Comparative bioinformatic analysis of genes expressed in common bean (<i>Phaseolus vulgaris</i> L.) seedlings
Bibliographic record
Abstract
To rapidly and cost-effectively generate gene expression data, we developed an annotated unigene database of common bean (Phaseolus vulgaris L.). In this study, 3 cDNA libraries were constructed from the bean breeding line SEL1308, 1 from young leaf and 2 from seedlings inoculated or not inoculated with the fungal pathogen Colletotrichum lindemuthianum (Sacc. & Magnus) Briosi & Cavara, which causes anthracnose in common bean. To this date, 5255 single-pass sequences have been included in the database after selection based on sequence quality. These ESTs were trimmed and clustered using the computer programs Phred and CAP3 to form a unigene collection of 3126 unique sequences. Within clusters, 318 single nucleotide polymorphisms (SNPs) and 68 insertions-deletions (indels) were found, indicating the presence of paralogous gene families in our database. Each unigene sequence was analyzed for possible function using their similarity to known genes represented in the GenBank database and classified into 14 categories. Only 314 unigenes showed significant similarities to Phaseolus genomic sequences and P. vulgaris ESTs, which indicates that 90% (2818 unigenes) of our database represent newly discovered common bean genes. In addition, 12% (387 unigenes) were shown to be specific to common bean. This study represents a first step towards the discovery of novel genes in beans and a valuable source of molecular markers for expressed gene tagging and mapping.
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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 | 0.001 |
| 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".