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Record W1993953131 · doi:10.1139/b07-038

Identification of the full-length <i>Hs1<sup>pro-1</sup></i> coding sequence and preliminary evaluation of soybean cyst nematode resistance in soybean transformed with <i>Hs1<sup>pro-1</sup></i> cDNA

2007· article· en· W1993953131 on OpenAlexaffvenue
Michael D. McLean, Gordon J. Hoover, Bonnie Bancroft, Amina Makhmoudova, Shawn M. Clark, T. W. Welacky, Daina H. Simmonds, Barry J. Shelp

Bibliographic record

VenueCanadian Journal of Botany · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicNematode management and characterization studies
Canadian institutionsUniversity of GuelphAgriculture and Agri-Food Canada
Fundersnot available
KeywordsSoybean cyst nematodeBiologySugar beetGeneCoding regionMolecular biologyPolymerase chain reactionGeneticsPotato cyst nematodeGenetically modified cropsNematodeTransgeneHorticulture

Abstract

fetched live from OpenAlex

The Hs1 pro-1 gene reportedly confers resistance to the beet cyst nematode in wild beet and sugar beet. Here, we tested the hypothesis that Hs1 pro-1 confers resistance in soybean against the soybean cyst nematode (SCN). The full-length Hs1 pro-1 coding sequence, which encodes a predicted polypeptide of 490 amino acids, was first acquired then expressed in ‘Westag’ soybean using a constitutive octopine synthase – mannopine synthase promoter. Thirty T 0 lines that successfully expressed the Hs1 pro-1 gene, as indicated by both polymerase chain reaction and reverse transcriptase – polymerase chain reaction analyses, were generated. Bioassay of the T 1 progeny from these lines revealed that only five T 0 lines grew normally and exhibited a high degree of SCN resistance. On average, these T 1 transgenic progeny were about 70% more resistant to SCN than susceptible control cultivars. These preliminary data suggest that Hs1 pro-1 is a promising candidate for genetically engineering SCN resistance in elite, locally adapted soybean cultivars.

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)0.002
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 score0.770
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.028
GPT teacher head0.237
Teacher spread0.209 · 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
Published2007
Admission routes2
Has abstractyes

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