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Record W2761759859 · doi:10.1038/ismej.2017.167

Single cell genomics of uncultured marine alveolates shows paraphyly of basal dinoflagellates

2017· article· en· W2761759859 on OpenAlexafffund
Jürgen F. H. Strassert, Anna Karnkowska, Elisabeth Hehenberger, Javier del Campo, Martin Kolísko, Noriko Okamoto, Fabien Burki, Jan Janouškovec, Camille Poirier, Guy Leonard, Steven Hallam, Thomas A. Richards, Alexandra Z. Worden, Alyson E. Santoro, Patrick J. Keeling

Bibliographic record

VenueThe ISME Journal · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtist diversity and phylogeny
Canadian institutionsUniversity of British Columbia
FundersFP7 People: Marie-Curie ActionsTula FoundationGordon and Betty Moore FoundationDavid and Lucile Packard Foundation
KeywordsBiologyParaphylyDinoflagellateHaptophyteSister groupEukaryotePhylogenetic treeGenePhylogeneticsGeneticsGymnodiniumEvolutionary biologyRibosomal RNAGenomeBotanyCladeEcology

Abstract

fetched live from OpenAlex

Abstract Marine alveolates (MALVs) are diverse and widespread early-branching dinoflagellates, but most knowledge of the group comes from a few cultured species that are generally not abundant in natural samples, or from diversity analyses of PCR-based environmental SSU rRNA gene sequences. To more broadly examine MALV genomes, we generated single cell genome sequences from seven individually isolated cells. Genes expected of heterotrophic eukaryotes were found, with interesting exceptions like presence of proteorhodopsin and vacuolar H+-pyrophosphatase. Phylogenetic analysis of concatenated SSU and LSU rRNA gene sequences provided strong support for the paraphyly of MALV lineages. Dinoflagellate viral nucleoproteins were found only in MALV groups that branched as sister to dinokaryotes. Our findings indicate that multiple independent origins of several characteristics early in dinoflagellate evolution, such as a parasitic life style, underlie the environmental diversity of MALVs, and suggest they have more varied trophic modes than previously thought.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.258

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.217
Teacher spread0.203 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations43
Published2017
Admission routes2
Has abstractyes

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