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Frequency and Distribution of Crossovers in Caenorhabditis elegans Meiosis by SNP Genotyping using Real-time PCR

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wisepair: a computer program for individual matching in genetic tracking studies.

Andrew P Rothstein¹, Ryan McLaughlin¹, Alejandro Acevedo-Gutiérrez¹

¹Department of Biology, Western Washington University, Bellingham, WA, 98225, USA.

Molecular Ecology Resources

|August 5, 2016

Summary

This study introduces wisepair, a Python program that improves genetic tracking of individuals in ecology and evolution. It efficiently matches genotypes and optimizes sampling designs, reducing lab errors and enhancing ecological research.

Keywords:

Allobates femoralis Lutra lutra Phoca vitulina genetic tracking individual identification simulation software

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Area of Science:

Ecology and evolutionary biology
Genetics
Bioinformatics

Background:

Individual-based data are crucial for ecological and evolutionary studies.
Genetic tagging offers a non-invasive method for tracking organisms, especially those with limited phenotypic variation.
Challenges in genetic tracking include accurate genotype matching and optimizing field sampling designs.

Purpose of the Study:

To develop an efficient Python-based program, wisepair, for defining sampling designs and reducing genotyping errors in individual-based genetic studies.
To assess the effectiveness of wisepair using empirical data from different species and sampling strategies.
To provide a tool for researchers to set a priori parameters for genetic tracking studies.

Main Methods:

Development of a Python-based computer-modelling program, wisepair.
Assessment of wisepair's performance using three empirical datasets: diurnal poison frogs, harbour seals, and Eurasian otters.
Incorporation of sample rerun error data, allelic pairwise comparisons, and probabilistic simulations for matching thresholds.

Main Results:

Wisepair demonstrated superior performance compared to existing genotype matching programs.
The program was effective with both reference and non-reference genotype datasets.
Optimal sampling designs for future projects were proposed based on harbour seal data analysis.

Conclusions:

Wisepair is an effective tool for reducing genotyping errors and optimizing sampling designs in genetic tracking studies.
The program offers a unique capability for researchers to define study parameters a priori.
Wisepair enhances the accuracy and efficiency of ecological and evolutionary research relying on individual-based genetic data.