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Record W2252719254 · doi:10.1139/gen-2015-0154

Development of new PCR-based markers specific for chromosome arms of rye (<i>Secale cereale</i> L.)

2016· article· en· W2252719254 on OpenAlexvenueno aff
Ling Qiu, Zongxiang Tang, Meng Li, Shulan Fu

Bibliographic record

VenueGenome · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Disease Resistance and Genetics
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsSecaleBiologyCommon wheatGeneticsTriticaleChromosomeGenetic markerGeneBotany

Abstract

fetched live from OpenAlex

PCR-based rye (Secale cereale L.) chromosome-specific markers can contribute to the effective utilization of elite genes of rye in wheat (Triticum aestivum L.) breeding programs. In the present study, 578 new PCR-based rye-specific markers have been developed by using specific length amplified fragment sequencing (SLAF-seq) technology, and 76 markers displayed different polymorphism among rye Kustro, Imperial, and King II. A total of 427 and 387 markers were, respectively, located on individual chromosomes and chromosome arms of Kustro by using a set of wheat-rye monosomic addition lines and 13 monotelosomic addition lines, which were derived from T. aestivum L. 'Mianyang11' × S. cereale L. 'Kustro'. In addition, two sets of wheat-rye disomic addition lines, which were derived from T. aestivum L. var. Chinese Spring × S. cereale L. var. Imperial and T. aestivum L. 'Holdfast' × S. cereale L. var. King II, were used to test the chromosomal specificity of the 427 markers. The chromosomal locations of 281 markers were consistent among the three sets of wheat-rye addition lines. The markers developed in this study can be used to identify a given segment of rye chromosomes in wheat background and accelerate the utilization of elite genes on rye chromosomes in wheat breeding programs.

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 score0.747
Threshold uncertainty score0.344

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 head0.030
GPT teacher head0.207
Teacher spread0.178 · 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

Citations29
Published2016
Admission routes1
Has abstractyes

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