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Sample GSM1559510

Query DataSets for GSM1559510

Status

Public on Jul 20, 2015

Title

ChIP GFP C2C12-H3.2-D

Sample type

SRA

Source name

C2C12 cells_H3.2_Differentiated

Organism

Mus musculus

Characteristics

cell type: myoblast
cell line: C2C12
antibody: rat monoclonal antibody against GFP (1A5, 2 ug, Bio Academia)
culture status: differentiation (D)

Treatment protocol

Differentiated cells were transferred to DMEM containing 2% horse serum upon reaching confluence and harvested 48 h later.

Growth protocol

Cells were grown in Dulbecco's modified Eagle's medium (DMEM) supplemented with 20% fetal bovine serum. Undifferentiated cells were harvested at 60–70% confluence.

Extracted molecule

genomic DNA

Extraction protocol

Cultured cells were cross-linked in 0.5% formaldehyde and suspended in ChIP buffer (5 mM PIPES, 200 mM KCl, 1 mM CaCl2, 1.5 mM MgCl2, 5% sucrose, 0.5% NP-40, and protease inhibitor cocktail; Nacalai Tesque). Samples were sonicated for 5 s three times, and digested with micrococcal nuclease (1 ul; New England Biolabs, Ipswich, MA) at 37°C for 40 min. The digested samples were centrifuged at 15,000 × g for 10 min. Supernatant containing 4–8 ug DNA was incubated with a rat monoclonal antibody against GFP (1A5, 2 ug, Bio Academia) pre-bound to magnetic beads at 4°C overnight with rotation. The immune complexes were eluted from the beads using 1% SDS in TE, followed by washing with ChIP buffer and TE buffer (both twice). Cross-links were reversed, and DNA was purified using a Qiaquick PCR purification kit (Qiagen, Valencia, CA).
ChIP libraries were prepared for sequencing using standard Illumina protocols.

Library strategy

ChIP-Seq

Library source

genomic

Library selection

ChIP

Instrument model

Illumina HiSeq 1500

Description

Tet-On-C2C12 cells that harbor the N-terminal-GFP-tagged H3.2 gene under a doxycycline (Dox)-inducible promoter.

Data processing

Illumina RTA 1.17 software used for basecalling.
The sequence reads for GFP, and Input were aligned to the reference mouse genome (mm9, build 37) using Bowtie 2 software (version 2.2.2) (Langmead and Salzberg, 2012). PCR duplicates were removed from uniquely mapped reads using samtools (version 0.1.19).
We defined “ChIP-Seq signal intensity” as described below. First, mapped reads on the genome in a defined window size of 1,000 bp windows by 100 bp intervals; were counted and then normalized as RPKM (reads per kilobases per million reads) (Mortazavi et al., 2008). The ChIP-Seq signal intensities were then calculated as RPKM differences between ChIP and input DNA control data (i.e. ChIP – control) for each bin.
genome build: mm9
processed data files format and content: bigWig files of ChIP-Seq signal intensity (as described above)

Submission date

Dec 05, 2014

Last update date

May 15, 2019

Contact name

Yasuyuki Ohkawa

E-mail(s)

yohkawa@bioreg.kyushu-u.ac.jp

Organization name

Kyushu University

Department

Medical Institute of Bioregulation, Medical Institute of Bioregulation