Researchers at the Max Planck Institute of Biochemistry report that they have developed a better way to measure the amount of transfer RNAs (tRNAs) in cells. Mim-tRNAseq, which is described in a Molecular Cell paper published last month, can be used to quantify tRNAs in any organism.
The levels of individual tRNAs are dynamically regulated in different tissues and during development, and tRNA defects are linked to neurogical diseases and cancer. The molecular origins of these links remain unclear, because quantifying the abundance and modifications of tRNAs in cells has long remained a challenge. Now, according to Danny Nedialkova, senior author of the paper, there is method that accurately measures the abundance and modification status of different tRNAs in cells.
To measure the levels of multiple RNAs simultaneously, scientists use reverse transcriptase to first rewrite RNA into DNA. Millions of these DNA copies can then be quantified in parallel by high-throughput sequencing. Rewriting tRNAs into DNA has been tremendously hard since many tRNA modifications block the reverse transcriptase, causing it to stop synthesizing DNA.
"Many researches have proposed elegant solutions to this problem, but all of them relieve only a fraction of the modification roadblocks in tRNAs," explains Nedialkova. "We noticed that one specific reverse transcriptase seemed to be much better at reading through modified tRNA sites. By optimizing the reaction conditions, we could significantly improve the enzyme's efficiency, enabling it to read through nearly all tRNA modification roadblocks," adds Nedialkova. This made it possible to construct DNA libraries from full-length tRNA copies and use them for high-throughput sequencing.
The analysis of the resulting sequencing data also presented significant challenges. "We identified two major issues: the first one is the extensive sequence similarity between different tRNA transcripts," explains Andrew Behrens, first author of the paper. "The second one comes from the fact that an incorrect nucleotide is introduced at many modified sites during reverse transcription. Both make it extremely challenging to assign each DNA read to the tRNA molecule it originated from," adds Behrens.
The team tackled these issues with novel computational approaches, including the use of modification annotation to guide accurate read alignment. The resulting comprehensive toolkit is packaged into a freely available pipeline for alignment, analysis and visualization of tRNA-derived sequencing data. Researchers can use mim-tRNAseq to not only measure tRNA abundance, but also to map and quantify tRNA modifications that induce nucleotide misincorporations by the reverse transcriptase.