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Abstract Structural variants (SVs) can promote speciation by directly causing reproductive isolation or by suppressing recombination across large genomic regions. Whereas examples of each mechanism have been documented, systematic tests of the role of SVs in speciation are lacking. Here, we take advantage of long‐read (Oxford nanopore) whole‐genome sequencing and a hybrid zone between twoLycaeidesbutterfly taxa (L.melissaand Jackson HoleLycaeides) to comprehensively evaluate genome‐wide patterns of introgression for SVs and relate these patterns to hypotheses about speciation. We found >100,000 SVs segregating within or between the two hybridizing species. SVs and SNPs exhibited similar levels of genetic differentiation between species, with the exception of inversions, which were more differentiated. We detected credible variation in patterns of introgression among SV loci in the hybrid zone, with 562 of 1419 ancestry‐informative SVs exhibiting genomic clines that deviated from null expectations based on genome‐average ancestry. Overall, hybrids exhibited a directional shift towards Jackson HoleLycaeidesancestry at SV loci, consistent with the hypothesis that these loci experienced more selection on average than SNP loci. Surprisingly, we found that deletions, rather than inversions, showed the highest skew towards excess ancestry from Jackson HoleLycaeides. Excess Jackson HoleLycaeidesancestry in hybrids was also especially pronounced for Z‐linked SVs and inversions containing many genes. In conclusion, our results show that SVs are ubiquitous and suggest that SVs in general, but especially deletions, might disproportionately affect hybrid fitness and thus contribute to reproductive isolation.
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This content will become publicly available on November 1, 2025
A Next Generation of Hierarchical Bayesian Analyses of Hybrid Zones Enables Model‐Based Quantification of Variation in Introgression in R
ABSTRACT Hybrid zones, where genetically distinct groups of organisms meet and interbreed, offer valuable insights into the nature of species and speciation. Here, we present a new R package,bgchm, for population genomic analyses of hybrid zones. This R package extends and updates the existingbgcsoftware and combines Bayesian analyses of hierarchical genomic clines with Bayesian methods for estimating hybrid indexes, interpopulation ancestry proportions, and geographic clines. Compared to existing software,bgchmoffers enhanced efficiency through Hamiltonian Monte Carlo sampling and the ability to work with genotype likelihoods combined with a hierarchical Bayesian approach, enabling inference for diverse types of genetic data sets. The package also facilitates the quantification of introgression patterns across genomes, which is crucial for understanding reproductive isolation and speciation genetics. We first describe the models underlyingbgchmand then provide an overview of the R package and illustrate its use through the analysis of simulated and empirical data sets. We show thatbgchmgenerates accurate estimates of model parameters under a variety of conditions, especially when the genetic loci analyzed are highly ancestry informative. This includes relatively robust estimates of genome‐wide variability in clines, which has not been the focus of previous models and methods. We also illustrate how both selection and genetic drift contribute to variability in introgression among loci and how additional information can be used to help distinguish these contributions. We conclude by describing the promises and limitations ofbgchm, comparingbgchmto other software for genomic cline analyses, and identifying areas for fruitful future development.
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- Award ID(s):
- 1844941
- PAR ID:
- 10584198
- Publisher / Repository:
- John Wiley & Sons Ltd.
- Date Published:
- Journal Name:
- Ecology and Evolution
- Volume:
- 14
- Issue:
- 11
- ISSN:
- 2045-7758
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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