|
| Status |
Public on Oct 22, 2019 |
| Title |
Replicate1,chrRNA-seq WildType |
| Sample type |
SRA |
| |
|
| Source name |
HeLa cells
|
| Organism |
Homo sapiens |
| Characteristics |
cell type: cervical cancer cells
genotype/variation: wild type
|
| Treatment protocol |
Lipofectamine 2000 was used to deliver RNAseH1 over-expressing plasmid (pRNH1-GFP), RNaseH1 catalytically dead mutant (pRNH1-D210N-GFP) Rnase H1 non binding ctalytically dead mutant (pRNH1-WKKD-GFP) and pGFP. For RDIP-seq experiments recombinant RNase H was added the sonicated HeLa cells before S9.6 immunoprecipitation. All HeLa cells used in Chromatin associated RNA-seq and ChrCAP-seq were GFP FACs sorted. For ChrCAP-seq, chromatin RNA were treated with Terminator exonuclease followed by calf intestine phosphatase before CAP-CLIP (5' pyrophosphatase) treatment.
|
| Growth protocol |
HeLa cells were maintained in DMEM supplemented with 10%FBS
|
| Extracted molecule |
total RNA |
| Extraction protocol |
Lysates were clarified from sonicated nuclei and 1) RNA:DNA hybrids were isolated with S9.6 antibody for RDIP-seq 2) RNA:DNA hybrids were isolated with GFP antibody for RR-ChIP-seq
For the RDIP-seq and RR-ChIP-seq, the RNA component of the R-loop was used to prepare the library using NEBNext Ultra II Directional RNA Library Prep Kit for Illumina, (E7760S) according to manufacturer's guidelines. For the ChrRNA-seq and ChrCAP-seq, chromatin associated RNA was used for library prepration as for RDIP-seq.
|
| |
|
| Library strategy |
OTHER |
| Library source |
transcriptomic |
| Library selection |
other |
| Instrument model |
Illumina HiSeq 2000 |
| |
|
| Description |
chrRNA-seq
chromatin RNA
|
| Data processing |
Library strategy: chrRNA-seq
For chrRNA-seq, adaptors were trimmed using Cutadapt. Paired-end reads for each sample were mapped to human genome reference assembly GRh37/hg19 (build 37.2, February 2009) with Tophat v. 2.0.13 with parameters -g 1 -r 3000 --no-coverage-search.
RR-ChIP-seq reads were demultiplexed and aligned to reference genome hg19/GRCh37 using Bowtie2 alignment software.Plus and minus strand were assigned to mapped reads using SAMtools. RR-ChIP-seq peaks were called using MACS2 algorithm with default options
Genome_build: hg19
Supplementary_files_format_and_content: BigWig file containing read densities from RNA-seq experiments.
|
| |
|
| Submission date |
Oct 04, 2016 |
| Last update date |
Oct 22, 2019 |
| Contact name |
Nicholas Proudfoot |
| E-mail(s) |
nicholas.proudfoot@path.ox.ac.uk
|
| Organization name |
Sir William Dunn School of Pathology, University of Oxford
|
| Street address |
South Parks Road
|
| City |
Oxford |
| ZIP/Postal code |
OX1 3RE |
| Country |
United Kingdom |
| |
|
| Platform ID |
GPL11154 |
| Series (1) |
| GSE87607 |
R-loops promote antisense transcription across the mammalian genome |
|
| Relations |
| BioSample |
SAMN05861227 |
| SRA |
SRX2210290 |
