GENOTYPING CORE

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This is a revision of Program Project proposal 1 PO1 HD-047609 "Gene-Environment Interactions in Human Parturition" that was submitted in October 2003, reviewed by an NICHD Special Emphasis Panel, and received a priority score of 199 (30th percentile). In this research program we proposed to identify the genetic and environmental determinants of the length of human gestation/ timing of onset of spontaneous parturition, and to model the gene, environment, and maternal-fetal interactions that may underlie the risk of premature birth among three racial/ ethnic populations: African-Americans, Hispanics and nonHispanic Whites. The previous review commented very favorably on all aspects of the Genotyping Core as proposed, and noted that the expertise of the Core Director (Hixson) and track record of gene sequencing efforts at the University of Texas Human Genetics Center would ensure the goals will be realized and the reliability of the results will be at the highest possible level. The review did not raise any concerns. The Core received a priority score of 110. One issue that was brought up in the review of Project III relates to the accuracy of the MALDI-TOF platform for SNP assay in a high throughput environment. Since this issue is pertinent to the Genotyping Core, it is addressed here in the present revision with the following data about assay reliability that was generated by the Core. "Mefhodo/ogy for re-sequencing and SNP typing are not fully established in Core C and Project 1 on which Project 3 depends - accuracy of the allele calls with the MALDI-TOF platform of SNP assay is still not fully documented in a high throughput environment." Many different automated platforms have been developed for high-throughput genotyping based on a wide array of current molecular technologies. The Brucker Biflex III MALDI-TOF system (Sequenom, Inc.) is a proven and wellestablished genotyping platform that is based on distinguishing allele-specific mini-sequencing reactions using mass spectrometry analysis. In our hands, we have found that the Sequenom platform produces accurate and consistent allele calls in a high-throughput environment. We have used this instrument for several large epidemiological studies that included comprehensive blind duplicate programs to assess genotyping error rates. The numbers of blind duplicates in these studies range from 5% to 10% of the samples. Table 1 presents results from a monthly survey of blind duplicate data for an on-going study. This analysis of seven different polymorphisms (A-G) yielded 98-100% agreement for blind duplicate allele calls. This information is now included in the revised description of the Core (p.304).