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Removal of potentially confounding phenotypes from a Siamese-derived feline glaucoma breeding colony.

ABSTRACT: Feline breeding colonies face genetic constraints involving founder effects. A Siamese-founded colony used to study primary congenital glaucoma displayed coat colors additional to the Siamese coat. Genes affecting pigment can exhibit pleiotropy on ocular development and function. To remove potentially confounding phenotypes from our colony, we documented the source and frequency of the Siamese allele at the gene for tyrosinase (TYR), the dilution allele at melanophilin (MLPH), and the brown allele at tyrosinase-related protein 1 (TYRP1). We used PCR-RFLP diagnostics to genotype cats in our colony for the published alleles. A commercially acquired phenotypically normal tom was the source of the dilute allele. A founding Siamese queen was the source of the brown allele. Founders also were blood-typed and screened for disease-associated alleles segregating in Siamese cats at 3 loci (ASB, GLB1, and CEP290). Siamese founders were normal at all loci except ASB, at which both animals carried the hypomorpic allele. Current stock is being managed to limit production of glaucomatous cats with brown, dilute, or Siamese phenotypes or homozygosity for the ASB hypomorphic allele. Genotyping will aid in the elimination of these alleles. The clinical effect of these phenotypes and alleles on the glaucoma phenotype is uncertain, but their elimination will remove potentially confounding effects. In conclusion, when founding a colony, stock should be selected or screened to limit potentially confounding phenotypes. When studying the immune, nervous, and visual systems, screening stock for alleles known to be associated with coat color may be warranted.

SUBMITTER: Rutz-Mendicino MM

PROVIDER: S-EPMC3123758 | biostudies-literature | 2011 Jun

REPOSITORIES: biostudies-literature

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Removal of potentially confounding phenotypes from a Siamese-derived feline glaucoma breeding colony.

Rutz-Mendicino Michelle M MM Snella Elizabeth M EM Jens Jackie K JK Gandolfi Barbara B Carlson Steven A SA Kuehn Markus H MH McLellan Gillian J GJ Ellinwood N Matthew NM

Comparative medicine 20110601 3

Feline breeding colonies face genetic constraints involving founder effects. A Siamese-founded colony used to study primary congenital glaucoma displayed coat colors additional to the Siamese coat. Genes affecting pigment can exhibit pleiotropy on ocular development and function. To remove potentially confounding phenotypes from our colony, we documented the source and frequency of the Siamese allele at the gene for tyrosinase (TYR), the dilution allele at melanophilin (MLPH), and the brown alle ...[more]

PMID: 21819695

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Project description:PurposePrimary open-angle glaucoma (POAG) is one of the leading causes of irreversible blindness in the United States and worldwide. Although deep learning methods have been proposed to diagnose POAG, these methods all used a single image as input. Contrastingly, glaucoma specialists typically compare the follow-up image with the baseline image to diagnose incident glaucoma. To simulate this process, we proposed a Siamese neural network, POAGNet, to detect POAG from optic disc photographs.DesignThe POAGNet, an algorithm for glaucoma diagnosis, is developed using optic disc photographs.ParticipantsThe POAGNet was trained and evaluated on 2 data sets: (1) 37 339 optic disc photographs from 1636 Ocular Hypertension Treatment Study (OHTS) participants and (2) 3684 optic disc photographs from the Sequential fundus Images for Glaucoma (SIG) data set. Gold standard labels were obtained using reading center grades.MethodsWe proposed a Siamese network model, POAGNet, to simulate the clinical process of identifying POAG from optic disc photographs. The POAGNet consists of 2 side outputs for deep supervision and uses convolution to measure the similarity between 2 networks.Main outcome measuresThe main outcome measures are the area under the receiver operating characteristic curve, accuracy, sensitivity, and specificity.ResultsIn POAG diagnosis, extensive experiments show that POAGNet performed better than the best state-of-the-art model on the OHTS test set (area under the curve [AUC] 0.9587 versus 0.8750). It also outperformed the baseline models on the SIG test set (AUC 0.7518 versus 0.6434). To assess the transferability of POAGNet, we also validated the impact of cross-data set variability on our model. The model trained on OHTS achieved an AUC of 0.7490 on SIG, comparable to the previous model trained on the same data set. When using the combination of SIG and OHTS for training, our model achieved superior AUC to the single-data model (AUC 0.8165 versus 0.7518). These demonstrate the relative generalizability of POAGNet.ConclusionsBy simulating the clinical grading process, POAGNet demonstrated high accuracy in POAG diagnosis. These results highlight the potential of deep learning to assist and enhance clinical POAG diagnosis. The POAGNet is publicly available on https://github.com/bionlplab/poagnet.

Project description:Background: Eusociality is widely considered to evolve through kin selection, where the reproductive success of an individual’s close relative is favored at the expense of its own. High genetic relatedness is thus considered a prerequisite for eusociality. While ants are textbook examples of eusocial animals, not all ants form colonies of closely related individuals. One such example is the ectatommine ant Rhytidoponera metallica, which predominantly forms predominantly queen-less colonies that have such a low intra-colony relatedness that they have been proposed to represent a transient, unstable form of eusociality. However, R. metallica is among the most abundant and widespread ants on the Australian continent. This apparent contrast provides an example of how inclusive fitness may not by itself explain the maintenance of eusociality and raises the question of what other selective advantages maintain their eusocial lifestyle. Results: We provide a comprehensive portrait of the venom of R. metallica and show that the colony-wide venom consists of a, for an ant, exceptionally high diversity of functionally distinct toxins. These toxins have evolved under strong positive selection, which is normally expected to reduce genetic variance. Yet, R. metallica exhibits remarkable intra-colony variation, with workers sharing only a relatively small proportion of toxins in their venoms. We also find that this variation is not due to the presence of chemical castes, but that it has a genetic foundation that is at least in part explained by toxin allelic diversity. Conclusions: Taken together, our results suggest that the toxin diversity contained in R. metallica colonies may be maintained by a form of group selection, which selects for colonies that can exploit more resources and defend against a wider range of predators. We propose that increased intra-colony genetic variance resulting from low kinship may itself provide a selective advantage in the form of an expanded pharmacological venom repertoire. These findings provide an example of how group selection on adaptive phenotypes may contribute to maintaining eusociality where a prerequisite for kin selection is diminished.

Dataset Information

Removal of potentially confounding phenotypes from a Siamese-derived feline glaucoma breeding colony.

Publications

Removal of potentially confounding phenotypes from a Siamese-derived feline glaucoma breeding colony.

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