Methods

If you are using data presented in this web-site, please cite our publication:

Sedlyarov V, Fallmann J, Ebner F, Huemer J, Sneezum L, Ivin M, Kreiner K, Tanzer A, Vogl C, Hofacker I & Kovarik P (2016) Tristetraprolin binding site atlas in the macrophage transcriptome reveals a switch for inflammation resolution. Molecular Systems Biology 12: 868. PMID: 27178967

PAR-iCLIP

UV-crosslinking, immunoprecipitation and library preparation was performed as described [1,2]. Briefly, BMDMs were cultured on 15 cm cell-culture treated dishes 15x106 cells per plate in medium supplemented with 100 µM 4-thiouridine (Sigma) for 16 hours prior to experiment. The cells were then stimulated with LPS (10 ng/ml) for 6 hours. Cells were washed with PBS (Sigma) and exposed to 365 nm UV-light at 0.15 J/cm2. Subsequently, 108 cells were harvested in 3 volumes lysis buffer (50 mM Tris-HCl pH 7.4, 100 mM NaCl, 1% NP40, 0.1% SDS, 0.5% sodium deoxycholate, protease inhibitor cocktail). Lysate was treated with 10 U/µl (2 U/µl, 0.5 U/µl) RNase I and 10 U DNase I for 3 min at 37°C. TTP was immunoprecipitated with 50 µl TTP rabbit antiserum [3] bound to Protein G Dynabeads. After washing, 32P-labeled RNA adaptor (1 µmole/sample) was ligated to 3’ end of RNA. Protein-RNA complexes were eluted from beads by incubating in 20 µl 1x NuPAGE LDS sample buffer for 10 min at 70°C, separated on pre-cast 4-12% NuPAGE Bis-Tris gel and transferred to nitrocellulose membrane using wet-transfer (Bio-Rad). Radioactive signal was visualized using phosphorimager screen, and bands corresponding to TTP-RNA complexes were cut out. RNA was recovered from the membrane using 10 µl proteinase K digestion at 37°C for 40 min with shaking. RNA was reverse transcribed with Super Script III and primers specific for 3’-adaptor. cDNA was fractionated using non-denaturing 6% PAAG gel, and fragments in the ranges of 120-200 nt (high), 85-120 nt (medium) and 70-85 nt (low) were recovered by gel elution in TE buffer for 2 hours at 37°C with intensive shaking followed by circularization using Circligase II. DNA oligo complementary to BamHI site was annealed and digested with BamHI in order to linearize cDNA. cDNA was PCR-amplified with primers specific to linker regions. Library was subjected to high-throughput sequencing 100 bp single end on an Illumina HiSeq 2000 platform at at the CSF NGS unit.

Measurement of RNA stability

BMDMs, 5x106 cells were stimulated with LPS (10 ng/ml). Medium was then replaced by a fresh medium containing actinomycin D (5 µg/ml). Total RNA was isolated using TRIzol Reagent 0, 45, 90 min after addition of actinomycin D. Total RNA was isolated with TRIzol reagent according to the manufacturer protocol. Libraries were RNA-Seq prepared using SENCE mRNA-Seq Library Prep Kit (Lexogen) as described in the supplied manual. Library was subjected to high-throughput sequencing 100 bp single end on an Illumina HiSeq 2000 platform at at the CSF NGS unit.

PAR-iCLIP data analysis

PAR-iCLIP and RNA-Seq reads were pre-processed (includes demultiplexing, barcode trimming and adaptor removal with Cutadapt [4]. After quality control with FASTQC, reads were mapped to the mouse genome assembly mm9/NCBI37 using Segemehl v0.1.3-349M [5]. A peak is defined as a region with a significantly higher number of read pileup at a given genomic position than would be expected by chance. We used the Pyicos ModFDR method [6] for peak finding, together with a modified filtering algorithm for the use with PAR-iCLIP crosslink sites, which can be seen as reads of length one. Due to the nucleotide resolution of PAR-iCLIP, peak width can range from one nucleotide for very sharp signals, to several hundred nucleotides for regions with e.g. multiple consecutive binding sites. Our custom filtering method splits peak regions surrounding the highest peak signal, henceforth named summit in accordance with Pyicos, once certain height-thresholds are reached. Cutoffs were defined based on signals detected in known TTP targets. Peaks with a summit signal below 100 pileups are considered background and discarded. With a sliding window approach, starting from the summit, a peak is first split when its height falls below 30% of the summit signal. Emerging subpeaks with a summit above this cutoff and 100 pileups are then recursively split when their signal falls below 10% of their summit. Final split-peaks contain a high amount of crosslink signal and allow us to analyze protein binding sites with high resolution. Replicates of each experimental setup were analyzed separately. Width and position of peaks vary slightly between experiments. For the ranked lists of TTP and HuR target genes, we collect peaks from all replicates and filter out peaks that do not have an overlap with peaks in all other replicates. Resulting filtered peaks were then applied to downstream analysis, e.g. annotation and motif analysis.

Crosslinks derived from uniquely mapped reads in peak regions were annotated using the ENSEMBL Perl API for mouse annotation version 67. For gene statistics we applied an exon first approach, where all transcript isoforms of a target gene are taken into account: A peak region is classified as exonic if it occurs in an exon of at least one transcript isoform; it is intronic if it occurs in an intron of at least one isoform and never in an exon.

References

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  2. König, J., Zarnack, K., Rot, G., Curk, T., Kayikci, M., Zupan, B., … Ule, J. (2010). iCLIP reveals the function of hnRNP particles in splicing at individual nucleotide resolution. Nature Structural & Molecular Biology, 17(7), 909–15. doi:10.1038/nsmb.1838
  3. Kratochvill, F., Machacek, C., Vogl, C., Ebner, F., Sedlyarov, V., Gruber, A. R., … Kovarik, P. (2011). Tristetraprolin-driven regulatory circuit controls quality and timing of mRNA decay in inflammation. Molecular Systems Biology, 7, 560. doi:10.1038/msb.2011.93
  4. Martin, M. (2011, May 2). Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet.journal. Retrieved from http://journal.embnet.org/index.php/embnetjournal/article/view/200/479
  5. Althammer, S., González-Vallinas, J., Ballaré, C., Beato, M., & Eyras, E. (2011). Pyicos: a versatile toolkit for the analysis of high-throughput sequencing data. Bioinformatics (Oxford, England), 27(24), 3333–40. http://doi.org/10.1093/bioinformatics/btr570