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Record W4200598959 · doi:10.3389/fmars.2021.788307

Comparative Analysis of Chloroplast Genomes of Thalassiosira Species

2021· article· en· W4200598959 on OpenAlexaff
Kuiyan Liu, Yang Chen, Zongmei Cui, Shuya Liu, Qing Xu, Nansheng Chen

Bibliographic record

VenueFrontiers in Marine Science · 2021
Typearticle
Languageen
FieldMaterials Science
TopicDiatoms and Algae Research
Canadian institutionsSimon Fraser University
FundersNational Key Research and Development Program of ChinaInstitute of Oceanology, Chinese Academy of SciencesChinese Academy of Sciences
KeywordsBiologyPhylogenetic treeDiatomThalassiosira weissflogiiBotanyGenomeEvolutionary biologyGenePhytoplanktonEcologyGenetics

Abstract

fetched live from OpenAlex

Thalassiosira is a species-rich genus in Bacillariophyta with important ecological contribution to primary productivity but can also pose negative impact on ecology by developing harmful algal blooms (HABs). However, genomic resources of only a few Thalassiosira species are currently available. Here, we constructed complete chloroplast genomes (cpDNAs) of six Thalassiosira strains (representing six Thalassiosira species T. rotula , T. profunda , T. nordenskioeldii , T. tenera , T. weissflogii , and Thalassiosira sp.), and compared them with published cpDNAs of other diatoms. Comparative analysis revealed that Thalassiosira cpDNAs have generally conventional and conserved quadripartite structure with important exceptions. Gene orders of cpDNAs of Thalassiosira sp. (CNS00561) and T. oceanica were different from that of other Thalassiosira species. Additionally, endosymbiotic gene transfers (EGT) were found to occur in the evolution of Thalassiosira cpDNAs. Furthermore, genomic regions of cpDNAs were found to be highly variable, which could be used to construct molecular markers for distinguishing Thalassiosira species with high resolution and high specificity. This study also demonstrated that Thalassiosira species emerged roughly around 51 MYA and diversified 17–28 MYA. Thalassiosira cpDNAs are not only valuable as super-barcode for phylogenetic analysis, but also important for functional and evolutionary analysis of diatoms.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.902

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.005
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.289
Teacher spread0.266 · 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

Citations18
Published2021
Admission routes1
Has abstractyes

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