unitas: the universal tool for annotation of small RNAs

Abstract

Background: Next 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. 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). 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 base on available ncRNA sequence information. 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. 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.

miR-206 family is important for mitochondrial and muscle function, but not essential for myogenesis in vitro

“…In general, mapped percentage is more than 95%. Unitas v.1.5.1 (with SeqMap v1.0.13) (Gebert et al, 2017; Jiang and Wong, 2008) was used for miRNA abundance quantification with setting –species_miR_only –species mus_musculus to map the reads to mouse sequence of miRBase Release 22 (Kozomara et al, 2019). This setting (equivalent to –tail 2 –intmod 1 –mismatch 1 –insdel 0) will allow 2 non-templated 3’ nucleotides and 1 internal mismatch for miRNA mapping.…”

tRNA-derived fragments and microRNAs in the maternal-fetal interface of a mouse maternal-immune-activation autism model

“…Total number of mapped reads and percentage of mapping is summarized in Table S1. To quantify small RNAs, unitas v1.7.3 [105] (with SeqMap v1.0.13 [106]) was used to map the reads to mouse sequence of miRBase Release 22 [107], genomic tRNA database [108], Ensembl Release 96 and SILVA rRNA database Release 132. Unitas setting (-species_miR_only -species mus_musculus) was used.…”

Conserved and ubiquitous expression of piRNAs and PIWI genes in mollusks antedates the origin of somatic PIWI/piRNA expression to the root of bilaterians

“…We further observed a smaller fraction of RNAs in the range of 24-29 nt in both probes (Figure 2A). sRNA sequence annotation with unitas (Gebert et al 2017) revealed a similar proportion of different sRNA classes in the two probes, with miRNAs accounting for 46% and 51% of reads in the reproductive tract and muscle, respectively ( Figure 2B). Interestingly, we ascertained a substantial difference considering the abundance of tRNA fragments (tRFs).…”