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Record W4413948805 · doi:10.1002/npp2.70019

Genome resequencing and genome‐wide polymorphisms in Chinese population of <i>Phyllotreta striolata</i> (Coleoptera, Chrysomelidae)

2025· article· en· W4413948805 on OpenAlexaboutno aff
Kui Wang, Beibei Cao, Changlong Shu, Jie Zhang

Bibliographic record

VenueNew plant protection. · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInsect Resistance and Genetics
Canadian institutionsnot available
FundersNational Key Research and Development Program of China
KeywordsBiologyGenomeGeneticsPopulation geneticsPopulationGeneMedicine

Abstract

fetched live from OpenAlex

Abstract The striped flea beetle, Phyllotreta striolata , is a globally notorious pest of cruciferous vegetables. In this study, we sequenced the genome of a Chinese population of P . striolata and aligned it with the reference genome from a Canadian population. Through Illumina sequencing and reference‐based genome polishing, we obtained a high‐quality genome of 131.31 Mb with an N50 size of 8.68 Mb. Genome comparison revealed that the Chinese and Canadian populations of P . striolata presented 175 and 122 population‐specific genes, respectively. Through a genome‐wide screening, six genes were identified as potential RNA interference targets influencing the development or survival of P . striolata . Additionally, we identified 1.16 million high‐confidence variants in the Chinese P . striolata population, including 0.69 million single‐nucleotide polymorphisms and 0.43 million insertions/deletions. Variant effect analysis and functional annotation revealed 7571 variants with high‐impact effects, and the related genes were involved in various basic biological processes in P . striolata . Overall, our findings provide valuable resources for advancing genomic research on P . striolata as well as for those pursuing targeted biopesticides for effective control strategies.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.839
Threshold uncertainty score0.572

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 head0.007
GPT teacher head0.220
Teacher spread0.213 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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