Step-wise evolution of complex chemical defenses in millipedes: a phylogenomic approach

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Abstract

With fossil representatives from the Silurian capable of respiring atmospheric oxygen, millipedes are among the oldest terrestrial animals, and likely the first to acquire diverse and complex chemical defenses against predators. Exploring the origin of complex adaptive traits is critical for understanding the evolution of Earth’s biological complexity, and chemical defense evolution serves as an ideal study system. The classic explanation for the evolution of complexity is by gradual increase from simple to complex, passing through intermediate “stepping stone” states. Here we present the first phylogenetic-based study of the evolution of complex chemical defenses in millipedes by generating the largest genomic-based phylogenetic dataset ever assembled for the group. Our phylogenomic results demonstrate that chemical complexity shows a clear pattern of escalation through time. New pathways are added in a stepwise pattern, leading to greater chemical complexity, independently in a number of derived lineages. This complexity gradually increased through time, leading to the advent of three distantly related chemically complex evolutionary lineages, each uniquely characteristic of each of the respective millipede groups.

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ASTRAL: genome-scale coalescent-based species tree estimation

S. Mirarab, R. Reaz, Md. S. Bayzid … (2014)

Motivation: Species trees provide insight into basic biology, including the mechanisms of evolution and how it modifies biomolecular function and structure, biodiversity and co-evolution between genes and species. Yet, gene trees often differ from species trees, creating challenges to species tree estimation. One of the most frequent causes for conflicting topologies between gene trees and species trees is incomplete lineage sorting (ILS), which is modelled by the multi-species coalescent. While many methods have been developed to estimate species trees from multiple genes, some which have statistical guarantees under the multi-species coalescent model, existing methods are too computationally intensive for use with genome-scale analyses or have been shown to have poor accuracy under some realistic conditions. Results: We present ASTRAL, a fast method for estimating species trees from multiple genes. ASTRAL is statistically consistent, can run on datasets with thousands of genes and has outstanding accuracy—improving on MP-EST and the population tree from BUCKy, two statistically consistent leading coalescent-based methods. ASTRAL is often more accurate than concatenation using maximum likelihood, except when ILS levels are low or there are too few gene trees. Availability and implementation: ASTRAL is available in open source form at https://github.com/smirarab/ASTRAL/. Datasets studied in this article are available at http://www.cs.utexas.edu/users/phylo/datasets/astral. Contact: warnow@illinois.edu Supplementary information: Supplementary data are available at Bioinformatics online.

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Estimating Absolute Rates of Molecular Evolution and Divergence Times: A Penalized Likelihood Approach

M. Sanderson (2002)

Rates of molecular evolution vary widely between lineages, but quantification of how rates change has proven difficult. Recently proposed estimation procedures have mainly adopted highly parametric approaches that model rate evolution explicitly. In this study, a semiparametric smoothing method is developed using penalized likelihood. A saturated model in which every lineage has a separate rate is combined with a roughness penalty that discourages rates from varying too much across a phylogeny. A data-driven cross-validation criterion is then used to determine an optimal level of smoothing. This criterion is based on an estimate of the average prediction error associated with pruning lineages from the tree. The methods are applied to three data sets of six genes across a sample of land plants. Optimally smoothed estimates of absolute rates entailed 2- to 10-fold variation across lineages.

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Estimating trait-dependent speciation and extinction rates from incompletely resolved phylogenies.

Richard G. FitzJohn, Wayne P. Maddison, Sarah Otto (2009)

Species traits may influence rates of speciation and extinction, affecting both the patterns of diversification among lineages and the distribution of traits among species. Existing likelihood approaches for detecting differential diversification require complete phylogenies; that is, every extant species must be present in a well-resolved phylogeny. We developed 2 likelihood methods that can be used to infer the effect of a trait on speciation and extinction without complete phylogenetic information, generalizing the recent binary-state speciation and extinction method. Our approaches can be used where a phylogeny can be reasonably assumed to be a random sample of extant species or where all extant species are included but some are assigned only to terminal unresolved clades. We explored the effects of decreasing phylogenetic resolution on the ability of our approach to detect differential diversification within a Bayesian framework using simulated phylogenies. Differential diversification caused by an asymmetry in speciation rates was nearly as well detected with only 50% of extant species phylogenetically resolved as with complete phylogenetic knowledge. We demonstrate our unresolved clade method with an analysis of sexual dimorphism and diversification in shorebirds (Charadriiformes). Our methods allow for the direct estimation of the effect of a trait on speciation and extinction rates using incompletely resolved phylogenies.

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Author and article information

Contributors

Jason E. Bond: jeb0037@auburn.edu

Journal

Journal ID (nlm-ta): Sci Rep

Journal ID (iso-abbrev): Sci Rep

Title: Scientific Reports

Publisher: Nature Publishing Group UK (London )

ISSN (Electronic): 2045-2322

Publication date (Electronic): 16 February 2018

Publication date PMC-release: 16 February 2018

Publication date Collection: 2018

Volume: 8

Electronic Location Identifier: 3209

Affiliations

[1 ]ISNI 0000 0001 2297 8753, GRID grid.252546.2, Department of Biological Sciences, , Auburn University, ; Auburn, AL 36849 USA

[2 ]CSIRO, Australian National Insect Collection, Canberra, ACT 2601 Australia

[3 ]ISNI 0000 0001 2228 0996, GRID grid.267893.1, Department of Chemistry, , Virginia Military Institute, ; Lexington, VA 24450 USA

[4 ]ISNI 0000 0001 0476 8496, GRID grid.299784.9, Zoology Department, , The Field Museum, ; Chicago, IL 60605 USA

[5 ]ISNI 0000 0001 0694 4940, GRID grid.438526.e, Department of Entomology, , Virginia Tech, ; Blacksburg, VA 24061 USA

[6 ]ISNI 0000 0001 0426 7392, GRID grid.256771.0, Biology Department, , Hampden-Sydney College, ; Farmville, VA 23943 USA

[7 ]ISNI 0000 0001 2191 0423, GRID grid.255364.3, Department of Biology, , East Carolina University, ; Greenville, NC 27858 USA

[8 ]ISNI 0000 0001 0727 7545, GRID grid.411015.0, Department of Biological Sciences, , University of Alabama, ; Tuscaloosa, AL 35487 USA

Article

Publisher ID: 19996

DOI: 10.1038/s41598-018-19996-6

PMC ID: 5816663

PubMed ID: 29453332

SO-VID: c53ef2cf-69d1-4693-9490-b3f26d085ec3

License:

Open Access 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/.

History

Date received : 6 September 2017

Date accepted : 11 January 2018

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Step-wise evolution of complex chemical defenses in millipedes: a phylogenomic approach

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Most cited references 55

ASTRAL: genome-scale coalescent-based species tree estimation

Estimating Absolute Rates of Molecular Evolution and Divergence Times: A Penalized Likelihood Approach

Estimating trait-dependent speciation and extinction rates from incompletely resolved phylogenies.

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Cited by 16

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