Early Evolution of Ionotropic GABA Receptors and Selective Regimes Acting on the Mammalian-Specific Theta and Epsilon Subunits
Bibliographic record
Abstract
BACKGROUND: The amino acid neurotransmitter GABA is abundant in the central nervous system (CNS) of both invertebrates and vertebrates. Receptors of this neurotransmitter play a key role in important processes such as learning and memory. Yet, little is known about the mode and tempo of evolution of the receptors of this neurotransmitter. Here, we investigate the phylogenetic relationships of GABA receptor subunits across the chordates and detail their mode of evolution among mammals. PRINCIPAL FINDINGS: Our analyses support two major monophyletic clades: one clade containing GABA(A) receptor alpha, gamma, and epsilon subunits, and another one containing GABA(A) receptor rho, beta, delta, theta, and pi subunits. The presence of GABA receptor subunits from each of the major clades in the Ciona intestinalis genome suggests that these ancestral duplication events occurred before the divergence of urochordates. However, while gene divergence proceeded at similar rates on most receptor subunits, we show that the mammalian-specific subunits theta and epsilon experienced an episode of positive selection and of relaxed constraints, respectively, after the duplication event. Sites putatively under positive selection are placed on a three-dimensional model obtained by homology-modeling. CONCLUSIONS: Our results suggest an early divergence of the GABA receptor subunits, before the split from urochordates. We show that functional changes occurred in the lineages leading to the mammalian-specific subunit theta, and we identify the amino acid sites putatively responsible for the functional divergence. We discuss potential consequences for the evolution of mammals and of their CNS.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".