June 2013
Volume 54, Issue 15
Free
ARVO Annual Meeting Abstract  |   June 2013
Methylation landscape of ocular tissue and their correlation to peripheral leucocytes
Author Affiliations & Notes
  • Alex Hewitt
    Department of Ophthalmology, Centre for Eye Research Australia, Surrey Hills, VIC, Australia
    Lions Eye Institute, University of Western Australia, Perth, WA, Australia
  • Jihoon Joo
    Murdoch Childrens Research Institute, The Royal Children’s Hospital, Melbourne, VIC, Australia
  • Jie Wang
    Department of Ophthalmology, Centre for Eye Research Australia, Surrey Hills, VIC, Australia
  • Jamie Craig
    Department of Ophthalmology, Flinders University of South Australia, Adelaide, SA, Australia
  • Richard Saffery
    Murdoch Childrens Research Institute, The Royal Children’s Hospital, Melbourne, VIC, Australia
  • Footnotes
    Commercial Relationships Alex Hewitt, None; Jihoon Joo, None; Jie Wang, None; Jamie Craig, None; Richard Saffery, None
  • Footnotes
    Support None
Investigative Ophthalmology & Visual Science June 2013, Vol.54, 1739. doi:
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      Alex Hewitt, Jihoon Joo, Jie Wang, Jamie Craig, Richard Saffery; Methylation landscape of ocular tissue and their correlation to peripheral leucocytes. Invest. Ophthalmol. Vis. Sci. 2013;54(15):1739.

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Abstract
 
Purpose
 

The aim of this study was to investigate the whole genome methylation profiles of ocular tissues. In comparing this profile to unfractionated blood samples from the same individuals, we also sought to investigate the utility of leucocyte DNA methylation in the study of ocular disease.

 
Methods
 

Whole blood from the subclavian vein and whole eyes (N=##?) were obtained post-mortem. DNA was extracted from whole blood as well as neurosensory retina, retinal pigment epithelium (RPE)/choroid and optic nerve tissue. Following bisulfite conversion samples were hybridized to Illumina Infinium HumanMethylation450 BeadChips according to the manufacture’s protocols. Data were analysed using R v2.15.1.

 
Results
 

Following QC a total of 464,993 CpG sites common to all samples were used for subsequent analysis. Unstructured hierarchical clustering of all CpG sites for each sample revealed well-defined groupings across individual tissue subtypes. Despite this discrete clustering, there was generally a strong correlation between methylation profiles, across all tissues from each individual (median (range) Pearsons corr=0.923 (0.851-0.991)). Over 250,000 CpG sites were found to have similar methylation levels (beta <0.2 or beta >0.8) across different tissues in the same individuals, with a further ~18,000 sites having similar methylation profiles in all ocular tissue only.

 
Conclusions
 

Our results reveals a strong correlation between the methylation status of peripheral blood leukocytes and different ocular tissues, highlighting the utility of using whole blood to study potential epigenetic changes in ophthalmic disease. These results are particularly encouraging for research where non-end organ tissue is difficult to obtain. An improved understanding of the epigenetic landscape of ocular tissue will have important ramifications for regenerative medicine and ongoing dissection of gene-environment interactions in eye disease.

 
 
Genome-wide CpG site inter-tissue and inter-sample relationships. A) Hierarchical clustergram across all samples. Individuals are represented by their corresponding code, B) Scatter plot of individual CpG sites mean methylation levels across different tissue.
 
Genome-wide CpG site inter-tissue and inter-sample relationships. A) Hierarchical clustergram across all samples. Individuals are represented by their corresponding code, B) Scatter plot of individual CpG sites mean methylation levels across different tissue.
 
Keywords: 539 genetics • 533 gene/expression • 536 gene modifiers  
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