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Sample GSM2219115

Query DataSets for GSM2219115

Status

Public on Oct 04, 2017

Title

Mrd1_DMSO_in_vitro_1

Sample type

SRA

Source name

purified 35S pre-ribosomal RNP treated with DMSO

Organism

Saccharomyces cerevisiae

Characteristics

strain: BY4741 with mrd1-deltaRDB5-TAP::K.I.TRP1, pGAL-HA-MRD1::URA3
rna type: pre-ribosomal RNA

Growth protocol

S.cerevisiae strains were grown in YPD (1% yeast extract, 2% peptone, 2% dextrose) or YPG/R (YP with 2% Galactose and 2% Raffinose) at 30ºC.

Extracted molecule

total RNA

Extraction protocol

Immunoprecipitations with HTP-and TAP-tagged proteins were performed with TNM150 buffer (50 mM Tris-HCl pH 7.8, 1.5 mM MgCl2, 150 mM NaCl, 0.1% NP-40 and 5 mM b-mercaptoethanol), essentially as previously described (Granneman et al., 2009). RNA was extracted using a GTC phenol solution (4 M guanidine thiocyanate, 0.05 M Tris at pH 8.0, 0.01 M EDTA, 2% sarcosyl, 1% β-mercaptoethanol, 50% [v/v] phenol) as previously described (Sambrook, 1989).
cDNA libraries were generated from purified ribosomal RNA using an RT oligonucteotide containing random hexamers (SuperScript III, Invitrogen). 5' adapters were ligated on (CircLigase II, EpiCentre) and 3' adaptors generated during PCR amplification.

Library strategy

OTHER

Library source

transcriptomic

Library selection

other

Instrument model

Illumina HiSeq 2000

Description

purified 35S pre-ribosomal RNP treated with DMSO
High-throughput RNA structure probing library

Data processing

Library strategy: CRAC
Base-calling by Illumina
Raw data processing was carried out using tools described in the pyCRAC software package (Webb et al Genome Biology 2014; https://bitbucket.org/sgrann/pycrac)
The pyBarcodeFilter tool was used to split reads based on barcoded indexes. Random nucleotide information from the in-read adapter is included in the headers of the forward reads. See characters after the two hashes (##).
PyFastqDuplicateRemover was used to remove potential PCR duplicates using random nucleotide information in the 5? adapter sequence
pyPileup and pyGTF2sgr.py were used to generate count data for the genes of interest. Raw 1M7 reactivities were calculated according to Tang et al Bioinformatics 2015
Genome_build: Reads were mapped to the Saccharomyces cerevisiae 35S gene (RDN37-1) using Novoalign version 2.07
Burlacu et al Table S2 contains all the calculated 1M7 reactivity for each RNA as well as the categorisations of the nucleotides. To calculate 1M7 reactivities we pooled the sequencing data of the biological replicates.

Submission date

Jun 28, 2016

Last update date

May 15, 2019

Contact name

Sander Granneman

E-mail(s)

[email protected]

Organization name

University of Edinburgh

Department

Centre for Synthetic and Systems Biology