Identification of stress-induced genes from the drought-tolerant plant Prosopis juliflora (Swartz) DC. through analysis of expressed sequence tags
Bibliographic record
Abstract
Abiotic stresses such as cold, salinity, drought, wounding, and heavy metal contamination adversely affect crop productivity throughout the world. Prosopis juliflora is a phreatophyte that can tolerate severe adverse environmental conditions such as drought, salinity, and heavy metal contamination. As a first step towards the characterization of genes that contribute to combating abiotic stress, construction and analysis of a cDNA library of P. juliflora genes is reported here. Random expressed sequence tag (EST) sequencing of 1750 clones produced 1467 high-quality reads. These clones were classified into functional categories, and BLAST comparisons revealed that 114 clones were homologous to genes implicated in stress response(s) and included heat shock proteins, metallothioneins, lipid transfer proteins, and late embryogenesis abundant proteins. Of the ESTs analyzed, 26% showed homology to previously uncharacterized genes in the databases. Fifty-two clones from this category were selected for reverse Northern analysis: 21 were shown to be upregulated and 16 downregulated. The results obtained by reverse Northern analysis were confirmed by Northern analysis. Clustering of the 1467 ESTs produced a total of 295 contigs encompassing 790 ESTs, resulting in a 54.2% redundancy. Two of the abundant genes coding for a nonspecific lipid transfer protein and late embryogenesis abundant protein were sequenced completely. Northern analysis (after polyethylene glycol stress) of the 2 genes was carried out. The implications of the analyzed genes in abiotic stress tolerance are also discussed.
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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 | 0.000 | 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) | 0.000 | 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".