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Related Concept Videos

Genome Annotation and Assembly03:36

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The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.
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Related Experiment Video

Updated: Aug 6, 2025

Hybrid De Novo Genome Assembly for the Generation of Complete Genomes of Urinary Bacteria using Short- and Long-read Sequencing Technologies
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Benchmarking genome assembly methods on metagenomic sequencing data.

Zhenmiao Zhang1, Chao Yang1, Werner Pieter Veldsman1

  • 1Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong.

Briefings in Bioinformatics
|March 14, 2023
PubMed
Summary
This summary is machine-generated.

This study benchmarks 19 metagenome assembly tools across various sequencing technologies. Linked-read and hybrid approaches show promise for reconstructing high-quality microbial genomes, offering practical guidance for tool selection.

Keywords:
genome assembly toolslinked-read sequencinglong-read sequencingmetagenome-assembled genomemetagenomic sequencingshort-read sequencing

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Area of Science:

  • Genomics
  • Bioinformatics
  • Microbial Ecology

Background:

  • Metagenome assembly reconstructs microbial genomes from sequencing data.
  • Short-read sequencing is common, but long- and linked-read technologies offer improved DNA connectedness.
  • Existing tools lack comprehensive evaluation and practical selection guidance.

Purpose of the Study:

  • To benchmark 19 metagenome assembly tools using diverse sequencing data.
  • To evaluate assembly performance across short-, linked-, and long-read technologies.
  • To provide practical guidance for selecting metagenome assembly tools.

Main Methods:

  • Assembly of simulated, mock community, and human gut microbiome datasets.
  • Utilized sequencing data from Illumina, BGISEQ, 10x Genomics, PacBio, and Oxford Nanopore.
  • Evaluated 19 commonly used metagenome assembly tools.

Main Results:

  • Long-read assemblers yielded high contig contiguity but fewer medium/high-quality MAGs.
  • Linked-read assemblers produced the most near-complete MAGs from gut microbiomes.
  • Hybrid assemblers demonstrated potential for improving assembly length and MAG completeness.

Conclusions:

  • No single sequencing technology or assembler is optimal for all metagenome assembly tasks.
  • Linked-read and hybrid approaches are effective for high-quality MAG reconstruction.
  • This benchmark provides essential guidance for selecting appropriate metagenome assembly tools and strategies.