RNA sequencing approach offers real-time and programmable transcriptome sequencing

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The high complexity and diversity of the eukaryotic transcriptome poses significant challenges for the efficient detection of specific transcripts. Conventional targeted RNA-seq methods often require labor-intensive pre-sequencing enrichment steps, which can compromise comprehensive transcriptome profiling and limit their broader applications.

Recently, Prof. Zhao Fangqing's team from the Institute of Zoology of the Chinese Academy of Sciences, has developed a novel targeted RNA sequencing approach called PROgrammable Full-length Isoform Transcriptome sequencing (PROFIT-seq). This strategy effectively captures a broad spectrum of transcriptome samples, providing effective enrichment of target transcripts while maintaining unbiased quantification of the entire transcriptome.

The study, titled "Real-time and programmable transcriptome sequencing with PROFIT-seq," was published in Nature Cell Biology.

PROFIT-seq introduces a programmable transcriptome sequencing strategy that leverages an AI-driven adaptive sequencing algorithm. Unlike conventional methods that rely on complex experimental enrichment, PROFIT-seq requires only the sequence information of the targets, enabling real-time, flexible, and programmable enrichment of different transcript types.

It also employs a rolling circle amplification technique to generate full-length cDNA read-through products that facilitate correction of nanopore sequencing errors, resulting in high-fidelity consensus transcript sequences.

In addition, PROFIT-seq employs combinatorial reverse transcription to capture polyadenylated, non-polyadenylated, and circular RNAs. It also integrates an EM-based model to achieve unbiased transcriptome quantification using both fully sequenced targets and partially rejected sequences, providing efficient and accurate single-molecule characterization of any target transcript.

The research team further demonstrated the applicability of PROFIT-seq across various scenarios. In clinical samples, PROFIT-seq significantly increased the detection throughput of target pathogen transcripts and reduced the time required to identify key pathogen mutations through real-time enrichment of pneumonia-associated pathogens in sputum samples.

Additionally, PROFIT-seq enabled simultaneous detection of colorectal cancer-associated microbiota and host immune repertoire sequences, revealing intricate interactions between the host immune system and gut microbiota during the malignant transformation of colorectal polyps.

Overall, PROFIT-seq offers a powerful tool for accurate and efficient sequencing of target transcripts while preserving total transcriptome quantification, with broad potential for clinical diagnostics and targeted transcript enrichment scenarios.

More information: Jinyang Zhang et al, Real-time and programmable transcriptome sequencing with PROFIT-seq, Nature Cell Biology (2024). DOI: 10.1038/s41556-024-01537-1

Journal information: Nature Cell Biology

Provided by Chinese Academy of Sciences