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BMC evolutionary biology2018; 18(1); 70; doi: 10.1186/s12862-018-1192-3

A comparison of methods for estimating substitution rates from ancient DNA sequence data.

Abstract: Phylogenetic analysis of DNA from modern and ancient samples allows the reconstruction of important demographic and evolutionary processes. A critical component of these analyses is the estimation of evolutionary rates, which can be calibrated using information about the ages of the samples. However, the reliability of these rate estimates can be negatively affected by among-lineage rate variation and non-random sampling. Using a simulation study, we compared the performance of three phylogenetic methods for inferring evolutionary rates from time-structured data sets: regression of root-to-tip distances, least-squares dating, and Bayesian inference. We also applied these three methods to time-structured mitogenomic data sets from six vertebrate species. Our results from 12 simulation scenarios show that the three methods produce reliable estimates when the substitution rate is high, rate variation is low, and samples of similar ages are not all grouped together in the tree (i.e., low phylo-temporal clustering). The interaction of these factors is particularly important for least-squares dating and Bayesian estimation of evolutionary rates. The three estimation methods produced consistent estimates of rates across most of the six mitogenomic data sets, with sequence data from horses being an exception. We recommend that phylogenetic studies of ancient DNA sequences should use multiple methods of inference and test for the presence of temporal signal, among-lineage rate variation, and phylo-temporal clustering in the data.
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Publication Date: 2018-05-16 PubMed ID: 29769015PubMed Central: PMC5956955DOI: 10.1186/s12862-018-1192-3Google Scholar: Lookup
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  • Comparative Study
  • Journal Article
  • Research Support
  • Non-U.S. Gov't

Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

The research in this article focuses on comparing three phylogenetic methods for calculating evolutionary rates using DNA from modern and ancient samples. The aim was to establish which method provided the most reliable results in different circumstances. The authors suggested muti-method inference and testing for certain data characteristics for optimal evaluation of ancient DNA sequences.

Phylogenetic analysis of DNA samples

  • The researchers’ main task was to analyze DNA from modern and ancient samples to reconstruct demographic and evolutionary processes. They were particularly interested in estimating evolutionary rates, which can provide insights into the genetic changes in species over time.
  • These rates can be calibrated using information about the ages of the samples. However, two issues can negatively affect the rate estimates: variation in rates among different lineages and non-random sampling.

Comparison of different methods

  • The study compared three methods for determining evolutionary rates from time-structured data sets. These methods include: regression of root-to-tip distances, least-squares dating, and Bayesian inference.
  • These were applied to time-structured mitogenomic data sets from six different vertebrate species to evaluate their effectiveness for different types and amounts of data.

Findings from the simulation scenarios

  • The results from 12 simulation scenarios demonstrated that all three methods tend to make reliable estimates when the following conditions are met: the substitution rate is high, rate variation is low, and samples of similar ages are scattered throughout the tree, rather than being grouped together (also known as low phylo-temporal clustering).
  • The interaction between these factors was noted to be particularly significant for the least-squares dating and Bayesian estimation methods. This means that if these conditions are not met, these latter two methods may produce less accurate rate estimates.
  • The three methods provided largely consistent estimates of rates across most of the six mitogenomic data sets. However, the sequence data from horses was a notable exception, indicating potential limitations of these methods for certain types of data.

Recommendations for future research

  • The authors recommend using a mixed-methods approach in future phylogenetic studies of ancient DNA sequence data to provide a more robust analysis.
  • Additionally, researchers should also test for the presence of temporal signal, among-lineage rate variation, and phylo-temporal clustering in the data as these factors can significantly affect the accuracy of the evolutionary rate estimates.

Cite This Article

APA
Tong KJ, Duchêne DA, Duchêne S, Geoghegan JL, Ho SYW. (2018). A comparison of methods for estimating substitution rates from ancient DNA sequence data. BMC Evol Biol, 18(1), 70. https://doi.org/10.1186/s12862-018-1192-3

Publication

BMC evolutionary biology
ISSN: 1471-2148
NlmUniqueID: 100966975
Country: England
Language: English
Volume: 18
Issue: 1
Pages: 70
PII: 70

Researcher Affiliations

Tong, K Jun
  • School of Life and Environmental Sciences, University of Sydney, Sydney, Australia.
Duchêne, David A
  • School of Life and Environmental Sciences, University of Sydney, Sydney, Australia.
Duchêne, Sebastián
  • Department of Biochemistry and Molecular Biology, Bio21 Molecular Science and Biotechnology Institute, University of Melbourne, Melbourne, Australia.
Geoghegan, Jemma L
  • Department of Biological Sciences, Macquarie University, Sydney, Australia.
Ho, Simon Y W
  • School of Life and Environmental Sciences, University of Sydney, Sydney, Australia. simon.ho@sydney.edu.au.

MeSH Terms

  • Animals
  • Base Sequence
  • Bayes Theorem
  • Computer Simulation
  • DNA, Ancient
  • Evolution, Molecular
  • Genome, Mitochondrial
  • Genomics / methods
  • Horses
  • Mutation / genetics
  • Phylogeny
  • Time Factors
  • Uncertainty
  • Vertebrates / genetics

Grant Funding

  • FT160100167 / Australian Research Council

Conflict of Interest Statement

ETHICS APPROVAL AND CONSENT TO PARTICIPATE: Not applicable. COMPETING INTERESTS: The authors declare that they have no competing interests. PUBLISHER’S NOTE: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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