Metazoan evolution of glutamate receptors reveals unreported phylogenetic groups and divergent lineage-specific events
Abstract
Glutamate receptors are divided in two unrelated families: ionotropic (iGluR), driving synaptic transmission, and metabotropic (mGluR), which modulate synaptic strength. The present classification of GluRs is based on vertebrate proteins and has remained unchanged for over two decades. Here we report an exhaustive phylogenetic study of GluRs in metazoans. Importantly, we demonstrate that GluRs have followed different evolutionary histories in separated animal lineages. Our analysis reveals that the present organization of iGluRs into six classes does not capture the full complexity of their evolution. Instead, we propose an organization into four subfamilies and ten classes, four of which have never been previously described. Furthermore, we report a sister class to mGluR classes I-III, class IV. We show that many unreported proteins are expressed in the nervous system, and that new Epsilon receptors form functional ligand-gated ion channels. We propose an updated classification of glutamate receptors that includes our findings.
Data availability
All data generated or analysed during this study are included in the manuscript and supporting files. Source data files have been provided for Figures 1, Figure 1 - figure supplement 1, Figure 1 - figure supplement 3, Figure 1 - figure supplement 4, Figure2, Figure 4, Figure 4 - figure supplement 1 and Figure 4 - figure supplement 3.
-
The genome of the sea urchin Strongylocentrotus purpuratusEnsembl Metazoa, Strongylocentrotus purpuratus.
-
Insights into bilaterian evolution from three spiralian genomesEnsembl Metazoa, Lottia gigantea.
-
Insights into bilaterian evolution from three spiralian genomesEnsembl Metazoa, Capitella teleta.
-
Finding the missing honey bee genes: lessons learned from a genome upgradeEnsembl Metazoa, Apis mellifera.
-
Sea anemone genome reveals ancestral eumetazoan gene repertoire and genomic organizationEnsembl Metazoa, Nematostella vectensis.
-
The Trichoplax genome and the nature of placozoansEnsembl Metazoa, Trichoplax adhaerens.
-
The genome of the ctenophore Mnemiopsis leidyi and its implications for cell type evolutionEnsembl Metazoa, Mnemiopsis leidyi.
-
Analysis of the genome sequence of the flowering plant Arabidopsis thalianaThe Arabidopsis Information Resource, TAIR.
-
Genome Reference Consortium Zebrafish Build 11Ensembl, danio_rerio.
-
Decelerated genome evolution in modern vertebrates revealed by analysis of multiple lancelet genomesLanceletDB, B.belcheri_HapV2(v7h2)_cds.
-
Hemichordate genomes and deuterostome originsMarine Genomics Unit, Ptychodera flava.
-
Using the Acropora digitifera genome to understand coral responses to environmental changeMarine Genomics Unit, Acropora digitifera.
-
The amphioxus genome and the evolution of the chordate karyotypeJoint Genome Institute, Brafl1.
Article and author information
Author details
Funding
Ministerio de Economía y Competitividad (BFU2012-34398)
- David Ramos-Vicente
- Gemma Gou
- Rita Reig-Viader
- Javier Luís
- Àlex Bayés
Ministerio de Economía y Competitividad (BFU2014-57562-P)
- David Soto
Centre National de la Recherche Scientifique (ANR-16-CE12-0008-01)
- Hector Escriva
Ministerio de Economía y Competitividad (BFU2017-83317-P)
- David Soto
Ministerio de Economía y Competitividad (RD16/0008/0014)
- David Soto
Ministerio de Economía y Competitividad (BFU2015-69717-P)
- David Ramos-Vicente
- Gemma Gou
- Rita Reig-Viader
- Javier Luís
- Àlex Bayés
Seventh Framework Programme (304111)
- David Ramos-Vicente
- Gemma Gou
- Rita Reig-Viader
- Javier Luís
- Àlex Bayés
Ministerio de Economía y Competitividad (RYC-2011-08391)
- Àlex Bayés
Ministerio de Economía y Competitividad (RYC-2010-06210)
- Nerea Roher
China Scholarship Council (CSC-2013-06300075)
- Jie Ji
Ministerio de Economía y Competitividad (SAF2014-57994-R)
- Pablo Fuentes-Prior
Ministerio de Economía y Competitividad (AGL2015-65129-R)
- Jie Ji
- Nerea Roher
Generalitat de Catalunya (SGR-345-2014)
- David Ramos-Vicente
- Gemma Gou
- Rita Reig-Viader
- Javier Luís
- Àlex Bayés
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2018, Ramos-Vicente 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
-
- 4,180
- views
-
- 601
- downloads
-
- 46
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
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)
Further reading
-
- Evolutionary Biology
With the availability of high-quality full genome polymorphism (SNPs) data, it becomes feasible to study the past demographic and selective history of populations in exquisite detail. However, such inferences still suffer from a lack of statistical resolution for recent, for example bottlenecks, events, and/or for populations with small nucleotide diversity. Additional heritable (epi)genetic markers, such as indels, transposable elements, microsatellites, or cytosine methylation, may provide further, yet untapped, information on the recent past population history. We extend the Sequential Markovian Coalescent (SMC) framework to jointly use SNPs and other hyper-mutable markers. We are able to (1) improve the accuracy of demographic inference in recent times, (2) uncover past demographic events hidden to SNP-based inference methods, and (3) infer the hyper-mutable marker mutation rates under a finite site model. As a proof of principle, we focus on demographic inference in Arabidopsis thaliana using DNA methylation diversity data from 10 European natural accessions. We demonstrate that segregating single methylated polymorphisms (SMPs) satisfy the modeling assumptions of the SMC framework, while differentially methylated regions (DMRs) are not suitable as their length exceeds that of the genomic distance between two recombination events. Combining SNPs and SMPs while accounting for site- and region-level epimutation processes, we provide new estimates of the glacial age bottleneck and post-glacial population expansion of the European A. thaliana population. Our SMC framework readily accounts for a wide range of heritable genomic markers, thus paving the way for next-generation inference of evolutionary history by combining information from several genetic and epigenetic markers.
-
- Computational and Systems Biology
- Evolutionary Biology
There is growing interest in designing multidrug therapies that leverage tradeoffs to combat resistance. Tradeoffs are common in evolution and occur when, for example, resistance to one drug results in sensitivity to another. Major questions remain about the extent to which tradeoffs are reliable, specifically, whether the mutants that provide resistance to a given drug all suffer similar tradeoffs. This question is difficult because the drug-resistant mutants observed in the clinic, and even those evolved in controlled laboratory settings, are often biased towards those that provide large fitness benefits. Thus, the mutations (and mechanisms) that provide drug resistance may be more diverse than current data suggests. Here, we perform evolution experiments utilizing lineage-tracking to capture a fuller spectrum of mutations that give yeast cells a fitness advantage in fluconazole, a common antifungal drug. We then quantify fitness tradeoffs for each of 774 evolved mutants across 12 environments, finding these mutants group into classes with characteristically different tradeoffs. Their unique tradeoffs may imply that each group of mutants affects fitness through different underlying mechanisms. Some of the groupings we find are surprising. For example, we find some mutants that resist single drugs do not resist their combination, while others do. And some mutants to the same gene have different tradeoffs than others. These findings, on one hand, demonstrate the difficulty in relying on consistent or intuitive tradeoffs when designing multidrug treatments. On the other hand, by demonstrating that hundreds of adaptive mutations can be reduced to a few groups with characteristic tradeoffs, our findings may yet empower multidrug strategies that leverage tradeoffs to combat resistance. More generally speaking, by grouping mutants that likely affect fitness through similar underlying mechanisms, our work guides efforts to map the phenotypic effects of mutation.