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Related Experiment Video

Updated: Oct 20, 2025

Hybrid De Novo Genome Assembly for the Generation of Complete Genomes of Urinary Bacteria using Short- and Long-read Sequencing Technologies

Hybrid De Novo Genome Assembly for the Generation of Complete Genomes of Urinary Bacteria using Short- and Long-read Sequencing Technologies

Published on: August 20, 2021

Trycycler: consensus long-read assemblies for bacterial genomes.

Ryan R Wick¹, Louise M Judd², Louise T Cerdeira²

¹Department of Infectious Diseases, Central Clinical School, Monash University, Melbourne, VIC, 3004, Australia. rrwick@gmail.com.

|September 15, 2021

Summary

This summary is machine-generated.

Trycycler improves bacterial genome assembly accuracy by creating a consensus from multiple long-read assemblies. Combining Trycycler with polishing yields the most accurate bacterial genomes, surpassing single-tool approaches.

Keywords:

Bacterial genomics Genome assembly Long-read sequencing Oxford Nanopore sequencing Whole-genome sequencing

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Last Updated: Oct 20, 2025

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Published on: August 20, 2021

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Published on: January 25, 2019

Area of Science:

Genomics
Bioinformatics
Computational Biology

Background:

Long-read sequencing technologies enable complete bacterial genome assembly.
However, long-read assemblies often contain various errors, impacting downstream analyses.
Existing assembly tools may not consistently produce high-accuracy genomes.

Purpose of the Study:

To introduce Trycycler, a novel tool for generating a consensus genome assembly from multiple input assemblies.
To evaluate the accuracy of Trycycler-generated assemblies compared to single-tool assemblies.
To assess the impact of post-assembly polishing on the accuracy of Trycycler assemblies.

Main Methods:

Development of Trycycler, a tool that takes multiple long-read assemblies of the same genome as input.
Benchmarking Trycycler against standalone assembly tools using various datasets.
Application of post-assembly polishing methods to Trycycler and single-tool assemblies.
Comparative analysis of error rates and overall genome accuracy.

Main Results:

Trycycler assemblies demonstrated significantly fewer errors than assemblies generated by single tools.
Post-assembly polishing further reduced errors in Trycycler-generated assemblies.
Trycycler combined with polishing produced the most accurate bacterial genomes in the study.
Despite requiring manual input, Trycycler output showed user convergence towards accurate assemblies.

Conclusions:

Trycycler is an effective tool for improving bacterial genome assembly accuracy.
Combining Trycycler with polishing represents a robust strategy for obtaining highly accurate long-read genome assemblies.
The consensus approach offers a significant advantage over single-tool assembly methods for bacterial genomics.