Abstract In the past two decades, genomic data have been widely used to detect historical gene flow between species in a variety of plants and animals. The Tamias quadrivittatus group of North America chipmunks, which originated through a series of rapid speciation events, are known to undergo massive amounts of mitochondrial introgression. Yet in a recent analysis of targeted nuclear loci from the group, no evidence for cross-species introgression was detected, indicating widespread cytonuclear discordance. The study used the heuristic method HYDE to detect gene flow, which may suffer from low power. Here we use the Bayesian method implemented in the program BPP to re-analyze these data. We develop a Bayesian test of introgression, calculating the Bayes factor via the Savage-Dickey density ratio using the Markov chain Monte Carlo (MCMC) sample under the model of introgression. We take a stepwise approach to constructing an introgression model by adding introgression events onto a well-supported binary species tree. The analysis detected robust evidence for multiple ancient introgression events affecting the nuclear genome, with introgression probabilities reaching 63%. We estimate population parameters and highlight the fact that species divergence times may be seriously underestimated if ancient cross-species gene flow is ignored in the analysis. We examine the assumptions and performance of HYDE and demonstrate that it lacks power if gene flow occurs between sister lineages or if the mode of gene flow does not match the assumed hybrid-speciation model with symmetrical population sizes. Our analyses highlight the power of likelihood-based inference of cross-species gene flow using genomic sequence data. [Bayesian test; BPP; chipmunks; introgression; MSci; multispecies coalescent; Savage-Dickey density ratio.]
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Phylogenomic Data Reveal Widespread Introgression Across the Range of an Alpine and Arctic Specialist
Abstract Understanding how gene flow affects population divergence and speciation remains challenging. Differentiating one evolutionary process from another can be difficult because multiple processes can produce similar patterns, and more than one process can occur simultaneously. Although simple population models produce predictable results, how these processes balance in taxa with patchy distributions and complicated natural histories is less certain. These types of populations might be highly connected through migration (gene flow), but can experience stronger effects of genetic drift and inbreeding, or localized selection. Although different signals can be difficult to separate, the application of high-throughput sequence data can provide the resolution necessary to distinguish many of these processes. We present whole-genome sequence data for an avian species group with an alpine and arctic tundra distribution to examine the role that different population genetic processes have played in their evolutionary history. Rosy-finches inhabit high elevation mountaintop sky islands and high-latitude island and continental tundra. They exhibit extensive plumage variation coupled with low levels of genetic variation. Additionally, the number of species within the complex is debated, making them excellent for studying the forces involved in the process of diversification, as well as an important species group in which to investigate species boundaries. Total genomic variation suggests a broadly continuous pattern of allele frequency changes across the mainland taxa of this group in North America. However, phylogenomic analyses recover multiple distinct, well supported, groups that coincide with previously described morphological variation and current species-level taxonomy. Tests of introgression using D-statistics and approximate Bayesian computation reveal significant levels of introgression between multiple North American taxa. These results provide insight into the balance between divergent and homogenizing population genetic processes and highlight remaining challenges in interpreting conflict between different types of analytical approaches with whole-genome sequence data. [ABBA-BABA; approximate Bayesian computation; gene flow; phylogenomics; speciation; whole-genome sequencing.]
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- Award ID(s):
- 1837940
- PAR ID:
- 10302316
- Editor(s):
- Smith, Stephen
- Date Published:
- Journal Name:
- Systematic Biology
- Volume:
- 70
- Issue:
- 3
- ISSN:
- 1063-5157
- Page Range / eLocation ID:
- 527 to 541
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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