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Updated: Oct 29, 2025

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Two-Target Quantitative PCR To Predict Library Composition for Shallow Shotgun Sequencing.

Matthew Y Cho1,2,3, Marc Oliva4,5, Anna Spreafico4

  • 1Department of Medicine, University of Torontogrid.17063.33, Toronto, Canada.

Msystems
|July 13, 2021
PubMed
Summary

Researchers developed a quantitative PCR (qPCR) assay to predict host-to-microbe ratios before shotgun sequencing. This method improves planning for shallow sequencing, ensuring more accurate human microbiota composition analysis.

Keywords:
host DNA proportionmetagenomicsmicrobiomesample compositionshallow shotgunshotgun sequencing

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Area of Science:

  • Microbiology
  • Genomics
  • Bioinformatics

Background:

  • Shotgun sequencing provides high-resolution data for human microbiota composition.
  • Accurate host-to-microbe ratios are crucial for effective shotgun sequencing, especially with shallow sequencing techniques.
  • Current methods lack precise pre-sequencing estimation of these ratios across diverse body sites.

Purpose of the Study:

  • To evaluate a quantitative PCR (qPCR)-based assay for predicting host-to-microbe ratios prior to sequencing.
  • To develop and validate a model for estimating these ratios using qPCR data.
  • To enhance the efficiency and accuracy of shotgun sequencing experimental design.

Main Methods:

  • Developed a two-target qPCR assay using bacterial 16S rRNA and human beta-actin genes.
  • Created a predictive model for human-to-microbe ratios based on qPCR results.
  • Validated the model on stool, oropharyngeal swabs, rectal swabs, and vaginal secretions.

Main Results:

  • The qPCR assay accurately predicted host-to-microbe ratios across a wide range of sample compositions (4%-98% nonhuman reads).
  • Observed proportions in the validation set varied by -18.8% to +19.2% from expected values.
  • Variable sequencing depth was shown to decrease alpha diversity metrics, with rates dependent on community composition.

Conclusions:

  • An easy-to-use qPCR assay can effectively predict host-to-microbe ratios, aiding shotgun sequencing experiment planning.
  • This approach is particularly valuable for shallow shotgun sequencing, mitigating negative impacts on microbial community metrics.
  • The developed model and tool assist researchers in assessing shallow sequencing viability and optimizing experimental design.