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Related Experiment Video

Updated: Jan 9, 2026

Author Spotlight: Cost-Effective Transcriptomic Drug Screening - Unlocking New Targets

Author Spotlight: Cost-Effective Transcriptomic Drug Screening - Unlocking New Targets

Published on: February 23, 2024

Long-read sequencing transcriptome quantification with lr-kallisto.

Rebekah K Loving¹, Delaney K Sullivan^1,2, Fairlie Reese^3,4

¹Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, United States of America.

Plos Computational Biology

|December 1, 2025

Summary

This summary is machine-generated.

Accurate full-length transcript isoform quantification is now possible with long-read sequencing data. Our new tool, lr-kallisto, improves quantification accuracy, especially when combined with exome capture.

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Area of Science:

Genomics
Bioinformatics
Molecular Biology

Background:

Short-read sequencing offers affordable gene-level RNA abundance quantification.
Definitive quantification of full-length transcript isoforms remains a significant challenge.
Long-read sequencing technologies hold promise for isoform-level analysis.

Purpose of the Study:

To develop a method for fast and accurate quantification of long-read RNA sequencing data.
To address bioinformatic challenges posed by long-read data types, isoform complexity, and genetic variation.
To improve isoform quantification through the integration of exome capture.

Main Methods:

Development of lr-kallisto, an adaptation of kallisto for long-read data.
Utilized Oxford Nanopore (ONT) sequencing data.
Incorporated exome capture techniques to enhance data quality.

Main Results:

Demonstrated that fast and accurate quantification of long-read data is achievable.
Showed that exome capture significantly improves quantification accuracy.
lr-kallisto successfully quantifies long-read RNA sequencing data.

Conclusions:

Long-read sequencing, coupled with lr-kallisto and exome capture, enables routine and accurate isoform quantification.
This advancement overcomes previous limitations in transcript isoform analysis.
The developed method has broad implications for various biological research areas.