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Record W7127206121

QTL Analysis of Body Size and Development Time in Dendroctonus ponderosae

2023· article· W7127206121 on OpenAlexaboutno aff
Camille Pushman

Bibliographic record

VenueThinkIR: The University of Louisville's Institutional Repository (University of Louisville) · 2023
Typearticle
Language
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsnot available
Fundersnot available
KeywordsQuantitative trait locusDendroctonusLinkage (software)Adaptation (eye)Genetic architectureMicrosatelliteGenomeGenetic linkageFamily-based QTL mapping
DOInot available

Abstract

fetched live from OpenAlex

The mountain pine beetle (MPB, Dendroctonus ponderosae) is a pest species found in western Norh America that attacks and kills Pinus host trees. Previous studies have identified genetic divergence between populations and variation in life-history traits (body size and development time) that are likely important in local adaptation. To understand the underlying genetic architecture of MPB adaptation and divergence, we performed an F1 intercross between two distinct populations (Utah & Arizona) and performed a QTL analysis. We analyzed double digest RAD sequencing data from 181 F2 individuals. Our final dataset consists of 986 SNPs and we were able to successfully map all 12 linkage groups and characterize recombination across the genome. We identified a significant QTL peak for development time on the X chromosome. No significant QTL was detected for body size. Lastly, we compared our linkage map to an existing map created using MPB populations from Canada. We found the linkage maps were largely similar, suggesting no major genome structure differences or changes in general patterns of recombination across different populations.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.594
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0020.005
Scholarly communication0.0000.001
Open science0.0010.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.175
Teacher spread0.168 · 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; both teacher heads agree on what is shown here.

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
Published2023
Admission routes1
Has abstractyes

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