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Improving Translational Accuracy

Improving Translational Accuracy

Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...

Improving Translational Accuracy

Improving Translational Accuracy

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Related Experiment Video

Updated: Mar 12, 2026

RNA Next-Generation Sequencing and a Bioinformatics Pipeline to Identify Expressed LINE-1s at the Locus-Specific Level

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Published on: May 19, 2019

LSCplus: a fast solution for improving long read accuracy by short read alignment.

Ruifeng Hu^1,2,3,4, Guibo Sun^1,2,3,4, Xiaobo Sun^5,6,7,8

¹Beijing Key Laboratory of Innovative Drug Discovery of Traditional Chinese Medicine (Natural Medicine) and Translational Medicine, Beijing, China.

BMC Bioinformatics

|November 11, 2016

Summary

This summary is machine-generated.

A new tool, LSCplus, significantly improves transcriptome analysis by efficiently correcting errors in long-read sequencing data from Pacific Biosciences (SMRT) technology. This advancement makes SMRT sequencing more accessible for researchers by reducing computational demands.

Keywords:

Error correction RNA-seq SMRT sequencing Time-consumption

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Published on: September 16, 2019

Area of Science:

Genomics
Bioinformatics
Molecular Biology

Background:

Single Molecule, Real-Time (SMRT) sequencing offers long reads for comprehensive transcriptome analysis.
Raw SMRT sequencing data has a high error rate (~15%), necessitating error correction.
Existing error correction tools, like LSC, are computationally intensive, limiting SMRT data application.

Purpose of the Study:

To develop an improved, computationally efficient tool for SMRT sequencing data error correction.
To enhance the usability of long-read transcriptome sequencing for research.

Main Methods:

Developed LSCplus, an enhanced version of the LSC error correction program.
Utilized a hybrid sequencing approach combining SMRT and next-generation sequencing (NGS) data.

Main Results:

LSCplus significantly reduces processing time compared to LSC (1/3-1/4 the time).
Error correction time is drastically decreased with LSCplus (1/20-1/25 the time).
The tool demonstrates precision and efficiency in error correction and isoform detection.

Conclusions:

LSCplus provides a faster and more resource-efficient solution for SMRT sequencing data error correction.
The improved tool facilitates broader application of long-read transcriptome sequencing.
LSCplus is freely available for academic and research use.