July 2018
Volume 59, Issue 9
Free
ARVO Annual Meeting Abstract  |   July 2018
Candidate gene analysis at two QTL modulating AII amacrine cell number in mouse retina
Author Affiliations & Notes
  • Bridget Kulesh
    Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara, Santa Barbara, California, United States
    Neuroscience Research Institute, University of California, Santa Barbara, Santa Barbara, California, United States
  • Patrick William Keeley
    Neuroscience Research Institute, University of California, Santa Barbara, Santa Barbara, California, United States
  • Benjamin E Reese
    Neuroscience Research Institute, University of California, Santa Barbara, Santa Barbara, California, United States
    Psychological and Brain Sciences, University of California, Santa Barbara, Santa Barbara, California, United States
  • Footnotes
    Commercial Relationships   Bridget Kulesh, None; Patrick Keeley, None; Benjamin Reese, None
  • Footnotes
    Support  NIH Grant EY019968
Investigative Ophthalmology & Visual Science July 2018, Vol.59, 588. doi:
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    • Get Citation

      Bridget Kulesh, Patrick William Keeley, Benjamin E Reese; Candidate gene analysis at two QTL modulating AII amacrine cell number in mouse retina. Invest. Ophthalmol. Vis. Sci. 2018;59(9):588.

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

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Abstract

Purpose : Retinal cell number is tightly controlled within inbred strains of mice, yet there is substantial variation between strains. To understand the genetic underpinnings of such variation, we used a panel of recombinant inbred (RI) strains to identify genomic loci that contribute to such strain differences, focusing on the population of AII amacrine cells. A candidate gene analysis was subsequently conducted to identify prospective genes at those loci.

Methods : AII amacrine cell number was determined in C57BL/6J and A/J strains and in 26 RI strains derived from them (the AXB/BXA strain set). Quantitative trait locus (QTL) mapping was performed using GeneNetwork. SNPs and Indels were identified in genes at QTL using the SANGER mouse database. Candidate genes were ranked through extensive screening of the variants. Coding mutations (frameshift, inframe, stop, and missense) were characterized by their ability to affect known domain or transmembrane regions of the protein; additionally, missense mutations were evaluated as to whether the variant affected amino acid traits such as charge and hydrophobicity. Potential regulatory variants (upstream, UTR, and splice site) were ranked based on the degree of homology across species at that nucleotide and surrounding regions. Variants found in 3’ UTRs were further screened for disrupting predicted microRNA binding regions.

Results : AII amacrine cell number demonstrated significant inter-strain variability across the strains, from a low of 57,141 cells to a high of 86,557 cells, yet showed minimal within-strain variability, the strains exhibiting a coefficient of variation averaging 0.05. The variation across RI strains mapped to two genomic loci, on Chrs 9 and 19, which were validated using chromosome substitution mice. Of the initial 115 genes at the QTL on Chr 9 and the 183 genes at the QTL on Chr 19, we eliminated those with no sequence variants. The remainder were ranked based on the number of variants that were predicted to affect gene expression or function. Further consideration of expression databases and functional analyses yielded a final prioritized list of 11 genes on Chr 9 and 10 genes on Chr 19.

Conclusions : 21 promising candidate genes, each exhibiting variants predicted to modulate gene expression or protein function, have been identified, and will be the object of further exploration to understand the genetic determinants of AII amacrine cell number.

This is an abstract that was submitted for the 2018 ARVO Annual Meeting, held in Honolulu, Hawaii, April 29 - May 3, 2018.

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