Evolution of New Hormone Function: Loss and Gain of a Receptor
Bibliographic record
Abstract
The vertebrate proglucagon gene encodes three glucagon-like sequences (glucagon, glucagon-like peptide-1 [GLP-1], and glucagon-like peptide 2 [GLP-2]) that have distinct functions in regulating metabolism in mammals. In contrast, glucagon and GLP-1 have similar physiological actions in fish, that of mammalian glucagon. We have identified sequences similar to receptors for proglucagon-derived peptides from the genomes of two fish (pufferfish and zebrafish), a frog (Xenopus tropicalis), and a bird (chicken). Phylogenetic analysis of the receptor sequences suggested an explanation for the divergent function of GLP-1 in fish and mammals. The phylogeny of our predicted and characterized receptors for proglucagon-derived peptides demonstrate that receptors for glucagon, GLP-1, and GLP-2 have an origin before the divergence of fish and mammals; however, fish have lost the gene encoding the GLP-1 class of receptors, and likely the incretin action of GLP-1. Receptors that bind GLP-1, but yield glucagon-like action, have been characterized in goldfish and zebrafish, and these sequences are most closely related to glucagon receptors. Both pufferfish and zebrafish have a second glucagon receptor-like gene that is most closely related to the characterized goldfish glucagon receptor. The phylogeny of glucagon receptor-like genes in fish indicates that a duplication of the glucagon receptor gene occurred on the ancestral fish lineage, and could explain the shared action of glucagon and GLP-1. We suggest that the binding specificity of one of the duplicated glucagon receptors has diverged, yielding receptors for GLP-1 and glucagon, but that ancestral downstream signaling has been maintained, resulting in both receptors retaining glucagon-stimulated downstream effects.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".