triangulaR: an R package for identifying AIMs and building triangle plots using SNP data from hybrid zones

Area of Science:

• Evolutionary Biology
• Genetics
• Speciation Research

Background:

• Hybridization is crucial for understanding speciation and generating genetic diversity.
• Analyzing hybrid zones reveals insights into reproductive isolation mechanisms.
• Existing tools for analyzing next-generation sequencing data in hybrid zones are computationally intensive and lack visualization capabilities.

Purpose of the Study:

• To develop a user-friendly resource for identifying ancestry-informative markers (AIMs) from SNP data.
• To enable accurate calculation of hybrid index and interclass heterozygosity for hybrid zone studies.
• To provide a tool for visualizing genetic admixture patterns using triangle plots.

Main Methods:

• Implementation of methods in the R package triangulaR.
• Identification of AIMs using single nucleotide polymorphism (SNP) datasets.
• Calculation of hybrid index and interclass heterozygosity.
• Validation using empirical data and simulations of genetic data from hybrid zones.
• Exploration of allele frequency difference thresholds for AIM identification.

Main Results:

• triangulaR accurately and precisely estimates hybrid index and interclass heterozygosity.
• The package performs comparably to existing software (bgchm) with small sample sizes (as low as five individuals per parental group).
• The choice of allele frequency difference threshold impacts the accuracy and precision of estimates.

Conclusions:

• triangulaR offers an efficient and accessible solution for analyzing genetic data in hybrid zones.
• The package facilitates the study of speciation processes and reproductive isolation.
• Recommendations are provided for best practices in AIM identification and triangle plot construction.