University of Oulu

Ottenburghs, J., Honka, J., Müskens, G.J.D.M. et al. Recent introgression between Taiga Bean Goose and Tundra Bean Goose results in a largely homogeneous landscape of genetic differentiation. Heredity 125, 73–84 (2020). https://doi.org/10.1038/s41437-020-0322-z

Recent introgression between Taiga Bean Goose and Tundra Bean Goose results in a largely homogeneous landscape of genetic differentiation

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Author: Ottenburghs, Jente1; Honka, Johanna2; Müskens, Gerard J. D. M.3;
Organizations: 1Department of Evolutionary Biology, University of Uppsala, Uppsala, Sweden
2Department of Ecology and Genetics, University of Oulu, PO Box 3000, FI-90014, Oulu, Finland
3Team Animal Ecology, Wageningen Environmental Research, Wageningen University & Research, Droevendaalsesteeg 3-3A, 6708 PB, Wageningen, The Netherlands
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 1.9 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2020090167153
Language: English
Published: Springer Nature, 2020
Publish Date: 2020-09-01
Description:

Abstract

Several studies have uncovered a highly heterogeneous landscape of genetic differentiation across the genomes of closely related species. Specifically, genetic differentiation is often concentrated in particular genomic regions (“islands of differentiation”) that might contain barrier loci contributing to reproductive isolation, whereas the rest of the genome is homogenized by introgression. Alternatively, linked selection can produce differentiation islands in allopatry without introgression. We explored the influence of introgression on the landscape of genetic differentiation in two hybridizing goose taxa: the Taiga Bean Goose (Anser fabalis) and the Tundra Bean Goose (A. serrirostris). We re-sequenced the whole genomes of 18 individuals (9 of each taxon) and, using a combination of population genomic summary statistics and demographic modeling, we reconstructed the evolutionary history of these birds. Next, we quantified the impact of introgression on the build-up and maintenance of genetic differentiation. We found evidence for a scenario of allopatric divergence (about 2.5 million years ago) followed by recent secondary contact (about 60,000 years ago). Subsequent introgression events led to high levels of gene flow, mainly from the Tundra Bean Goose into the Taiga Bean Goose. This scenario resulted in a largely undifferentiated genomic landscape (genome-wide FST = 0.033) with a few notable differentiation peaks that were scattered across chromosomes. The summary statistics indicated that some peaks might contain barrier loci while others arose in allopatry through linked selection. Finally, based on the low genetic differentiation, considerable morphological variation and incomplete reproductive isolation, we argue that the Taiga and the Tundra Bean Goose should be treated as subspecies.

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Series: Heredity
ISSN: 0018-067X
ISSN-E: 1365-2540
ISSN-L: 0018-067X
Volume: 125
Issue: 1-2
Pages: 73 - 84
DOI: 10.1038/s41437-020-0322-z
OADOI: https://oadoi.org/10.1038/s41437-020-0322-z
Type of Publication: A1 Journal article – refereed
Field of Science: 1184 Genetics, developmental biology, physiology
1181 Ecology, evolutionary biology
Subjects:
Funding: We thank members of the Ellegren lab and the Suh lab for insightful discussions. We are indebted to the Naturhistoriska Riksmuseet in Stockholm and the Finnish Game and Fisheries Research Institute (now the Natural Resources Institute Finland) for providing several samples. This research was made possible by grants from the Swedish Research Council (contract 2013-8271) and the Knut and Alice Wallenberg foundation (contract 2014.0044). Sequencing was performed by the SNP&SEQ Technology Platform in Uppsala. The facility is part of the National Genomics Infrastructure (NGI) Sweden and Science for Life Laboratory. The SNP&SEQ Platform is also supported by the Swedish Research Council and the Knut and Alice Wallenberg Foundation. Computations were performed on resources provided by the Swedish National Infrastructure for Computing (SNIC) through Uppsala Multidisciplinary Center for Advanced Computational Science (UPPMAX).
Copyright information: © The Author(s) 2020. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
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