|
| Status |
Public on Jun 03, 2016 |
| Title |
H2217-WT-GAL.5-12-1-12.16.09-222-1-4 |
| Sample type |
SRA |
| |
|
| Source name |
S. cerevisiae cells grown in a single carbon source
|
| Organism |
Saccharomyces cerevisiae |
| Characteristics |
condition description: single carbon source for 12 hours
|
| Treatment protocol |
All S. cerevisiae strains were grown aerobically in 60 mL of synthetic complete at 30°C in 250 mL baffled Erlenmeyer flasks shaken at 225 RPM. Cultures of cells for evaluating the impact of transcriptional interventions were performed in triplicate and initiated by inoculating overnight cultures into 60 mL of synthetic complete media supplemented with 20 g/L glucose and 50 g/L xylose resulting in a density of OD600=1.0+/- 0.2. Samples taken for RNA-seq were aliquoted from the primary culture, spun down at 3000 x g and frozen in liquid nitrogen. Cultures for identification of differential expression associated with carbon sources were grown in triplicate in either 50 g/L glucose, 50 g/L xylose or 1.3 g/L ethanol for 8 hours prior to collection of biomass for RNA sequencing.
|
| Growth protocol |
All strains were constructed in the S. cerevisiae H2217-7 background. Cells were cultured overnight in synthetic complete medium with 2% glucose to a density of 1-2 OD600.
|
| Extracted molecule |
total RNA |
| Extraction protocol |
Total mRNA was isolated using the yeast RiboPure kit (Life Technologies, Carlsbad CA).
Libraries for RNA-Seq were prepared as in (Haynes, et al., 2011) except that the selection of poly(A) RNA from the total RNA isolated was accomplished using an mRNA Catcher Plus Kit (Life Technologies) and the resulting poly(A) RNA was subsequently sheared by incubating in TURBO DNA-free buffer at 75°C for 10 minutes and purified with a QIAquick PCR Purification Kit (Qiagen).
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| |
|
| Library strategy |
RNA-Seq |
| Library source |
transcriptomic |
| Library selection |
cDNA |
| Instrument model |
Illumina Genome Analyzer IIx |
| |
|
| Description |
wildtype in 5% Galactose for 12 hours
|
| Data processing |
Sequenced reads were aligned to the S. cerevisiae S288C reference sequence genome release R63 (Engel et al. 2013) using TopHat version 2.0.4 (Trapnell et al. 2009) and Bowtie version 0.12.8 (Langmead et al. 2009).
Reads that aligned uniquely to the reference sequence were considered for gene expression quantification with Cufflinks version 2.0.2 (Trapnell et al. 2010). Gene expression was quantitated against known gene boundaries from the gene annotations provided by the SGD S288C reference genome release R63. Gene expression was normalized using the Cufflinks upper-quartile normalization option.
After gene expression quantification, samples not passing the following quality control filters were removed from consideration. Each sample was required to be sequenced at a depth of at least 750,000 reads. The expression of the deleted gene in mutant expression profiles was required to be less than 10% of its expression in WT. The mean and median expression of the deleted genes were 1.3% and 0% of the WT levels respectively. The low levels of expression that remained for some samples were likely the result of errors in the sequencing process itself, either due to contamination between samples or a low level of error in matching barcodes for multiplexed samples to reads. In addition, within each replicate set containing 3 biological replicates outlier gene expression profiles were detected and removed if the outlier caused the median of all genes’ coefficients of variation (CoV -- the standard deviation divided by the mean) to be greater than 0.5 for the replicate set or if the outlier caused the Pearson Correlation Coefficient between replicate gene expression profiles to be less than 0.8.
Counts of reads mapping to each gene were quantitated using the htseq-count tool in version 0.5.3 of the HTSeq Python package (Anders et al. 2014).
Batch effects were removed from RNA-seq read counts using Remove Unwanted Variation (RUV) (Risso et al. 2014). Unwanted variation due to technical batch effects was identified and removed, using RUVg, through factor analysis on a set of negative control genes that were not expected to respond to the biological treatments. The set of 192 negative control genes used to identify batch effects are not predicted to be regulated by any of the deleted regulators in the top 100,000 network predicted interactions, and their expression did not change significantly (log2 fold change < 1.3 and adjusted p-value > 0.1) between any pair of expression profiled single carbon growth conditions. Dropping the first factor of unwanted variation, by using RUVg with the parameter k set to 1, was sufficient to remove the majority of the batch effect.
Differential expression analysis comparing expression profiles sets was performed by using LIMMA(Smyth 2004) with the voom transformation applied to read counts (Law et al. 2014).
Genome_build: S. cerevisiae S288C reference sequence genome release R63 (Engel et al. 2013)
Supplementary_files_format_and_content: cuff: Gene expression was quantified by processing tophat produced bam alignments with Cufflinks v2.0.2 with S. cerevisiae S288c reference sequence genome release R63 (Engel et al. 2013). Expression was normalized by applying the Cufflinks supplied upper-quartile normalization routine. counts: Counts of reads mapping to each gene were quantitated using the htseq-count tool in version 0.5.3 of the HTSeq Python package (Anders et al. 2014).The expression.mtr file is a matrix of fully processed gene expression values (upper-quartile normalized Cufflinks reported FPKM values). The matrix is of size: number of S. cerevisiae genes (rows) BY number of expression profiles (columns). Each column in the expression.mtr file lists gene FPKM values from the matching .cuff file.
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| |
|
| Submission date |
Jun 09, 2015 |
| Last update date |
May 15, 2019 |
| Contact name |
Ezekiel John Maier |
| E-mail(s) |
[email protected]
|
| Organization name |
Washington University
|
| Department |
Computer Science
|
| Lab |
Michael Brent
|
| Street address |
4444 Forest Park Ave
|
| City |
Saint Louis |
| State/province |
MO |
| ZIP/Postal code |
63112 |
| Country |
USA |
| |
|
| Platform ID |
GPL13272 |
| Series (1) |
| GSE69682 |
Transcriptome Engineering Promotes a Fermentative Transcriptional State |
|
| Relations |
| BioSample |
SAMN03765913 |
| SRA |
SRX1054042 |
