RNA-sequencing analysis of fungi-induced transcripts from the bamboo wireworm Melanotus cribricollis (Coleoptera: Elateridae) larvae
Bibliographic record
Abstract
Larvae of Melanotus cribricollis, feed on bamboo shoots and roots, causing serious damage to bamboo in Southern China. However, there is currently no effective control measure to limit the population of this underground pest. Previously, a new entomopathogenic fungal strain isolated from M. cribricollis larvae cadavers named Metarhizium pingshaense WP08 showed high pathogenic efficacy indoors, indicated that the fungus could be used as a bio-control measure. So far, the genetic backgrounds of both M. cribricollis and M. pingshaense WP08 were blank. Here, we analyzed the whole transcriptome of M. cribricollis larvae, infected with M. pingshaense WP08 or not, using high-throughput next generation sequencing technology. In addition, the transcriptome sequencing of M. pingshaense WP08 was also performed for data separation of those two non-model species. The reliability of the RNA-Seq data was also validated through qRT-PCR experiment. The de novo assembly, functional annotation, sequence comparison of four insect species, and analysis of DEGs, enriched pathways, GO terms and immune related candidate genes were operated. The results indicated that, multiple defense mechanisms of M. cribricollis larvae are initiated to protect against the more serious negative effects caused by fungal infection. To our knowledge, this was the first report of transcriptome analysis of Melanotus spp. infected with a fungus, and it could provide insights to further explore insect-fungi interaction mechanisms.
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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 | 0.001 |
| 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 | 0.001 |
| 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".