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Sample GSM1696048

Query DataSets for GSM1696048

Status

Public on Jun 19, 2015

Title

shSmarca4_RNAseq, replicate 2

Sample type

SRA

Source name

immortalized fibroblast

Organism

Mus musculus

Characteristics

strain: CAST/Ei x 129/Sv/Jae
cell type: Xi GFP tail-tip fibroblast
genetic manipulation: Stable shRNA knockdown of Smarca4

Treatment protocol

Cells were treated with 0.3 uM azacytidine and 0.3 uM etoposide for 3 days

Growth protocol

Cells were cultured in regular fibroblast medium (1% Pen/Strep, high-glucose DMEM+GlutaMAX) with 10% FBS

Extracted molecule

total RNA

Extraction protocol

ChIP-seq: Cells were crosslinked with 1% formaldeyde for 10 min, then nuclei were isolated and lysed. Chromatin was sheared by sonication to a size of ~200-400 bp. Cleared lysates were precleared for 1 hour, then 10% saved as input, and lysates were incubated with Dynabeads Protein G pre-bound with the antibody of choice. After stringent washes, ChIP DNA was eluted from beads, and together with input chromtain was reverse-crosslinked with proteinase K. DNA was purified by phenol/chloroform extraction and ethanol precipitation. Hi-C: Hi-C experiments were conducted using HindIII according to the method described in Lieberman-Aiden, E. et al. Comprehensive mapping of long-range interactions reveals folding principles of the human genome. Science 326, 289-93 (2009). RNA-seq: Xi-TgGFP TTFs (68-5-11) with the stable knock down of candidates were treated with 5’-azacytidine and etoposide at 0.3 uM each for 3 days. Strand specific RNA-seq, the library preparation, deep sequencing, and data analysis was followed as described in J. T. Kung et al., Locus-specific targeting to the X chromosome revealed by the RNA interactome of CTCF. Molecular cell 57, 361-375 (2015). All libraries were sequenced with Illumina Hiseq 2000 or 2500 using 50 cycles to obtain paired end reads.
ChIP-seq: Libraries were constructed using the NEBNext ChIP-seq Library Preparation Kit with no modifications to the protocol. We used 16 cycles during the PCR step. Hi-C: Sequencing libraries were constructed according to the method described in Lieberman-Aiden, E. et al. Comprehensive mapping of long-range interactions reveals folding principles of the human genome. Science 326, 289-93 (2009). RNA-seq: Total RNA was harvested using trizol extraction, and ribosomal RNA was removed using RiboMinus. Strand-specific libraries were generated by performing reverse transcription with Superscript III, followed by second-strand synthesis using the NEBNext second-strand synthesis module supplemented with dUTP, and then libraries were generated using the NEBNext ChIP-seq Library Preparation Kit.

Library strategy

RNA-Seq

Library source

transcriptomic

Library selection

cDNA

Instrument model

Illumina HiSeq 2000

Data processing

ChIP-seq: Reads were aligned separately to the mus/129 and cas genomes using novoalign with default parameters for paired-end alignment, the coordinates of these alignments were then converted to mm9 coordinates with custom scripts. Following alignment, coverage files were generated for the composite set of reads (comp), as well as allelic reads that aligned better to mus (mus) or cas (cas) using custom perl scripts, SAMtools and bedtools to extract and sort allelic reads, remove duplicates and generate coverage files. The coverage files presented in the paper and in this archive are fpm normalized. Peaks were called using macs2 with default settings. Hi-C: The individual ends of the read-pairs were aligned to the mus and cas reference genomes separately using novoalign with default parameters for single-end alignments, and the quality score of the alignment was used to determine whether each end could be assigned to either the mus or the cas haplotype. The single-end alignments were merged into a HiCsummary file using custom scripts to determine whether a given read-pair could be assigned to the mus or cas haplotype and to pair up the two ends of the read-pair. RNA-seq: To determine the allelic origin of each sequencing read from the hybrid cells, reads were first depleted of adaptors dimers and PCR duplicates, followed by the alignment to custom mus/129 and cas genomes to separate mus and cas reads. Once completed, reads were then mapped back to reference mm9 genome using Tophat v2.0.10 (-g 1 --no-coverage-search --read-edit-dist 3 --read-mismatches 3 --read-gap-length 3 --b2-very-sensitive --mate-inner-dist 50 --mate-std-dev 50 --library-type fr-firststrand). Following alignment, gene expression levels within each library were quantified using Homer v4.7 (rna mm9 -count genes -strand + -noadj -condenseGenes) and the normalized differential expression analyses across samples were performed by using EdgeR.
Genome_build: mm9
Supplementary_files_format_and_content: ChIP-seq: bigWig (bw) files for all reads (.comp), regardless of whether they are allele-specific or not, cas-specific (.cas) and mus-specific (.mus). All bigWig files are fpm-normalized, but not input normalized or smoothed. Hi-C: data is present in a Hi-C summary file, where each line corresponds to the coordinates of the the two end-pairs in the alignment. This format is suitable for generating Hi-C contact matrices using programs such as homer. As for the ChIP-seq, reads are broken down into comp, cas and mus sets. Supplementary files included in this series consist of an excel file containing .fpkm values and the results of the differential expression analysis using edgeR for all RNA-seq experiments.

Submission date

May 26, 2015

Last update date

May 15, 2019

Contact name

John Edward Froberg

E-mail(s)

jfroberg@fas.harvard.edu

Phone

8479770174

Organization name

Harvard University