Several strains of the lethal malaria parasite, Plasmodium falciparum, have recently been sequenced, providing a rich comparative database of DNA diversity for this species. This vast information could spur exciting new research; however, the inability to easily assay this variation on a whole-genome scale in natural populations is a significant hindrance. High-density comparative genome hybridization (CGH) can be used to scan genomes for variation such as copy number polymorphisms, indels, and even SNPs. The apicomplexan P. falciparum genome is relatively small (23 Mb) and haploid in human red blood cells, making it a superb candidate for CGH genotyping. A drawback is the A - T richness of this species (80%), a challenge that can be overcome by using longer oligonucleotide probes to compensate for the relatively low melting temperature while also reducing the likelihood of cross-hybridization potential from other loci in the genome. A CGH platform that uses a maskless photolithography technology holds great promise for hybridization-based genotyping and re-sequencing because it uses longer and variable length probes in a high density format, and allows for cost-effective, as-needed, single chip designs; consequently, different chip configurations can be evaluated for their ability to detect SNPs. We have performed CGH for P. falciparum using longer probes and have had success identifying a spectrum of polymorphisms, including single base changes. Moreover, we have demonstrated that variations in probe parameters significantly influence this capacity. The goal of this proposal is to systematically optimize a P. falciparum genotyping chip. We will do this by using the SNP database compiled by the Broad/Harvard/MIT sequencing consortium to directly optimize our probe configurations.
Specific Aim 1 : To optimize probes for SNP detection using co- hybridization of the HB3 and 3D7 strain DNAs to a series of chips consisting of single- base tiled probes spanning known SNPs.
Specific Aim 2. To apply the optimized probes to select single feature polymorphisms (SNPs and indels) genome-wide, including regions of increasing sequence repetitiveness, and to directly re-sequence twp 48kb regions.
Specific Aim 3 : To extend these design parameters to all known polymorphisms and develop a custom P. falciparum genotyping chip. Our raw data, analysis, and chip designs will be made available as generated to facilitate rapid community use of this technology. Malaria kills more than 2 million kids in Africa and infects more than 500 million people worldwide each year. The recently completed Plasmodium falciparum comparative genome sequencing project at the Broad Institute provides a vast view of genetic diversity of this species; however, there is no way for researchers to assay this variation in large populations. Our proposal aims to develop a genotyping microarray platform that will facilitate association studies and haplotype mapping to find the genetic determinants of malaria parasite drug resistance and virulence. This knowledge will lead to new avenues of attack against this disease. ? ? ?

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Exploratory/Developmental Grants (R21)
Project #
1R21AI072517-01A1
Application #
7315580
Study Section
Genetic Variation and Evolution Study Section (GVE)
Program Officer
Joy, Deirdre A
Project Start
2007-09-19
Project End
2009-08-31
Budget Start
2007-09-19
Budget End
2008-08-31
Support Year
1
Fiscal Year
2007
Total Cost
$222,500
Indirect Cost
Name
University of Notre Dame
Department
Biology
Type
Schools of Arts and Sciences
DUNS #
824910376
City
Notre Dame
State
IN
Country
United States
Zip Code
46556
Tan, John C; Miller, Becky A; Tan, Asako et al. (2011) An optimized microarray platform for assaying genomic variation in Plasmodium falciparum field populations. Genome Biol 12:R35
Tan, John C; Patel, Jigar J; Tan, Asako et al. (2009) Optimizing comparative genomic hybridization probes for genotyping and SNP detection in Plasmodium falciparum. Genomics 93:543-50