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Record W2170856263 · doi:10.1534/g3.111.001156

An Evaluation of<i>Arabidopsis thaliana</i>Hybrid Traits and Their Genetic Control

2011· article· en· W2170856263 on OpenAlexafffund
Siobhan Moore, Lewis Lukens

Bibliographic record

VenueG3 Genes Genomes Genetics · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Molecular Biology Research
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsArabidopsis thalianaBiologyControl (management)ArabidopsisGeneticsEvolutionary biologyComputational biologyGeneComputer scienceArtificial intelligenceMutant

Abstract

fetched live from OpenAlex

Heterosis is an important phenomenon in agriculture. However, heterosis often greatly varies among hybrids and among traits. To investigate heterosis across a large number of traits and numerous genotypes, we evaluated 12 life history traits on parents and hybrids derived from five Arabidopsis thaliana ecotypes (Col, Ler-0, Cvi, Ws, and C24) by using a complete diallel analysis containing 20 hybrids. Parental contributions to heterosis were hybrid and trait specific with a few reciprocal differences. Most notably, C24 generated hybrids with flowering time, biomass, and reproductive traits that often exceeded high-parent values. However, reproductive traits of C24 and Col hybrids and flowering time traits of C24 and Ler hybrids had no heterosis. We investigated whether allelic variation at flowering time genes FRIGIDA (FRI) and FLOWERING LOCUS C (FLC) could explain the genotype- and trait-specific contribution of C24 to hybrid traits. We evaluated both Col and Ler lines introgressed with various FRI and FLC alleles and hybrids between these lines and C24. Hybrids with functional FLC differed from hybrids with nonfunctional FLC for 21 of the 24 hybrid-trait combinations. In most crosses, heterosis was fully or partially explained by FRI and FLC. Our results describe the genetic diversity for heterosis within a sample of A. thaliana ecotypes and show that FRI and FLC are major factors that contribute to heterosis in a genotype and trait specific fashion.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.795
Threshold uncertainty score0.326

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.055
GPT teacher head0.253
Teacher spread0.198 · 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

Citations27
Published2011
Admission routes2
Has abstractyes

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