Peer Review #2 of "Using electroretinograms and multi-model inference to identify spectral classes of photoreceptors and relative opsin expression levels (v0.1)" [peer_review]

J Marshall
2017 unpublished
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 absorbance 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
more » ... e fused, and can form vertical tiers. Akaike's Information Criterion (AIC) 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 Scone 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 oversimplification 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. ABSTRACT 33 Understanding how individual photoreceptor cells factor in the spectral sensitivity of a 34 visual system is essential to explain how they contribute to the visual ecology of the animal in 35 question. Existing methods that model the absorption of visual pigments use templates which 36 correspond closely to data from thin cross-sections of photoreceptor cells. However, few 37 modeling approaches use a single framework to incorporate physical parameters of real 38 photoreceptors, which can be fused, and can form vertical tiers. Akaike's Information Criterion 39 (AIC) was used here to select absorptance models of multiple classes of photoreceptor cells that 40 maximize information, given visual system spectral sensitivity data obtained using extracellular 41 electroretinograms and structural parameters obtained by histological methods. This framework 42 was first used to select among alternative hypotheses of photoreceptor number. It identified 43 spectral classes from a range of dark-adapted visual systems which have between one and four 44 spectral photoreceptor classes. These were the velvet worm, Principapillatus hitoyensis, the 45 branchiopod water flea, Daphnia magna, normal humans, and humans with enhanced S-cone 46 syndrome, a condition in which S-cone frequency is increased due to mutations in a transcription 47 factor that controls photoreceptor expression. Data from the Asian swallowtail, Papilio xuthus, 48 which has at least five main spectral photoreceptor classes in its compound eyes, were included 49 to illustrate potential effects of model oversimplification on multi-model inference. The multi-50 model framework was then used with parameters of spectral photoreceptor classes and the 51 structural photoreceptor array kept constant. The goal was to map relative opsin expression to 52 visual pigment concentration. The framework identified relative opsin expression differences for 53 two populations of the bluefin killifish, Lucania goodei. The modeling approach presented here 54 will be useful in selecting the most likely alternative hypotheses of opsin-based spectral 55 photoreceptor classes, using relative opsin expression and extracellular electroretinography. Manuscript to be reviewed 361 Akaike H. 1974. A new look at the statistical model identification. IEEE transactions on 362 automatic control 19:716-723. 363 Arendt D., Tessmar-Raible K., Snyman H., Dorresteijn AW., Wittbrodt J. 2004. Ciliary 364 photoreceptors with a vertebrate-type opsin in an invertebrate brain. sensitivity in Onychophora (velvet worms) revealed by electroretinograms, phototactic 375 behaviour and opsin gene expression. Journal of Experimental Biology 218:915-922. 376 Bowmaker JK. 1999. Molecular biology of photoreceptor spectral sensitivity. In: Adaptive 377 Mechanisms in the Ecology of Vision. Dordrecht: Kluwer Academic Publishers, 439-464. 378 Bowmaker JK., Dartnall HJ. 1980. Visual pigments of rods and cones in a human retina. The 379 Journal of Physiology 298:501-511. 380 Bruno M., Barnes S., Goldsmith TH. 1977. The visual pigment and visual cycle of the lobster,
doi:10.7287/peerj.3595v0.1/reviews/2 fatcat:256g235zfvffhhhtfmf3n4fb2i