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Related Concept Videos

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The size of the unit cell and the arrangement of atoms in a crystal may be determined from measurements of the diffraction of X-rays by the crystal, termed X-ray crystallography.
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Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
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HPC: Hierarchical phylogeny construction.

Anindya Das1, Xiaoqiu Huang1

  • 1Department of Computer Science, Iowa State University, Ames, Iowa, United States of America.

Plos One
|August 23, 2019
PubMed
Summary
This summary is machine-generated.

A new hierarchical approach improves phylogenetic tree construction for similar genome sequences with varying single nucleotide polymorphism (SNP) rates. This method is significantly more efficient and accurate for analyzing large datasets of closely related isolates.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Evolutionary Biology

Background:

  • Advancements in DNA sequencing yield numerous similar genome sequences.
  • A wide range of single nucleotide polymorphism (SNP) rates among isolates presents challenges for phylogenetic tree construction.
  • Existing phylogenetic methods struggle with large datasets of highly similar isolates exhibiting diverse SNP rates.

Purpose of the Study:

  • To develop a novel hierarchical approach for constructing phylogenetic trees.
  • To address the computational challenges posed by sequencing data with variable SNP rates.
  • To improve the efficiency and accuracy of phylogenetic analysis for closely related isolates.

Main Methods:

  • A multi-level hierarchical strategy for phylogeny construction.
  • Identification of isolate groups based on similarity levels at each hierarchical stage.
  • Phylogenetic tree construction within identified groups.
  • Utilizing a subset of alignment columns for computational efficiency.

Main Results:

  • The hierarchical approach demonstrates 20-60 times greater efficiency compared to existing programs.
  • The method shows improved accuracy, particularly for highly similar isolates with disparate SNP rates.
  • Successful construction of phylogenetic trees for challenging datasets.

Conclusions:

  • The developed hierarchical method offers a more efficient and accurate solution for phylogenetic analysis of large, similar genome datasets.
  • This approach effectively handles variations in single nucleotide polymorphism (SNP) rates among isolates.
  • The findings have significant implications for evolutionary studies and microbial genomics.