Abstract
BackgroundNext generation sequencing is a key technique in small RNA biology research that has led to the discovery of functionally different classes of small non-coding RNAs in the past years. However, reliable annotation of the extensive amounts of small non-coding RNA data produced by high-throughput sequencing is time-consuming and requires robust bioinformatics expertise. Moreover, existing tools have a number of shortcomings including a lack of sensitivity under certain conditions, limited number of supported species or detectable sub-classes of small RNAs.ResultsHere we introduce unitas, an out-of-the-box ready software for complete annotation of small RNA sequence datasets, supporting the wide range of species for which non-coding RNA reference sequences are available in the Ensembl databases (currently more than 800). unitas combines high quality annotation and numerous analysis features in a user-friendly manner. A complete annotation can be started with one simple shell command, making unitas particularly useful for researchers not having access to a bioinformatics facility. Noteworthy, the algorithms implemented in unitas are on par or even outperform comparable existing tools for small RNA annotation that map to publicly available ncRNA databases.Conclusionsunitas brings together annotation and analysis features that hitherto required the installation of numerous different bioinformatics tools which can pose a challenge for the non-expert user. With this, unitas overcomes the problem of read normalization. Moreover, the high quality of sequence annotation and analysis, paired with the ease of use, make unitas a valuable tool for researchers in all fields connected to small RNA biology.
Highlights
Generation sequencing is a key technique in small RNA biology research that has led to the discovery of functionally different classes of small non-coding RNAs in the past years
On the technical side, existing tools cover particular aspects of sequence annotation which means that complete annotation including all types of sncRNAs requires installation of a set of programs with different dependencies, some of which are restricted to specific operating systems
Illustrating the complexity of the task, a typical annotation process could include the following steps: i) 3’ adapter recognition with Minion [8] or DNApi [9], ii) adapter trimming with e.g. reaper [8] or cutadapt [10], iii) filtering of low complexity sequences with dustmasker [11] or RepeatSoaker [12], iv) miRNA annotation with Chimira [13], v) annotation of tRNA-derived fragments with tDRmapper [14] or MINTmap [15], vi) annotation of other ncRNA or mRNA fragments with NCBI BLAST and, if applicable, vii) annotation of phased RNAs with PhaseTank [16] or viii) annotation of putative piRNAs by mapping sncRNA sequences to known piRNA producing loci [17]
Summary
Generation sequencing is a key technique in small RNA biology research that has led to the discovery of functionally different classes of small non-coding RNAs in the past years. Reliable annotation of the extensive amounts of small non-coding RNA data produced by high-throughput sequencing is time-consuming and requires robust bioinformatics expertise. Existing tools have a number of shortcomings including a lack of sensitivity under certain conditions, limited number of supported species or detectable sub-classes of small RNAs. Results: Here we introduce unitas, an out-of-the-box ready software for complete annotation of small RNA sequence datasets, supporting the wide range of species for which non-coding RNA reference sequences are available in the Ensembl databases (currently more than 800). Conclusions: unitas brings together annotation and analysis features that hitherto required the installation of numerous different bioinformatics tools which can pose a challenge for the non-expert user. The high quality of sequence annotation and analysis, paired with the ease of use, make unitas a valuable tool for researchers in all fields connected to small RNA biology. The unitas source code and precompiled executable files are freely available at http://www.smallrnagroup. uni-mainz.de/software.html
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