Identification, expression, and artificial selection of silkworm epigenetic modification enzymes
Bibliographic record
Abstract
BACKGROUND: Understanding the genetic basis of phenotype variations during domestication and breeding is of great interest. Epigenetics and epigenetic modification enzymes (EMEs) may play a role in phenotypic variations; however, no comprehensive study has been performed to date. Domesticated silkworm (Bombyx mori) may be utilized as a model in determining how EMEs influence domestication traits. RESULTS: We identified 44 EMEs in the genome of silkworm (Bombyx mori) using homology searching. Phylogenetic analysis showed that genes in a subfamily among different animals were well clustered, and the expression pattern of EMEs is constant among Bombyx mori, Drosophila melanogaster, and Mus musculus. These are most highly expressed in brain, early embryo, and internal genitalia. By gene-related selective sweeping, we identified five BmEMEs under artificial selection during the domestication and breeding of silkworm. Among these selected genes, BmSuv4-20 and BmDNMT2 harbor selective mutations in their upstream regions that alter transcription factor-binding sites. Furthermore, these two genes are expressed higher in the testis and ovary of domesticated silkworm compared to wild silkworms, and correlations between their expression pattern and meiosis of the sperm and ova were observed. CONCLUSIONS: The domestication of silkworm has induced artificial selection on epigenetic modification markers that may have led to phenotypic changes during domestication. We present a novel perspective to understand the genetic basis underlying animal domestication and breeding.
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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 | 0.000 | 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 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".