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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 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 score0.072
Threshold uncertainty score0.143

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 science0.0000.000
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 head0.007
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 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

Citations0
Published2025
Admission routes1
Has abstractyes

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