Rna clean and concentrator spin columns

Frozen tissues were shipped to MOgene, Inc. (St. Louis, MO) on dry ice. High quality RNA was isolated (RNA Integrity Number of 7.5-10 and 28S/18S ratio of 1.6-2.1) and confirmed with an Agilent Bioanalyzer at MOgene, Inc. Five hundred ng of total RNA was amplified using Agilent QuickAmp Labeling Kit (no dye) and purified using Zymo Research RNA Clean and Concentrator spin columns. Three μg of amplified RNA was Cy-labeled using the Kreatech ULS Labeling Kit, fragmented according to Agilent specifications and hybridized to the Agilent sheep gene expression microarray (Agilent Technologies, Santa Clara CA) for 17 hours at 65°C and 10 rpm. Slides were scanned on an Agilent C scanner (20 bit) at 5 μm resolution. Sixteen microarray hybridizations were performed, each with samples from an ANG II, losartan infused fetus (n = 4 for each), or a paired twin control (n = 8), using a mixed design on 2 slides with 8 microarrays per slide. Microarray data were submitted to the NCBI Gene Expression Omnibus (GEO), and can be accessed at http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE45463 (project accession no. GSE45463).

RNA-seq libraries were made following the previously established SMARTseq2 protocol^{38 (link)}. Briefly, total RNA was extracted using Qiazol (Qiagen) from 300 CART19 cells and recovered by RNA Clean and Concentrator spin columns (Zymo) followed by incubation with Oligo-dT. The transcription reaction was carried out on 100pg of cDNA for 1min at 55°C. Libraries were uniquely barcoded^{39 (link)} and amplified for 14 cycles. Fragment size distribution was verified, and paired-end sequencing (2 x 75 bp reads) was carried out on an Illumina NextSeq 500.
Raw reads were mapped to the GRCh37/hg19 genome assembly using the RNA-seq aligner STAR (version 2.5.4b)^{40 (link)}. The algorithm was given known gene models provided by GENCODE (release_27_hg19, www.gencodegenes.org) to achieve higher mapping accuracy. Quantification was also performed by STAR using the --quantMode GeneCounts flag. Raw counts were normalized (TMM normalization implemented in edgeR, followed by the voom transformation). Lastly the Bioconductor package limma was used to assess differential expression using linear models. Genes with differential expression at a false discovery rate (FDR) < 0.05 and a log fold change (LFC) > 0.5 between replicates were considered for further analysis. Visualization was performed using the R package ggplot2.