The strains used in this study are described in Table S1. Yeast transformants were generated by conventional lithium acetate and polyethylene glycerol procedures with selectable or counter-selectable transforming DNA. Insertions at the PRM1 ORF were obtained by a two-step process in which a construct containing I-SceI and its restriction site was first inserted and subsequently replaced with a desired sequence (Storici, et al. 2003).
H2A.Z-specific polyclonal antisera were generated against a peptide specific for the C-terminus of S. cerevisiae H2A.Z (custom-generated). The HA epitope tag in the degron alleles was detected using monoclonal antibody HA.11 (Covance). Abf1 was detected using polyclonal antibodies directed towards the Abf1 C-terminus (yC-20, Santa Cruz). Histone H3-specific polyclonal antibodies were directed towards the C-terminus of human histone H3 (ab1791, abcam).
Microarray data can be obtained from NCBI GEO at series accession GSE13446.
Chromatin immunoprecipitation and QPCR
Gene expression profiling
For each strain, total RNA from four independently grown cultures was prepared using a TRIZOL procedure and spiked with RNA from the Agilent Dual-color RNA Spike-in Kit. Aminoallyl-dUTP-labeled probe was generated by reverse transcription, and hybridizations were carried out using 4×44k Agilent microarrays that cover 6256 S. cerevisiae
features, each of which are replicated 7 times on the array (Agilent design ID 015072). Dye swaps were incorporated such that for each experiment, there were 2 arrays of one dye configuration, and vice-versa. Data normalization was performed using a composite loess procedure that used 1:1 DCP probes for the spike-in loess curve (Yang, et al. 2002
). Expression ratios for each gene per array then were derived by calculating the mean of up to 7 technical replicates, while discarding any replicates that were not within 2 standard deviations.
Assaying the requirement of essential genes with degron technology
The essential genes ABF1, REB1, and STH1 were studied by regulated degradation of their encoded protein via degron alleles. Each degron allele was under the control of the pMET3 promoter, which is repressed by methionine. The REB1 and STH1 degron alleles had an arginine-capped N-terminal fusion of DHFRts and a triple-HA tag, while the ABF1 degron allele was an abf1(M1R) allele. UBR1, the N-end rule pathway E3 ubiquitin ligase, was placed under the control of a pGAL1 promoter.
To study phenotypes arising from loss of Abf1, Reb1 or Sth1, degron cultures were grown at 30°C to mid-log phase in synthetic complete media lacking methionine and cysteine with 2% raffinose and 0.1% dextrose as carbon sources. Activation of the degron was achieved by first adding galactose to a final concentration of 2% for 30 min, followed by centrifugation at room temperature to collect the cells. These cells were next grown at 37°C in rich media prewarmed at 37°C and supplemented with 2% galactose (YPAG).
Preparation of DNA for mapping nucleosome positions
Cultures in mid-log phase (which ranged from an OD600 of 0.7-0.9) were crosslinked with 1% formaldehyde for 15 min at the same temperature used for growth, followed by a quenching step for 5 min at room temperature with 0.125M glycine. Cells were washed twice with cold ddH2O prior to storage.
Approximately 20 OD600 units of cells were spheroplasted with 0.25 mg Zymolyase 100-T (Seikagaku) in 2 ml Buffer Z (1M sorbitol, 50mM Tris-Cl pH 7.4, 10mM β-mercaptoethanol) at 30°C with shaking. The spheroplasting time ranged from 30 min to 75 min, depending on the strain and media conditions used for growth. The ideal spheroplasting time was one that yielded appropriately digested chromatin (~90% mononucleosomal-sized DNA) after 20 min of micrococcal nuclease (MNase) treatment. Spheroplasts were collected by centrifugation at 4°C and resuspended in 500μl MNase digestion buffer (0.075% NP-40, 50mM NaCl, 10mM Tris-Cl pH 7.4, 5mM MgCl2, 1mM CaCl2). Chromatin was digested with 3 units of MNase (Worthington) for 20 min at 37°C. Digestions were quenched with 50mM EDTA, and spheroplasts were lysed with 0.1% SDS and centrifuged to transfer the supernatant away from insoluble material. The supernatant containing solublized chromatin was incubated at 65°C overnight with 0.4 mg/ml proteinase K to deproteinize DNA and reverse methylene crosslinks. DNA was recovered by two extractions with phenol and one extraction with chloroform, followed by ethanol precipitation and resuspension in Tris-EDTA (TE) pH 8.0 supplemented with 10 μg/ml RNase A. After a 30 min treatment at 37°C, the DNA was ready for probe generation by linear amplification.
Preparation of reference genomic DNA
Genomic DNA was prepared by purification with a Qiagen 100 column after treating spheroplasts with RNase A and proteinase K. Purified DNA was digested with MNase at room temperature to obtain DNA that ranged in size from 100-300bp. This digested DNA was phenol-extracted twice, chloroform-extracted once, and then ethanol-precipitated and resuspended in TE pH 8.0. Genomic reference probe was then prepared by linear amplification in the same manner as mononucleosomal-sized probe.
Linear amplification of DNA to generate microarray RNA probe
Probes for use in microarray experiments were prepared by linear amplification (Liu et al., 2003
) but instead of preparing aminoallyl-cDNA probe, aminoallyl-RNA probe was prepared. In brief, DNA obtained by MNase digestion was first treated with calf intestinal phosphatase (New England Biolabs (NEB)) and then thymidine-tailed using terminal dideoxytransferase (NEB). A T7 promoter was adapted to these T-tailed DNA via second strand synthesis with Klenow exo-polymerase (NEB). RNA was next generated using a MegaScript T7 RNA polymerase kit (Ambion) with a 2.3:1 ratio of aminoallyl-UTP to UTP.
Mapping nucleosome positions using tiling microarrays
Nucleosome positions were mapped using a 20bp resolution tiling microarray with the majority of the probes being identical to a previously described microarray version (Yuan et al., 2005
). We designed the remaining probes, which included coverage of the PRM1
ORF. This tiling microarray was printed using a custom arrayer and consisted of 32 print blocks with a total of 16,429 bona fide probes. Unless otherwise specified, nucleosomes were mapped in four independently grown cultures for each strain by hybridizing 5μg of mononucleosomal-sized probe and 5μg of reference genomic DNA probe. Hybridizations were conducted at 65°C for at least 12 hr prior to scanning. Dye swaps were incorporated into the experiments in a balanced manner such that with four mononucleosome:reference replicates, two were labeled as Cy3:Cy5 and the remaining two Cy5:Cy3.
Microarray data processing
Raw microarray data was processed and analyzed using custom-written software implemented with Python. Algorithms for statistical analysis were provided by the R statistics software package. A mononucleosome:reference ratio was calculated for each feature by first subtracting the feature median background intensity from the feature foreground intensity and then taking the log base 2 transformed ratio. The feature ratios in each print block were normalized for intensity-dependent bias using a LOESS regression algorithm with a smooth value of 0.4 (LOESS function provided by the R statistics package).
Preparing nucleosome position data for analysis
Analysis of nucleosome enrichment data was done using custom-written software implemented with Python that integrated statistical algorithms from the R statistics package. Nucleosome enrichment values for each experiment were determined by taking the mean of the experiment replicates and applying a centered moving average with a window of 5 features (100 bp). This moving average was strictly implemented such that no missing values were permitted within the window, and each feature in the window must be offset by 20 bp (the array resolution) from its immediate neighbor.
Generation of difference maps
While results from two experiments can be compared side-by-side, generation of a difference map that represents differences between experiments is useful to highlight how the datasets differ from one another. As nucleosome enrichment data are in log2 space, difference maps were generated by subtracting probe data for a control experiment from corresponding probe data for the second experiment. For example, to generate the difference map shown in , probe data from a control experiment that lacked the Reb1 degron were subtracted from corresponding probe data from an experiment that contained the Reb1 degron. The strains used for both experiments were grown under the same conditions.
Analysis of nucleosome position data as a one-dimensional line trace
Nucleosome positioning data shown in the Figures were generated by the Matplotlib plotting engine module for Python using a coordinate system with probe data representing nucleosome positions overlaid on the positions of features in the genome.
Generation of two-dimensional stacks of nucleosome positioning data and alignment of data at the boundary between NFRs and their downstream nucleosomes
Comparison of nucleosome positions among a set of ORFs is easily achievable by generating a two-dimensional stack in which each row represents data associated with one ORF and each column represents probe data that is relative to a defined reference point in each ORF. These two-dimensional stacks were generated using custom-written Python software for graphical visualization with Java TreeView.
For the specific purposes of this work, all two-dimensional stacks were generated for ORFs that were associated with probe data. As the resolution of the tiling microarray platform is 20bp, bins of 20bp were defined relative to the translational start site of each ORF, and available probe data 1000bp upstream and downstream of each ORF were assigned to the appropriate bin by the coordinate representing the last nucleotide of the probe. This process generated a two-dimensional stack of data arranged by ORF, but centered at the translational start site. This is not an ideal arrangement for analyzing nucleosome-free regions as the distance between translational start sites and NFRs can vary among ORFs. Therefore we developed a method of analyzing nucleosome positions about NFRs in a two-dimensional stack of data in which data for each ORF was aligned at the nucleosome downstream of the NFR.
Analyzing experimental data in aligned two-dimensional stacks
Alignments of extracted ORF data at the +1 nucleosome downstream of the NFR were calculated only for experimental data that served as controls. In this work, alignments were calculated using data from a strain isogenic to the degron strains, except that they lacked a degron allele, from a wild-type strain with the Reb1:dT7 sequence inserted into the PRM1 gene, and from a rpb1-1 strain at its permissive temperature. Nucleosome positions for the degron control strain were aligned using data under both degron-inactive and degron-active growth conditions.
Once these alignment maps were generated, experimental data were overlaid onto these maps to determine how nucleosome positioning is affected. For example, nucleosome positioning data from a strain carrying the Sth1-degron grown under degron-inducing conditions were overlaid on the alignment map generated from the control strain grown under the same conditions. Difference maps that highlighted the changes in nucleosome positions between strains were overlaid on alignment maps by first subtracting control probe data from corresponding experimental probe data, and then overlaying the differences onto alignment maps generated from nucleosome positions in the control data.