218 research outputs found

    'Next-generation' sequencing becomes 'now-generation'

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    A report on the Advances in Genome Biology & Technology conference, Marco Island, USA, 2-5 February 2011

    Probing Plasmodium falciparum sexual commitment at the single-cell level

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    Background: Malaria parasites go through major transitions during their complex life cycle, yet the underlying differentiation pathways remain obscure. Here we apply single cell transcriptomics to unravel the program inducing sexual differentiation in Plasmodium falciparum. Parasites have to make this essential life-cycle decision in preparation for human-to-mosquito transmission. Methods: By combining transcriptional profiling with quantitative imaging and genetics, we defined a transcriptional signature in sexually committed cells. Results: We found this transcriptional signature to be distinct from general changes in parasite metabolism that can be observed in response to commitment-inducing conditions. Conclusions: This proof-of-concept study provides a template to capture transcriptional diversity in parasite populations containing complex mixtures of different life-cycle stages and developmental programs, with important implications for our understanding of parasite biology and the ongoing malaria elimination campaign

    Complex selection on 5' splice sites in intron-rich organisms

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    In contrast to the typically streamlined genomes of prokaryotes, many eukaryotic genomes are riddled with long intergenic regions, spliceosomal introns, and repetitive elements. What explains the persistence of these and other seemingly suboptimal structures? There are three general hypotheses: (1) the structures in question are not actually suboptimal but optimal, being favored by selection, for unknown reasons; (2) the structures are not suboptimal, but of (essentially) equal fitness to 'optimal' ones; or (3) the structures are truly suboptimal, but selection is too weak to systematically eliminate them. The 5' splice sites of introns offer a rare opportunity to directly test these hypotheses. Intron-poor species show a clear consensus splice site; most introns begin with the same six nucleotide sequence (typically GTAAGT or GTATGT), indicating efficient selection for this consensus sequence. In contrast, intron-rich species have much less pronounced boundary consensus sequences, and only small minorities of introns in intron-rich species share the same boundary sequence. We studied rates of evolutionary change of 5' splice sites in three groups of closely related intron-rich species--three primates, five Drosophila species, and four Cryptococcus fungi. Surprisingly, the results indicate that changes from consensus-to-variant nucleotides are generally disfavored by selection, but that changes from variant to consensus are neither favored nor disfavored. This evolutionary pattern is consistent with selective differences across introns, for instance, due to compensatory changes at other sites within the gene, which compensate for the otherwise suboptimal consensus-to-variant changes in splice boundaries

    A genomic and evolutionary approach reveals non-genetic drug resistance in malaria

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    Background: Drug resistance remains a major public health challenge for malaria treatment and eradication. Individual loci associated with drug resistance to many antimalarials have been identified, but their epistasis with other resistance mechanisms has not yet been elucidated. Results: We previously described two mutations in the cytoplasmic prolyl-tRNA synthetase (cPRS) gene that confer resistance to halofuginone. We describe here the evolutionary trajectory of halofuginone resistance of two independent drug resistance selections in Plasmodium falciparum. Using this novel methodology, we discover an unexpected non-genetic drug resistance mechanism that P. falciparum utilizes before genetic modification of the cPRS. P. falciparum first upregulates its proline amino acid homeostasis in response to halofuginone pressure. We show that this non-genetic adaptation to halofuginone is not likely mediated by differential RNA expression and precedes mutation or amplification of the cPRS gene. By tracking the evolution of the two drug resistance selections with whole genome sequencing, we further demonstrate that the cPRS locus accounts for the majority of genetic adaptation to halofuginone in P. falciparum. We further validate that copy-number variations at the cPRS locus also contribute to halofuginone resistance. Conclusions: We provide a three-step model for multi-locus evolution of halofuginone drug resistance in P. falciparum. Informed by genomic approaches, our results provide the first comprehensive view of the evolutionary trajectory malaria parasites take to achieve drug resistance. Our understanding of the multiple genetic and non-genetic mechanisms of drug resistance informs how we will design and pair future anti-malarials for clinical use. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0511-2) contains supplementary material, which is available to authorized users

    The Evolution of the Anopheles 16 Genomes Project

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    We report the imminent completion of a set of reference genome assemblies for 16 species of Anopheles mosquitoes. In addition to providing a generally useful resource for comparative genomic analyses, these genome sequences will greatly facilitate exploration of the capacity exhibited by some Anopheline mosquito species to serve as vectors for malaria parasites. A community analysis project will commence soon to perform a thorough comparative genomic investigation of these newly sequenced genomes. Completion of this project via the use of short next-generation sequence reads required innovation in both the bioinformatic and laboratory realms, and the resulting knowledge gained could prove useful for genome sequencing projects targeting other unconventional genomes

    COIL: a methodology for evaluating malarial complexity of infection using likelihood from single nucleotide polymorphism data.

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    International audienceComplex malaria infections are defined as those containing more than one genetically distinct lineage of Plasmodium parasite. Complexity of infection (COI) is a useful parameter to estimate from patient blood samples because it is associated with clinical outcome, epidemiology and disease transmission rate. This manuscript describes a method for estimating COI using likelihood, called COIL, from a panel of bi-allelic genotyping assays. COIL assumes that distinct parasite lineages in complex infections are unrelated and that genotyped loci do not exhibit significant linkage disequilibrium. Using the population minor allele frequency (MAF) of the genotyped loci, COIL uses the binomial distribution to estimate the likelihood of a COI level given the prevalence of observed monomorphic or polymorphic genotypes within each sample. COIL reliably estimates COI up to a level of three or five with at least 24 or 96 unlinked genotyped loci, respectively, as determined by in silico simulation and empirical validation. Evaluation of COI levels greater than five in patient samples may require a very large collection of genotype data, making sequencing a more cost-effective approach for evaluating COI under conditions when disease transmission is extremely high. Performance of the method is positively correlated with the MAF of the genotyped loci. COI estimates from existing SNP genotype datasets create a more detailed portrait of disease than analyses based simply on the number of polymorphic genotypes observed within samples. The capacity to reliably estimate COI from a genome-wide panel of SNP genotypes provides a potentially more accurate alternative to methods relying on PCR amplification of a small number of loci for estimating COI. This approach will also increase the number of applications of SNP genotype data, providing additional motivation to employ SNP barcodes for studies of disease epidemiology or control measure efficacy. The COIL program is available for download from GitHub, and users may also upload their SNP genotype data to a web interface for simple and efficient determination of sample COI
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