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Hybrid dynamics in a species group of swallowtail butterflies
Author(s) -
Dupuis J. R.,
Sperling F. A. H.
Publication year - 2016
Publication title -
journal of evolutionary biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.289
H-Index - 128
eISSN - 1420-9101
pISSN - 1010-061X
DOI - 10.1111/jeb.12931
Subject(s) - biology , hybrid zone , microsatellite , evolutionary biology , population , identification (biology) , backcrossing , genetic marker , genetics , single nucleotide polymorphism , genetic variation , gene flow , ecology , gene , genotype , allele , demography , sociology
Hybrid zones provide unique natural laboratories for studying mechanisms of evolution. But identification and classification of hybrid individuals (F1, F2, backcross, etc.) can be complicated by real population changes over time as well as by use of different marker types, both of which challenge documentation of hybrid dynamics. Here, we use multiple genetic markers (mitochondrial DNA , microsatellites and genomewide single nucleotide polymorphisms) to re‐examine population structure in a hybrid zone between two species of swallowtail butterflies in western Canada, Papilio machaon and P. zelicaon . Our aim was to test whether their hybrid dynamics remain the same as found 30 years ago using morphology and allozymes, and we compared different genetic data sets as well as alternative hybrid identification and classification methods. Overall, we found high differentiation between the two parental species, corroborating previous research from the 1980s. We identified fewer hybrid individuals in the main zone of hybridization in recent years, but this finding depended on the genetic markers considered. Comparison of methods with simulated data sets generated from our data showed that single nucleotide polymorphisms were more powerful than microsatellites for both hybrid identification and classification. Moreover, substantial variation among comparisons underlined the value of multiple markers and methods for documenting evolutionarily dynamic systems.