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Updated: Oct 7, 2025

Author Spotlight: AQRNA-seq Role in Mapping Small RNAs and Unraveling Protein Translation Mechanisms

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Partitioning RNAs by length improves transcriptome reconstruction from short-read RNA-seq data.

Francisca Rojas Ringeling¹, Shounak Chakraborty¹, Caroline Vissers²

¹Gene Center, Ludwig-Maximilians-Universität München, Munich, Germany.

Nature Biotechnology

|January 11, 2022

Summary

Ladder-seq improves RNA sequencing by separating transcripts by length, enhancing gene quantification and assembly accuracy. This novel method significantly boosts precision and sensitivity for complex gene analysis.

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Identification of Alternative Splicing and Polyadenylation in RNA-seq Data

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Published on: June 24, 2021

Area of Science:

Genomics
Molecular Biology
Bioinformatics

Background:

Short-read RNA sequencing faces limitations in transcript assembly accuracy due to a lack of long-range information.
Accurate transcript quantification and assembly are crucial for understanding gene expression and regulation.

Purpose of the Study:

To introduce Ladder-seq, a novel approach to enhance transcript assembly and quantification.
To evaluate the performance of Ladder-seq using simulated and experimental RNA sequencing data.

Main Methods:

Ladder-seq separates transcripts by length prior to sequencing.
Modified kallisto, StringTie2, and Trinity algorithms were used to process Ladder-seq data.
Simulated and experimental RNA sequencing datasets were analyzed.

Main Results:

Extended kallisto with Ladder-seq data showed substantially higher accuracy in quantifying complex gene transcripts.
Reference-based assembly using StringTie2 achieved 30.8% higher precision and over 30% increased sensitivity for complex genes.
De novo assembly using Trinity demonstrated 78% more correctly assembled transcripts and improved precision by 78%.

Conclusions:

Ladder-seq significantly improves transcript quantification and assembly accuracy compared to conventional RNA sequencing methods.
The approach reveals more genes with isoform switches and identifies widespread changes in isoform usage.
Ladder-seq offers a powerful tool for deeper insights into transcriptomic complexity and gene regulation.