Evolution and functional specializations in nocturnal environments: insights from visual pigments in Chiroptera
Bibliographic record
Abstract
Sensory systems act as a direct interface between organisms and their environment, constituting an ideal model to investigate how diverse evolutionary pressures shaped sensory adaptation. At the molecular level, vision is initiated through activation of visual pigments, light-sensitive complexes expressed in photoreceptor cells in the retina that have been shown to evolve in response to changes in ecology and light environment. In this thesis, I employ molecular evolutionary analyses and experimental characterization of visual pigments to study the molecular basis of visual system specializations in bats, one of the most striking and ecologically diverse mammalian radiations. In Chapter 2, I review recent work on the ecological and evolutionary pressures mediating sensory adaptation in vertebrates, including remarkable specializations of bats. In Chapter 3, I use comparative sequence analysis to test whether ecological factors known to influence bat visual ecology mediate shifts in evolutionary pressure in cone opsin genes, Lws and Sws1. I find significant evidence that long-term shifts in selection constraint in cone opsins occur in response to ecological factors underlying reliance on visual information and exposure to varying light environments. In Chapters 4 and 5, I focus my study on the evolution of the dim-light visual pigment rhodopsin (Rh1) in response to echolocation, a remarkable sensory adaptation of bats. In Chapter 4, I experimentally characterize rhodopsin of several bat species and find that changes in kinetic properties that influence dim-light visual performance are associated with differing echolocation abilities. In Chapter 5, I reconstruct and experimentally resurrect the ancestral rhodopsin pigment of Chiroptera and Scrotifera. I find that changes in rhodopsin kinetics occurred during the evolution of bats are likely associated with the origins of echolocation. This thesis combines in vitro and in silico approaches to investigate visual pigment evolution in Chiroptera. More broadly, this thesis also discusses the role of diverse ecological pressures in shaping visual gene evolution, the molecular underpinnings of visual pigment function and adaptation to light-limited environments as well as the complex interactions between sensory specializations.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".