May 2005
Volume 46, Issue 13
Free
ARVO Annual Meeting Abstract  |   May 2005
Use of Comparative Genomics to Facilitate Identification of Mutational Hotspots for Development of an RP Genotyping Array
Author Affiliations & Notes
  • G.J. McKay
    Ophthalmic Research Centre, Queen's University Belfast, Belfast, United Kingdom
  • A. Arora
    Ophthalmic Research Centre, Queen's University Belfast, Belfast, United Kingdom
  • S.K. Todd
    Ophthalmic Research Centre, Queen's University Belfast, Belfast, United Kingdom
  • G. Silvestri
    Ophthalmic Research Centre, Queen's University Belfast, Belfast, United Kingdom
  • D.A. C. Simpson
    Ophthalmic Research Centre, Queen's University Belfast, Belfast, United Kingdom
  • Footnotes
    Commercial Relationships  G.J. McKay, None; A. Arora, None; S.K. Todd, None; G. Silvestri, None; D.A.C. Simpson, None.
  • Footnotes
    Support  HPSS R&D Office RRG 11.14
Investigative Ophthalmology & Visual Science May 2005, Vol.46, 1811. doi:
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      G.J. McKay, A. Arora, S.K. Todd, G. Silvestri, D.A. C. Simpson; Use of Comparative Genomics to Facilitate Identification of Mutational Hotspots for Development of an RP Genotyping Array . Invest. Ophthalmol. Vis. Sci. 2005;46(13):1811.

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

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Abstract

Abstract: : Purpose: Over thirty genes have been implicated in Retinitis Pigmentosa (RP). It is apparent from analysis of well–characterised genes that mutations are not evenly distributed but are located in clusters or ‘hot spots’. These clusters are often within critical functional regions and for this reason are highly conserved amongst orthologs from other species. Our aim is to perform a systematic comparative sequence analysis of known RP genes. This will firstly define the extent of this correlation in those genes for which extensive mutation data is available and secondly predict mutational hotspots in less well–characterised genes. This information will facilitate development of a genotyping array. Methods: Orthologs of 14 ADRP and 17 ARRP genes were identified using Ensembl and aligned with ClustalW (EBI). A javascript was written to map mutational data from well–characterised genes to the multiple sequence alignment. Conserved regions were identified and compared with the distribution of mutations. Results: Analysis of well–characterised genes such as RP4 (RHO) and RP7 (RDS) confirmed that mutations occur preferentially in conserved regions. For RP4, analysis of close orthologs defined conserved regions comprising 93.4% of the coding sequence in which 98.5% of the 66 known missense mutations were included. Addition of further orthologs refined the conserved regions to 69.1% of the coding sequence in which 81.8% of mutations were found. Within the RP7 gene, regions conserved amongst close orthologs covered 78% of coding sequence encompassing 90% of the 40 mutated codons identified. Regions conserved amongst additional orthologs (43.8% of the coding sequence) were found to harbour 70% of the mutations. We have applied this comparative analysis to the other RP genes to refine conserved regions in which it is predicted that a high percentage of mutations will reside. Conclusions: Comparative genomics is a valuable tool to refine likely mutational hotspots in novel genes. Although refinement of conserved regions by consideration of additional orthologs reduces the absolute number of mutations predicted, the number of mutations predicted per codon analysed, increases. This information has been used to optimise the sequences included on a re–sequencing genotyping array designed to detect existing and novel mutations within RP genes. The availability of this comparative sequence data will provide an indication of the possible location of new sequence variants.

Keywords: mutations • gene screening • computational modeling 
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