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Record W4225155980 · doi:10.3390/genes13050793

Genetic and Epigenetic Signatures Associated with the Divergence of Aquilegia Species

2022· article· en· W4225155980 on OpenAlexaff
Zhenhui Wang, Tianyuan Lu, Mingrui Li, Ning Ding, Lizhen Lan, Xiang Gao, Ai‐Sheng Xiong, Jian Zhang, Linfeng Li

Bibliographic record

VenueGenes · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British ColumbiaMcGill University and Génome Québec Innovation CentreJewish General Hospital
FundersDepartment of Science and Technology of Jilin ProvinceNational Natural Science Foundation of China
KeywordsBiologyEvolutionary biologyEpigeneticsLineage (genetic)PopulationAdaptation (eye)Genetic variationGeneticsGene

Abstract

fetched live from OpenAlex

Widely grown in the Northern Hemisphere, the genus Aquilegia (columbine) is a model system in adaptive radiation research. While morphological variations between species have been associated with environmental factors, such as pollinators, how genetic and epigenetic factors are involved in the rapid divergence in this genus remains under investigated. In this study, we surveyed the genomes and DNA methylomes of ten Aquilegia species, representative of the Asian, European and North American lineages. Our analyses of the phylogeny and population structure revealed high genetic and DNA methylomic divergence across these three lineages. By multi-level genome-wide scanning, we identified candidate genes exhibiting lineage-specific genetic or epigenetic variation patterns that were signatures of inter-specific divergence. We demonstrated that these species-specific genetic variations and epigenetic variabilities are partially independent and are both functionally related to various biological processes vital to adaptation, including stress tolerance, cell reproduction and DNA repair. Our study provides an exploratory overview of how genetic and epigenetic signatures are associated with the diversification of the Aquilegia species.

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 score0.589
Threshold uncertainty score0.301

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 head0.026
GPT teacher head0.172
Teacher spread0.146 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

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