Evaluation of Bioinformatics Approaches for Next-Generation Sequencing Analysis of microRNAs with a Toxicogenomics Study Design.

摘要: MicroRNAs (miRNAs) are key post-transcriptional regulators that affect protein translation by targeting mRNAs. Their role in disease etiology and toxicity well recognized. Given the rapid advancement of next-generation sequencing techniques, miRNA profiling has been increasingly conducted with RNA-seq, namely miRNA-seq. Analysis miRNA-seq data requires several steps: (1) mapping reads to miRBase, (2) considering mismatches during hairpin alignment (windowing), (3) counting (quantification). The choice made each step respect parameter settings could quantification, differentially expressed miRNAs (DEMs) detection novel identification. Furthermore, these parameters do not act isolation their joint effects impact results interpretation. In toxicogenomics, variation associated setting should overpower treatment effect (such as dose/time-dependent effect). this study, four commonly used analysis tools (i.e., miRDeep2, miRExpress, miRNAkey, sRNAbench) were comparatively evaluated a standard toxicogenomics study design. We tested 30 different on generated from thioacetamide-treated rat liver samples for three dose levels across time points, followed normalization options. Because both miRExpress miRNAkey yielded larger than multiple settings, our analyses mainly focused side-by-side comparison between miRDeep2 sRNAbench. While number detected was almost subset those sRNAbench, DEMs identified comparable under same method. Change nucleotides out mature sequence (window option) largest quantification detection. However, such is relatively small compared when more critical interpret toxicological effect. methods introduced large DEMs, toxic behavior thioacetamide showed consistency trend time-dose responses. Overall, found be preferable over other choices window option allowed up ends.