Human RNA sequencing

Changes in isoform variants and relative abundancies are an important clue in deciphering how genomic variants drive the phenotypic differences between health and disease. Only long-read sequencing can provide unbiased, direct detection of all the isoforms present in your sample.

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Profile transcriptome complexity without assembly

Single Molecule, Real-Time (SMRT) sequencing delivers the long reads needed to capture intact isoform information without assembly or complicated algorithms. Use the Iso-Seq method to:

  • Profile whole transcriptomes exhaustively at the isoform level
  • Characterize alternative start and polyadenylation sites as well as exon skipping events
  • Detect isoforms as potential biomarkers
  • Target genes of interest using synthetic probes with sample multiplexing to query isoforms in a cost-effective manner

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Workflow: from RNA to full-length transcripts

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Sample + library preparation

Prepare full-length transcripts with flexible sample and library workflows

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Simplify sample prep workflow and reduce project costs by using the Sequel II and IIe systems

Scale throughput on Sequel systems

  • Use the Sequel II and IIe systems to generate up to 4 million* full-length reads per SMRT Cell 8M*
  • Or use the Sequel II and IIe systems to generate up to 500,000* FLNC reads per SMRT Cell 1M

* Read lengths, number of reads, data per SMRT Cell, and other sequencing performance results vary based on sample quality/type and insert size, among other factors.

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Data analysis

Output high-quality, full-length transcript sequences; no assembly required.

  • Generate highly accurate long reads (HiFi reads) to characterize whole transcriptomes
  • Use the Iso-Seq analysis in SMRT Link to output high-quality, full-length transcript FASTA sequences, with no assembly required, to characterize transcripts and splice variants
  • Run Iso-Seq analysis with or without a reference genome. Follow up with community tools for different analyses such as SQANTI3 (transcript classification), tappAS (differential expression analysis), and TAMA (annotation).

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Application brief

Long-read RNA sequencing

Learn more about these best practices for long-read RNA sequencing.




Scientists used the Iso-Seq method to identify novel isoforms uniquely associated with breast cancer subtypes and survival outcomes.

Veiga et al., “A comprehensive long-read isoform analysis platform and sequencing resource for breast cancer“, Science Advances (2022)

Novel full-length isoforms

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