Estimating sample sizes for DNA barcoding

Area of Science:

• Genetics
• Biodiversity research
• Conservation biology

Background:

• DNA barcoding is a key tool for biodiversity assessment.
• Determining appropriate sample sizes is a persistent challenge in DNA barcoding projects.
• Accurate genetic diversity assessment relies on adequate sampling.

Purpose of the Study:

• To propose a simple resampling approach for estimating critical sample sizes in DNA barcoding.
• To evaluate the impact of population structure on sample size estimation.
• To address the insufficiency of commonly used sample sizes in DNA barcoding.

Main Methods:

• Developed and applied a resampling approach to estimate sample sizes.
• Utilized coalescent-simulated structured populations for validation.
• Tested the approach on real skipper butterfly species data.

Main Results:

• Widely adopted sample sizes in DNA barcoding are inadequate for assessing species' genetic diversity.
• Population structure significantly influences sample size estimations.
• Inadequate sampling and population structure can introduce bias in species identification.

Conclusions:

• The proposed resampling method provides a more accurate estimation of necessary sample sizes for DNA barcoding.
• Researchers must consider population structure when planning DNA barcoding studies.
• Insufficient sample sizes pose a risk to the reliability of biodiversity assessments and species identification.