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Record W4311795228 · doi:10.26508/lsa.202201833

Convergent evolution and horizontal gene transfer in Arctic Ocean microalgae

2022· article· en· W4311795228 on OpenAlexafffund
Richard G. Dorrell, Alan Kuo, Zoltán Füssy, Elisabeth Richardson, Asaf Salamov, Nikola Zarevski, Nastasia J. Freyria, Federico M. Ibarbalz, Jerry Jenkins, Juan José Pierella Karlusich, Andrei Stecca Steindorff, Robyn Edgar, Lori H. Handley, Kathleen Lail, Anna Lipzen, Vincent Lombard, John McFarlane, Charlotte Nef, Anna MG Novák Vanclová, Yi Peng, Christopher Plott, Marianne Potvin, Fabio Rocha Jimenez Vieira, Kerrie Barry, Colomban de Vargas, Bernard Henrissat, Éric Pelletier, Jeremy Schmutz, Patrick Wincker, Joel B. Dacks, Chris Bowler, Igor V. Grigoriev, Connie Lovejoy

Bibliographic record

VenueLife Science Alliance · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial Community Ecology and Physiology
Canadian institutionsUniversité LavalUniversity of Alberta
FundersEuropean Research CouncilUniversité de Recherche Paris Sciences et LettresCentre National de la Recherche ScientifiqueOffice of ScienceAgence Nationale de la RechercheNatural Sciences and Engineering Research Council of CanadaEuropean CommissionUS-UK Fulbright CommissionJoint Genome InstituteUniversity of WashingtonU.S. Department of Energy
KeywordsBiomeArcticBiologySea iceEcologyArctic ice packConvergent evolutionOceanographyPhylogeneticsGeneGeologyEcosystem

Abstract

fetched live from OpenAlex

Microbial communities in the world ocean are affected strongly by oceanic circulation, creating characteristic marine biomes. The high connectivity of most of the ocean makes it difficult to disentangle selective retention of colonizing genotypes (with traits suited to biome specific conditions) from evolutionary selection, which would act on founder genotypes over time. The Arctic Ocean is exceptional with limited exchange with other oceans and ice covered since the last ice age. To test whether Arctic microalgal lineages evolved apart from algae in the global ocean, we sequenced four lineages of microalgae isolated from Arctic waters and sea ice. Here we show convergent evolution and highlight geographically limited HGT as an ecological adaptive force in the form of PFAM complements and horizontal acquisition of key adaptive genes. Notably, ice-binding proteins were acquired and horizontally transferred among Arctic strains. A comparison with Tara Oceans metagenomes and metatranscriptomes confirmed mostly Arctic distributions of these IBPs. The phylogeny of Arctic-specific genes indicated that these events were independent of bacterial-sourced HGTs in Antarctic Southern Ocean microalgae.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.600
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.010
GPT teacher head0.212
Teacher spread0.202 · 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.

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

Citations44
Published2022
Admission routes2
Has abstractyes

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