Computational protocol: RNA expression of TLR10 in normal equine tissues

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Protocol publication

[…] Tissue samples for RNAseq: details of these samples, generation of RNAseq data and mapping to the horse genome have been published previously [, ]. Briefly, the samples consisted of five tissue samples (kidney, jejunum, liver, spleen and mesenteric lymph node) collected from an aged gelding, lymphocytes isolated by Ficoll Paque (GE healthcare) from a healthy 11 year old welsh mountain pony gelding and RNA from lymphocytes isolated from a healthy thoroughbred mare (the same horse whose DNA the horse genome is derived from) (Additional file : Table S2). The RNA samples were extracted, prepared and sequenced on a SOLiD 3 ABi sequencer to generate 50 bp reads. These reads were mapped to the equine reference genome EquCab2 and the transcriptome data was generated as in Moreton et al. []. The data for the TLR genes was retrieved from the annotated transcriptome [data available at EBI sequence read archive (SRA) under the study accession number ERP001116 and at 10.7717/peerj.382/supp-6]. Relative expression is given as reads per kilobase per million reads (RPKM) [].Tissue samples for RT-qPCR based TLR10 expression analysis: Samples were collected post mortem from healthy animals euthanized for other reasons than this study. Approximately 5 mm3 tissue samples (kidney, spleen, liver, colon, lung, bronchial and mesenteric lymph nodes) were collected and stored in RNA later (Additional file : Table S2). Biopsies were homogenised using a 5 mm stainless steel ball-bearing in a Retsch® Bead Mill MM 301 at 30 shakes per second for 4 min (colon, lung, bronchial and mesenteric lymph nodes), 5 min (spleen) or 6 min (liver and kidney), RNA extraction was performed using the Nucleospin RNA II mini kit (Machery Nagel) according to manufacturer’s instructions. RNA was converted to cDNA using random hexamer primers (promega) and M-MLV reverse transcriptase (promega) as per manufacturer’s instructions. RNA quality was determined using RNA 6000 Nano Kit® Bioanalyser (Agilent technologies, Waldbronn, Germany), for RNA integrity numbers (RIN) see Additional file : Table S2. A cut off value of a RIN of 5 was set as the quality threshold for a sample to be included in the study as recommended for qPCR studies in Fleige and Pfaffl [].Tissues from all horses were considered to be in a “resting” state without obvious gross pathology.For each predicted TLR like horse gene the longest open reading frame was translated and aligned with known TLR1,2,6 and 10 proteins from Swissprot. All known vertebrate TLR10 genes were identified and predicted protein sequences were identified. In each case, sequences were aligned using Muscle and a phylogenetic tree generated using PhyML under the LG model with 4 rate classes and NNI tree searching and 100 bootstrap replicates. The resulting trees were visualised using Figtree ( quantitative reverse transcriptase real time PCR (RT-qPCR) experiments were designed and performed to comply with the quality controls detailed in the MIQE guidelines []. SYBR green RT-qPCR was performed on cDNA using primer sets for TLR10 and reference genes succinate dehydrogenase complex subunit A (SDHA) and Hypoxanthine phosphoribosyl transferase (HPRT) (Additional file : Table S3). Specificity of the PCR amplicons was confirmed by sequencing.The Light Cycler 480 DNA SYBR green 1 master mix (Roche) in a 20 μl reaction volume was used according to manufacturer’s instructions. Cycling conditions consisted of 98 °C for 15 min then 45 cycles of 98 °C for 15 s, 58 °C for 30 s and 72 °C for 30 s. Reactions were performed on a Light Cycler 480 96 well plate real time PCR system (Roche). Serial dilutions of control cDNA were used to assess primer efficiency. Relative expression was calculated using the following formula []: Corrected Ct value = Ct + (Nt – Ct′) * S/S′ where Ct = mean sample Ct, Nt = experimental reference gene mean, Ct′ = mean reference gene of sample, S = TLR slope, S′ = reference gene slope. […]

Pipeline specifications

Software tools PhyML, FigTree
Applications Phylogenetics, RNA-seq analysis
Organisms Equus caballus, Homo sapiens
Diseases Liver Diseases