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isONform: reference-free transcriptome reconstruction from Oxford Nanopore data.

Alexander J Petri1, Kristoffer Sahlin1

  • 1Department of Mathematics, Science for Life Laboratory, Stockholm University, Stockholm 106 91, Sweden.

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Summary
This summary is machine-generated.

We developed isONform, a novel algorithm for constructing gene isoforms from Oxford Nanopore Technologies (ONT) cDNA sequencing data. This method offers higher sensitivity for transcript isoform prediction, especially for organisms lacking detailed genomic annotations.

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Area of Science:

  • Bioinformatics
  • Genomics
  • Molecular Biology

Background:

  • Long-read transcriptome sequencing, particularly Oxford Nanopore Technologies (ONT), enables comprehensive transcript characterization.
  • However, ONT data requires significant bioinformatic processing for accurate isoform prediction due to transcript variability and sequencing errors.
  • Existing reference-based methods rely on high-quality genomes and annotations, while reference-free methods lack comparable sensitivity.

Purpose of the Study:

  • To present isONform, a high-sensitivity algorithm for constructing gene isoforms from ONT cDNA sequencing data.
  • To address the limitations of existing reference-free and reference-based transcript prediction methods.
  • To provide a tool for isoform construction in organisms with limited genomic resources and for validating existing predictions.

Main Methods:

  • isONform employs an iterative bubble-popping approach on gene graphs constructed from fuzzy seeds derived from ONT reads.
  • The algorithm was evaluated using simulated, synthetic, and biological ONT cDNA datasets.
  • Performance was compared against the reference-free method RATTLE and the annotation-based method StringTie2.

Main Results:

  • isONform demonstrated substantially higher sensitivity in predicting transcript isoforms compared to RATTLE across various datasets.
  • While isONform showed a slight decrease in precision, its predictions on biological data exhibited significantly higher consistency with StringTie2.
  • The algorithm effectively handles transcript variability and sequencing errors inherent in long-read data.

Conclusions:

  • isONform is a sensitive algorithm for constructing transcript isoforms from ONT cDNA sequencing data.
  • It is particularly valuable for studying organisms with poorly annotated genomes and for cross-validation with reference-based methods.
  • The tool enhances the characterization of transcriptomes using long-read sequencing technologies.