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Published on: August 14, 2018
Developmental characters in phylogenetic inference and their absolute timing information
Michel Laurin1, Damien Germain
1UMR CNRS 7207 "Centre de Recherches sur la Paléobiodiversité et les Paléoenvironnements," Muséum National d'Histoire Naturelle, Département Histoire de la Terre, Bâtiment de Géologie, Case Postale 48, 43 Rue Buffon, F-75231 Paris Cedex 05, France. michel.laurin@upmc.fr
This study shows that developmental data can reliably inform evolutionary trees. A new coding method for ontogenetic sequences effectively captures phylogenetic signals, outperforming older techniques.
Area of Science:
- Evolutionary Biology
- Developmental Biology
- Phylogenetics
Background:
- Limited research exists on phylogenetic signals within developmental characters.
- The utility of developmental data in phylogenetics hinges on capturing these signals effectively.
Purpose of the Study:
- To evaluate the phylogenetic signal in developmental characters.
- To compare different coding methods for analyzing ontogenetic data in phylogenetics.
- To validate the use of developmental data for inferring evolutionary relationships.
Main Methods:
- Simulated developmental data were analyzed using various coding schemes.
- Comparison of 'continuous analysis' with standardized time/ontogenetic sequences against 'event pairing' and 'event cracking'.
- Parsimony analysis was employed to assess phylogenetic reconstruction accuracy.
Main Results:
- All tested coding methods, including event pairing and standardized ontogenetic sequences, yield phylogenetically informative data.
- The new coding method for continuous analysis outperforms event pairing, recovering fewer incorrect clades.
- Parsimony analysis of developmental characters converges on the correct phylogeny with increasing data, despite some character dependence.
Conclusions:
- Ontogenetic data are validated for use in phylogenetic inference.
- A simple coding scheme effectively extracts reliable phylogenetic signals from developmental data.
- The continuous analysis method offers an improved approach for analyzing evolutionary developmental data.
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