Hybrid zone analysis with the R package triangulaR: lessons learned from simulations and empirical datasets

Wiens, Ben

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Hybrid zone analysis with the R package triangulaR: lessons learned from simulations and empirical datasets

Wiens, Ben

Abstract

Describing patterns of genetic variation across populations and species is a fundamental goal of molecular phylogeography and population genetics. Within those fields, studies that use molecular data to investigate hybridization between two or more species present an opportunity to describe the evolutionary processes that contribute to or break down species boundaries, providing critical insight into the speciation process. Triangle plots, which use genetic data to show the relationship between hybrid index and interclass heterozygosity, can distinguish among multiple hybrid classes (e.g., F1s, F2s, backcrosses). They are also an effective method for distinguishing between continuous variation in a single taxon and hybridization between two taxa. Further, they can provide insight into the details of hybrid zone dynamics by describing the distribution of hybrid classes across the hybrid zone. Here, we introduce triangulaR, an R package for identifying ancestry-informative markers (AIMs) from genetic datasets, calculating hybrid index and interclass heterozygosity, and visualizing triangle plots. We validate our methods using simulations of genetic data from a hybrid zone of two parental groups at various levels of divergence. We explore how parental group sample sizes and the allele frequency difference threshold for AIM identification influence the accuracy and precision of hybrid index and interclass heterozygosity estimates. We contextualize interpretation of triangle plots by describing theoretical expectations under Hardy-Weinberg Equilibrium and provide recommendations for best practices for building triangle plots. Finally, we demonstrate the utility of triangulaR using case studies from empirical datasets.

Description

These are the slides from a presentation given at the American Society of Ornithology held in St. Louis, Missouri on 08/13/2025.

Date

2025-08-13

Publisher

University of Kansas

Hybrid zone analysis with the R package triangulaR: lessons learned from simulations and empirical datasets

Wiens, Ben

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