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      A DNA pooling-based case-control study of myopia candidate genes COL11A1, COL18A1, FBN1, and PLOD1 in a Chinese population

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          Abstract

          Purpose

          We examined the relationship between high myopia and common polymorphisms in four candidate genes: collagen, type XI, alpha 1 ( COL11A1); collagen, type XVIII, alpha 1 ( COL18A1); fibrillin 1 ( FBN1); and procollagen-lysine 1,2-oxoglutarate 5-dioxygenase 1 ( PLOD1). These genes were selected because rare pathogenic mutations in these genes cause disease syndromes that have myopia, usually high myopia, as one of the common presenting features.

          Methods

          This study recruited 600 unrelated Han Chinese subjects including 300 cases with high myopia (spherical equivalent or SE≤-8.00 diopters) and 300 controls (SE within ±1.00 diopter). A total of 66 tag single nucleotide polymorphisms (SNPs) were selected for study from these four candidate genes. The study adopted a DNA pooling strategy with an initial screen of DNA pools to identify putatively positive SNPs and then confirmed the “positive” SNPs by genotyping individual samples forming the original DNA pools. DNA pools were each constructed by mixing equal amounts of DNA from 50 individuals with the same phenotype status. Six case pools were prepared from 300 cases and six control pools from 300 controls. Allele frequencies of DNA pools were estimated by analyzing the primer-extended products with denaturing high performance liquid chromatography and compared between case pools and control pools with nested ANOVA.

          Results

          In the first stage, 60 SNPs from the 4 candidate genes were successfully screened using the DNA pooling approach. Of these, 6 SNPs showed a statistical significant difference in estimated allele frequencies between case pools and controls at p<0.10. In the second stage, these “positive” SNPs were followed up by individual genotyping, but failed to be confirmed via standard single-marker and haplotype analyses.

          Conclusions

          Common polymorphisms in these four candidate genes ( COL11A1, COL18A1, FBN1 and PLOD1) were unlikely to play important roles in the genetic susceptibility to high myopia.

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          Most cited references28

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          Efficiency and power in genetic association studies.

          We investigated selection and analysis of tag SNPs for genome-wide association studies by specifically examining the relationship between investment in genotyping and statistical power. Do pairwise or multimarker methods maximize efficiency and power? To what extent is power compromised when tags are selected from an incomplete resource such as HapMap? We addressed these questions using genotype data from the HapMap ENCODE project, association studies simulated under a realistic disease model, and empirical correction for multiple hypothesis testing. We demonstrate a haplotype-based tagging method that uniformly outperforms single-marker tests and methods for prioritization that markedly increase tagging efficiency. Examining all observed haplotypes for association, rather than just those that are proxies for known SNPs, increases power to detect rare causal alleles, at the cost of reduced power to detect common causal alleles. Power is robust to the completeness of the reference panel from which tags are selected. These findings have implications for prioritizing tag SNPs and interpreting association studies.
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            DNA Pooling: a tool for large-scale association studies.

            DNA pooling is a practical way to reduce the cost of large-scale association studies to identify susceptibility loci for common diseases. Pooling allows allele frequencies in groups of individuals to be measured using far fewer PCR reactions and genotyping assays than are used when genotyping individuals. Here, we discuss recent developments in quantitative genotyping assays and in the design and analysis of pooling studies. Sophisticated pooling designs are being developed that can take account of hidden population stratification, confounders and inter-loci interactions, and that allow the analysis of haplotypes.
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              Detection of genotyping errors by Hardy-Weinberg equilibrium testing.

              Genotyping data sets may contain errors that, in some instances, lead to false conclusions. Deviation from Hardy-Weinberg equilibrium (HWE) in random samples may be indicative of problematic assays. This study has analysed 107,000 genotypes generated by TaqMan, RFLP, sequencing or mass spectrometric methods from 443 single-nucleotide polymorphisms (SNPs). These SNPs are distributed both within genes and in intergenic regions. Genotype distributions for 36 out of 313 assays (11.5%) whose minor allele frequencies were >0.05 deviated from HWE (P<0.05). Some of the possible reasons for this deviation were explored: assays for five SNPs proved nonspecific, and genotyping errors were identified in 21 SNPs. For the remaining 10 SNPs, no reasons for deviation from HWE were identified. We demonstrate the successful identification of a proportion of nonspecific assays, and assays harbouring genotyping error. Consequently, our current high-throughput genotyping system incorporates tests for both assay specificity and deviation from HWE, to minimise the genotype error rate and therefore improve data quality.
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                Author and article information

                Journal
                Mol Vis
                MV
                Molecular Vision
                Molecular Vision
                1090-0535
                2011
                26 March 2011
                : 17
                : 810-821
                Affiliations
                [1 ]Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong SAR, China
                [2 ]Centre for Myopia Research, School of Optometry, The Hong Kong Polytechnic University, Hong Kong SAR, China
                [3 ]Department of Psychiatry, The University of Hong Kong, Hong Kong SAR, China
                Author notes
                Correspondence to: Prof. Shea Ping Yip, Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong SAR, China; Phone: +852 3400 8571; FAX: +852 2362 4365; email: shea.ping.yip@ 123456inet.polyu.edu.hk
                Article
                92 2011MOLVIS0059
                3081793
                21527992
                bdb9d18f-9194-4ac3-b612-9cdede6bcde1
                Copyright © 2011 Molecular Vision.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 13 February 2011
                : 18 March 2011
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                Vision sciences
                Vision sciences

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