Support for a clade of Placozoa and Cnidaria in genes with minimal compositional bias
- Wellcome Trust Sanger Institute, United Kingdom
- Max Planck Institute for Marine Microbiology, Germany
- University of Hawaii at Manoa, United States
- University of California, Santa Cruz, United States
- The Natural History Museum, United Kingdom
- Harvard University, United States
Abstract
The phylogenetic placement of the morphologically simple placozoans is crucial to understanding the evolution of complex animal traits. Here, we examine the influence of adding new genomes from placozoans to a large dataset designed to study the deepest splits in the animal phylogeny. Using site-heterogeneous substitution models, we show that it is possible to obtain strong support, in both amino acid and reduced-alphabet matrices, for either a sister-group relationship between Cnidaria and Placozoa, or for Cnidaria and Bilateria as seen in most published work to date, depending on the orthologues selected to construct the matrix. We demonstrate that a majority of genes show evidence of compositional heterogeneity, and that support for the Cnidaria+Bilateria clade can be assigned to this source of systematic error. In interpreting these results, we caution against a peremptory reading of placozoans as secondarily reduced forms of little relevance to broader discussions of early animal evolution.
Data availability
SRA accession codes, where used, and all alternative sources for sequence data (e.g. individually hosted websites, personal communications), are listed above in the Materials and Methods section. A DataDryad accession is available at https://doi.org/10.5061/dryad.6cm1166, which makes available all helper scripts, orthogroups, multiple sequence alignments, phylogenetic program output, and raw host proteomes inputted to OrthoFinder. Metagenomic bins containing placozoan host contigs and raw RNA reads used to derive gene annotations from H4, H6 and H11 isolates are also provided in this accession. PhyloBayes .chain files, due to their large size, are separately accessioned at in Zenodo at https://doi.org/10.5281/zenodo.1197272.
-
Data from: Placozoa and Cnidaria are sister taxaDOI: https://doi.org/10.5061/dryad.6cm1166.
Article and author information
Author details
Christopher E Laumer
Funding
Max-Planck-Institute fuer Marine Microbiologie
- Harald Gruber-Vodicka
EMBL-European Bioinformatics Institute
- John C Marioni
Harvard University Faculty of Arts and Sciences
- Gonzalo Giribet
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2018, Laumer et al.
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.
Metrics
-
- 5,264
- views
-
- 730
- downloads
-
- 87
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
A two-part list of links to download the article, or parts of the article, in various formats.
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Support for a clade of Placozoa and Cnidaria in genes with minimal compositional bias
eLife 7:e36278.
https://doi.org/10.7554/eLife.36278
Further reading
-
- Evolutionary Biology
The majority of highly polymorphic genes are related to immune functions and with over 100 alleles within a population, genes of the major histocompatibility complex (MHC) are the most polymorphic loci in vertebrates. How such extraordinary polymorphism arose and is maintained is controversial. One possibility is heterozygote advantage (HA), which can in principle maintain any number of alleles, but biologically explicit models based on this mechanism have so far failed to reliably predict the coexistence of significantly more than 10 alleles. We here present an eco-evolutionary model showing that evolution can result in the emergence and maintenance of more than 100 alleles under HA if the following two assumptions are fulfilled: first, pathogens are lethal in the absence of an appropriate immune defence; second, the effect of pathogens depends on host condition, with hosts in poorer condition being affected more strongly. Thus, our results show that HA can be a more potent force in explaining the extraordinary polymorphism found at MHC loci than currently recognised.
-
- Computational and Systems Biology
- Evolutionary Biology
As pathogens spread in a population of hosts, immunity is built up, and the pool of susceptible individuals are depleted. This generates selective pressure, to which many human RNA viruses, such as influenza virus or SARS-CoV-2, respond with rapid antigenic evolution and frequent emergence of immune evasive variants. However, the host’s immune systems adapt, and older immune responses wane, such that escape variants only enjoy a growth advantage for a limited time. If variant growth dynamics and reshaping of host-immunity operate on comparable time scales, viral adaptation is determined by eco-evolutionary interactions that are not captured by models of rapid evolution in a fixed environment. Here, we use a Susceptible/Infected model to describe the interaction between an evolving viral population in a dynamic but immunologically diverse host population. We show that depending on strain cross-immunity, heterogeneity of the host population, and durability of immune responses, escape variants initially grow exponentially, but lose their growth advantage before reaching high frequencies. Their subsequent dynamics follows an anomalous random walk determined by future escape variants and results in variant trajectories that are unpredictable. This model can explain the apparent contradiction between the clearly adaptive nature of antigenic evolution and the quasi-neutral dynamics of high-frequency variants observed for influenza viruses.
