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Sample GSM781945 Query DataSets for GSM781945
Status Public on Jan 18, 2013
Title Yeast Cse4 scm3 ChIP-Seq
Sample type SRA
 
Source name Yeast cell
Organism Saccharomyces cerevisiae
Characteristics strain: W303 Pgal1-Cse4-3xHA-KanMX4 (internal tag) scm3::HphMX4
antibody: anti-HA EZview affinity gel (Sigma)
antibody manufacturer: Sigma
Growth protocol Yeast cells were grown in 500 mL rich medium supplemented with adenine and uracil, in the presence of raffinose and galactose (YPAURG) to mid-log phase (OD = 0.5-0.7).
Extracted molecule genomic DNA
Extraction protocol ChIP-Seq experiments were performed at least in independent biological duplicates, as described previously (Aparicio et al., Curr Protoc Cell Biol (2004); Lefrançois et al., BMC Genomics (2009); Lefrançois et al., Methods Enzymology (2010)). Yeast strains were grown in 500 mL YP media supplemented with adenine and uracil, in presence of glucose or galactose/raffinose, to mid-log phase (OD 600=0.5-0.7). Proteins were crosslinked to DNA by treating cells with formaldehyde (1% final concentration) for 15 minutes, then quenched with glycine. Cells were collected by filtration after two washes. After cell lysis using a FastPrep machine (MP Biomedical), chromatin was sheared by sonication using a Branson Digital 450 sonifier (Branson). Clarified, sonicated lysates were taken at this step for Sono-Seq, prior to immunopreciptation. Immunoprecipitations of Myc-tagged and HA-tagged strains, as well as those of the respective control untagged strains, were carried out overnight with EZ-View anti-Myc or anti-HA affinity gels (Sigma). For native RNA Polymerase II ChIP, cell lysates were incubated with Pol II 8WG16 mouse monoclonal antibody (Covance) and pulled down using Protein G agarose beads (Millipore). After several washes and reversal of protein-DNA crosslinks, ChIP DNA was purified through a Qiagen MinElute PCR purification column (Qiagen). Illumina sequencing libraries were generated using adapters for multiplexing as described (Lefrançois et al., BMC Genomics (2009); Lefrançois et al., Methods Enzymology (2010)), and following Illumina’s manufacturer recommendations. Four barcoded libraries were mixed in equimolar ratios and processed on an Illumina Genome Analyzer II. We have also used previously published Cse4 ChIP-Seq data, with normal Cse4 levels, which were deposited in the Gene Expression Omnibus (GEO) database under GSE13322.
 
Library strategy ChIP-Seq
Library source genomic
Library selection ChIP
Instrument model Illumina Genome Analyzer II
 
Description Cse4 ChIP-Seq, scm3 deletion
Data processing Raw sequencing data were first processed by the built-in Illumina analysis pipeline. Prior to the actual sequence mapping, reads were parsed according to the 4-bp index, and barcodes were then removed. Those reads lacking an intact index were discarded. The remaining bases were aligned against the S. cerevisiae S288c reference genome version 2 (SGD/UCSC sacCer2, June 2008) by the ELAND algorithm (Illumina). The peak scoring algorithm PeakSeq (Rozowsky et al., Nat Biotech (2009)) was used to identify statistically significant binding sites, changing only the following parameters to account for the compact S. cerevisiae genome: window size of 10 kb during the normalization step and bin size of 1 kb during the linear regression step (PeakSeqOutput files, with Q-value < 0.05). ChIP-Seq data from epitope-tagged strains were scored against ChIP-Seq data from their matching untagged strains. In both cases, anti-Myc antibodies were used during ChIP. Scoring reference sets were created by pooling uniquely-mapping reads from biological replicates of untagged control strains. As a reference sample marking open chromatin (Auerbach et al., PNAS (2009)), two lists of Sono-Seq significant regions were generated, obtained after scoring against either anti-Myc or anti-HA control sets. To uncover Centromere-like Regions (CLRs), we took a conservative, stringent approach to minimize false positives lacking functional significance or failing qPCR validation. For each biological replicate of a particular kinetochore component, only putative binding regions with Q-value < 10-5 were considered (Target bed files). Several other criteria were then applied. First, binding sites called in two biological replicates from Cse4, Mif2, Ndc10 and Ndc80 ChIP-Seq data, in either a Cse4 overexpression strain or in a wild-type strain, were overlapped with maxgap=150 (maximum gap between non-overlapping peaks). Next, to identify a binding region as a CLR, 1) all four kinetochore proteins must be present at the putative site given the q-value threshold; and 2), for proteins in direct contact with DNA, mean PeakSeq ratios between both replicates at a particular target site should be above 2.00 for open chromatin marker Cse4 (same for PolII and Sono-Seq regions), and 1.50 for direct DNA binders Mif2 and Ndc10. Several other filters were used to distinguish between lower confidence regions and higher confidence regions for subsequent functional analyses, including comparison of PeakSeq experimental reads and PeakSeq background reads between CLRs and CENs, inspection of normalized signal tracks (good tagged/untagged signal ratio and low background in the appropriate untagged control desired), binding over a highly PolII-occupied ORF, and presence in a HOT region. Regions that passed those criteria and filters were termed CLRs (Centromere-Like Regions). Other binding sites that did not pass the aforementioned filters were referred to as LCNCRs (for low-confidence, negative control regions).
 
Submission date Aug 18, 2011
Last update date May 15, 2019
Contact name Raymond K Auerbach
Organization name Yale University
Street address 266 Whitney Ave
City New Haven
State/province CT
ZIP/Postal code 06511
Country USA
 
Platform ID GPL9377
Series (1)
GSE31466 Centromere-Like Regions in Budding Yeast
Relations
SRA SRX092434
BioSample SAMN00710380

Supplementary file Size Download File type/resource
GSM781945_Cse4_scm3_Rep1_ACGT.eland.txt.gz 67.5 Mb (ftp)(http) TXT
GSM781945_Cse4_scm3_Rep1_ACGT.sgr.gz 11.5 Mb (ftp)(http) SGR
GSM781945_Cse4_scm3_Rep1_ACGT_PeakSeqOutput.txt.gz 107.4 Kb (ftp)(http) TXT
GSM781945_Cse4_scm3_Rep1_ACGT_targets.bed.gz 20.3 Kb (ftp)(http) BED
GSM781945_Cse4_scm3_Rep2_TGCT.eland.txt.gz 56.0 Mb (ftp)(http) TXT
GSM781945_Cse4_scm3_Rep2_TGCT.sgr.gz 10.6 Mb (ftp)(http) SGR
GSM781945_Cse4_scm3_Rep2_TGCT_PeakSeqOutput.txt.gz 103.4 Kb (ftp)(http) TXT
GSM781945_Cse4_scm3_Rep2_TGCT_targets.bed.gz 17.1 Kb (ftp)(http) BED
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Raw data are available in SRA
Processed data provided as supplementary file

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