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Record W3165209188 · doi:10.1186/s12864-021-07666-3

Re-examination of two diatom reference genomes using long-read sequencing

2021· article· en· W3165209188 on OpenAlexafffund
Gina V. Filloramo, Bruce A. Curtis, Emma Blanche, John M. Archibald

Bibliographic record

VenueBMC Genomics · 2021
Typearticle
Languageen
FieldMaterials Science
TopicDiatoms and Algae Research
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of CanadaGordon and Betty Moore Foundation
KeywordsThalassiosira pseudonanaPhaeodactylum tricornutumGenomeBiologyDNA sequencingComputational biologyGenomicsGeneticsReference genomeEvolutionary biologyWhole genome sequencingGeneDiatomBotanyEcology

Abstract

fetched live from OpenAlex

BACKGROUND: The marine diatoms Thalassiosira pseudonana and Phaeodactylum tricornutum are valuable model organisms for exploring the evolution, diversity and ecology of this important algal group. Their reference genomes, published in 2004 and 2008, respectively, were the product of traditional Sanger sequencing. In the case of T. pseudonana, optical restriction site mapping was employed to further clarify and contextualize chromosome-level scaffolds. While both genomes are considered highly accurate and reasonably contiguous, they still contain many unresolved regions and unordered/unlinked scaffolds. RESULTS: We have used Oxford Nanopore Technologies long-read sequencing to update and validate the quality and contiguity of the T. pseudonana and P. tricornutum genomes. Fine-scale assessment of our long-read derived genome assemblies allowed us to resolve previously uncertain genomic regions, further characterize complex structural variation, and re-evaluate the repetitive DNA content of both genomes. We also identified 1862 previously undescribed genes in T. pseudonana. In P. tricornutum, we used transposable element detection software to identify 33 novel copia-type LTR-RT insertions, indicating ongoing activity and rapid expansion of this superfamily as the organism continues to be maintained in culture. Finally, Bionano optical mapping of P. tricornutum chromosomes was combined with long-read sequence data to explore the potential of long-read sequencing and optical mapping for resolving haplotypes. CONCLUSION: Despite its potential to yield highly contiguous scaffolds, long-read sequencing is not a panacea. Even for relatively small nuclear genomes such as those investigated herein, repetitive DNA sequences cause problems for current genome assembly algorithms. Determining whether a long-read derived genomic assembly is 'better' than one produced using traditional sequence data is not straightforward. Our revised reference genomes for P. tricornutum and T. pseudonana nevertheless provide additional insight into the structure and evolution of both genomes, thereby providing a more robust foundation for future diatom research.

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.105
GPT teacher head0.334
Teacher spread0.229 · 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 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

Citations52
Published2021
Admission routes2
Has abstractyes

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