Genomic distribution of MITEs in barley determined by MITE-AFLP mapping
Bibliographic record
Abstract
Miniature inverted-repeat transposable elements (MITEs) represent a large superfamily of transposons that are moderately to highly repetitive and frequently found near or within plant genes. To elucidate the organization of MITEs in the barley genome, MITEs were integrated into the genetic map of barley. In this report, we describe the use of MITEs in amplified fragment length polymorphism (AFLP) mapping, and demonstrate their superiority over conventional AFLP mapping. Barley MITEs include members of the Stowaway, Barfly, and Pangrangja families. By amplifying the flanking sequences of these MITEs, a total of 214 loci were mapped from a population of 93 doubled-haploid segregating individuals between Hordeum vulgare ssp. vulgare and H. vulgare ssp. spontaneum. The 214 MITE-AFLP and 40 anchor simple sequence repeat (SSR) loci were distributed on 7 linkage groups, covering a total map distance of 1 165 cM. The average marker density on each chromosome ranged between 3.4 and 9.6 cM per locus. Only 1 MITE-based locus was frequently found to be associated with MITE loci from the same family, resulting in clusters in chromosomal subregions. In barley, it will be possible to cover the entire genome with a limited set of MITE-based primers and to build highly dense maps of specific regions.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".