RNA molecules are not just simple messengers that carry genetic information. They are chemically modified in many ways, and these modifications can influence how genes are regulated and how cells function. Detecting these changes across the entire transcriptome has been challenging, especially at high resolution.

Researchers at the Centre for Genomic Regulation (CRG) have developed a new method called FIRST-seq to better study RNA modifications and structure. The approach is based on nanopore sequencing, which allows long RNA molecules to be read in a single pass.

Comparison of reverse transcriptase (RT) performance in
MgCl2 and MnCl2 buffers across different enzymes

(a) Schematic comparing workflows of dcDNA-seq and FIRST-seq. FIRST-seq simplifies the process by sequencing only the first cDNA strand, eliminating the need for strand-switching and second-strand synthesis. This allows for the use of a broader range of reverse transcriptases and avoids strand-switching artifacts. dcDNA-seq, on the other hand, captures both strands, but is limited by the requirement of strand-switching for fulllength cDNA synthesis

FIRST-seq takes advantage of how RNA modifications affect reverse transcription, a step where RNA is converted into DNA for sequencing. Certain modifications cause errors or pauses during this process, and these patterns can be used as signals to identify where modifications occur.

A key advantage of this method is its simplicity. It avoids additional steps like second-strand synthesis and PCR amplification, which can introduce bias or obscure signals. This makes the workflow more flexible and compatible with different enzymes and experimental conditions.

The researchers also optimized the process by testing different reverse transcriptase enzymes and reaction conditions. This helped reduce unwanted interruptions during sequencing and improved the ability to detect modification-related signals with higher accuracy.

When combined with chemical probing techniques, FIRST-seq was able to map RNA structure and identify specific modifications such as m1A and m3C at single-nucleotide resolution. The method successfully reproduced known RNA structures both in laboratory experiments and in living systems.

Overall, this approach provides a powerful and cost-effective way to study RNA biology in greater detail. By improving how RNA sequencing captures modifications and structure, it opens new opportunities for understanding gene regulation, disease mechanisms, and cellular function.

Availability – All code has been deposited in GitHub (https://github.com/novoalab/firstseq).