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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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Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
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Related Experiment Video

Updated: Jun 6, 2025

Demonstration of the Sequence Alignment to Predict Across Species Susceptibility Tool for Rapid Assessment of Protein Conservation
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Evaluating Sequence Alignment Tools for Antimicrobial Resistance Gene Detection in Assembly Graphs.

Yusreen Shah1, Somayeh Kafaie1

  • 1Department of Mathematics and Computing Science, Saint Mary's University, Halifax, NS B3H 3C3, Canada.

Microorganisms
|November 27, 2024
PubMed
Summary
This summary is machine-generated.

Bandage accurately identifies antimicrobial resistance (AMR) genes in bacterial genomes more effectively than other tools. This research aids in understanding AMR spread and developing mitigation strategies.

Keywords:
BandageGraphAlignerSPAlignerantimicrobial resistance (AMR)assembly graphssequence alignment

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Area of Science:

  • Genomics
  • Microbiology
  • Bioinformatics

Background:

  • Antimicrobial resistance (AMR) is a significant global health challenge.
  • Horizontal gene transfer (HGT) accelerates the spread of AMR genes.
  • Understanding AMR gene context is vital for controlling resistance.

Purpose of the Study:

  • To evaluate sequence alignment tools for AMR gene identification in microbial assembly graphs.
  • To compare the performance of Bandage, SPAligner, and GraphAligner.
  • To assess the efficiency and accuracy of identifying AMR genes and HGT events.

Main Methods:

  • Comparative analysis of Bandage, SPAligner, and GraphAligner.
  • Qualitative and quantitative performance evaluation.
  • Assessment of precision, computational efficiency, and accuracy using edit distance.

Main Results:

  • Bandage demonstrated superior precision and efficiency in identifying AMR gene sequences.
  • GraphAligner and SPAligner showed comparable, but lower, performance.
  • Analysis included path similarity and output accuracy metrics.

Conclusions:

  • Bandage is a highly effective tool for accurate AMR gene identification in bacterial populations.
  • This tool aids in studying AMR mechanisms and HGT events.
  • Findings support the development of strategies to mitigate AMR spread.