Nanopore direct RNA sequencing (DRS) is an advanced technology that allows scientists to study RNA molecules directly, without converting them into cDNA (complementary DNA) first. This direct approach provides detailed insights into RNA, including native modifications, which are important for understanding gene expression and regulation. However, one challenge with this technique is the lack of efficient methods to handle multiple samples simultaneously, which can be costly and time-consuming.

SeqTagger is a new method developed by researchers at the Centre for Genomic Regulation (CRG) to make direct RNA sequencing more efficient and cost-effective. It allows researchers to process multiple RNA samples at once—up to 96 samples—using a technique called multiplexing. This means that scientists can analyze many different RNA samples together in a single sequencing run, saving both time and resources.

Schematic overview of the direct RNA sequencing (DRS) demultiplexing workflow

(A) Overview of the barcoded direct RNA sequencing workflow in which the standard reverse transcription adapter (RTA) is replaced with a barcode-containing adapter. Following adapter ligation and reverse transcription the RNA ligation adapter (RLA), containing the helicase enzyme, is ligated, making the library sequencing-ready. (B) Overview of the demultiplexing workflow performed by SeqTagger. The algorithm first segments the raw current intensity signal by identifying the poly-(A)-tail signal to extract the barcode-containing RT adapter. Following signal normalisation, the DNA sequence is basecalled and aligned to a set of reference barcodes. Finally, a filtering step is applied based on the median base quality (BaseQ) to remove misassigned barcode sequences.

The beauty of SeqTagger lies in its high precision and accuracy. With 99% precision and 95% recall, SeqTagger can accurately identify which sample each RNA molecule belongs to, even in complex datasets. This method works well with different RNA types, whether they have a standard poly-(A) tail or are custom libraries like Nano-tRNAseq, which don’t follow the usual patterns.

SeqTagger can be used both on its own or as part of a larger system called MasterOfPores NextFlow, making it flexible and adaptable to various laboratory setups. By enabling more accurate and efficient multiplexing, SeqTagger reduces the costs associated with RNA sequencing, especially when working with small or limited biological samples.

In summary, SeqTagger addresses some of the key limitations of nanopore direct RNA sequencing, such as handling multiple samples and improving precision. This development paves the way for more cost-effective and high-quality RNA analysis, which will be crucial for advancing research in fields like gene regulation, disease mechanisms, and personalized medicine.

Availability – https://github.com/novoalab/SeqTagger/

Pryszcz LP, Diensthuber G, Llovera L, Medina R, Delgado-Tejedor A, Cozzuto L, Ponomarenko J, Novoa EM. (2025) Rapid and accurate demultiplexing of direct RNA nanopore sequencing datasets with SeqTagger. Genome Res [Epub ahead of print]. [article]

Nanopore direct RNA sequencing (DRS) is an advanced technology that allows scientists to study RNA molecules directly, without converting them into cDNA (complementary DNA) first. This direct approach provides detailed insights into RNA, including native modifications, which are important for understanding gene expression and regulation. However, one challenge with this technique is the lack of efficient methods to handle multiple samples simultaneously, which can be costly and time-consuming.

SeqTagger is a new method developed by researchers at the Centre for Genomic Regulation (CRG) to make direct RNA sequencing more efficient and cost-effective. It allows researchers to process multiple RNA samples at once—up to 96 samples—using a technique called multiplexing. This means that scientists can analyze many different RNA samples together in a single sequencing run, saving both time and resources.

Schematic overview of the direct RNA sequencing (DRS) demultiplexing workflow

(A) Overview of the barcoded direct RNA sequencing workflow in which the standard reverse transcription adapter (RTA) is replaced with a barcode-containing adapter. Following adapter ligation and reverse transcription the RNA ligation adapter (RLA), containing the helicase enzyme, is ligated, making the library sequencing-ready. (B) Overview of the demultiplexing workflow performed by SeqTagger. The algorithm first segments the raw current intensity signal by identifying the poly-(A)-tail signal to extract the barcode-containing RT adapter. Following signal normalisation, the DNA sequence is basecalled and aligned to a set of reference barcodes. Finally, a filtering step is applied based on the median base quality (BaseQ) to remove misassigned barcode sequences.

The beauty of SeqTagger lies in its high precision and accuracy. With 99% precision and 95% recall, SeqTagger can accurately identify which sample each RNA molecule belongs to, even in complex datasets. This method works well with different RNA types, whether they have a standard poly-(A) tail or are custom libraries like Nano-tRNAseq, which don’t follow the usual patterns.

SeqTagger can be used both on its own or as part of a larger system called MasterOfPores NextFlow, making it flexible and adaptable to various laboratory setups. By enabling more accurate and efficient multiplexing, SeqTagger reduces the costs associated with RNA sequencing, especially when working with small or limited biological samples.

In summary, SeqTagger addresses some of the key limitations of nanopore direct RNA sequencing, such as handling multiple samples and improving precision. This development paves the way for more cost-effective and high-quality RNA analysis, which will be crucial for advancing research in fields like gene regulation, disease mechanisms, and personalized medicine.

Availability – https://github.com/novoalab/SeqTagger/

Pryszcz LP, Diensthuber G, Llovera L, Medina R, Delgado-Tejedor A, Cozzuto L, Ponomarenko J, Novoa EM. (2025) Rapid and accurate demultiplexing of direct RNA nanopore sequencing datasets with SeqTagger. Genome Res [Epub ahead of print]. [article]

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