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Record W2003010041 · doi:10.1038/nature12221

Pan genome of the phytoplankton Emiliania underpins its global distribution

2013· article· en· W2003010041 on OpenAlexaff
Betsy Read, Jessica Kegel, Mary J. Klute, Alan Kuo, Stephane C. Lefebvre, Florian Maumus, Christoph Mayer, J. J. Miller, Adam Monier, Asaf Salamov, J. R. Young, María José Cuesta Aguilar, Jean‐Michel Claverie, Stephan Frickenhaus, Karina González, Emily K. Herman, Yao‐Cheng Lin, Johnathan A. Napier, Hiroyuki Ogata, Analissa F. Sarno, Jeremy Shmutz, Declan C. Schroeder, Colomban De Vargas, Frédéric Verret, Peter von Dassow, Klaus-Ulrich Valentin, Yves Van de Peer, Glen Wheeler, Joel B. Dacks, Charles F. Delwiche, Sonya T. Dyhrman, Gernot Glöckner, Uwe John, Thomas A. Richards, Alexandra Z. Worden, Xiaoyu Zhang, Igor V. Grigoriev

Bibliographic record

VenueNature · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial Community Ecology and Physiology
Canadian institutionsUniversity of Alberta
FundersBiotechnology and Biological Sciences Research CouncilOffice of ScienceAgence Nationale de la RechercheSight Research UKJoint Genome InstituteNatural Environment Research CouncilU.S. Department of Energy
KeywordsEmiliania huxleyiHaptophyteCoccolithophorePhytoplanktonBiologyOceanographyEcologyEvolutionary biologyGeologyNutrient

Abstract

fetched live from OpenAlex

A reference genome from the coccolithophore Emiliania huxleyi is presented, along with sequences from 13 additional isolates, revealing a pan genome comprising core genes and genes variably distributed between strains: E. huxleyi is found to harbour extensive genetic variability under different metabolic repertoires, explaining its ability to thrive under a diverse range of environmental conditions. This paper presents a reference genome from the coccolithophore Emiliania huxleyi strain CCMP1516. Coccolithophores are a major component of marine phytoplankton and can account for 20% of total carbon fixation in some systems, so have an important influence on global climate. Comparison of the reference genome to sequences from 13 other strains reveals a pan genome composed of core genes and genes variably distributed between strains. The findings indicate extensive genome variability reflected in different metabolic repertoires, explaining in part how E. huxleyi can thrive and form large-scale episodic blooms under a wide variety of environments. Coccolithophores have influenced the global climate for over 200 million years1. These marine phytoplankton can account for 20 per cent of total carbon fixation in some systems2. They form blooms that can occupy hundreds of thousands of square kilometres and are distinguished by their elegantly sculpted calcium carbonate exoskeletons (coccoliths), rendering them visible from space3. Although coccolithophores export carbon in the form of organic matter and calcite to the sea floor, they also release CO2 in the calcification process. Hence, they have a complex influence on the carbon cycle, driving either CO2 production or uptake, sequestration and export to the deep ocean4. Here we report the first haptophyte reference genome, from the coccolithophore Emiliania huxleyi strain CCMP1516, and sequences from 13 additional isolates. Our analyses reveal a pan genome (core genes plus genes distributed variably between strains) probably supported by an atypical complement of repetitive sequence in the genome. Comparisons across strains demonstrate that E. huxleyi, which has long been considered a single species, harbours extensive genome variability reflected in different metabolic repertoires. Genome variability within this species complex seems to underpin its capacity both to thrive in habitats ranging from the equator to the subarctic and to form large-scale episodic blooms under a wide variety of environmental conditions.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.004
GPT teacher head0.212
Teacher spread0.208 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations528
Published2013
Admission routes1
Has abstractyes

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