Evolutionary Insights into the Steroid Sensitive kiss1 and kiss2 Neurons in the Vertebrate Brain
Bibliographic record
Abstract
Kisspeptin was originally found as a peptide product of Kiss1 gene and is now supposed to be an essential central regulator of reproduction in mammals. However, there is now a growing body of evidence to suggest that kiss2, the paralogous gene for kiss1, evolved in parallel during vertebrate lineage, and the kiss2 product also activates the GPR54 (kisspeptin receptor) signaling pathways. Therefore, it is now widely accepted that both kiss1 and kiss2 are the kisspeptin genes. Interestingly, either kiss1 or kiss2 or both have been lost during evolution in many vertebrate species, and the functional significance of kiss1 or kiss2 for the central regulation of reproduction is suggested to vary according to the species. Here, we argue that the steroid sensitivity of the kiss1 or kiss2 neurons has been well conserved during evolution among tetrapods and teleosts, and thus it may be the key to understanding the functional homologies of certain populations of kisspeptin (kiss1 or kiss2) neurons among different species of vertebrates. In the present review, we will first introduce recent advances in the study of steroid sensitive kiss1 and kiss2 systems in vertebrates and effects of peptide administrations in vivo. By comparing the similarities and differences between kiss1 and kiss2 of neuronal localization and sensitivity to gonadal steroids in various tetrapods and teleosts, we discuss the evolution of kisspeptin neuronal systems after gene duplication of ancestral kisspeptin genes to give rise to kiss1 and kiss2.
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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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".