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Record W2583215900 · doi:10.1111/mec.14043

Transcriptome dynamics over a lunar month in a broadcast spawning acroporid coral

2017· article· en· W2583215900 on OpenAlexafffund
Matthew Oldach, Matthew L. Workentine, Mikhail V. Matz, Tung‐Yung Fan, Peter D. Vize

Bibliographic record

VenueMolecular Ecology · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicCoral and Marine Ecosystems Studies
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaNational Museum of Marine Biology and Aquarium
KeywordsFull moonBiologyNew moonHermaphroditeDiurnal cycleTranscriptomePlanetSunsetAstrobiologyEcologyEvolutionary biologyGeologyAtmospheric sciencesGeneAstronomy

Abstract

fetched live from OpenAlex

On one night per year, at a specific point in the lunar cycle, one of the most extraordinary reproductive events on the planet unfolds as hundreds of millions of broadcast spawning corals release their trillions of gametes into the waters of the tropical seas. Each species spawns on a specific night within the lunar cycle, typically from full moon to third quarter moon, and in a specific time window after sunset. This accuracy is essential to achieve efficient fertilization in the vastness of the oceans. In this report, we use transcriptome sequencing at noon and midnight across an entire lunar cycle to explore how acroporid corals interpret lunar signals. The data were interrogated by both time-of-day-dependent and time-of-day-independent methods to identify different types of lunar cycles. Time-of-day methods found that genes associated with biological clocks and circadian processes change their diurnal cycles over the course of a synodic lunar cycle. Some genes have large differences between day and night at some lunar phases, but little or no diurnal differences at other phases. Many clock genes display an oscillation pattern indicative of phase shifts linked to the lunar cycle. Time-independent methods found that signal transduction, protein secretion and modification, cell cycle and ion transport change over the lunar timescale and peak at various phases of the moon. Together these data provide unique insights into how the moon impinges on coral transcription cycles and how lunar light may regulate circalunar timing systems and coral biology.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.981

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 science0.0000.000
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 head0.006
GPT teacher head0.231
Teacher spread0.225 · 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 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
Published2017
Admission routes2
Has abstractyes

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