sRNAbench: profiling of small RNAs and its sequence variants in single or multi-species high-throughput experiments

The availability of high-throughput sequencing (HTS) technologies plays now a pivotal role in the expression profiling of known small RNAs and the discovery of novel classes of non-coding RNA [1]. Over the last decade, in both plants and animals a notable number of novel small RNA classes have been described [2, 3]. It became apparent that the biogenesis of microRNAs and other small RNA classes, their contribution to gene regulation mechanisms and the cellular control of their expression are more complex than previously envisioned. Therefore, apart from microRNA profiling and detection, the analysis of other small RNAs became an important task. In plants, small interfering RNAs (siRNA), trans-acting RNAs (ta-RNA) and heterochromatic siRNAs have been shown to regulate gene expression and being responsible for the deposition of repressive chromatin marks (DNA methylation and histone marks) [4]. In animals, apart from microRNAs and piRNAs, other putatively important processed small RNA fragments do exist, including yRNA, tRNA and snoRNA fragments [5, 6]. Furthermore, microRNAs are reproducibly diversified at the sequence level in both animals and plants, including posttranscriptional modifications such as adenylation [7–9]. Many tools have been developed to analyze HTS small RNA data covering many crucial aspects, such as quality control, expression profiling, prediction of novel microRNAs, snoRNAs, tRNAs, piRNAs or ta-siRNAs, identification of siRNAs or piRNAs clusters and isomiR quantification. In order of appearance: small RNA toolkit Abstract: MicroRNAs and other small RNAs are known to play important functions in gene regulation. Over the last years, it became also apparent that many virus genomes encode microRNAs and that those strongly interact with the host transcriptome. Important functions include the evasion of the immune response and the regulation of the switch to lytic infection. Since the advent of deep sequencing protocols for small RNAs, expression profiles can be routinely determined. However, currently the tools developed for the data analysis of small RNA deep sequencing experiments are limited to the analysis of only one species at a time. In order to facilitate the analysis of experimental setups that include genetic material from several species, we developed sRNAbench. It maintains the main features implemented in its predecessor program, miRanalyzer, and includes new functionalities such as full isomiR support including statistical test on differential frequency, improved prediction of novel microRNAs, extended summary files and data visualization support. Both a standalone program and a webserver are available at: http://bioinfo5.ugr.es/sRNAbench/. Research Article Open Access