Analysis of whole genomes using mapping by admixture linkage disequilibrium (MALD) and candidate genes requires an appropriate set of markers and the ability to accurately genotype hundreds to thousands of patients with hundreds to thousands of markers. Markers appropriate for MALD must have large differences between racial groups. While our first applications of MALD are in African Americans, we expect that MALD in other admixed groups like Hispanics will also be explored by ourselves and other researchers. To that end, we collected data for 3,669 high difference single nucleotide polymorphisms (SNPs) from Asians, Amerindians, Africans, African Americans and European Americans. These analyses identified 2,148 loci with sufficiently large differences between groups for use in analyses of African American patients. These results have been recently published? Genotyping with the 384-well panels has been largely automated. A Genetix automated pipettor can precisely add a few microliters of water to each of 384 wells in seconds. Then polymorphic chain reaction (PCR) cocktails and enzymatic genotyping reagents are added with 16-channel pipettors from Matrix. Total volumes have been reduced to 5 ul and DNA is used in quantities as low as 0.7 nanograms. These lower amounts are reducing the cost of genotyping reagents such that the increase in going from 96- to 384-well conserves DNA with little additional cost. Previously, setting up a few thousand PCR reactions took an hour or two. With these developments in automation and scale reduction it is possible to set up and analyze thousands of reactions at the same time. Always on the lookout for bottlenecks, the current one is now analysis of polymorphisms as they are determined, and subsequent epidemiological analyses. The reduced sample handling has resulted in fewer missing data points that were the result of pipetting errors made in the complex set-up of reactions. In the MALD map project, our error rate was low with 61 discrepancies out of 12,447 (0.49%) in replicate and independent determinations. The implementation of 384-well matrix-based microtiter plate technology is allowing us to address genetic questions that previously required heroic handling of many plates and detailed sample tracking.? ? After piloting various high throughput genotyping platforms and analyzing the data quality from these platforms, the Laboratory of Genomic Diversity (LGD) decided to acquire a ParAllele High Throughput Genotyping System and an Illumina one. These High Throughput systems have now been delivered, set up, validated, and found to successfully run at the LGD. The LGD laboratory technicians are now fully versed in successfully implementing and running these systems. Thus, the LGD has already begun large scale SNP genotyping association studies investigating the more than 16,000 patient DNA samples along with their related extensively-annotated clinical information via the ParAllele High Throughput Genotyping System. This information will allow the LGD to elucidate the genetic components underlying HIV/AIDS and many other complex multigenic disorders such as; persistent hepatitis B, viliuisk encephalomyelitis, nasopharyngeal carcinoma, prostate cancer, focal segmented glomerulosclerosis disease, and end stage renal disease.? ? In another development, we have begun amplifying DNA as a means of maintaining a renewable source for genetic analysis. Whole genome amplification is a method of enzymatically synthesizing renewable DNA from sources of limited DNA (a few nanograms from buccal cells, small blood samples, body fluids, hair, and non-viable cells). The whole gene amplification method uses hexamers in multiple displacement amplification of the entire genome from 1-20ng of genomic DNA. ?

Agency
National Institute of Health (NIH)
Institute
Division of Basic Sciences - NCI (NCI)
Type
Intramural Research (Z01)
Project #
1Z01BC010270-09
Application #
7291806
Study Section
(LGD)
Project Start
Project End
Budget Start
Budget End
Support Year
9
Fiscal Year
2005
Total Cost
Indirect Cost
Name
Basic Sciences
Department
Type
DUNS #
City
State
Country
United States
Zip Code
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