June 2020
Volume 61, Issue 7
Free
ARVO Annual Meeting Abstract  |   June 2020
A novel systems genetics approach identifies a naturally occurring mouse model of photoreceptor degeneration
Author Affiliations & Notes
  • Lu Lu
    Genetics, Genomics and Informatics, UTHSC, Memphis, Tennessee, United States
  • David Ashbook
    Genetics, Genomics and Informatics, UTHSC, Memphis, Tennessee, United States
  • Fuyi Xu
    Genetics, Genomics and Informatics, UTHSC, Memphis, Tennessee, United States
  • Kin-Sang Cho
    Ophthalmology, Schepens Eye Research Institute of Mass Eye and Ear, Harvard Medical School, Boston, Massachusetts, United States
  • Yizhen Tang
    Ophthalmology, Schepens Eye Research Institute of Mass Eye and Ear, Harvard Medical School, Boston, Massachusetts, United States
  • Robert Williams
    Genetics, Genomics and Informatics, UTHSC, Memphis, Tennessee, United States
  • Dongfeng Chen
    Ophthalmology, Schepens Eye Research Institute of Mass Eye and Ear, Harvard Medical School, Boston, Massachusetts, United States
  • Footnotes
    Commercial Relationships   Lu Lu, None; David Ashbook, None; Fuyi Xu, None; Kin-Sang Cho, None; Yizhen Tang, None; Robert Williams, None; Dongfeng Chen, None
  • Footnotes
    Support  NIH Grant R01EY025259
Investigative Ophthalmology & Visual Science June 2020, Vol.61, 1291. doi:
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      Lu Lu, David Ashbook, Fuyi Xu, Kin-Sang Cho, Yizhen Tang, Robert Williams, Dongfeng Chen; A novel systems genetics approach identifies a naturally occurring mouse model of photoreceptor degeneration. Invest. Ophthalmol. Vis. Sci. 2020;61(7):1291.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : Retinitis pigmentosa (RP) is a group of congenital photoreceptor degenerative disorders. Genetic studies have identified causes for only ~50% of patients. Pinpointing mutations in RP patients remains a great challenge. Here, we used a novel systems genetics approach, taking advantage of the reproducibility of recombinant inbred strains and deep sequencing data, to identify causal gene(s) for photoreceptor degeneration in the large BXD family.

Methods : We used the top 100 transcripts whose expression significantly correlates with photoreceptor number in a subset of BXD strains to calculate the first principal component eigengene. This eigengene was used as a consensus photoreceptor biomarker and to predict photoreceptor viability. Retinal morphology and function were tracked non-invasively using optic coherence tomography (OCT) and electroretinogram (ERG), and photoreceptor cell counts were carried out in immunolabeled sections for a subset of strains with possible photoreceptor degeneration. Linked-read whole-genome sequencing data for all 150 BXD strains was used to nominate high likelihood candidate genes underlying degeneration. Variants were annotated using the Variant Effect Predictor.

Results : We identified three BXD strains as likely to have abnormal photoreceptor number: including two that have been previously identified (BXD32 and BXD24), and one novel mutant—BXD83. We confirmed these findings using OCT, ERG and retinal histology, and found significant, progressive loss of photoreceptor cells and visual function deterioration in postnatal BXD83 cases compared to means of other BXD strains. Using DNA-seq data, we identified 522 de novo mutations unique to BXD83, and one of these was predicted high impact, a stop-gain in Prom1.

Conclusions : We present a novel strategy for prioritizing candidate gene mutations that enables effective discovery and localization of disease causative genes. Moreover, we have identified a new mouse model of photoreceptor degeneration likely associated with Prom1, a gene previously linked to Stargardt disease and rod-cone dystrophy. This novel model will allow exploration of the mechanisms underlying the disorder and the testing of therapeutics.

This is a 2020 ARVO Annual Meeting abstract.

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