Abstract
In this study, we interpreted RNA-seq time-course data of three developmental stages of Plasmodium species by clustering genes based on similarities in their expression profile without prior knowledge of the gene function. Functional enrichment of clusters of upregulated genes at specific time-points reveals potential targetable biological processes with information on their timings. We identified common consensus sequences that these clusters shared as potential points of coordinated transcriptional control. Five cluster groups showed upregulated profile patterns of biological interest. This included two clusters from the Intraerythrocytic Developmental Cycle (cluster 4 = 16 genes, and cluster 9 = 32 genes), one from the sexual development stage (cluster 2 = 851 genes), and two from the gamete-fertilization stage in the mosquito host (cluster 4 = 153 genes, and cluster 9 = 258 genes). The IDC expressed the least numbers of genes with only 1448 genes showing any significant activity of the 5020 genes (~29%) in the experiment. Gene ontology (GO) enrichment analysis of these clusters revealed a total of 671 uncharacterized genes implicated in 14 biological processes and components associated with these stages, some of which are currently being investigated as drug targets in on-going research. Five putative transcription regulatory binding motifs shared by members of each cluster were also identified, one of which was also identified in a previous study by separate researchers. Our study shows stage-specific genes and biological processes that may be important in antimalarial drug research efforts. In addition, timed-coordinated control of separate processes may explain the paucity of factors in parasites.
Highlights
In the past two decades, there has been an extraordinary commitment to the control and elimination of malaria which has resulted to a significant decrease in global malaria morbidity and mortality (Rao, 2015)
Significant genes and clustering of profiles Identification of statistically significant expressed genes (p < 0.05) and expression profile clustering for the IDC, SEX and MOS development stages of P. berghei was done in R on a Windows 64-bit platform using the maSigPro package. maSigPro was initially designed for microarray time course experiments but has since been upgraded to handle next-generation sequencing (NGS) series data properly
Experiments by McGarvey et al (1984) in recombinant clones corresponding to genes expressed during the late schizont-merozoite stage of P. falciparum development showed that the maturation of the parasite in this stage was associated with the selective activation of a relatively small set of genes
Summary
In the past two decades, there has been an extraordinary commitment to the control and elimination of malaria which has resulted to a significant decrease in global malaria morbidity and mortality (Rao, 2015). In the bid to finding new ideas to deal with the disease, we have witnessed a shift from orthodox independent studies in biochemistry and microbiology to using a more multidisciplinary and robust approach that embraces other fields such as computer science and mathematics. The so called “omics” science has been employed with some measure of success in malaria research (Sarker et al, 2013). Studies in the transcriptome of malaria causative parasites in both human and animal models have revealed the integral role of transcriptional regulation in Plasmodium biology. Taking advantage of the availability of the full genome sequence data of P. falciparum, the parasite’s complex expression patterns through each developmental stage within its respective unique environment have been studied using microarray. Whole transcriptome short-gun techniques (RNA-seq) have been shown to be a more accurate predictor of expression trends than micro arrays (Wang et al, 2009). Storm & Muller (2012)
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