|
| Status |
Public on Nov 12, 2016 |
| Title |
Meth_Clone_4T1-P_Round_1 |
| Sample type |
SRA |
| |
|
| Source name |
4T1 Mammary Cancer Cell Line
|
| Organism |
Mus musculus |
| Characteristics |
clone: Clone-P (derived From Single Cell)
intravasating capacity: Non-Intravasating
|
| Growth protocol |
DMEM high glucose (Life Technologies) supplemented with 5% fetal bovine serum (Thermo Scientific), 5% fetal calf serum (Thermo Scientific), non-essential amino acids (Life Technologies) and penicillin streptomycin (Life Technologies)
|
| Extracted molecule |
genomic DNA |
| Extraction protocol |
Genomic DNA was purified using the QIAamp DNA Blood Mini Kit (Qiagen) and was fragmented using the Covaris LE220 sonicator according to the manufacturer’s instruction to yield a target fragment size of 300 bp.
The fragmented DNA was end repaired, A-tailored and ligated to methylated Illumina adapters. Ligated fragments were then bisulfite converted using the EZ-DNA Methylation-Gold Kit (Zymo).
Following PCR enrichment, each sample was sequenced on the Illumina HiSeq sequencer generating 76 nt paired-end (PE) reads.
|
| |
|
| Library strategy |
Bisulfite-Seq |
| Library source |
genomic |
| Library selection |
RANDOM |
| Instrument model |
Illumina HiSeq 2500 |
| |
|
| Description |
Bisulphate Converted genomic DNA
|
| Data processing |
1) Data was processed with Methpipe pipeline to calculate the methylation levels at each CpG and to call hypomethylated regions (Song, Q. et al. A reference methylome database and analysis pipeline to facilitate integrative and comparative epigenomics. PloS one 8, e81148, doi:10.1371/journal.pone.0081148 (2013)).
2) For clustering, the hypomethylated regions of different clones were collapsed together into a consensus set using the Bedtools intersectBed function (merging when a single base of overlap existed).
3) Reads were normalized across samples using DESeq (bioconductor)
4) For each clone, the average methylation levels of the CpGs within the consensus regions were calculated. The median absolute deviations (MAD) of the resultant methylation levels were then used to identify the top 10% most variable for clustering.
5) Promoter methylation levels were calculated as the average CpG methylation level within 1kbp of the transcription start site of each gene. The top 10% most variable promoter regions (based on MAD) were clustered.
Genome_build: mm10
Supplementary_files_format_and_content: HMR_Methylation.txt: field 1 is the chromosome location of the HMR, field 2 is the start position of the HMR, field 3 is the end position of the HMR. All other fields represent the average methylation levels of the different clones within the HMR region. Clones are annotated in the header.
Supplementary_files_format_and_content: Promoter_Methylation.txt: field 1 is the RefSeq gene symbol of the promoter. All other fields represent the average methylation levels of the different clones within the gene promoter region. Clones are annotated in the header.
|
| |
|
| Submission date |
Nov 11, 2014 |
| Last update date |
May 15, 2019 |
| Contact name |
Simon Robert Vincent Knott |
| Organization name |
Cold Spring Harbor Laboratory
|
| Department |
Biology
|
| Lab |
Hannon
|
| Street address |
1 Bungtown Rd
|
| City |
Cold Spring Harbor |
| State/province |
NY |
| ZIP/Postal code |
11724 |
| Country |
USA |
| |
|
| Platform ID |
GPL17021 |
| Series (1) |
| GSE63181 |
DNA methylation status of Individual 4T1 Clonal Populations |
|
| Relations |
| BioSample |
SAMN03175114 |
| SRA |
SRX757475 |
