Next-generation sequencing reveals endosymbiont variability in cassava whitefly, <i>Bemisia tabaci</i>, across the agro-ecological zones of Kerala, India
Bibliographic record
Abstract
Silverleaf whitefly, Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae), is one of the most notorious invasive insect pests, infesting more than 900 species of plants and spreading more than 200 viral diseases. This polyphagous agricultural pest harbours diverse bacterial communities in its gut, which perform multiple functions in whiteflies, including nutrient provisioning, amino acid biosynthesis, and virus transmission. The present exploratory study compares the bacterial communities associated with silverleaf whitefly infesting cassava, also known as cassava whitefly, collected from two different zones (zone P: plains; zone H: high ranges), from Kerala, India, using next-generation sequencing of 16S rDNA. The data sets for these two regions consisted of 1 321 906 and 690 661 high-quality paired-end sequences with mean length of 150 bp. Highly diverse bacterial communities were present in the sample, containing approximately 3513 operational taxonomic units (OTUs). Sequence analysis showed a marked difference in the relative abundance of bacteria in the populations. A total of 16 bacterial phyla, 27 classes, 56 orders, 91 families, 236 genera, and 409 species were identified from the P population, against 16, 31, 60, 88, 225, and 355, respectively, in the H population. Arsenophonus sp. (Enterobacteriaceae), which is important for virus transmission by whiteflies, was relatively abundant in the P population, whereas in the H population Bacillus sp. was the most dominant group. The association of whitefly biotypes and secondary symbionts suggests a possible contribution of these bacteria to host characteristics such as virus transmission, host range, insecticide resistance, and speciation.
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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 | 0.001 | 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 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".