Construction and characterization of two bacterial artificial chromosome libraries of pea (<i>Pisum sativum</i> L.) for the isolation of economically important genes
Bibliographic record
Abstract
Pea (Pisum sativum L.) has a genome of about 4 Gb that appears to share conserved synteny with model legumes having genomes of 0.2-0.4 Gb despite extensive intergenic expansion. Pea plant inventory (PI) accession 269818 has been used to introgress genetic diversity into the cultivated germplasm pool. The aim here was to develop pea bacterial artificial chromosome (BAC) libraries that would enable the isolation of genes involved in plant disease resistance or control of economically important traits. The BAC libraries encompassed about 3.2 haploid genome equivalents consisting of partially HindIII-digested DNA fragments with a mean size of 105 kb that were inserted in 1 of 2 vectors. The low-copy oriT-based T-DNA vector (pCLD04541) library contained 55 680 clones. The single-copy oriS-based vector (pIndigoBAC-5) library contained 65 280 clones. Colony hybridization of a universal chloroplast probe indicated that about 1% of clones in the libraries were of chloroplast origin. The presence of about 0.1% empty vectors was inferred by white/blue colony plate counts. The usefulness of the libraries was tested by 2 replicated methods. First, high-density filters were probed with low copy number sequences. Second, BAC plate-pool DNA was used successfully to PCR amplify 7 of 9 published pea resistance gene analogs (RGAs) and several other low copy number pea sequences. Individual BAC clones encoding specific sequences were identified. Therefore, the HindIII BAC libraries of pea, based on germplasm accession PI 269818, will be useful for the isolation of genes underlying disease resistance and other economically important traits.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".