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Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
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Deep sequencing of evolving pathogen populations: applications, errors, and bioinformatic solutions.

Kerensa McElroy1, Torsten Thomas, Fabio Luciani

  • 1Centre for Marine Bio-Innovation and School of Biotechnology and Biomolecular Sciences, UNSW, Sydney, NSW 2052, Australia. kerensa@unsw.edu.au.

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Deep sequencing analyzes pathogen evolution by examining individual genetic reads. This review covers its use in viral and bacterial populations, highlighting bioinformatic challenges and solutions for variant detection.

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Area of Science:

  • Microbiology
  • Genomics
  • Evolutionary Biology

Background:

  • Next-generation sequencing (NGS) technologies enable deep sequencing, generating large population samples.
  • Deep sequencing treats information in individual reads as meaningful for population analysis.
  • Pathogen evolution studies benefit from high-throughput sequencing data.

Purpose of the Study:

  • To review the applications of deep sequencing in pathogen evolution research.
  • To discuss pioneering studies in virology and bacterial genomics.
  • To summarize bioinformatic challenges and solutions in deep sequencing analysis.

Main Methods:

  • Review of existing literature on deep sequencing applications in pathogen evolution.
  • Discussion of specific examples, including hepatitis C virus (HCV) and HIV dynamics.
  • Exploration of deep sequencing in bacterial populations and emerging technologies.

Main Results:

  • Deep sequencing has been successfully applied to study viral pathogens like HCV and HIV.
  • The approach is being extended to analyze bacterial populations.
  • Bioinformatic challenges, such as low-frequency variant detection and haplotype reconstruction, are being addressed.

Conclusions:

  • Deep sequencing offers unprecedented potential for understanding pathogen population genetics and evolutionary history.
  • Overcoming bioinformatic hurdles is crucial for maximizing the utility of deep sequencing.
  • Continued development of sequencing technologies and analytical methods will advance pathogen evolution studies.