Ancient Duplications Have Led to Functional Divergence of Vitellogenin-Like Genes Potentially Involved in Inflammation and Oxidative Stress in Honey Bees
Bibliographic record
Abstract
Protection against inflammation and oxidative stress is key in slowing down aging processes. The honey bee (Apis mellifera) shows flexible aging patterns linked to the social role of individual bees. One molecular factor associated with honey bee aging regulation is vitellogenin, a lipoglycophosphoprotein with anti-inflammatory and antioxidant properties. Recently, we identified three genes in Hymenopteran genomes arisen from ancient insect vitellogenin duplications, named vg-like-A, -B, and -C. The function of these vitellogenin homologs is unclear. We hypothesize that some of them might share gene- and protein-level similarities and a longevity-supporting role with vitellogenin. Here, we show how the structure and modifications of the vg-like genes and proteins have diverged from vitellogenin. Furthermore, all three vg-like genes show signs of positive selection, but the spatial location of the selected protein sites differ from those found in vitellogenin. We show that all these genes are expressed in both long-lived winter worker bees and in summer nurse bees with intermediate life expectancy, yet only vg-like-A shows elevated expression in winter bees as found in vitellogenin. Finally, we show that vg-like-A responds more strongly than vitellogenin to inflammatory and oxidative conditions in summer nurse bees, and that also vg-like-B responds to oxidative stress. We associate vg-like-A and, to lesser extent, vg-like-B to the antiaging roles of vitellogenin, but that vg-like-C probably is involved in some other function. Our analysis indicates that an ancient duplication event facilitated the adaptive and functional divergence of vitellogenin and its paralogs in the honey bee.
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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) | 0.001 | 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".