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Record W2045411183 · doi:10.1139/g03-052

Microsatellite variability and heterozygote deficiency in the arcticalpine Alaskan wheatgrass (<i>Elymus</i><i>alaskanus</i>) complex

2003· article· en· W2045411183 on OpenAlexaffvenueabout
Genlou Sun, Björn Salomon

Bibliographic record

VenueGenome · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic diversity and population structure
Canadian institutionsSaint Mary's University
FundersPolarforskningssekretariatet
KeywordsBiologyMicrosatelliteLoss of heterozygosityGeneticsLocus (genetics)RAPDElymusGenetic variationAlleleGenetic diversityPopulationHeterozygote advantageGeneEcologyPoaceaeDemography

Abstract

fetched live from OpenAlex

Genetic variation in the allotetraploid grass Elymus alaskanus complex was assessed using microsatellites in seven populations from Canada, Greenland, and the U.S.A. Microsatellite variation was compared with allozyme and RAPD variation. Our results indicated that E. alaskanus was highly homozygous but also highly variable. The polymorphic loci ranged from 50 to 100% with a mean of 78.6%, and the mean number of allele per locus was 3.14. Average expected heterozygosity value (HE, gene diversity) varied across populations and ranged from 0.244 to 0.651 with mean of 0.414. The mean value of HE across Canadian populations (0.517) was significantly higher than that across populations in Greenland (0.367). The correlation between allozyme and microsatellite gene diversity value (HE) showed a high positive correlation (r = 0.68), but between RAPD and microsatellite showed a low positive correlation (r = 0.08). Populations were highly differentiated, with 38% of variation among populations. Interpopulation genetic distance showed no association with geographic distance between the population sites of origin. A Hardy-Weinberg exact test for all loci and all populations reveals a significant heterozygote deficiency. Possible explanations for heterozygote deficiency are discussed.

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 score0.848
Threshold uncertainty score0.482

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 head0.014
GPT teacher head0.228
Teacher spread0.214 · 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

Citations44
Published2003
Admission routes3
Has abstractyes

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