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Record W4366998747 · doi:10.1093/dnares/dsad006

Telomere-to-telomere genome assembly of matsutake (<i>Tricholoma matsutake</i>)

2023· article· en· W4366998747 on OpenAlexfundno aff
Hiroyuki Kurokochi, Naoyuki Tajima, Mitsuhiko Sato, Kazutoshi Yoshitake, Shuichi Asakawa, Sachiko Isobe, Kenta Shirasawa

Bibliographic record

VenueDNA Research · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Phylogenetic Studies
Canadian institutionsnot available
FundersInstitute of GeneticsJapan Society for the Promotion of Science
KeywordsBiologyTelomereGenomeIntergenic regionGeneticsGeneGenomics

Abstract

fetched live from OpenAlex

Here, we report the first telomere-to-telomere genome assembly of matsutake (Tricholoma matsutake), which consists of 13 sequences (spanning 161.0 Mb) and a 76 kb circular mitochondrial genome. All the 13 sequences were supported with telomeric repeats at the ends. GC-rich regions are located at the middle of the sequences and are enriched with long interspersed nuclear elements (LINEs). Repetitive sequences including long-terminal repeats (LTRs) and LINEs occupy 71.6% of the genome. A total of 21,887 potential protein-coding genes were predicted. The genomic data reported in this study served not only matsutake gene sequences but also genome structures and intergenic sequences. The information gained would be a great reference for exploring the genetics, genomics, and evolutionary study of matsutake in the future, and ultimately facilitate the conservation of this vulnerable genetic resource.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.061
GPT teacher head0.353
Teacher spread0.292 · 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

Citations16
Published2023
Admission routes1
Has abstractyes

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