Functional genomics of Plasmodium falciparum through transposon-mediated mutagenesis

Plasmodium falciparum is the causative agent for the most lethal form of human malaria, killing millions annually. Genetic analyses of P. falciparum have been relatively limited due to the lack of robust techniques to manipulate this parasite. Development of transfection technologies and whole genome analyses have helped in understanding the complex biology of this parasite. Even with this wealth of information functional genomics approaches are still very limited in P. falciparum due to the cumbersome and inefficient methods of genetic manipulation. This review focuses on a recently developed, highly efficient method for transposon-based mutagenesis and transgene expression in P. falciparum that will allow functional genomics studies to be performed proficiently on this deadly malaria parasite. By using a piggyBac-based transposition system, multiple random integrations have been obtained into the genome of the parasite. This technique could hence be employed to set up several biological screens in this lethal protozoan parasite that may lead to identification of novel drug targets and vaccine candidates.     

The conserved genome organisation of non-falciparum malaria species: the need to know more

The current knowledge on genomes of non-falciparum malaria species and the potential of model malaria parasites for functional analyses are reviewed and compared with those of the most pathogenic human parasite, Plasmodium falciparum. There are remarkable similarities in overall genome composition among the different species at the level of chromosome organisation and chromosome number, conserved order of individual genes, and even conserved functions of specific gene domains and regulatory control elements. With the initiative taken to sequence the genome of P. falciparum, a wealth of information is already becoming available to the scientific community. In order to exploit the biological information content of a complete genome sequence, simple storage of the bulk of sequence data will be inadequate. The requirement for functional analyses to determine the biological role of the open reading frames is commonly accepted and knowledge of the genomes of the animal model malaria species will facilitate these analyses. Detailed comparative genome information and sequencing of additional Plasmodium genomes will provide a deeper insight into the evolutionary history of the species, the biology of the parasite, and its interactions with the mammalian host and mosquito vector. Therefore, an extended and integrated approach will enhance our knowledge of malaria and will ultimately lead to a more rational approach that identifies and evaluates new targets for anti-malarial drug and vaccine development.     

PlasmoDB: the Plasmodium genome resource. A database integrating experimental and computational data

PlasmoDB (http://PlasmoDB.org) is the official database of the Plasmodium falciparum genome sequencing consortium. This resource incorporates the recently completed P. falciparum genome sequence and annotation, as well as draft sequence and annotation emerging from other Plasmodium sequencing projects. PlasmoDB currently houses information from five parasite species and provides tools for intra- and inter-species comparisons. Sequence information is integrated with other genomic-scale data emerging from the Plasmodium research community, including gene expression analysis from EST, SAGE and microarray projects and proteomics studies. The relational schema used to build PlasmoDB, GUS (Genomics Unified Schema) employs a highly structured format to accommodate the diverse data types generated by sequence and expression projects. A variety of tools allow researchers to formulate complex, biologically-based, queries of the database. A stand-alone version of the database is also available on CD-ROM (P. falciparum GenePlot), facilitating access to the data in situations where internet access is difficult (e.g. by malaria researchers working in the field). The goal of PlasmoDB is to facilitate utilization of the vast quantities of genomic-scale data produced by the global malaria research community. The software used to develop PlasmoDB has been used to create a second Apicomplexan parasite genome database, ToxoDB (http://ToxoDB.org).     

Defining endogenous barcoding sites for CRISPR/Cas9-based cell lineage tracing in zebrafish

There is a growing interest in developing experimental methods for tracking the developmental cell lineages of a complex organism.The recently developed CRISPR/Cas9-based barcoding method is,although highly promising,difficult to scale up because it relies on exogenous barcoding sequences that are engineered into the genome.In this study,we characterized 78 high-quality endogenous sites in the zebrafish genome that can be used as CRISPR/Cas9-based barcoding sites.The 78 sites are all highly expressed in most of the cell types according to single-cell RNA sequencing(scRNA-seq)data.Hence,the barcoding information of the 78 endogenous sites is recovered by the available scRNA-seq platforms,enabling simultaneous characterization of cell type and cell lineage information.     

Conditioned genome reconstruction: how to avoid choosing the conditioning genome

Genome phylogenies can be inferred from data on the presence and absence of genes across taxa. Logdet distances may be a good method, because they allow expected genome size to vary across the tree. Recently, Lake and Rivera proposed conditioned genome reconstruction (calculation of logdet distances using only those genes present in a conditioning genome) to deal with unobservable genes that are absent from every taxon of interest. We prove that their method can consistently estimate the topology for almost any choice of conditioning genome. Nevertheless, the choice of conditioning genome is important for small samples. For real bacterial genome data, different choices of conditioning genome can result in strong bootstrap support for different tree topologies. To overcome this problem, we developed supertree methods that combine information from all choices of conditioning genome. One of these methods, based on the BIONJ algorithm, performs well on simulated data and may have applications to other supertree problems. However, an analysis of 40 bacterial genomes using this method supports an incorrect clade of parasites. This is a common feature of model-based gene content methods and is due to parallel gene loss.     

Detecting strong positive selection in the genome

New statistical tests have been developed in the past decade that enable us to infer evidence of recent strong positive selection from genome-wide data on single-nucleotide polymorphism and to localize the targets of selection in the genome. Based on these tests, past demographic events that led to distortions of the site-frequency spectrum of variation can be distinguished from selection, in particular if linkage disequilibrium is taken into account. These methods have been successfully applied to species from which complete sequence information and polymorphism data are available, including Drosophila melanogaster, humans, and several plant species. To make full use of the available data, however, the tests that were primarily designed for panmictic populations need to be extended to spatially structured populations.     

Identification of a molecular marker for genotyping human lymphatic filarial nematode parasite Wuchereria bancrofti

In India, Mass Drug Administration is on going towards elimination of lymphatic filariasis in many areas, which might lead to intense selection pressure on the parasite populations and their genetic restructuring. This calls for molecular finger printing of Wuchereria bancrofti parasite populations at national level and monitoring genetic changes in the future. For this purpose a reliable, less expensive, rapid, and reproducible molecular tool is necessary, which is not available for W. bancrofti at this time. We identified robust molecular markers based on the comparison of random amplified polymorphic DNA (RAPD) and amplified fragment length polymorphism (AFLP) profiles and the genetic data generated from parasite populations collected from areas in Northern (Varanasi, Uttar Pradesh state), Southern (Kozhikode, Kerala State) and Central regions (Jagdalpur, Chattisgarh state) of India, where lymphatic filariasis is endemic for many decades. RAPD profiles for these parasite populations were generated using three different primers and the dendrograms constructed using the profiles were all different. In order to identify appropriate RAPD primer(s), we compared the results of RAPD with the fingerprint profile and genetic data obtained by the more reliable AFLP technique, using the parasite populations from the same areas. RAPD marker (OP8) primer produced phylogenetic data almost similar to that of AFLP analysis. The marker was able to reveal variations between the parasite populations collected from Varanasi, Kozhikode, and Jagdalpur. Most importantly, RAPD primer OP8 produced reproducible results, when tested in three different trials. In view of the limited availability of W. bancrofti parasite DNA, along with a lower cost and ease of performance, RAPD appears to be more suitable compared to AFLP at the present juncture, since complete genome information of this parasite is still not available. Thus, RAPD primer OP8 can be a very useful molecular maker for DNA finger printing of W. bancrofti populations at present.     

SAP-A Sequence Mapping and Analyzing Program for Long Sequence Reads Alignment and Accurate Variants Discovery

The third-generation of sequencing technologies produces sequence reads of 1000 bp or more that may contain high polymorphism information. However, most currently available sequence analysis tools are developed specifically for analyzing short sequence reads. While the traditional Smith-Waterman (SW) algorithm can be used to map long sequence reads, its naive implementation is computationally infeasible. We have developed a new Sequence mapping and Analyzing Program (SAP) that implements a modified version of SW to speed up the alignment process. In benchmarks with simulated and real exon sequencing data and a real E. coli genome sequence data generated by the third-generation sequencing technologies, SAP outperforms currently available tools for mapping short and long sequence reads in both speed and proportion of captured reads. In addition, it achieves high accuracy in detecting SNPs and InDels in the simulated data. SAP is available at https://github.com/davidsun/SAP.     

Drug-resistant genotypes and multi-clonality in Plasmodium falciparum analysed by direct genome sequencing from peripheral blood of malaria patients

Naturally acquired blood-stage infections of the malaria parasite Plasmodium falciparum typically harbour multiple haploid clones. The apparent number of clones observed in any single infection depends on the diversity of the polymorphic markers used for the analysis, and the relative abundance of rare clones, which frequently fail to be detected among PCR products derived from numerically dominant clones. However, minority clones are of clinical interest as they may harbour genes conferring drug resistance, leading to enhanced survival after treatment and the possibility of subsequent therapeutic failure. We deployed new generation sequencing to derive genome data for five non-propagated parasite isolates taken directly from 4 different patients treated for clinical malaria in a UK hospital. Analysis of depth of coverage and length of sequence intervals between paired reads identified both previously described and novel gene deletions and amplifications. Full-length sequence data was extracted for 6 loci considered to be under selection by antimalarial drugs, and both known and previously unknown amino acid substitutions were identified. Full mitochondrial genomes were extracted from the sequencing data for each isolate, and these are compared against a panel of polymorphic sites derived from published or unpublished but publicly available data. Finally, genome-wide analysis of clone multiplicity was performed, and the number of infecting parasite clones estimated for each isolate. Each patient harboured at least 3 clones of P. falciparum by this analysis, consistent with results obtained with conventional PCR analysis of polymorphic merozoite antigen loci. We conclude that genome sequencing of peripheral blood P. falciparum taken directly from malaria patients provides high quality data useful for drug resistance studies, genomic structural analyses and population genetics, and also robustly represents clonal multiplicity.     

A database for cell signaling networks.

We developed a data and knowledge base for cellular signal transduction in human cells, to make this rapidly growing information available. The database includes all the biological properties of cellular signal transduction, including biological reactions that transfer cellular signals and molecular attributes characterized by sequences, structures, and functions. Since the database is based on the object-oriented technique, highly flexible methods of data definition and modification are necessary to handle this diverse and complex biological information. The database includes attractive graphical representations of signaling cascades and the three-dimensional structure of molecules. The database is a novel application of ACEDB, which was the database originally developed to store the C. elegans genome. The database can be accessed through the Internet at http://geo.nihs.go.jp/csndb.html.     

Minimum taxonomic criteria for bacterial genome sequence depositions and announcements

Multiple bioinformatic methods are available to analyse the information encoded within the complete genome sequence of a bacterium and accurately assign its species status or nearest phylogenetic neighbour. However, it is clear that even now in what is the third decade of bacterial genomics, taxonomically incorrect genome sequence depositions are still being made. We outline a simple scheme of bioinformatic analysis and a set of minimum criteria that should be applied to all bacterial genomic data to ensure that they are accurately assigned to the species or genus level prior to database deposition. To illustrate the utility of the bioinformatic workflow, we analysed the recently deposited genome sequence of Lactobacillus acidophilus 30SC and demonstrated that this DNA was in fact derived from a strain of Lactobacillus amylovorus. Using these methods researchers can ensure that the taxonomic accuracy of genome sequence depositions is maintained within the ever increasing nucleic acid datasets.     

RNAi--prospects for a general technique for determining gene function

Gene discovery programs centred around expressed sequence tag (EST) and genome sequencing projects have predictably led to an exponential surge in the number of parasite gene sequences deposited in public databases. To take advantage of this wealth of sequence information, it is essential to develop rapid methods for elucidating the biological function or mode of action of individual genes. Here, Patricia Kuwabara and Alan Coulson discuss the virtues of a powerful epigenetic gene disruption technique, RNA-mediated interference (RNAi), which was originally developed for the nematode Caenorhabditis elegans. It is anticipated that this technique will not only provide insights into gene function, but also help investigators to mine the genome for candidate drug intervention or vaccine development targets, some of which may not be readily apparent on the basis of sequence information alone.     

Bioinformatic tools for DNA/protein sequence analysis, functional assignment of genes and protein classification

The development of efficient DNA sequencing methods has led to the achievement of the DNA sequence of entire genomes from (to date) 55 prokaryotes, 5 eukaryotic organisms and 10 eukaryotic chromosomes. Thus, an enormous amount of DNA sequence data is available and even more will be forthcoming in the near future. Analysis of this overwhelming amount of data requires bioinformatic tools in order to identify genes that encode functional proteins or RNA. This is an important task, considering that even in the well-studied Escherichia coli more than 30% of the identified open reading frames are hypothetical genes. Future challenges of genome sequence analysis will include the understanding of gene regulation and metabolic pathway reconstruction including DNA chip technology, which holds tremendous potential for biomedicine and the biotechnological production of valuable compounds. The overwhelming volume of information often confuses scientists. This review intends to provide a guide to choosing the most efficient way to analyze a new sequence or to collect information on a gene or protein of interest by applying current publicly available databases and Web services. Recently developed tools that allow functional assignment of genes, mainly based on sequence similarity of the deduced amino acid sequence, using the currently available and increasing biological databases will be discussed.     

The KEGG databases at GenomeNet

The Kyoto Encyclopedia of Genes and Genomes (KEGG) is the primary database resource of the Japanese GenomeNet service (http://www.genome.ad.jp/) for understanding higher order functional meanings and utilities of the cell or the organism from its genome information. KEGG consists of the PATHWAY database for the computerized knowledge on molecular interaction networks such as pathways and complexes, the GENES database for the information about genes and proteins generated by genome sequencing projects, and the LIGAND database for the information about chemical compounds and chemical reactions that are relevant to cellular processes. In addition to these three main databases, limited amounts of experimental data for microarray gene expression profiles and yeast two-hybrid systems are stored in the EXPRESSION and BRITE databases, respectively. Furthermore, a new database, named SSDB, is available for exploring the universe of all protein coding genes in the complete genomes and for identifying functional links and ortholog groups. The data objects in the KEGG databases are all represented as graphs and various computational methods are developed to detect graph features that can be related to biological functions. For example, the correlated clusters are graph similarities which can be used to predict a set of genes coding for a pathway or a complex, as summarized in the ortholog group tables, and the cliques in the SSDB graph are used to annotate genes. The KEGG databases are updated daily and made freely available (http://www.genome.ad.jp/kegg/).     

u-Genome: a database on genome design in unicellular genomes

Unicellular eukaryotes were among the first ones to be selected for complete genome sequencing because of the small size of their genomes and their interactions with humans and a broad range of animals and plants. Currently, ten completely sequenced unicellular genome sequences have been publicly released and as the number of available unicellular genomes increases, comparative genomics analysis within this group of organisms becomes more and more instructive. However, such an analysis is difficult to carry out without a suitable platform gathering not only the original annotations but also relevant information available in public databases or obtained by applying common bioinformatics methods. With the aim of solving these difficulties, we have developed a web-accessible database named u-Genome, the unicellular genome design database. The database is unique in featuring three datasets namely (1) orthologous proteins (2) paralogous proteins and (3) statistical distributions on exons, introns, intergenic DNA and correlations between them. A tool, Uniview, designed to visualize the gene structures for individual genes in the genome is also integrated. This database is of importance in understanding unicellular genome design and architecture and evolution related studies. The database is available through a web interface at http://sege.ntu.edu.sg/wester/ugenome.     

Detecting gene-gene interactions using affected sib pair analysis with covariates

Interest has recently focussed on allowing for interactions between loci as a way to increase power to detect linkage. In this paper, a simplified logistic regression method was used to perform affected sib pair analyses allowing for the inclusion of data from other loci. A systematic search of two-locus disease models was carried out to determine the situations in which this was advantageous. If IBD information is available (e.g. from a genome scan), it is unlikely that allowing for interactions will give a large lod score in the absence of linkage evidence from sinlge-locus analysis. Furthermore, allowing for interactions rarely gave a significant increase in power to detect linkage over a single-locus analysis, except for heterogeneity models with low K(P). Conversely, the availability of disease-associated genotypes may greatly increase the power both to detect linkage to a second locus and interaction between the loci. These results indicate that when only IBD information is available, two-locus analysis of genome scan data should be restricted to regions giving peaks under single-locus analysis. If disease-associated genotypes are available, it may be worth re-analysing the whole genome.