 |
 |
GEO help: Mouse over screen elements for information. |
|
| Status |
Public on Nov 30, 2018 |
| Title |
spt6-S8A H3 ChIP Rep1 |
| Sample type |
SRA |
| |
|
| Source name |
yeast cells
|
| Organism |
Saccharomyces cerevisiae |
| Characteristics |
antibody: anti-H3
genotype: spt6-S8A
|
| Treatment protocol |
Yeast cells of the indicated genotypes were grown as described above. Other than fixing the cells for ChIPs no special treatments were followed. For ChIP seq, clarified sonicated lysates were incubated with anti H3 antibody to assess nucleosome occupancy changes
|
| Growth protocol |
WT, spt6S8A, Spt6S8E and spt6-1004 alleles were grown in YPD. For RNAseq and ChiPseq experiemnts, Overnight saturated cultures were diluted back to an ON of 0.2 and were allowed to grow until they reached an optical density of 1. They were collected and flash frozen in liquid nitrogen for RNA extraction and fixed in 1% Formaldehyde for 15 minutes and quenched with glycine and sonicated uisng established conditions as described in the proocol.
|
| Extracted molecule |
genomic DNA |
| Extraction protocol |
Yeast cultures of the indicated genotypes were grown at 30C and in YPD conditions and used for RNA extraction using acid phenole method as described in materials and methods. ChIPs were performed as described in materials and methods with anti-H3 antibody. Isolated ChiP DAN was quantified and used for the generation of libraries using Kappa Hyper kit.
For RNA seq: RNA was extracted using acid-phenol method (Collart and Oliviero, 2001) and was quantified spectrophotometrically. 2.5g of total RNA was used to deplete rRNA using the Ribo-zero kit (Illumina). ERCC spike-in controls were added to the RNA samples after rRNA clean-up and before proceeding on to the library preparation. Stranded RNA-seq libraries were prepared using TruSeq Stranded Total RNA sample preparation according to manufacturer’s instructions. The libraries were sequenced on Illumina HiSeq 2500, paired-end 50bp reads). For ChiP-seq ChIP was performed as described in the text and libraraies were prepared using akppa hyprep kit using manufacturers instructions.
|
| |
|
| Library strategy |
ChIP-Seq |
| Library source |
genomic |
| Library selection |
ChIP |
| Instrument model |
Illumina HiSeq 2500 |
| |
|
| Data processing |
RNA-seq reads were first trimmed for possible adapter contamination using cutadapt (v1.10), (Martin, 2011) with the recommended sequence for Illumina adapters as well as a minimum read length of 36 base pairs (bp). Low quality reads were then filtered with fastq_quality_filter, a function within the fastx-toolkit (v0.0.14), with command line options -p 90 and -q 20 to keep reads with at least a 20 Phred score at a minimum of 90% of the bases. Reads were then aligned to the sacCer3 genome using STAR (v2.5.2b), (Dobin et al., 2013) and the following options: --quantMode TranscriptomeSAM, --outFilterMismatchNmax 2, --alignIntronMax 1000000, --alignIntronMin 20, --chimSegmentMin 15, --chimJunctionOverhangMin 15, --outSAMtype BAM Unsorted, --outFilterType BySJout, --outFilterScoreMin 1, and --outFilterMultimapNmax 1. A GTF file was given for the --sjdbGTFfile option that was generated in house combining the sacCer3 RefSeq and ERCC spike-in GTFs. Finally, the Salmon (v0.8.1), (Patro et al., 2017) function quant was used to quantify RNA counts over each gene, and DESeq2 (v1.14.1), (Love et al., 2014) was used to calculate differential genes. Stranded RNA-seq allows us to map reads to specific strands, so all aligned reads were assigned sense or antisense based on whether they overlapped sacCer3 RefSeq genes in the same or opposite strand, respectively. Reads that didn’t overlap any gene were discarded for any stranded analyses as we couldn’t confidently assign them sense/antisense. Unfortunately, overlapping genes cause reads to be assigned to both sense and antisense, so regions of gene overlap plus 49bp on either side (to account for read length) were subtracted out using bedtools (v2.26), (Quinlan and Hall, 2010), and expression of the remaining regions was re-quantified. Antisense cryptic transcripts were identified using previously published methods with no changes except using a minimum of 0.5 RPKM versus their previous minimum of 4.0 FPKM (Dejean, 1970). File conversions were done with samtools (v1.3.1, (Li et al., 2009) and in-house scripts. Reads were initially aligned and processed as paired end fragments, however signal tracks demonstrated an unusual pile-up of reads at specific and consistent locations across the gene that only occurred in the “R1” reads. To eliminate potential biases this may have added to downstream analyses, we only used the “R2” reads in this work. As no global transcriptional changes were observed using the ERCC spike-in, ERCC reads were removed from the dataset and not used for downstream analysis or quantification.
ChIP-seq reads were first trimmed for possible adapter contamination using cutadapt (v1.10), (Martin, 2011) with the recommended sequence for Illumina adapters as well as a minimum read length of 36 base pairs (bp). Low quality reads were then filtered with fastq_quality_filter, a function within the fastx-toolkit (v0.0.14), with command line options -p 90 and -q 20 to keep reads with at least a 20 Phred score at a minimum of 90% of the bases. To eliminate possible PCR artifacts from library preparation, we used in-house scripts to keep at most 5 reads that had the same sequence, where those above that threshold were filtered out. As this was paired end sequencing, we used in-house scripts to re-synchronize the reads that were kept into proper, ordered pairs between “R1” and “R2” fastqs for alignment. Reads were then aligned to the sacCer3 genome using STAR (v2.5.2b), (Dobin et al., 2013) and the following options: --outFilterMultimapNmax 1, --outFilterMismatchNmax 2, --chimSegmentMin 15, --chimJunctionOverhangMin 15, --outSAMtype BAM Unsorted, --outFilterType BySJout, --outFilterScoreMin 1, and --outFilterMultimapNmax 1. The sacCer3 RefSeq GTF file was given for the option --sjdbGTFfile. Samtools (v1.3.1) (Li et al., 2009) was used to eliminate alignments that did not contain properly paired reads or were not primary alignments. Bigwigs were then made using genomeCov within bedtools (v2.26), (Quinlan and Hall, 2010) as well as tool bedGrapthToBigWig (Kent et al., 2010). To identify genes that had low 5’ levels of Spt6 ChIP-seq signal in spt6S8A8 relative to WT, we calculated the log2 ratio of average signal between the first and second half of each gene for both spt6S8A8 and WT. The variance of this score was calculated across three replicates, and genes with variance >0.01 for either spt6S8A8 or WT were removed to select genes with consistent signal across replicates. For the remaining genes, the difference of ratios between spt6S8A8 and WT were calculated (i.e., log2(avg(WT first half signal)/avg(WT second half signal) )- log2(avg(S8A first half signal)/avg(S8A second half signal) )). Those with a score of 0.15 or greater were selected for downstream analyses.
Genome_build: sacCer3
Supplementary_files_format_and_content: BigWig files for the stranded RNA-seq were provided, and represent read-depth normalized sense or antisense signal genome-wide.
|
| |
|
| Submission date |
Nov 16, 2018 |
| Last update date |
Dec 01, 2018 |
| Contact name |
Austin J Hepperla |
| E-mail(s) |
hepperla@unc.edu
|
| Organization name |
University of North Carolina at Chapel Hill
|
| Department |
Genetics
|
| Street address |
7018B Mary Ellen Jones Building
|
| City |
Chapel Hill |
| State/province |
NC |
| ZIP/Postal code |
27599 |
| Country |
USA |
| |
|
| Platform ID |
GPL17342 |
| Series (1) |
| GSE122620 |
Casein Kinase II Phosphorylation of Spt6 Enforces Transcriptional Fidelity by Maintaining Spn1-Spt6 Interaction |
|
| Relations |
| BioSample |
SAMN10435301 |
| SRA |
SRX5017462 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSM3476479_fSPT6S8A1_combined_STARAligned.out.sorted.spikeRemoved.centerWeighted40bp.sorted.bw |
29.1 Mb |
(ftp)(http) |
BW |
SRA Run Selector |
| Raw data are available in SRA |
| Processed data provided as supplementary file |
|
|
|
|
 |
