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nQuire: a statistical framework for ploidy estimation using next generation sequencing.

Clemens L Weiß1, Marina Pais2, Liliana M Cano2,3

  • 1Research Group for Ancient Genomics and Evolution, Department of Molecular Biology, Max Planck Institute for Developmental Biology, Tuebingen, Germany.

BMC Bioinformatics
|April 6, 2018
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Summary
This summary is machine-generated.

nQuire is a new tool that uses next-generation sequencing (NGS) to determine the ploidy level of organisms. This statistical framework accurately identifies diploids, triploids, and tetraploids, aiding in studies of pathogens and other eukaryotes.

Keywords:
Next generation sequencingPloidyProbabilistic modeling

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Area of Science:

  • Genomics
  • Computational Biology
  • Evolutionary Biology

Background:

  • Intraspecific ploidy variation is common in eukaryotes, including pathogens like oomycetes and yeasts.
  • Ploidy determination traditionally requires DNA content measurement, which is not always feasible.
  • Next-generation sequencing (NGS) offers an indirect method for inferring ploidy levels.

Purpose of the Study:

  • To introduce nQuire, a novel statistical framework for distinguishing between diploid, triploid, and tetraploid organisms using NGS data.
  • To provide a computational tool that efficiently handles large genomes and high sequencing coverage.
  • To enable the study of organisms with variable ploidy, including pathogens and ancient samples.

Main Methods:

  • nQuire employs a Gaussian Mixture Model to analyze base frequencies at variable sites in NGS data.
  • Maximum likelihood estimation is used to determine the most probable ploidy model.
  • The tool processes standard input file formats and is implemented as a command-line tool.

Main Results:

  • nQuire successfully determined ploidy in individual samples of *Phytophthora infestans* and *Saccharomyces cerevisiae*.
  • Ploidy assignment reliability was shown to be dependent on sequencing depth.
  • Multivariate Gaussian mixtures, using normalized maximized log-likelihoods, accurately clustered samples with ploidy heterogeneity, achieving >96% accuracy in *S. cerevisiae*.
  • nQuire can also identify chromosomal aneuploidies regionally.

Conclusions:

  • nQuire offers a robust statistical framework for investigating intraspecific ploidy variation.
  • The tool has potential applications in pathogen epidemiology, artificial selection studies, and analysis of ancient DNA.
  • nQuire is available as a freely accessible, stand-alone Linux command-line tool.