham operation, isoproterenol injection (subcutaneous, 3 mg/kg/day), or transverse aortic constriction (TAC) surgery for 7 days.
|
| Extracted molecule |
genomic DNA |
| Extraction protocol |
After 7 days, hearts were removed, snap frozen, and shipped to Active Motif (a pool of 3 hearts per condition).
Libraries were constructed by Active Motif (https://www.activemotif.com/).
|
| |
|
| Library strategy |
ChIP-Seq |
| Library source |
genomic |
| Library selection |
ChIP |
| Instrument model |
Illumina NextSeq 500 |
| |
|
| Description |
Includes Drosophila chromatin spike-in
|
| Data processing |
sequence analysis: The 75-nt sequence reads generated by Illumina sequencing (using NextSeq 500) are mapped to the genome using the BWA algorithm with default settings. Alignment information for each read is stored in the BAM format. Only reads that pass Illumina’s purity filter, align with no more than 2 mismatches, and map uniquely to the genome are used in the subsequent analysis. In addition, unless stated otherwise, duplicate reads (“PCR duplicates”) are removed.
determination of fragment density: Since the 5´-ends of the aligned reads (= “tags”) represent the end of ChIP/IP-fragments, the tags are extended in silico (using Active Motif software) at their 3´- ends to a length of 150-250 bp, depending on the average fragment length in the size selected library (normally 200 bp). To identify the density of fragments (extended tags) along the genome, the genome is divided into 32-nt bins and the number of fragments in each bin is determined. This information (“signal map”; histogram of fragment densities) is stored in a bigWig file, which can be visualized in genome browsers (see Section V.). bigWig files also provide the peak metrics in the Active Motif analysis program described below.
peak finding: The generic term “Interval” is used to describe genomic regions with local enrichments in tag numbers. Intervals are defined by the chromosome number and a start and end coordinate. The two main peak callers used at Active Motif are MACS (Zhang et al., Genome Biology 2008, 9:R137) and SICER (Zang et al., Bioinformatics 25, 1952-1958, 2009). MACS is suitable to identify the binding sites of transcription factors that bind to discrete sites (often containing a consensus DNA sequence) as well as many active histone marks and methyl-C enriched regions, while SICER is used to study proteins that bind to extended regions in the genome (such as repressive histone marks or RNA polymerase II). Both methods look for significant enrichments in the ChIP/IP data file when compared to the Input data file (~ random background).
Spike-in Adjustment: The number of test tags are adjusted (again by down-sampling) by a factor that would result in the same number of spikein Drosophila tags for each sample. Spike-in adjustment can be useful for rare assays where standard normalization does not result in the expected global differences in enrichments between test samples.
merged region analysis: To compare peak metrics between 2 or more samples, overlapping Intervals are grouped into “Merged Regions”, which are defined by the start coordinate of the most upstream Interval and the end coordinate of the most downstream Interval (= union of overlapping Intervals; “merged peaks”). In locations where only one sample has an Interval, this Interval defines the Merged Region. The use of Merged Regions is necessary because the locations and lengths of Intervals are rarely exactly the same when comparing different samples.
annotation: After defining the Intervals and Merged Regions, their genomic locations along with their proximities to gene annotations and other genomic features are determined and presented in Excel spreadsheets. In addition, average and peak (i.e. at “summit”) fragment densities within Intervals and Merged Regions are compiled.
Genome_build: mm10
Supplementary_files_format_and_content: bigWig files show peak shapes in the form of a signal histogram and can be visualized in the UCSC browser
Supplementary_files_format_and_content: Excel files show Merged Regions, which are genomic regions containing 1 or multiple overlapping intervals
|
| |
|
| Submission date |
Jan 21, 2020 |
| Last update date |
Jul 08, 2020 |
| Contact name |
Jessica Pfleger |
| E-mail(s) |
jessica.pfleger@temple.edu
|
| Organization name |
Temple University
|
| Street address |
3500 North Broad Street
|
| City |
Philadelphia |
| State/province |
PA |
| ZIP/Postal code |
19140 |
| Country |
USA |
| |
|
| Platform ID |
GPL19057 |
| Series (1) |
| GSE144011 |
FoxO1 Binding in Cardiac Hypertrophy |
|
| Relations |
| BioSample |
SAMN13896387 |
| SRA |
SRX7586624 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSM4278012_3_0430_00HGTemple_Isoprot_FOXO1_mm10_i93_dmnorm_signal.bw |
92.9 Mb |
(ftp)(http) |
BW |
SRA Run Selector |
| Raw data are available in SRA |
| Processed data provided as supplementary file |
| Processed data are available on Series record |
|
|
|
|
 |
