Transfer RNA fragments (tRFs) are an established class of constitutive regulatory molecules that arise from precursor and mature tRNAs. RNA deep sequencing (RNA-seq) has greatly facilitated the study of tRFs. However, the repeat nature of the tRNA templates and the idiosyncrasies of tRNA sequences necessitate the development and use of methodologies that differ markedly from those used to analyze RNA-seq data when studying microRNAs (miRNAs) or messenger RNAs (mRNAs).
Researchers from Thomas Jefferson University have developed MINTmap (for MItochondrial and Nuclear TRF mapping), a method and a software package that was developed specifically for the quick, deterministic and exhaustive identification of tRFs in short RNA-seq datasets. In addition to identifying them, MINTmap is able to unambiguously calculate and report both raw and normalized abundances for the discovered tRFs. Furthermore, to ensure specificity, MINTmap identifies the subset of discovered tRFs that could be originating outside of tRNA space and flags them as candidate false positives. A comparative analysis shows that MINTmap exhibits superior sensitivity and specificity to other available methods while also being exceptionally fast.
An example of an incomplete mature tRNA sequence
that can be found in a genomic region outside of tRNA space
The sequence shown in magenta is present on chromosome 7 and matches the first exon of several distinct isodecoders of the intron-containing tRNAIleTAT. However, the second exon of tRNAIleTAT is not present in the immediate vicinity of the shown sequence from chromosome 7. There are hundreds of such incomplete tRNA sequences in the human genome that need to be taken into account during tRF mapping and profiling.
Availability – The MINTmap codes are available through https://github.com/TJU-CMC-Org/MINTmap/ under an open source GNU GPL v3.0 license.