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Related Experiment Video

Updated: Sep 19, 2025

Using the E1A Minigene Tool to Study mRNA Splicing Changes

Using the E1A Minigene Tool to Study mRNA Splicing Changes

Published on: April 22, 2021

Improving gene isoform quantification with miniQuant.

Haoran Li^1,2, Dingjie Wang^1,2,3, Qi Gao¹

¹Gilbert S. Omenn Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.

Nature Biotechnology

|June 3, 2025

Summary

This summary is machine-generated.

Accurate gene isoform quantification is challenging with short RNA sequencing reads. The miniQuant tool integrates long and short reads to improve accuracy, revealing isoform switches in human cell differentiation.

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Area of Science:

Genomics
Bioinformatics
Molecular Biology

Background:

RNA sequencing is crucial for gene isoform quantification.
Short reads present limitations in accurately quantifying complex gene isoforms.
Ambiguous read alignments contribute to quantification errors.

Purpose of the Study:

Identify genes with quantification errors using short reads.
Demonstrate the benefit of long reads for complex gene quantification.
Develop a method for accurate gene isoform quantification.

Main Methods:

Developed miniQuant to rank genes with alignment ambiguity.
Integrated long and short reads for optimal quantification.
Validated methods with simulations, experimental data, and public datasets (GTEx, TCGA, ENCODE).

Main Results:

miniQuant accurately quantifies gene isoforms by combining long and short reads.
Identified genes with quantification challenges for short reads.
Uncovered isoform switches during human embryonic stem cell differentiation.

Conclusions:

miniQuant enhances gene isoform quantification accuracy.
The integration of long and short reads overcomes limitations of short-read sequencing.
This approach facilitates discoveries in developmental biology and disease research.