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Using electroretinograms and multi-model inference to identify spectral classes of photoreceptors and relative opsin expression levels

Understanding how individual photoreceptor cells factor in the spectral sensitivity of a visual system is essential to explain how they contribute to the visual ecology of the animal in question. Existing methods that model the absorption of visual pigments use templates which correspond closely to...

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Autor principal: Lessios, Nicolas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5522723/
https://www.ncbi.nlm.nih.gov/pubmed/28740757
http://dx.doi.org/10.7717/peerj.3595
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author Lessios, Nicolas
author_facet Lessios, Nicolas
author_sort Lessios, Nicolas
collection PubMed
description Understanding how individual photoreceptor cells factor in the spectral sensitivity of a visual system is essential to explain how they contribute to the visual ecology of the animal in question. Existing methods that model the absorption of visual pigments use templates which correspond closely to data from thin cross-sections of photoreceptor cells. However, few modeling approaches use a single framework to incorporate physical parameters of real photoreceptors, which can be fused, and can form vertical tiers. Akaike’s information criterion (AIC(c)) was used here to select absorptance models of multiple classes of photoreceptor cells that maximize information, given visual system spectral sensitivity data obtained using extracellular electroretinograms and structural parameters obtained by histological methods. This framework was first used to select among alternative hypotheses of photoreceptor number. It identified spectral classes from a range of dark-adapted visual systems which have between one and four spectral photoreceptor classes. These were the velvet worm, Principapillatus hitoyensis, the branchiopod water flea, Daphnia magna, normal humans, and humans with enhanced S-cone syndrome, a condition in which S-cone frequency is increased due to mutations in a transcription factor that controls photoreceptor expression. Data from the Asian swallowtail, Papilio xuthus, which has at least five main spectral photoreceptor classes in its compound eyes, were included to illustrate potential effects of model over-simplification on multi-model inference. The multi-model framework was then used with parameters of spectral photoreceptor classes and the structural photoreceptor array kept constant. The goal was to map relative opsin expression to visual pigment concentration. It identified relative opsin expression differences for two populations of the bluefin killifish, Lucania goodei. The modeling approach presented here will be useful in selecting the most likely alternative hypotheses of opsin-based spectral photoreceptor classes, using relative opsin expression and extracellular electroretinography.
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spelling pubmed-55227232017-07-24 Using electroretinograms and multi-model inference to identify spectral classes of photoreceptors and relative opsin expression levels Lessios, Nicolas PeerJ Animal Behavior Understanding how individual photoreceptor cells factor in the spectral sensitivity of a visual system is essential to explain how they contribute to the visual ecology of the animal in question. Existing methods that model the absorption of visual pigments use templates which correspond closely to data from thin cross-sections of photoreceptor cells. However, few modeling approaches use a single framework to incorporate physical parameters of real photoreceptors, which can be fused, and can form vertical tiers. Akaike’s information criterion (AIC(c)) was used here to select absorptance models of multiple classes of photoreceptor cells that maximize information, given visual system spectral sensitivity data obtained using extracellular electroretinograms and structural parameters obtained by histological methods. This framework was first used to select among alternative hypotheses of photoreceptor number. It identified spectral classes from a range of dark-adapted visual systems which have between one and four spectral photoreceptor classes. These were the velvet worm, Principapillatus hitoyensis, the branchiopod water flea, Daphnia magna, normal humans, and humans with enhanced S-cone syndrome, a condition in which S-cone frequency is increased due to mutations in a transcription factor that controls photoreceptor expression. Data from the Asian swallowtail, Papilio xuthus, which has at least five main spectral photoreceptor classes in its compound eyes, were included to illustrate potential effects of model over-simplification on multi-model inference. The multi-model framework was then used with parameters of spectral photoreceptor classes and the structural photoreceptor array kept constant. The goal was to map relative opsin expression to visual pigment concentration. It identified relative opsin expression differences for two populations of the bluefin killifish, Lucania goodei. The modeling approach presented here will be useful in selecting the most likely alternative hypotheses of opsin-based spectral photoreceptor classes, using relative opsin expression and extracellular electroretinography. PeerJ Inc. 2017-07-21 /pmc/articles/PMC5522723/ /pubmed/28740757 http://dx.doi.org/10.7717/peerj.3595 Text en © 2017 Lessios http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Animal Behavior
Lessios, Nicolas
Using electroretinograms and multi-model inference to identify spectral classes of photoreceptors and relative opsin expression levels
title Using electroretinograms and multi-model inference to identify spectral classes of photoreceptors and relative opsin expression levels
title_full Using electroretinograms and multi-model inference to identify spectral classes of photoreceptors and relative opsin expression levels
title_fullStr Using electroretinograms and multi-model inference to identify spectral classes of photoreceptors and relative opsin expression levels
title_full_unstemmed Using electroretinograms and multi-model inference to identify spectral classes of photoreceptors and relative opsin expression levels
title_short Using electroretinograms and multi-model inference to identify spectral classes of photoreceptors and relative opsin expression levels
title_sort using electroretinograms and multi-model inference to identify spectral classes of photoreceptors and relative opsin expression levels
topic Animal Behavior
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5522723/
https://www.ncbi.nlm.nih.gov/pubmed/28740757
http://dx.doi.org/10.7717/peerj.3595
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