 |
 |
GEO help: Mouse over screen elements for information. |
|
| Status |
Public on Jan 18, 2019 |
| Title |
exp.4_wt-Hel2-HTP |
| Sample type |
SRA |
| |
|
| Source name |
wt-Hel2-HTP
|
| Organism |
Saccharomyces cerevisiae |
| Characteristics |
5'-linker identifier: NNNCACTAGC
additional notes: single size fraction
molecule: protein-crosslinked RNA
|
| Treatment protocol |
Cells were crosslinked for 100s and harvested by centrifugation.
|
| Growth protocol |
Cells were grown in SD media lacking Trp and containing 2% glucose to OD600 0.5.
|
| Extracted molecule |
total RNA |
| Extraction protocol |
Cells were lysed, UV-crosslinked protein-RNA complexes were purified by tandem purification on IgG, TEV cleavage and immobilisation on Ni-NTA.
Libraries were constructed using the published CRAC protocol with minor modifications (Granneman et al., 2009).
|
| |
|
| Library strategy |
OTHER |
| Library source |
transcriptomic |
| Library selection |
other |
| Instrument model |
Illumina MiniSeq |
| |
|
| Description |
CRAC sample
|
| Data processing |
Library strategy: CRAC
Base calling was done using Illumina standard software.
Data were split according to i7 indices using Illumina software.
Reads from different lanes belonging to the same sample were concatenated.
Reads were split according to in-line barcodes.
For submission to GEO, reads from the same sample, but carrying different i7 indices, and for exp.1 and exp.2 from two different size fractions, were combined and only identical parts of a5'-linkers were removed, while random nucleotides and parts of the 5'linkers that differed between samples were retained. For further data processing, these parts were removed.
Further processing: 3'-adapters were removed using flexbar. pyFastqDuplicateRemover.py from the pyCRAC package (Webb et al., 2014) was used to collapse data (files belonging to the same sample but with different indices & 5'linkers with 3'-terminal N were treated separately, as reads definitely result from separate RNA molecules, to retain greater sequencing depth and collapsed files were combined thereafter - available upon request).
Collapsed and uncollapsed data were aligned using novoalign. Reads were mapped using pyReadCounters from the pyCRAC package. Bedgraphs were generated from pyReadCounters output and converted to bigwig format using bedGraphToBigWig.
Genome_build: sacCer3, EF4.74
Supplementary_files_format_and_content: bedgraph files showing hit density (actual counts) for aligned, collapsed data.
|
| |
|
| Submission date |
May 14, 2018 |
| Last update date |
Jan 18, 2019 |
| Contact name |
Marie-Luise Winz |
| E-mail(s) |
[email protected]
|
| Organization name |
University of Edinburgh
|
| Department |
Wellcome Centre for Cell Biology
|
| Lab |
Tollervey Lab
|
| Street address |
Max Born Crescent
|
| City |
Edinburgh |
| ZIP/Postal code |
EH9 3BF |
| Country |
United Kingdom |
| |
|
| Platform ID |
GPL22715 |
| Series (2) |
| GSE114420 |
Molecular interactions between Hel2 and RNA supporting ribosome-associated quality control [II] |
| GSE114429 |
Molecular interactions between Hel2 and RNA supporting ribosome-associated quality control |
|
| Relations |
| BioSample |
SAMN09206825 |
| SRA |
SRX4081745 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSM3141485_exp.4_wt-Hel2-HTP_count_output_reads.gtf_minus_strand_reads.bedgraph.gz |
1.4 Mb |
(ftp)(http) |
BEDGRAPH |
| GSM3141485_exp.4_wt-Hel2-HTP_count_output_reads.gtf_plus_strand_reads.bedgraph.gz |
1.4 Mb |
(ftp)(http) |
BEDGRAPH |
SRA Run Selector |
| Raw data are available in SRA |
| Processed data provided as supplementary file |
|
|
|
|
 |
