GEO Accession viewer

NCBI > GEO > Accession Display

Not logged in | Login

GEO help: Mouse over screen elements for information.

Sample GSM1464186

Query DataSets for GSM1464186

Status

Public on Sep 11, 2014

Title

Lib75PUcontrolHSrep2_CMC_treatment

Sample type

SRA

Source name

Saccharomyces cerevisiae_CMC_treatment

Organism

Saccharomyces cerevisiae

Characteristics

knockdown: None
knockout: None
growth condition: 45 deg
treatment: CMC_treatment

Extracted molecule

total RNA

Extraction protocol

Enrichment of polyadenylated RNA (polyA+ RNA) from total RNA was performed using one round of enrichment using Oligo(dT) dynabeads (Invitrogen) according to the manufacturer’s protocol. CMC-treatment was performed essentially as described in (Bakin and Ofengand, 1993; Bakin and Ofengand, 1998). Specifically, pelleted polyA+ RNA was resuspended in 30 mL of 0.17M CMC in BEU buffer (50mM bicine, pH 8.3, 4 mM EDTA, and 7M urea) or in 30 mL of BEU buffer as input at 37°C for 20 min. Reaction was stopped with 100 mL of 0.3M NaOAc and 0.1 mM EDTA, pH 5.6 (Buffer A), 700 mL of EtOH, and 1 mL of glycogen. After chilling for 5 min in dry ice, the pellet was recovered, washed with 70% EtOH, dissolved in 100 mL of Buffer A, and reprecipitated with 300 mL of EtOH and 1 mL of glycogen. After washing as above, the pellet was dried, dissolved in 40 mL of 50 mM sodium bicarbonate, pH 10.4, and incubated at 37°C for 3 hours. The RNA was precipitated by addition of 100 mL of Buffer A, 700 mL EtOH, and 1 mL of glycogen. The pellet was washed with 70 % EtOH and then dissolved with water for subsequent library preparation.
The mRNA was chemically fragmented into ~80-150 nt-long fragments by performing a short fragmentation (30 seconds) using RNA fragmentation reagent and stop solution (Ambion). RNA was subjected to FastAP Thermosensitive Alkaline Phosphatase (Thermo Scientific), followed by a 3’ ligation of an RNA adapter using T4 ligase (New England Biolabs). Ligated RNA was reverse transcribed using AffinityScript Multiple Temperature Reverse Transcriptase (Agilent) or SuperScript III (Life Technologies), and the cDNA was subjected to a 3’ ligation with a second adapter using T4 ligase. The single-stranded cDNA product was then amplified for 9-12 cycles in a PCR reaction. Libraries were sequenced on Illumina HiSeq 2500 platforms generating paired end reads (30 bp from each end).

Library strategy

RNA-Seq

Library source

transcriptomic

Library selection

cDNA

Instrument model

Illumina HiSeq 2500

Data processing

Reads were mapped against the yeast genome (sacCer3) using Bowtie (version 0.12.7), with the following parameters: ‘-k 8 --best --strata --sam --maxins 50000’. Reads were mapped against the human (hg19) genome using Tophat (version 1.4.1), with the parameters ‘--max-multihits 1 –prefilter-multihits’ and ‘–transcriptome-index’, for which we assigned a pre-indexed version of the relevant transcriptomes, based on the UCSC Known Genes set of annotations. An in-house script was then used to project all reads aligning to the genome to yeast and human transcriptomes. Only read pairs fully matching a transcript structure, as defined by the ‘UCSC Known Genes’ transcriptome annotation, were retained. Each read pair was computationally extended in transcriptome space from the beginning of the first read to the end of its mate, whereupon, for each nucleotide, we recorded both the number of ‘left’ reads initiating at each position (corresponding to the last position traversed by reverse transcriptase) and the number of overall reads covering each position. In addition, to facilitate examination of sites in rRNA and snRNAs, we used Bowtie to directly align reads against a transcriptomic database, harboring these two classes of RNA. These alignments were processed as above, to record the number of reads starting and overlapping each position.
Putative Ψ sites were identified using the following approach: (1) For each treated or non-treated sample, a Ψ-ratio was calculated, corresponding to the number of reads beginning at the position divided by the overall number of reads covering it (Figure 1B). A pseudocount of 1 was added to both the numerator and denominator to stabilize the ratio and avoid division by 0. (2) Log2 fold changes of Ψ ratios in the treated versus non-treated samples were generated, to yield the Ψ-fold change. All positions with a Ψ-ratio >0.1, a Ψ-fc >3 (corresponding to 8 fold enrichment) and with >5 reads beginning at the position were considered putative pseudouridylated sites. (3) To allow comparison across multiple conditions/perturbations, we first merged from all samples the positions of all windows passing step (2), to define a set of all unique sites passing the filters in at least one condition. For each such site, we then calculated a Ψ-ratio and Ψ-fc in each sample. We then calculated a median Ψ-ratio and median Ψ-fc across all samples, and considered all sites in which these values exceeded 0.1 and 3, respectively (unless explicitly otherwise stated). (4) As identical genes are often present in the genome in multiple copies (e.g. rRNA and tRNA), we demanded that each sequence of 21 nucleotides surrounding the putative pseudouridylated position in the dataset be unique; All redundancies were filtered out. Finally, we also filtered out sites in positions other than immediately following ‘U’.
Genome_build: sacCer3. hg19, mm9
Supplementary_files_format_and_content: text tables with putative pseudouridylation sites. Each tables contains genomic coordinates of the site, along with information pertaining to the PSI ratios and fold changes calculated for each site across the different experiments. Also the underlying raw data in terms of read counts is provided for each site, including the number of reads beginning and overlapping each position in the treated and input samples.

Submission date

Aug 04, 2014

Last update date

May 15, 2019

Contact name

Schraga Schwartz

Organization name

WEIZMANN INSTITUTE OF SCIENCE

Street address

Herzl 234, Department of Molecular Genetics

City

Rehovot