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Record W4403583147 · doi:10.1101/2024.10.18.619046

Chromosomal-level reference genome and microRNAs of the ricefield flatsedge <i>Cyperus iria</i>

2024· preprint· en· W4403583147 on OpenAlexaff
Stacey S.K. Tsang, Wenyan Nong, Sean T.S. Law, Jacqueline C. Bede, Shanshan Chen, Sa Li, Yichun Xie, Thomas Swale, Yiqiang Zhao, David T. W. Lau, Zhen‐peng Kai, Ting‐Fung Chan, Stephen S. Tobe, William G. Bendena, Jerome H. L. Hui

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2024
Typepreprint
Languageen
FieldAgricultural and Biological Sciences
TopicBotany, Ecology, and Taxonomy Studies
Canadian institutionsUniversity of TorontoQueen's UniversityMcGill University
Fundersnot available
KeywordsBiologyGeneticsGenomemicroRNAGeneComputational biology

Abstract

fetched live from OpenAlex

Abstract Background Grass-like plants in the Cyperaceae family, commonly known as sedges, have a global distribution and include many economically problematic weeds. The ricefield flatsedge, Cyperus iria , is an aggressive weed in rice crops in Asia. Result Here, we present a chromosomal-level genome assembly for C. iria (461.2 Mb, scaffold N50 = 7.3 Mbp, 99.6% BUSCO score) providing potential targets for the control of this devastating weed. Based on the genome assembly and transcriptomes of vegetative tissues, 52,574 protein-coding genes were predicted to be encoded. A total of 26 conserved and 75 novel microRNAs, including 9 microRNA clusters, were also annotated. Synteny and microRNA cluster analyses further showed that C. iria had undergone at least one round of whole genome duplication. Conclusion The genomic resource established in this study sets up a foundation to further address basic and applied questions in the Cyperaceae.

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 score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.034
GPT teacher head0.204
Teacher spread0.170 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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