Computational protocol: Translatome Regulation in Neuronal Injury and Axon Regrowth

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[…] Cre driver lines were crossed with RiboTag mice to generate animals heterozygous for Cre and homozygous for the Rpl22-HA allele, except for Advillin-Cre crosses that were used as heterozygotes for both alleles. Tissues were extracted and HA immunoprecipitation (IP) was conducted as previously described (), with slight modifications. Briefly, DRG or neurons resuspended from culture were homogenized on ice in supplemented homogenization buffer [50 mM Tris (pH 7.0), 100 mM KCl, 12 mM MgCl2, 1% NP-40, and 1 mM DTT, 1.5× protease inhibitor cocktail, 300 units/ml RNasin (Promega), 150-µg/µl cyclohexamide, and 200 mM RVC] using 2-ml glass Teflon Potter Elv tissue grinders. After homogenization, lysates were transferred to Eppendorf tubes and centrifuged at 4°C for 10 min at 6,932 × g. Supernatants were collected to low bind tubes and 10% of each sample was set aside as input; 5 µg of anti-HA antibody was added to each sample and incubated on rotator for 4 h at 4°C. Magnetics beads were washed with the homogenization buffer and added to the Ab-homogenates mix, 100 µl of beads per sample, for overnight incubation at 4°C on rotor. Beads were washed three times, 5 min each, with high salt buffer [50 mM Tris (pH 7.0), 300 mM KCl, 12 mM MgCl2, 1% NP-40, and 1 mM DTT, 1× protease inhibitor cocktail, 200 units/ml RNasin, and 150-µg/µl cycloheximide]. After washes, RNA was eluted and purified using the Qiagen RNeasy micro kit including on-column DNase digestion.RNA-seq libraries were prepared in three to five replicates per condition, using at least 5 ng of starting total RNA for each replicate. Processing was with Ribo-Zero Gold (Epicentre), using the Ovation RNA-seq system V2 (NuGEN). After library preparation, amplified double-stranded cDNA was fragmented into 125 bp (Covaris-S2) DNA fragments, which were (200 ng) end-repaired to generate blunt ends with 5’-phosphates and 3’-hydroxyls and adapters ligated. The purified cDNA library products were evaluated using the Agilent Bioanalyzer and diluted to 10 nM for cluster generation in situ on the HiSeq paired-end flow cell using the CBot automated cluster generation system. All samples were multiplexed into a single pool to avoid batch effects () and sequenced using an Illumina HiSeq 2500 Sequencer (Illumina) across multiple lanes of 50-bp paired-end sequencing, corresponding to three samples per lane and yielding between 44 and 85 million reads per sample. Quality control was performed on base qualities and nucleotide composition of sequences, with removal of outliers. Alignment to the Mus musculus (mm10) refSeq (refFlat) reference gene annotation was performed using the STAR spliced read aligner () with default parameters. On average, 83.7 ± 8% of the reads mapped uniquely to the mouse genome. Total counts of read-fragments aligned to candidate gene regions were derived using the HTSeq program (http://htseq.readthedocs.io/) with mouse mm10 (December 2011) refSeq (refFlat table) as a reference and used as a basis for the quantification of gene expression. Only uniquely mapped reads were used for subsequent analyses. Differential expression analysis was conducted with R-project and the Bioconductor package edgeR (). Statistical significance of the differential expression was determined at false discovery rate (FDR) <0.1 ().RNA-seq data were deposited within the Gene Expression Omnibus (GEO) repository (www.ncbi.nlm.nih.gov/geo), accession numbers GSE102316 (RiboTag data from DRG ganglia) and GSE110374 (RiboTag data from neuronal cultures). The Matlab function “clustergram” was used for generating hierarchical trees of differentially expressed genes (DEGs) and generating heatmaps. The “cosine” option was used for distance measurement (“Pdist value”) using average linkage (“LinkageValue”). No standardization was used. Gene ontology (GO) term enrichment analyses were done with the Ontologizer GO analysis tool (; http://ontologizer.de/webstart/), using total genome entries as background and the topology-weighted algorithm to identify-enriched GO terms. […]

Pipeline specifications

Software tools STAR, HTSeq, edgeR, Ontologizer
Databases GEO
Application RNA-seq analysis