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| Status |
Public on Mar 01, 2016 |
| Title |
yjm789_ypd_S1 |
| Sample type |
SRA |
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| Source name |
yeast cells
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| Organism |
Saccharomyces cerevisiae |
| Characteristics |
strain: S96 YRR1_delta
yrr1_ allele transformed: YRR1_YJM789
growth medium: YPD
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| Growth protocol |
Each of the three untagged isogenic strains with different alleles YRR1_S96, YRR1_YJM789, YRR1_S96-I775E, respectively, were grown as two replicated cultures in liquid YPD or YPglycerol medium to mid-log phase. Each YPD culture was diluted to early-log phase and divided into two subcultures. One subculture was incubated in liquid YPD medium with 0.25 µg/ml 4NQO and the other subculture without 4NQO. Both subcultures for each replicate were further grown for 2.5 h.
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| Extracted molecule |
total RNA |
| Extraction protocol |
Total RNA was extracted from each sample and multiplexed unstranded paired-end cDNA libraries were prepared using Illumina TruSeq RNA Sample Prep Kit v2.
RNA libraries were prepared for sequencing on Illumina MiSeq using standard Illumina protocols
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| Library strategy |
RNA-Seq |
| Library source |
transcriptomic |
| Library selection |
cDNA |
| Instrument model |
Illumina MiSeq |
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| Data processing |
Base-calling was performed via Illumina CASAVA version 1.7.
Tophat v2.0.12 (Kim et al. 2013; Trapnell et al. 2009) was used to map the RNA-Seq reads to the S288c genome and to generate .bam files for mapped reads. The reads were first mapped to ribosomal RNA and transfer RNA genes; 1.05-1.94 million read pairs per sample were not matched to those RNA genes, and 91.2-95.5% of those unmatched reads were then matched to the whole gene pool of S288c. The reads matched to rRNA and tRNA were excluded because these RNAs tend to be extracted at high and/or variable abundances across replicates, thus may bias the calculation of FPKM (fragments per kb gene per million mapped fragments).
The following approach was used to quantify gene expression from the mapped reads in .bam files. The R-package Rsubread v1.18.0 (Liao et al. 2013) was used to generate count tables based on the annotations of S288c genome release R64-1-1. Then DESeq2 v1.8.1 (Anders and Huber, 2010) was used to quantify differential expression.
Genome_build: sacCer3
Supplementary_files_format_and_content: Table S1 as a single .xlsx file with multiple worksheets: Read counts and differential expression data from RNA-Seq. In each comparison for differential expression in the format of 'condition_A...condition_B', condition_A is the denominator and condition_B is the numerator when calculating fold change. • Rsubread_count_table: count table generated by Rsubread package, input for differential expression analysis by DESeq2 package. • Rsubread_FPKM: FPKM data calculated based on 'Rsubread_count_table'. • DESeq: differential expression data generated by DESeq2 package.
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| Submission date |
Nov 03, 2015 |
| Last update date |
May 15, 2019 |
| Contact name |
Xiaoqing Rong-Mullins |
| Organization name |
West Virginia University
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| Street address |
53 Campus Dr
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| City |
Morgantown |
| State/province |
West Virginia |
| ZIP/Postal code |
26505 |
| Country |
USA |
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| Platform ID |
GPL17143 |
| Series (1) |
| GSE74642 |
RNA-Seq of Saccharomyces cerevisiae cells carrying different YRR1 alleles in response to 4-nitroquinoline-N-oxide (4NQO) and to glycerol as the sole carbon source |
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| Relations |
| BioSample |
SAMN04233122 |
| SRA |
SRX1411148 |
| Supplementary data files not provided |
SRA Run Selector |
| Raw data are available in SRA |
| Processed data are available on Series record |
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