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Record W4200608451 · doi:10.1038/s41467-021-27510-2

Large-scale genome-wide study reveals climate adaptive variability in a cosmopolitan pest

2021· article· en· W4200608451 on OpenAlex
Yanting Chen, Zhaoxia Liu, Jacques Régnière, Liette Vasseur, Jian Lin, Shiguo Huang, Fushi Ke, Shaoping Chen, Jianyu Li, Jieling Huang, Geoff M. Gurr, Minsheng You, Shijun You

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNature Communications · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect-Plant Interactions and Control
Canadian institutionsMinistry of AgricultureBrock UniversityNatural Resources CanadaCanadian Forest Service
FundersRecruitment Program of Global ExpertsFujian Agriculture and Forestry UniversityScientific Research Foundation of Graduate School of Fujian Agriculture and Forestry UniversityNational Natural Science Foundation of China
KeywordsDiamondback mothAdaptation (eye)BiologyIntraspecific competitionGenetic variationPEST analysisClimate changeEvolutionary biologyLocal adaptationEcologyGenetic variabilityPlutellaGeneticsPopulationGeneGenotypeLepidoptera genitalia

Abstract

fetched live from OpenAlex

Understanding the genetic basis of climatic adaptation is essential for predicting species' responses to climate change. However, intraspecific variation of these responses arising from local adaptation remains ambiguous for most species. Here, we analyze genomic data from diamondback moth (Plutella xylostella) collected from 75 sites spanning six continents to reveal that climate-associated adaptive variation exhibits a roughly latitudinal pattern. By developing an eco-genetic index that combines genetic variation and physiological responses, we predict that most P. xylostella populations have high tolerance to projected future climates. Using genome editing, a key gene, PxCad, emerged from our analysis as functionally temperature responsive. Our results demonstrate that P. xylostella is largely capable of tolerating future climates in most of the world and will remain a global pest beyond 2050. This work improves our understanding of adaptive variation along environmental gradients, and advances pest forecasting by highlighting the genetic basis for local climate adaptation.

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.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.019
GPT teacher head0.274
Teacher spread0.254 · 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