TruSeq RNA Library Prep Kit v2

Protocol tips

Upstream tips	Protocol tips	Downstream tips
	0.1 - 1 ug total RNA or 10 - 400 ng previously isolated mRNA (from species with polyA tails)

Protocol tips
0.1 - 1 ug total RNA or 10 - 400 ng previously isolated mRNA (from species with polyA tails)

Publication protocol

The RNA, extracted with the RNeasy Mini Kit (Qiagen, Valencia, CA) from the two, carefully washed clones of PC12, wtPC12, and hrPC12 (previously referred to as PC12-27, D'Alessandro et al., 2008), was analyzed in duplicate with the Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA). Libraries, prepared starting from 2 μg of RNA/sample with the Illumina TruSeq RNA Sample Prep kit v2 procedure, were quantified by the Qubit BR assay (Life Technologies, Illkirch, France) and the Agilent 2100 Bioanalyzer, and sequenced on the Illumina HiSeq 2000 platform. On average we obtained about 90 million 100 bp PE (paired-end) reads per sample. Quality control of the obtained reads, and alignment to the rat reference genome (RGSC3.4/rn4) were performed using FASTQC suite with default parameters (FastQC, a quality control tool for high throughput sequence data, http://www.bioinformatics.babraham.ac.uk/projects/fastqc/) and the TopHat aligner (Trapnell et al., 2009). Gene expression read counts were exported and analyzed in R to identify differential expressed genes (DEGs), using the DESeq Bioconductor library (Anders and Huber, 2010). Genes with a baseMean value for all samples of < 5 or showing 0 reads as baseMean in either wtPC12 or hrP12 cells were filtered out to avoid infinite and 0 values of log 2-fold changes. P-values were adjusted using a threshold for false discovery rate (FDR) ≤ 0.01 (Benjamini and Hochberg, 1995). Genes listed as DEGs are reported in Table S1. Genes additionally filtered for absolute values of |log2 FC| > 2 (total 1770), were used for further analysis. Density and Volcano plot analyses, performed in R and heatmaps of expression values, were plotted with the pHeatmap library. Raw data are available through Gene Expression Omnibus (GEO) (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE59946). Further details about the methods employed can be found in Garcia-Manteiga et al. (2015).

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