Isolation of novel dinucleotide tandem repeat sequences from the pineapple genome
Bibliographic record
Abstract
The aim of this research is to develop micro satellites marker for pineapple and the information develop from this research will be useful to improve the quality of the crop. Microsatellite is a type of DNA markers consists of several important features which make them useful in plant genetic studies such as population analysis, genetic mapping, paternity analysis, germplasm characterization, marker assisted breeding and varietals identification. Microsatellites loci can be isolated using a simple and fast technique, 5' – anchored PCR developed by Fisher et al. (1996). In this research, a single degenerate primer, PCT7 [5 '-KKVRVRV(AC)10�³'] was used and the PCR program was optimized. A total of 13 micro satellites (dinucleotide and trinucleotide) were isolated. Four plasmid DNA contained inserts were successfully sequenced. Similarity tests (BLAST) were performed and the E-values showed that there were no significantly similarities founded. These newly isolated sequences (ACPCT72, ACPC73, ACPCT74 and ACPCT79) were deposited into the GenBank database. The GenBank accession numbers obtained were EF032604, EF032605, EF032606 and EF032607. Four specific primer pairs (ACPCT72, ACPCT73, ACPCT79A and ACPCT79B) were designed and synthesized. A total of 15 individuals of pineapple were successfully amplified using the primer pairs. In conclusion, the 5' -anchored PCR proved to be a simple, rapid and efficient method to isolate the microsatellites. The specific designed primer pairs will be used to study the genetic variation in local pineapple populations and serve as an important genetic marker for quality improvement purpose.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".