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Record W2033759863 · doi:10.1139/g03-103

Sequence diversity analysis of dihydroflavonol 4-reductase intron 1 in common bean

2004· article· en· W2033759863 on OpenAlexvenueno aff
Phillip E. McClean, Rian K. Lee, Phillip N. Miklas

Bibliographic record

VenueGenome · 2004
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant pathogens and resistance mechanisms
Canadian institutionsnot available
FundersU.S. Department of Agriculture
KeywordsBiologyGeneticsLinkage disequilibriumGenotypeAlleleIntronGeneHaplotypePhaseolusNucleotide diversityGenetic variationPopulationGenetic diversityBotany

Abstract

fetched live from OpenAlex

Variation in common bean (Phaseolus vulgaris L.) was investigated by sequencing intron 1 of the dihydroflavonol 4-reductase (DFR) gene for 92 genotypes that represent both landraces and cultivars. We were also interested in determining if introns provide sufficient variation for genetic diversity studies and if the sequence data could be used to develop allele-specific primers that could differentiate genotypes using a standard PCR assay. Sixty-nine polymorphic sites were observed. Nucleotide variation (pi/bp) was 0.0481, a value higher than that reported for introns from other plant species. Tests for significant deviation from the mutation drift model were positive for the population as a whole, the cultivar and landrace subsets, and the Middle American landrace set. Significant linkage disequilibrium extended about 300 nucleotides. Twenty haplotypes were detected among the cultivated genotypes. Seven recombination events were detected for the whole population, and six events for the landraces. Recombination was not observed among the landraces within either the Middle American or Andean gene pools. Evidence for hybridization between the two gene pools was discovered. Five allele-specific primers were developed that could distinguish 56 additional genotypes. The allele-specific primers were used to map duplicate DFR genes on linkage group B8.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.919
Threshold uncertainty score0.495

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.022
GPT teacher head0.209
Teacher spread0.186 · 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 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

Citations41
Published2004
Admission routes1
Has abstractyes

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