Computational protocol: Binding to RNA regulates Set1 function

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Protocol publication

[…] Cells in exponential phase were crosslinked with a Megatron for 100 s (Set1) and 50 s (Rpb1), harvested by centrifugation, resuspended in 2.4 volume/g of cells of TN150 buffer (50 mM Tris pH 7.8, 150 mM NaCl, 0.1% NP-40 and 5 mM beta mercaptoethanol) supplemented with protease inhibitors (complete, Mini, EDTA-free Protease Inhibitor Cocktail). This suspension was flash frozen in droplets and cells were mechanically broken using the Mixer Mill MM 400 by doing five cycles of 3 min at 20 Hz. A non-crosslinked sample was treated in parallel as a background control.Powders were thawed and the resulting extracts were treated for one hour at 25 °C with DNase I (165 U/g of cells) to solubilize chromatin and then clarified by centrifugation for 20′ at 20 000 g at 4 °C. Subsequent purifications steps were performed essentially as described with minor modifications from Granneman et al. []. For both nPTH-Set1 and Rpb1-HTP strains, adaptors were modified in order to sequence RNA molecules from the 3′-end.The RNA was recovered after proteinase K treatment and reverse transcribed using specific primers. The resulting complementary DNA was used to perform multiple PCR reactions in a final volume of 25 μl using the following conditions: 0.4 μM of each primers 0.2 mM dNTP, 2.5 U LA Taq DNA polymerase from Takara, 1X LA PCR Buffer II and 2 μl of complementary DNA per reaction with the programme: 2′ at 95 °C, (30′′ at 95 °C, 45′′ at 58 °C, 1′ at 72 °C) × 13 cycles, 5′ at 72 °C. PCR were pooled and treated with 200 U of Exonuclease I (NEB) per milliliter of PCR reaction for 1 h at 37 °C. After Exonuclease I inactivation for 20′ at 80 °C, DNA was purified on PCR clean up columns (NucleoSpin Gel and PCR Clean-up, Macherey-Nagel, Düren, Germany) and sequenced using Illumina technology (San Diego, CA, USA). Primers are indicated in .Samples were demultiplexed using the pyBarcodeFilter script from the pyCRAC utility suite. Subsequently, the 3′ adaptor is clipped with Cutadapt and the resulting insert is quality trimmed from the 3′-end using Trimmomatic rolling mean clipping (window size=5, minimum quality=25). At this stage, the pyCRAC script pyFastqDuplicateRemover is used to collapse PCR duplicates and ensure each insert is represented only once. Each unique insert in our library is associated with a six-nucleotides random tag within the 5′ adaptor. The resulting sequences are reverse complemented with Fastx_reverse_complement (part of the fastx toolkit []), and mapped to the R64 genome (sgd) with bowtie2 (-N 1 –f).Read counts were normalized relative to reads derived from an S. pombe spike that was added to S. cerevisiae cells before the crosslinking step. The S. pombe spike cells contain a non-relevant protein tagged with the same HTP tag that was co-purified with the S. cerevisiae material. The positionally weighted average poly(A) addition site (wPAS) for every gene was calculated by weighting the position of each poly(A) site using its intensity and calculating an average position. [...] ChIP of Myc-Set1 and PTH-Set1 were performed as previously described [] with 9E10 (anti-MYC, Santa Cruz Biotechnology, Dallas, TX, USA) and anti-Set1 monoclonal antibodies (P Nagy, University of Toronto, Toronto, Canada). Libraries were prepared from fragmented DNA using the Chip-seq MicroPlex Library Preparation Kit v2 samples preparation (Diagenode, Seraing, Belgium) according to the manufacturer’s instructions. In all, 2 ng from IP samples were used as the starting material. Each library was barcoded using MicroPlex Single Index (Diagenode): iPCRtagT5, T6, T7 and T8 and amplified for 10 and 6 cycles for IP and input samples, respectively. Each library was quantified on Qubit with Qubit dsDNA HS Assay Kit (Life Technologies, Carlsbad, CA, USA) and then, size distribution was examined on the Bioanalyser with High Sensitivity DNA chip (Agilent, Santa Clara, CA, USA), to ensure that the samples have the proper size, no adaptor contamination and to estimate sample molarity. Each library was diluted to 4 nM and then pulled together at equimolar ratio. Libraries were denatured according to the manufacturer’s instruction and sequenced on a mid-output flow cell (130 M clusters) using the NextSeq 500/550 High Output v2 150 cycles kit (Illumina), in paired-end 75/7 nt mode, according to the manufacturer’s instructions. In all, 148 million (M) paired-end reads were generated (34–39 M per sample) with 93% >= Q30.ChIP-Seq data quality was assessed using FastQC. FasQC: a quality control tool for high-throughput sequence data. Available online at: Sequencing reads (FastQ format) were mapped to the Saccharomyces cerevisiae genome (sacCer3) using BFAST alignment tool with default parameters [] (PMID 19907642) to obtain a Binary Alignment Mapped (BAM) file. The sorted BAM files were used to determine average profiles of ChIP-Seq read density using ngs.plot software [], (PMID 24735413) around the transcription start site. Read counts were normalized to the total number of million uniquely mapped reads or to read count per million of mapped reads (RPM). The RPM values allow samples to be compared regardless of differences in sequencing depth. To generate BedGraphs for visualization on genome browsers, ChIP-Seq BAM files were processed using HOMER package. The tag directory for each sample was then created using the makeTagDirectory tool and the corresponding BedGraph was generated using makeUCSCfile tool with default options. Only uniquely mappable reads (non-secondary alignment) were considered to create BedGraphs with a normalization to 10 million mapped reads for each sample. To compare Set1 binding positions on RNA with Set1 occupancy on genes of interest, the Multicov command from Bedtools [] was used to obtain read counts within each gene.For ChIP-qPCR, samples were prepared as previously described []. DNA was analyzed by real-time qPCR using SYBR Green Premix Ex Taq (Takara, Mountain View, CA, USA) in a Rotor Gene 6000 (Corbett Research, Labgene, Archamps, France). Primers are listed in . The following antibodies were used: anti-H3 (Abcam1791, Cambridge, UK), anti-H3K4me2 (Abcam-ab7766, Cambridge, UK), anti-H3K4me3 (Abcam-ab8580), anti-Myc 9E10 (Santa Cruz Biotechnology-sc-40) and anti-Rap1 (V. Géli’s laboratory, Marseille, France). […]

Pipeline specifications

Software tools FastQC, BFAST, ngs.plot, BEDTools
Application ChIP-seq analysis