Dataset Information

A microarray platform and novel SNP calling algorithm to evaluate Plasmodium falciparum field samples of low DNA quantity.

ABSTRACT: Analysis of single nucleotide polymorphisms (SNPs) derived from whole-genome studies allows for rapid evaluation of genome-wide diversity, and genomic epidemiology studies of Plasmodium falciparum provide insights into parasite population structure, gene flow, drug resistance and vaccine development. In areas with adequate cold chain facilities, large volumes of leukocyte-depleted patient blood can be frozen for use in parasite genomic analyses. In more remote endemic areas smaller volumes of infected blood are taken by finger prick, and dried and stored on filter paper. These dried blood spots do not generally yield enough concentrated parasite DNA for whole-genome sequencing.A DNA microarray was designed for use on field samples to type a genome-wide set of SNPs which prior sequencing had shown to be variable in Africa, Southeast Asia, and Papua New Guinea. An algorithm was designed to call SNPs in samples with low parasite DNA. With this new algorithm SNP-calling accuracy of 98% was measured by hybridizing purified DNA from malaria lab strains and comparing calls with SNPs called from full genome sequences. An average accuracy of >98% was likewise obtained for DNA extracted from malaria field samples collected in studies in Southeast Asia, with an average call rate of > 82%.This new high-density microarray provided high quality SNP calls from a wide range of parasite DNA quantities, and represents a robust tool for genome-wide analysis of malaria parasites in diverse settings.

SUBMITTER: Jacob CG

PROVIDER: S-EPMC4153902 | biostudies-literature | 2014 Aug

REPOSITORIES: biostudies-literature

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A microarray platform and novel SNP calling algorithm to evaluate Plasmodium falciparum field samples of low DNA quantity.

Jacob Christopher G CG Tan John C JC Miller Becky A BA Tan Asako A Takala-Harrison Shannon S Ferdig Michael T MT Plowe Christopher V CV

BMC genomics 20140826

<h4>Background</h4>Analysis of single nucleotide polymorphisms (SNPs) derived from whole-genome studies allows for rapid evaluation of genome-wide diversity, and genomic epidemiology studies of Plasmodium falciparum provide insights into parasite population structure, gene flow, drug resistance and vaccine development. In areas with adequate cold chain facilities, large volumes of leukocyte-depleted patient blood can be frozen for use in parasite genomic analyses. In more remote endemic areas sm ...[more]

PMID: 25159520

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Project description:BackgroundMicroarrays are widely used to investigate the blood stage of Plasmodium falciparum infection. Starting with synchronized cells, gene expression levels are continually measured over the 48-hour intra-erythrocytic cycle (IDC). However, the cell population gradually loses synchrony during the experiment. As a result, the microarray measurements are blurred. In this paper, we propose a generalized deconvolution approach to reconstruct the intrinsic expression pattern, and apply it to P. falciparum IDC microarray data.MethodsWe develop a statistical model for the decay of synchrony among cells, and reconstruct the expression pattern through statistical inference. The proposed method can handle microarray measurements with noise and missing data. The original gene expression patterns become more apparent in the reconstructed profiles, making it easier to analyze and interpret the data. We hypothesize that reconstructed gene expression patterns represent better temporally resolved expression profiles that can be probabilistically modeled to match changes in expression level to IDC transitions. In particular, we identify transcriptionally regulated protein kinases putatively involved in regulating the P. falciparum IDC.ResultsBy analyzing publicly available microarray data sets for the P. falciparum IDC, protein kinases are ranked in terms of their likelihood to be involved in regulating transitions between the ring, trophozoite and schizont developmental stages of the P. falciparum IDC. In our theoretical framework, a few protein kinases have high probability rankings, and could potentially be involved in regulating these developmental transitions.ConclusionsThis study proposes a new methodology for extracting intrinsic expression patterns from microarray data. By applying this method to P. falciparum microarray data, several protein kinases are predicted to play a significant role in the P. falciparum IDC. Earlier experiments have indeed confirmed that several of these kinases are involved in this process. Overall, these results indicate that further functional analysis of these additional putative protein kinases may reveal new insights into how the P. falciparum IDC is regulated.

Dataset Information

A microarray platform and novel SNP calling algorithm to evaluate Plasmodium falciparum field samples of low DNA quantity.

Publications

A microarray platform and novel SNP calling algorithm to evaluate Plasmodium falciparum field samples of low DNA quantity.

Similar Datasets

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