Exploring The Genome of The Oribatid Mite, <i>Oppia Nitens</i> – Environmental Stress Response and Toxicity Adaptation
Bibliographic record
Abstract
Abstract Oribatid mites are one of the most abundant groups of microarthropods in soil. Oppia nitens , belonging to the family Oppiidae, one of the largest and most diverse families of oribatid mites, has been developed as a standardized model test organism for assessing soil contamination. However, the limited availability of genomic information for this species hinders our understanding of its physiological adaptation and sensitivity to chemical and environmental stressors in soil. Hence, we present the annotated O. nitens draft genome assembled using both Oxford Nanopore Technologies and Illumina sequencing platforms as a basis to identify potential genes that can be linked to adaptation to chemical and environmental stressors. The sequences were assembled into 65 scaffolds spanning 125.4Mb with a 24.5% GC content and an N50 length of 4.41Mb. Genome quality and completeness were checked using arthropod Benchmarking Universal Single-Copy Orthologs (BUSCO) analysis, which identified 93.5 % complete single-copy orthologs, 3.4% complete but duplicated orthologs, 0.5% fragmented, and 2.6% missing orthologs (n=2934). The NCBI Eukaryotic Genome Annotation Pipeline annotated 15,291 genes, 16,969 mRNAs, and 14,938 proteins. Here, we describe the O. nitens complete draft genome and discuss its utility as a genetic basis for further investigations and understanding of the molecular mechanisms and physiological functions in adaptations to environmental change, especially tolerance to metal stress.
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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 | 0.000 |
| 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".