eggNOG v2.0: extending the evolutionary genealogy of genes with enhanced non-supervised orthologous groups, species and functional annotations

Muller, Jean; Szklarczyk, Damian; Julien, Philippe; Letunić, Ivica; Röth, Alexander; Kuhn, Michael; Powell, Sean; Mering, Christian von; Doerks, Tobias; Jensen, Lars Juhl; Bork, Peer

doi:10.1093/nar/gkp951

Cited by 204 publications

(190 citation statements)

References 42 publications

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“…Additions were made to a previous set of H V 1s and other VSD-containing proteins (24) by searching the updated eggNOG (57) database, which uses criteria that provide high-confidence homologs. The full set of VSDs was realigned using PromalS3D (58) as previously described (24).…”

Section: Methodsmentioning

confidence: 99%

Voltage-gated proton channel in a dinoflagellate

Smith

Morgan

Musset

et al. 2011

Proc. Natl. Acad. Sci. U.S.A.

113

214

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Fogel and Hastings first hypothesized the existence of voltagegated proton channels in 1972 in bioluminescent dinoflagellates, where they were thought to trigger the flash by activating luciferase. Proton channel genes were subsequently identified in human, mouse, and Ciona intestinalis, but their existence in dinoflagellates remained unconfirmed. We identified a candidate proton channel gene from a Karlodinium veneficum cDNA library based on homology with known proton channel genes. K. veneficum is a predatory, nonbioluminescent dinoflagellate that produces toxins responsible for fish kills worldwide. Patch clamp studies on the heterologously expressed gene confirm that it codes for a genuine voltage-gated proton channel, kH V 1: it is proton-specific and activated by depolarization, its g H -V relationship shifts with changes in external or internal pH, and mutation of the selectivity filter (which we identify as Asp 51 ) results in loss of proton-specific conduction. Indirect evidence suggests that kH V 1 is monomeric, unlike other proton channels. Furthermore, kH V 1 differs from all known proton channels in activating well negative to the Nernst potential for protons, E H . This unique voltage dependence makes the dinoflagellate proton channel ideally suited to mediate the proton influx postulated to trigger bioluminescence. In contrast to vertebrate proton channels, whose main function is acid extrusion, we propose that proton channels in dinoflagellates have fundamentally different functions of signaling and excitability.ion selectivity | ion channel | permeation | channel gating | action potential

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Section: Methodsmentioning

confidence: 99%

Voltage-gated proton channel in a dinoflagellate

Smith

Morgan

Musset

et al. 2011

Proc. Natl. Acad. Sci. U.S.A.

113

214

View full text Add to dashboard Cite

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“…ORFs were called with the help of the ab initio gene finder MetageneMark 56 . We used BLASTP to query the protein sequences encoded by the predicted genes in eggNOG 57 and iPath 58 with an E-value cutoff of <1 × 10 −5 . PCR amplification was conducted with the 515f/806r primer set that amplifies the V4 region of the 16S rRNA gene.…”

Section: Competing Financial Interestsmentioning

confidence: 99%

Whole-genome sequencing of the snub-nosed monkey provides insights into folivory and evolutionary history

et al. 2014

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Colobines are a unique group of Old World monkeys that principally eat leaves and seeds rather than fruits and insects. We report the sequencing at 146× coverage, de novo assembly and analyses of the genome of a male golden snub-nosed monkey (Rhinopithecus roxellana) and resequencing at 30× coverage of three related species (Rhinopithecus bieti, Rhinopithecus brelichi and Rhinopithecus strykeri). Comparative analyses showed that Asian colobines have an enhanced ability to derive energy from fatty acids and to degrade xenobiotics. We found evidence for functional evolution in the colobine RNASE1 gene, encoding a key secretory RNase that digests the high concentrations of bacterial RNA derived from symbiotic microflora. Demographic reconstructions indicated that the profile of ancient effective population sizes for R. roxellana more closely resembles that of giant panda rather than its congeners. These findings offer new insights into the dietary adaptations and evolutionary history of colobine primates.Knowledge of the patterns and processes underlying the evolution of alternative dietary strategies in nonhuman primates is critical to understanding hominin evolution, nutritional ecology and applications in biomedicine 1 . Colobines, a group of Old World monkeys, serve as an important model organism for studying the evolution of the primate diet because of their adaptation to folivory: they primarily eat leaves and seeds rather than fruits and insects as their major food source. In their specialized and compartmentalized stomachs, colobines allow symbiotic bacteria in the foregut to ferment structural carbohydrates and then recover nutrients by digesting the bacteria 2 . This strategy is similar to that used by other foregut fermenters found in an evolutionarily distantly related group of mammals (for example, artiodactyls). Although a number of primate genomes have been sequenced thus far, high-quality genome sequence information is absent for Asian and African colobines, a key group for elucidating the evolution and adaptation of primates as a whole. Snub-nosed monkeys (Rhinopithecus species) are a group of endangered colobines, which were once widely distributed in Asia but are now limited to mountain forests in China and Vietnam 3 (Supplementary Fig. 1).The golden snub-nosed monkey (GSM, R. roxellana) is recognized as an iconic endangered species in China for its golden coat, blue facial coloration, snub nose and specialized life history. Among its congeners, the black-white snub-nosed monkey (R. bieti), endemic to the Tibetan plateau, has the highest altitudinal distribution (>4,000 m above sea level) of any nonhuman primate. Given the above features and the fact that Rhinopithecus species consume difficult-to-digest foods that contain tannins (for example, leaves and pine seeds), we expected to identify genetic adaptations that enhance the breakdown of toxins, improve the regulation of energy metabolism and facilitate the digestion of symbiotic microbacteria. RESULTS Genomic sequences and the accumulation of...

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“…More precisely, each protein has been associated to a binary feature vector, representing a protein profile, whose [3] Motif fingerprints InterPro [45] Protein families, domains and functional sites EggNOG [46] Non-supervised Orthologous Groups Pfam [19] Protein domain Swiss-Prot [5] Manually curated keywords describing the function of the proteins Protein superfamilies [23] Structural and functional annotations elements are 1 when the protein is annotated for a specific feature (e.g. includes a specific domain, or a specific motif), and 0 otherwise.…”

Section: Datamentioning

confidence: 99%

Learning node labels with multi-category Hopfield networks

Frasca

Bassis

Valentini

2015

Neural Comput & Applic

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In several real-world node-label prediction problems on graphs, in fields ranging from computational biology to World-Wide-Web analysis, nodes can be partitioned into categories different from the classes to be predicted, on the basis of their characteristics or their common properties. Such partitions may provide further information about node classification that classical machine learning algorithms do not take into account. We introduce a novel family of parametric Hopfield networks (m-Category Hopfield Networks) and a novel algorithm (Hopfield Multi-Category -HoMCat), designed to appropriately exploit the presence of propertybased partitions of nodes into multiple categories. Moreover, the proposed model adopts a cost-sensitive learning strategy to prevent the remarkable decay in performance usually observed when instance labels are unbalanced, that is when one class of labels is highly under-represented than the other one. We validate the proposed model on both synthetic and real-world data, in the context of multi-species function prediction, where the classes to be predicted are the Gene Ontology terms and the categories the different species in the multi-species protein network. We carried out an intensive experimental validation, which on the one hand compares HoMCat with several state-of-the-art graph-based algorithms, and on the other hand reveals that exploiting meaningful prior partitions of input data can substantially improve classification performances.

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eggNOG v2.0: extending the evolutionary genealogy of genes with enhanced non-supervised orthologous groups, species and functional annotations

Cited by 204 publications

References 42 publications

Voltage-gated proton channel in a dinoflagellate

Voltage-gated proton channel in a dinoflagellate

Whole-genome sequencing of the snub-nosed monkey provides insights into folivory and evolutionary history

Learning node labels with multi-category Hopfield networks

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