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Estimation of species divergence times in presence of cross-species gene flow.

Publication ,  Journal Article
Tiley, GP; Flouri, T; Jiao, X; Poelstra, JW; Xu, B; Zhu, T; Rannala, B; Yoder, AD; Yang, Z
Published in: Systematic biology
August 2023

Cross-species introgression can have significant impacts on phylogenomic reconstruction of species divergence events. Here, we used simulations to show how the presence of even a small amount of introgression can bias divergence time estimates when gene flow is ignored in the analysis. Using advances in analytical methods under the multispecies coalescent (MSC) model, we demonstrate that by accounting for incomplete lineage sorting and introgression using large phylogenomic data sets this problem can be avoided. The multispecies-coalescent-with-introgression (MSci) model is capable of accurately estimating both divergence times and ancestral effective population sizes, even when only a single diploid individual per species is sampled. We characterize some general expectations for biases in divergence time estimation under three different scenarios: 1) introgression between sister species, 2) introgression between non-sister species, and 3) introgression from an unsampled (i.e., ghost) outgroup lineage. We also conducted simulations under the isolation-with-migration (IM) model and found that the MSci model assuming episodic gene flow was able to accurately estimate species divergence times despite high levels of continuous gene flow. We estimated divergence times under the MSC and MSci models from two published empirical datasets with previous evidence of introgression, one of 372 target-enrichment loci from baobabs (Adansonia), and another of 1000 transcriptome loci from 14 species of the tomato relative, Jaltomata. The empirical analyses not only confirm our findings from simulations, demonstrating that the MSci model can reliably estimate divergence times but also show that divergence time estimation under the MSC can be robust to the presence of small amounts of introgression in empirical datasets with extensive taxon sampling. [divergence time; gene flow; hybridization; introgression; MSci model; multispecies coalescent].

Duke Scholars

Published In

Systematic biology

DOI

EISSN

1076-836X

ISSN

1063-5157

Publication Date

August 2023

Volume

72

Issue

4

Start / End Page

820 / 836

Related Subject Headings

  • Time Factors
  • Probability
  • Phylogeny
  • Models, Genetic
  • Gene Flow
  • Evolutionary Biology
  • Computer Simulation
  • 3105 Genetics
  • 3104 Evolutionary biology
  • 3103 Ecology
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Tiley, G. P., Flouri, T., Jiao, X., Poelstra, J. W., Xu, B., Zhu, T., … Yang, Z. (2023). Estimation of species divergence times in presence of cross-species gene flow. Systematic Biology, 72(4), 820–836. https://doi.org/10.1093/sysbio/syad015
Tiley, George P., Tomáš Flouri, Xiyun Jiao, Jelmer W. Poelstra, Bo Xu, Tianqi Zhu, Bruce Rannala, Anne D. Yoder, and Ziheng Yang. “Estimation of species divergence times in presence of cross-species gene flow.Systematic Biology 72, no. 4 (August 2023): 820–36. https://doi.org/10.1093/sysbio/syad015.
Tiley GP, Flouri T, Jiao X, Poelstra JW, Xu B, Zhu T, et al. Estimation of species divergence times in presence of cross-species gene flow. Systematic biology. 2023 Aug;72(4):820–36.
Tiley, George P., et al. “Estimation of species divergence times in presence of cross-species gene flow.Systematic Biology, vol. 72, no. 4, Aug. 2023, pp. 820–36. Epmc, doi:10.1093/sysbio/syad015.
Tiley GP, Flouri T, Jiao X, Poelstra JW, Xu B, Zhu T, Rannala B, Yoder AD, Yang Z. Estimation of species divergence times in presence of cross-species gene flow. Systematic biology. 2023 Aug;72(4):820–836.
Journal cover image

Published In

Systematic biology

DOI

EISSN

1076-836X

ISSN

1063-5157

Publication Date

August 2023

Volume

72

Issue

4

Start / End Page

820 / 836

Related Subject Headings

  • Time Factors
  • Probability
  • Phylogeny
  • Models, Genetic
  • Gene Flow
  • Evolutionary Biology
  • Computer Simulation
  • 3105 Genetics
  • 3104 Evolutionary biology
  • 3103 Ecology