Many amino acid substitution variants identified in DNA repair genes during human population screenings are predicted to impact protein function
Section snippets
Prediction of impact of substitutions on function and association with allele frequency
The dataset for analysis of the potential impact of common polymorphisms in DNA repair genes was 523 amino acid substitution variants identified in systematic sequencing of 91 human DNA repair and repair-related genes (summarized under Methods, Table 5). No missense variants were identified in the screening of 9 genes.
PolyPhen scores were obtained for 489 missense variants in 81 genes. Table 1 presents the distribution of the variants by PolyPhen score. To provide an overview of the
Discussion
It is generally acknowledged that most of the burden of common disease in the population exists as sporadic or noninherited cases and results from modest exposures in individuals with elevated susceptibility. This is expected to be especially important in diseases with late age of onset [42], [43], [44]. The hypothesis that elevated susceptibility is associated with polymorphic variants in disease-related genes, the “common variant–common disease” hypothesis has been extensively discussed [43],
The dataset
The majority of the variants included in this analysis were identified during the screening of 88–90 samples from the DNA Polymorphism Discovery Resource available at the Coriell Institute for Medical Research (Camden, NJ, USA). This resource was established by the NIH as a set of samples available to investigators screening for common genetic variants existing in the general population of the United States [76]. The samples are from U.S. residents and the major ethnic groupings of the
Acknowledgements
This work was performed under the auspices of the U.S. Department of Energy by the University of California, Lawrence Livermore National Laboratory, Contract W-7405-ENG-48, and supported by Interagency Agreement Y1-ES-8054-05 from NIEHS and NCI Grant 1 U-1 CA 83180-03. We thank David Wilson 3rd (National Institute of Aging) for many discussions, especially related to the APE1 variants, and Chad Garner (University of California at Irvine) for assistance with statistical analyses. We also
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