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Sequence evidence for common ancestry of eukaryotic endomembrane coatomers.

ABSTRACT: Eukaryotic cells are defined by compartments through which the trafficking of macromolecules is mediated by large complexes, such as the nuclear pore, transport vesicles and intraflagellar transport. The assembly and maintenance of these complexes is facilitated by endomembrane coatomers, long suspected to be divergently related on the basis of structural and more recently phylogenomic analysis. By performing supervised walks in sequence space across coatomer superfamilies, we uncover subtle sequence patterns that have remained elusive to date, ultimately unifying eukaryotic coatomers by divergent evolution. The conserved residues shared by 3,502 endomembrane coatomer components are mapped onto the solenoid superhelix of nucleoporin and COPII protein structures, thus determining the invariant elements of coatomer architecture. This ancient structural motif can be considered as a universal signature connecting eukaryotic coatomers involved in multiple cellular processes across cell physiology and human disease.

SUBMITTER: Promponas VJ

PROVIDER: S-EPMC4773986 | biostudies-literature | 2016 Mar

REPOSITORIES: biostudies-literature

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Sequence evidence for common ancestry of eukaryotic endomembrane coatomers.

Promponas Vasilis J VJ Katsani Katerina R KR Blencowe Benjamin J BJ Ouzounis Christos A CA

Scientific reports 20160302

Eukaryotic cells are defined by compartments through which the trafficking of macromolecules is mediated by large complexes, such as the nuclear pore, transport vesicles and intraflagellar transport. The assembly and maintenance of these complexes is facilitated by endomembrane coatomers, long suspected to be divergently related on the basis of structural and more recently phylogenomic analysis. By performing supervised walks in sequence space across coatomer superfamilies, we uncover subtle seq ...[more]

PMID: 26931514

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Project description:We address the problem of homology identification in complex multidomain families with varied domain architectures. The challenge is to distinguish sequence pairs that share common ancestry from pairs that share an inserted domain but are otherwise unrelated. This distinction is essential for accuracy in gene annotation, function prediction, and comparative genomics. There are two major obstacles to multidomain homology identification: lack of a formal definition and lack of curated benchmarks for evaluating the performance of new methods. We offer preliminary solutions to both problems: 1) an extension of the traditional model of homology to include domain insertions; and 2) a manually curated benchmark of well-studied families in mouse and human. We further present Neighborhood Correlation, a novel method that exploits the local structure of the sequence similarity network to identify homologs with great accuracy based on the observation that gene duplication and domain shuffling leave distinct patterns in the sequence similarity network. In a rigorous, empirical comparison using our curated data, Neighborhood Correlation outperforms sequence similarity, alignment length, and domain architecture comparison. Neighborhood Correlation is well suited for automated, genome-scale analyses. It is easy to compute, does not require explicit knowledge of domain architecture, and classifies both single and multidomain homologs with high accuracy. Homolog predictions obtained with our method, as well as our manually curated benchmark and a web-based visualization tool for exploratory analysis of the network neighborhood structure, are available at http://www.neighborhoodcorrelation.org. Our work represents a departure from the prevailing view that the concept of homology cannot be applied to genes that have undergone domain shuffling. In contrast to current approaches that either focus on the homology of individual domains or consider only families with identical domain architectures, we show that homology can be rationally defined for multidomain families with diverse architectures by considering the genomic context of the genes that encode them. Our study demonstrates the utility of mining network structure for evolutionary information, suggesting this is a fertile approach for investigating evolutionary processes in the post-genomic era.

Project description:BACKGROUND:The universal common ancestry (UCA) of all known life is a fundamental component of modern evolutionary theory, supported by a wide range of qualitative molecular evidence. Nevertheless, recently both the status and nature of UCA has been questioned. In earlier work I presented a formal, quantitative test of UCA in which model selection criteria overwhelmingly choose common ancestry over independent ancestry, based on a dataset of universally conserved proteins. These model-based tests are founded in likelihoodist and Bayesian probability theory, in opposition to classical frequentist null hypothesis tests such as Karlin-Altschul E-values for sequence similarity. In a recent comment, Koonin and Wolf (K&W) claim that the model preference for UCA is "a trivial consequence of significant sequence similarity". They support this claim with a computational simulation, derived from universally conserved proteins, which produces similar sequences lacking phylogenetic structure. The model selection tests prefer common ancestry for this artificial data set. RESULTS:For the real universal protein sequences, hierarchical phylogenetic structure (induced by genealogical history) is the overriding reason for why the tests choose UCA; sequence similarity is a relatively minor factor. First, for cases of conflicting phylogenetic structure, the tests choose independent ancestry even with highly similar sequences. Second, certain models, like star trees and K&W's profile model (corresponding to their simulation), readily explain sequence similarity yet lack phylogenetic structure. However, these are extremely poor models for the real proteins, even worse than independent ancestry models, though they explain K&W's artificial data well. Finally, K&W's simulation is an implementation of a well-known phylogenetic model, and it produces sequences that mimic homologous proteins. Therefore the model selection tests work appropriately with the artificial data. CONCLUSIONS:For K&W's artificial protein data, sequence similarity is the predominant factor influencing the preference for common ancestry. In contrast, for the real proteins, model selection tests show that phylogenetic structure is much more important than sequence similarity. Hence, the model selection tests demonstrate that real universally conserved proteins are homologous, a conclusion based primarily on the specific nested patterns of correlations induced in genetically related protein sequences. REVIEWERS:This article was reviewed by Rob Knight, Robert Beiko (nominated by Peter Gogarten), and Michael Gilchrist.

Project description:BACKGROUND: The Nuclear Pore Complex (NPC) facilitates molecular trafficking between nucleus and cytoplasm and is an integral feature of the eukaryote cell. It exhibits eight-fold rotational symmetry and is comprised of approximately 30 nucleoporins (Nups) in different stoichiometries. Nups are broadly conserved between yeast, vertebrates and plants, but few have been identified among other major eukaryotic groups. METHODOLOGY/PRINCIPAL FINDINGS: We screened for Nups across 60 eukaryote genomes and report that 19 Nups (spanning all major protein subcomplexes) are found in all eukaryote supergroups represented in our study (Opisthokonts, Amoebozoa, Viridiplantae, Chromalveolates and Excavates). Based on parsimony, between 23 and 26 of 31 Nups can be placed in LECA. Notably, they include central components of the anchoring system (Ndc1 and Gp210) indicating that the anchoring system did not evolve by convergence, as has previously been suggested. These results significantly extend earlier results and, importantly, unambiguously place a fully-fledged NPC in LECA. We also test the proposal that transmembrane Pom proteins in vertebrates and yeasts may account for their variant forms of mitosis (open mitoses in vertebrates, closed among yeasts). The distribution of homologues of vertebrate Pom121 and yeast Pom152 is not consistent with this suggestion, but the distribution of fungal Pom34 fits a scenario wherein it was integral to the evolution of closed mitosis in ascomycetes. We also report an updated screen for vesicle coating complexes, which share a common evolutionary origin with Nups, and can be traced back to LECA. Surprisingly, we find only three supergroup-level differences (one gain and two losses) between the constituents of COPI, COPII and Clathrin complexes. CONCLUSIONS/SIGNIFICANCE: Our results indicate that all major protein subcomplexes in the Nuclear Pore Complex are traceable to the Last Eukaryotic Common Ancestor (LECA). In contrast to previous screens, we demonstrate that our conclusions hold regardless of the position of the root of the eukaryote tree.

Dataset Information

Sequence evidence for common ancestry of eukaryotic endomembrane coatomers.

Publications

Sequence evidence for common ancestry of eukaryotic endomembrane coatomers.

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