Development of oligonucleotides and multiplex probes for quick and accurate identification of wheat and <i>Thinopyrum bessarabicum</i> chromosomes
Bibliographic record
Abstract
In comparison with general FISH for preparing probes in terms of time and cost, synthesized oligonucleotide (oligo hereafter) probes for FISH have many advantages such as ease of design, synthesis, and labeling. Low cost and high sensitivity and resolution of oligo probes greatly simplify the FISH procedure as a simple, fast, and efficient method of chromosome identification. In this study, we developed new oligo and oligo multiplex probes to accurately and efficiently distinguish wheat (Triticum aestivum, 2n = 6x, AABBDD) and Thinopyrum bessarabicum (2n = 2x = 14, JJ) chromosomes. The oligo probes contained more nucleotides or more repeat units that produced stronger signals for more efficient chromosome painting. Four Th. bessarabicum-specific oligo probes were developed based on genomic DNA sequences of Th. bessarabicum chromosome arm 4JL, and one of them (oligo DP4J27982) was pooled with the oligo multiplex #1 to simultaneously detect wheat and Th. bessarabicum chromosomes for quick and accurate identification of Chinese Spring (CS) - Th. bessarabicum alien chromosome introgression lines. Oligo multiplex #4 revealed chromosome variations among CS and eight wheat cultivars by a single round of FISH analysis. This research demonstrated the high efficiency of using oligos and oligo multiplexes in chromosome identification and manipulation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".