Admixture of evolutionary rates across a butterfly hybrid zone

Abstract
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Abstract

Hybridization is a major evolutionary force that can erode genetic differentiation between species, whereas reproductive isolation maintains such differentiation. In studying a hybrid zone between the swallowtail butterflies Papilio syfanius and Papilio maackii (Lepidoptera: Papilionidae), we made the unexpected discovery that genomic substitution rates are unequal between the parental species. This phenomenon creates a novel process in hybridization, where genomic regions most affected by gene flow evolve at similar rates between species, while genomic regions with strong reproductive isolation evolve at species-specific rates. Thus, hybridization mixes evolutionary rates in a way similar to its effect on genetic ancestry. Using coalescent theory, we show that the rate-mixing process provides distinct information about levels of gene flow across different parts of genomes, and the degree of rate-mixing can be predicted quantitatively from relative sequence divergence (F_ST) between the hybridizing species at equilibrium. Overall, we demonstrate that reproductive isolation maintains not only genomic differentiation, but also the rate at which differentiation accumulates. Thus, asymmetric rates of evolution provide an additional signature of loci involved in reproductive isolation.

Data availability

Source code is available at:https://github.com/tzxiong/2021_Maackii_Syfanius_HybridZoneWhole-genome sequences are deposited in the National Center for Biotechnology Information, Sequence Read Archive (BioProject Accession Number: PRJNA765117).

The following data sets were generated

1. Xiong T
2. Mallet J
(2022) Hybridization between Papilio syfanius and Papilio maackii
NCBI Sequence Read Archive, PRJNA765117.

https://www.ncbi.nlm.nih.gov/sra/PRJNA765117
1. Xiong T
(2022) Database for the code used in the 2021 manuscript on the hybrid zone between Papilio syfanius and Papilio maackii
GitHub.

https://github.com/tzxiong/2021_Maackii_Syfanius_HybridZone

The following previously published data sets were used

1. Lu S
2. Yang J
3. Dai X
4. Xie F
5. He J
6. Dong Z
7. Mao J
8. Liu G
9. Chang Z
10. Zhao R
11. Wan W
12. Zhang R
13. Li Y
14. Wang W
15. Li X
(2019) Supporting data for "Chromosomal-level reference genome of Chinese peacock butterfly (Papilio bianor) based on third-generation DNA sequencing and Hi-C analysis"
GigaDB Datasets, 100653.

http://dx.doi.org/10.5524/100653

Article and author information

Author details

Tianzhu Xiong

Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, United States

For correspondence
txiong@g.harvard.edu

Competing interests
The authors declare that no competing interests exist.

"This ORCID iD identifies the author of this article:" 0000-0002-4576-8764
Xueyan Li

Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China

Competing interests
The authors declare that no competing interests exist.
Masaya Yago

The University Museum, University of Tokyo, Tokyo, Japan

Competing interests
The authors declare that no competing interests exist.
James Mallet

Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, United States

Competing interests
The authors declare that no competing interests exist.

"This ORCID iD identifies the author of this article:" 0000-0002-3370-0367

Funding

American Philosophical Society (The Lewis and Clark Fund for Exploration and Field Research (2017-2018))

Tianzhu Xiong

The NSF-Simons Center for Mathematical and Statistical Analysis of Biology at Harvard (Award Number #1764269)

Tianzhu Xiong

The Harvard Quantitative Biology Initiative (Graduate Student Fellowship)

Tianzhu Xiong

Department of Organismic and Evolutionary Biology, Harvard University (Graduate Student Fellowship)

Tianzhu Xiong

Department of Organismic and Evolutionary Biology, Harvard University (Faculty Start-up Fund)

James Mallet

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.