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Record W2063731075 · doi:10.1139/g01-054

Preliminary interspecific genetic maps of the<i>Populus</i>genome constructed from RAPD markers

2001· article· en· W2063731075 on OpenAlexvenueno aff
Tongming Yin, Minren Huang, Mingxiu Wang, Zhao‐Bang Zeng, Rongling Wu

Bibliographic record

VenueGenome · 2001
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Mapping and Diversity in Plants and Animals
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyRAPDGeneticsGenetic linkageLoss of heterozygosityGene mappingGenetic markerGenomeHybridLinkage (software)Interspecific hybridsInterspecific competitionMicrosatelliteGeneEvolutionary biologyAlleleBotanyChromosomeGenetic diversityPopulation

Abstract

fetched live from OpenAlex

We have constructed RAPD-based linkage maps for an interspecific cross between two species of the genus Populus (P. adenopoda and P. alba), based on a double pseudo-test-cross strategy. Of a total of 360 polymorphic fragments scored, 290 showed a test-cross configuration, corresponding to DNA polymorphisms heterozygous in one parent and null in the other. In the female parent, P. adenopoda, 82 markers were grouped in 19 different linkage groups (553 cM), whereas in the male parent P. alba, 197 markers established a much more complete framework map with an observed genome length of 2300 cM covering 87% of the total P. alba genome. The larger number of test-cross markers detected for the P. alba parent than for the P. adenopoda parent might be due to a higher level of heterozygosity in the former than in the latter. In this study, we detected only a small percentage (2%) of the intercross dominant markers heterozygous in both parents and segregating 3:1 in the progeny. The further focus in this mapping study should be on the identification of more intercross markers, to align the two parent-specific maps into a consensus map for mapping important genes causing species differentiation during long evolutionary divergences.

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 score0.948
Threshold uncertainty score0.545

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 head0.009
GPT teacher head0.189
Teacher spread0.180 · 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

Citations32
Published2001
Admission routes1
Has abstractyes

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