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Sample GSM1817679

Query DataSets for GSM1817679

Status

Public on Jul 23, 2015

Title

K562_RNA_Seq

Sample type

SRA

Source name

Human chronic myelogenous leukemia; lymphoblastoid cells.

Organism

Homo sapiens

Characteristics

cell line: K562

Treatment protocol

For ChIP-seq 100 million of asynchronously growing cells were crosslinked with 1% formaldehyde for 10 min at room temperature, followed by quenching with 125 mM glycine for 10 min, washed twice with 1x PBS, and resuspended in ChIP lysis buffer (150 mM NaCl, 1% Triton X‐100, 0.1% SDS, 20 mM Tris–HCl pH8.0, 2 mM EDTA). Chromatin was sheared to an average length of 200–500 bp using a Bioruptor sonication.

Growth protocol

K562, Delta47, Ovcar8, NHDF and MCF7 cell lines were grown in DMEM supplemented with 10% FCS and penicillin-streptomycin.

Extracted molecule

total RNA

Extraction protocol

After overnight incubation with DiaMag magnetic beads (Diagenode, Inc.) and CTCF or BORIS monoclonal or polyclonal antibodies (characterized and described by PMID:15731119; PMID: 21659515; PMID:20231363), precipitated chromatin was then washed, decrosslinked, and digested with proteinase K. The resulting DNA was purified using phenol/chloroform/isoamyl alcohol. DNA concentration was assessed with Quant‐it PicoGreen dsDNA kit (Invitrogen) and 5–10 ng was used to generate sequencing libraries.
TruSeq ChIP Sample Preparation Kit (Illumina, Inc., USA). RNA-seq libraries were prepared using either Ion Total RNA-seq v2 kit or TruSeq Stranded RNA LT Kit (Illumina).

Library strategy

RNA-Seq

Library source

transcriptomic

Library selection

cDNA

Instrument model

Ion Torrent PGM

Description

Processed data for this sample is included in the file RNA_Seq_WT_K562_VS_BORIS_KO_Clone7.txt.gz available on the sample page for GSM1817680.

Data processing

Sequences generated by the Illumina genome analyzer (36bp and 50bp reads) were aligned against either human (build hg19) or mouse (build mm9) genome using Bowtie program (http://bowtie-bio.sourceforge.net). The alignment was performed with default parameters except the sequence tags that mapped to more than one location in the genome were excluded from the analysis using –m1 option.
Peaks were called using Model-based Analysis for ChIP-Seq (MACS) (http://liulab.dfci.harvard.edu/MACS) using default parameters. After MACS, we applied Peak Splitter algorithm (part of MACS) to call sub-peaks, summit of peaks and improve peak resolution.
For the Illumina RNA-seq library, fastq.gz files were mapped to UCSC Human reference (build hg19) using TopHat2 with the default parameter setting of 20 alignments per read and up to 2 mismatches per alignment.
For Ion Torrent RNA-seq sequencing, fastq.gz files were mapped to UCSC Human reference (build hg19) using two-step alignments. First, the reads were aligned with TopHat2. Second, the unmapped reads from the first step are then extracted and aligned with Bowtie2 with –local mode and --very-sensitive-local option.
For both Illumina and Ion Torrent RNA-seq, the resulting aligned reads (BAM files) were then analyzed with Cufflinks 2.0.0 to estimate the transcripts relative abundance using the UCSC reference annotated transcripts (build hg19). The expression of each transcript was quantified as the number of reads mapping to a transcript divided by the transcript length in kilobases and the total number of mapped reads in millions (FPKM).
Genome_build: hg19, mm9
Supplementary_files_format_and_content: Cuffdiff output.

Submission date

Jul 10, 2015

Last update date

May 15, 2019

Contact name

Elena Pugacheva

E-mail(s)

epugacheva@niaid.nih.gov

Phone

2407377366

Organization name

NIH