Computational protocol: Identification of aberrant tRNA halves expression patterns in clear cell renal cell carcinoma

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Protocol publication

[…] Small RNA sequencing was performed by Biogazelle (Zwijnaarde, Belgium) as a contract service. RNA isolates from 18 corresponding normal renal and ccRCC tissues (500 ng total RNA) were sent on dry ice to Biogazelle. Small RNA libraries were sequenced on an Illumina NextSeq500. Mapping was performed using the short-read aligner Bowtie ( Bowtie is a free, open source software, which aligns ultrafast and memory-efficient Illumina reads to the human genome version 19. Mapped reads were subsequently annotated to different contaminents (tRNA, rRNA, sn(o)RNA, piRNA) and mature miRNA using Ensembl genome annotation database, UCSC Genome browser, miRBase v20, and genomic tRNA database 2009. Mismatches were not allowed. In case of multi-mapped reads, we assigned the reads to the sncRNA with the lowest offset. demonstrates mean variance plots and scatterplots of miRNA and tRNA expression levels, used to ensure internal quality assurance.Statistical analysis has been performed using the R programming language and the edgeR package following workflow proposed by Anders et al.. Therefore, Counts Per Millions (CPM) have been calculated and sncRNA having less than 1 CPM in each sample pair been removed. This reduced the number of miRNAs from 2576 to 770 and of tRNAs from 624 to 345. For further analysis read counts have been normalized to the corresponding library sizes using edgeRs calcNormFactors function and sample variation has been taken into account by calculation the dispersion coefficients using the estimateCommonDisp, estimateTagwiseDisp functions. Detection of differentially expressed sncRNA has been performed using the exact test, as suggested by Robinson and Smyth and implemented edgeRs exctTest function. Subsequently, a sncRNA has been called differentially expressed if its fold change was >2 or <(−2) and its p-value <0.05 (after Benjamini-Hochberg correction). To validate these finding a Generalized Linear Model (GLM) has been fitted to the data and detection of differentially expressed sncRNA has been done using the Likelihood Ratio Test (LRT), implemented as glmFit and glmLRT in the edgeR package, with both methods yielding identical results. Cluster and miRNA/tRNA wise expression analyses has been done using log2 normalized pseudo counts under consideration of the differentially expressed sncRNA from upstream operations. The raw data from small RNA sequencing experiments data are deposited at Gene Expression Omnibus (GEO) database (record: GSE73342) [...] To validate the expression profiling experiments, we determined the expression of three differentially regulated targets. PCR experiments were performed on an ABIPrism 7900 HT Fast Real-Time PCR System (Applied Biosystems, Foster City, CA, USA). qRT-PCR experiments were performed with an independent cohort of 118 ccRCC and 74 normal renal tissue samples. In addition, a serum cohort (30 ccRCC and 15 healthy individuals) was investigated to determine the value of sncRNA as non-invasive biomarker. Therefore, cDNA was synthesized with 500 ng RNA using the miScript II RT Kit (Qiagen, Hilden, Germany). Quantitative real-time PCR (qRT-PCR) was performed with 5 ng/μl cDNA (tissue) or 6 μl (serum) cDNA template using Qiagen miScript SYBR Green PCR technology (Hilden, Germany). A pre-designed miScript Primer Assay was used to quantify the reference gene SNORD43 (MS00007476) and the target gene miR-122-5p (MS00003416) and miR-142-3p (MS00031451); a custom made miScript Primer Assay (MSC0074992) was used to detect 5′tRNA4-Val-AAC. Data were analyzed using Qbase+ (Biogazelle) with SNORD43 as reference gene in the 2−∆∆CT algorithm; target genes were scaled to the control group. Statistical analyses (Mann-Whitney-U test) were performed with SPSS Statistics v21 (IBM, Ehningen, Germany). […]

Pipeline specifications

Software tools Bowtie, edgeR, qbase+, SPSS
Databases miRBase GtRNAdb UCSC Genome Browser
Applications Miscellaneous, sRNA-seq analysis, qPCR
Diseases Carcinoma, Renal Cell