Characterizing the citrus cultivar Carrizo genome through 454 shotgun sequencing
Bibliographic record
Abstract
The citrus cultivar Carrizo is the single most important rootstock to the US citrus industry and has resistance or tolerance to a number of major citrus diseases, including citrus tristeza virus, foot rot, and Huanglongbing (HLB, citrus greening). A Carrizo genomic sequence database providing approximately 3.5×genome coverage (haploid genome size approximately 367 Mb) was populated through 454 GS FLX shotgun sequencing. Analysis of the repetitive DNA fraction indicated a total interspersed repeat fraction of 36.5%. Assembly and characterization of abundant citrus Ty3/gypsy elements revealed a novel type of element containing open reading frames encoding a viral RNA-silencing suppressor protein (RNA binding protein, rbp) and a plant cytokinin riboside 5′-monophosphate phosphoribohydrolase-related protein (LONELY GUY, log). Similar gypsy elements were identified in the Populus trichocarpa genome. Gene-coding region analysis indicated that 24.4% of the nonrepetitive reads contained genic regions. The depth of genome coverage was sufficient to allow accurate assembly of constituent genes, including a putative phloem-expressed gene. The development of the Carrizo database (http://citrus.pw.usda.gov/) will contribute to characterization of agronomically significant loci and provide a publicly available genomic resource to the citrus research community.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".