Comparative analysis of integument transcriptomes identifies genes that participate in marking pattern formation in three allelic mutants of silkworm, Bombyx mori
Bibliographic record
Abstract
The diversity markings and pigment patterns in insects are outcomes of adaptive evolution. The elucidation of the molecular mechanism underlying variations in pigment patterns may improve our understanding of the origin and evolution of these spectacular diverse phenotypes. Melanin, ommochrome, and pteridine are the three main types of insect pigments, and the genes that directly participate in pigment biosynthesis have been extensively studied. However, available information on gene interactions and the whole pigment regulatory network is limited. In this study, we performed integument transcriptome sequencing to analyze three larval marking allelic mutants, namely, multi lunar ( L ), L C , and L Ca , which have similar twin-spot markings on the dorsal side of multiple segments. Further analysis identified 336 differentially expressed genes (DEGs) between L and Dazao (wild type which exhibits normal markings), 68 DEGs between L C /+ and + LC /+ LC , and 188 DEGs between L Ca /+ and + LCa /+ LCa . Gene Ontology (GO) analysis indicated a significant DEG enrichment of the functional terms catalytic activity, binding, metabolic process, and cellular process. Furthermore, three mutants share six common enriched KEGG pathways. We finally identified eight common DEGs among three pairwise comparisons, including Krueppel -like factor, TATA-binding protein, protein patched, UDP-glycosyltransferase, an unknown secreted protein, and three cuticular proteins. Microarray-based gene expression analysis revealed that the eight genes are upregulated during molting, which coincides with marking formation, and are significantly differentially expressed between marking and non-marking regions. The results suggest that the eight common genes are involved in the construction of the multiple twin-spot marking patterns in the three mutants.
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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 | 0.000 | 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 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".