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Sample GSM3564280

Query DataSets for GSM3564280

Status

Public on Sep 13, 2019

Title

RNA-seq in RWPE1 rep3

Sample type

SRA

Source name

RNA-seq in RWPE1

Organism

Homo sapiens

Characteristics

cell line: RWPE1
cell type: Human normal prostate cell line

Growth protocol

The human prostate cancer C42B cells were obtained from ViroMed Laboratories (Minneapolis, MN, USA) whereas the human prostate cancer 22Rv1 (ATCC # CRL-2505) and normal prostate RWPE1 (ATCC # CRL-11609) cells were obtained from ATCC (https://www.atcc.org/). Cells were grown at 37ºC in 5% CO2; the corresponding culture medium for each cell line (RPMI 1640 for C42B and 22Rv1 and Keratinocyte Serum Free Medium for RWPE-1) was supplemented with 10% fetal bovine serum (Gibco by Thermo Fisher Scientific, Waltham, MA, USA) and 1% penicillin and streptomycin. All cell stocks were authenticated at the USC Norris Cancer Center cell culture facility by comparison to the ATCC and/or published genomic criteria for that specific cell line; all cells were documented as free of mycoplasma.

Extracted molecule

total RNA

Extraction protocol

In situ Hi-C experiments were performed following the original protocol by Rao et al with minor modifications. In situ Hi-C was performed in duplicate and 5 x 106 cells were used for each experiment. 100U of MboI restriction enzyme (NEB, R0147) was used to digest chromatin. For ligation, 2000U T4 DNA Ligase (NEB, M0202) was added and incubated at room temperature for 4 hours with slow rotation. Hi-C material was sheared to a size of 300-500bp using a Covaris instrument (Covaris S2, Woburn, MA). Biotin-tagged DNA was pulled down using Dynabeads MyOne Streptavidin C1 beads (Life technologies, 65002) with 2X Binding Buffer (2X BB: 10mM Tris-HCl (pH 7.5), 1nM EDTA, 2M NaCl).
ChIP assays were performed in C42B, 22Rv1 and RWPE1 cells using H3K9me3 (Cat# 13969 Lot# 1, Cell Signaling and Technology, Inc.), H3K27me3 (Cat# 9733 Lot# 8, Cell Signaling and Technology, Inc.), and H3K36me3 (Cat# 2901 Lot# 3, Cell Signaling and Technology, Inc.) antibodies, according to ENCODE standards (https://www.encodeproject.org/data-standards/).
RNA-seq was performed in triplicate for RWPE1, C42B, and 22Rv1 cells. RNA was extracted using Trizol reagent (Cat # 15596-018, Thermo Fisher Scientific, NY, USA) and the quality of RNA was assessed using a 2100 Bioanalyzer instrument (Cat # G2939AA, Agilent technologies), as described previously.
For NOMe-seq, after isolating nuclei from the cells, M.CviPI was treated to methylate accessible GpCs. After purifying M.CvPI-treated DNA, sonication was performed. Bisulfite treatment of M.CviPI-methylated DNA resulted to convert all unmethylated Cs to Ts.
In situ Hi-C ibraries were prepared using Kapa Hyper prep kit (Kapa #KK8503) according to the provided protocol. Library was amplified with PCR using Illumina primers.
ChIP-seq: Libraries were barcoded (NEXTflex™ DNA Barcodes) (Bio Scientific, Austin, TX).
RNA-seq libraries were made using KAPA Stranded mRNA-Seq Kit with KAPA mRNA Capture Beads (KK8420) (Kapa Biosystems, Woburn, MA).
NOMe-seq: Libraries were generated using the Accel-NGS Methyl-Seq DNA Library Kit for Illumina Platforms.

Library strategy

RNA-Seq

Library source

transcriptomic

Library selection

cDNA

Instrument model

Illumina HiSeq 3000

Data processing

The quality of each in situ Hi-C library was checked with FastQC and HIC-Pro version 2.8.0. Raw fastq files were processed through the HiC-Pro version 2.8.0 to make the raw contact count matrices for multiple resolutions. The matrices were normalized using the iterative correction method (iced python library). To increase the sequencing depth, replicates were pooled and processed as above described.
Each ChIP-seq experiment was performed in duplicate and ChIP-seq libraries were sequenced on an Illumina Hiseq machine. All ChIP-seq data were mapped to hg19 and peaks were called using MACS245 after preprocessing data with the ENCODE3 ChIP-seq pipeline (https://www.encodeproject.org/chip-seq/). To call reproducible peaks from two replicates, the naïve overlap tool for histone mark datasets was used, as suggested in the ENCODE3 ChIP-seq standards document (https://www.encodeproject.org/pages/pipelines/) and previously described.
For RNA-seq, reads were mapped to hg19 GENCODE version 19 using STAR 2.4.1d49 and aligned reads were quantified at the gene level using Partek® Flow® software Quantify to annotation model (Partek Inc., St. Louis, MO, USA). The RPKM normalization method was used and log2 transformed. Differentially expressed genes between normal and cancer cells were selected by using the Gene Specific Algorithm from Partek® Flow® software using the upper quartile normalization method (Partek Inc., St. Louis, MO, USA) (FDR <0.05).
For NOMe-seq, the fastq files were aligned to a bisulfite-converted genome using the BSMAP, and the Bis-SNP was used to call methylation sites. NDR was called using the findNDRs function from the aaRon R package (https://github.com/astatham/aaRon) (P-value cutoff, 1e-8).
Genome_build: GRCh37
Supplementary_files_format_and_content:
For in situ Hi-C, text files include contact count matrices at 10kb and 40kb, respectively
For ChIP-seq, tab-delimited text files include location of peaks
For RNA-seq, tab-delimited text files include log2(RPKM+1) for each gene.
For NOMe-seq, tab-delimited text files include location of nucleosome depleted regions

Submission date

Jan 15, 2019

Last update date

Sep 13, 2019

Contact name

Suhn K Rhie

Organization name

University of Southern California

Department

Biochemistry and Molecular Medicine

Lab

Rhie Lab