Nanopore long-read RNA-seq and absolute quantification delineate transcription dynamics in early embryo development of an insect pest
Bibliographic record
Abstract
The olive fruit fly, Bactrocera oleae, is the most important pest for the olive fruit but lacks adequate transcriptomic characterization that could aid in molecular control approaches. We apply nanopore long-read RNA-seq with internal RNA standards allowing absolute transcript quantification to analyze transcription dynamics during early embryo development for the first time in this organism. Sequencing on the MinION platform generated over 31 million reads. Over 50% of the expressed genes had at least one read covering its entire length validating our full-length approach. We generated a de novo transcriptome assembly and identified 1768 new genes and a total of 79,810 isoforms; a fourfold increase in transcriptome diversity compared to the current NCBI predicted transcriptome. Absolute transcript quantification per embryo allowed an insight into the dramatic re-organization of maternal transcripts. We further identified Zelda as a possible regulator of early zygotic genome activation in B. oleae and provide further insights into the maternal-to-zygotic transition. These data show the utility of long-read RNA in improving characterization of non-model organisms that lack a fully annotated genome, provide potential targets for sterile insect technic approaches, and provide the first insight into the transcriptome landscape of the developing olive fruit fly embryo.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 teacher head, 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".