525 research outputs found

    CANGS: a user-friendly utility for processing and analyzing 454 GS-FLX data in biodiversity studies

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    <p>Abstract</p> <p>Background</p> <p>Next generation sequencing (NGS) technologies have substantially increased the sequence output while the costs were dramatically reduced. In addition to the use in whole genome sequencing, the 454 GS-FLX platform is becoming a widely used tool for biodiversity surveys based on amplicon sequencing. In order to use NGS for biodiversity surveys, software tools are required, which perform quality control, trimming of the sequence reads, removal of PCR primers, and generation of input files for downstream analyses. A user-friendly software utility that carries out these steps is still lacking.</p> <p>Findings</p> <p>We developed CANGS (<b>C</b>leaning and <b>A</b>nalyzing <b>N</b>ext <b>G</b>eneration <b>S</b>equences) a flexible and user-friendly integrated software utility: CANGS is designed for amplicon based biodiversity surveys using the 454 sequencing platform. CANGS filters low quality sequences, removes PCR primers, filters singletons, identifies barcodes, and generates input files for downstream analyses. The downstream analyses rely either on third party software (e.g.: rarefaction analyses) or CANGS-specific scripts. The latter include modules linking 454 sequences with the name of the closest taxonomic reference retrieved from the NCBI database and the sequence divergence between them. Our software can be easily adapted to handle sequencing projects with different amplicon sizes, primer sequences, and quality thresholds, which makes this software especially useful for non-bioinformaticians.</p> <p>Conclusion</p> <p>CANGS performs PCR primer clipping, filtering of low quality sequences, links sequences to NCBI taxonomy and provides input files for common rarefaction analysis software programs. CANGS is written in Perl and runs on Mac OS X/Linux and is available at <url>http://i122server.vu-wien.ac.at/pop/software.html</url></p

    CANGS DB: a stand-alone web-based database tool for processing, managing and analyzing 454 data in biodiversity studies

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    <p>Abstract</p> <p>Background</p> <p>Next generation sequencing (NGS) is widely used in metagenomic and transcriptomic analyses in biodiversity. The ease of data generation provided by NGS platforms has allowed researchers to perform these analyses on their particular study systems. In particular the 454 platform has become the preferred choice for PCR amplicon based biodiversity surveys because it generates the longest sequence reads. Nevertheless, the handling and organization of massive amounts of sequencing data poses a major problem for the research community, particularly when multiple researchers are involved in data acquisition and analysis. An integrated and user-friendly tool, which performs quality control, read trimming, PCR primer removal, and data organization is desperately needed, therefore, to make data interpretation fast and manageable.</p> <p>Findings</p> <p>We developed CANGS DB (Cleaning and Analyzing Next Generation Sequences DataBase) a flexible, stand alone and user-friendly integrated database tool. CANGS DB is specifically designed to organize and manage the massive amount of sequencing data arising from various NGS projects. CANGS DB also provides an intuitive user interface for sequence trimming and quality control, taxonomy analysis and rarefaction analysis. Our database tool can be easily adapted to handle multiple sequencing projects in parallel with different sample information, amplicon sizes, primer sequences, and quality thresholds, which makes this software especially useful for non-bioinformaticians. Furthermore, CANGS DB is especially suited for projects where multiple users need to access the data. CANGS DB is available at <url>http://code.google.com/p/cangsdb/</url>.</p> <p>Conclusion</p> <p>CANGS DB provides a simple and user-friendly solution to process, store and analyze 454 sequencing data. Being a local database that is accessible through a user-friendly interface, CANGS DB provides the perfect tool for collaborative amplicon based biodiversity surveys without requiring prior bioinformatics skills.</p

    Secondary Evolve and Resequencing : An Experimental Confirmation of Putative Selection Targets without Phenotyping

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    Evolve and resequencing (E&R) studies investigate the genomic responses of adaptation during experimental evolution. Because replicate populations evolve in the same controlled environment, consistent responses to selection across replicates are frequently used to identify reliable candidate regions that underlie adaptation to a new environment. However, recent work demonstrated that selection signatures can be restricted to one or a few replicate(s) only. These selection signatures frequently have weak statistical support, and given the difficulties of functional validation, additional evidence is needed before considering them as candidates for functional analysis. Here, we introduce an experimental procedure to validate candidate loci with weak or replicate-specific selection signature(s). Crossing an evolved population from a primary E&R experiment to the ancestral founder population reduces the frequency of candidate alleles that have reached a high frequency. We hypothesize that genuine selection targets will experience a repeatable frequency increase after the mixing with the ancestral founders if they are exposed to the same environment (secondary E&R experiment). Using this approach, we successfully validate two overlapping selection targets, which showed a mutually exclusive selection signature in a primary E&R experiment of Drosophila simulans adapting to a novel temperature regime. We conclude that secondary E&R experiments provide a reliable confirmation of selection signatures that either are not replicated or show only a low statistical significance in a primary E&R experiment unless epistatic interactions predominate. Such experiments are particularly helpful to prioritize candidate loci for time-consuming functional follow-up investigations.Peer reviewe

    Drosophila Adaptation to Viral Infection through Defensive Symbiont Evolution

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    Microbial symbionts can modulate host interactions with biotic and abiotic factors. Such interactions may affect the evolutionary trajectories of both host and symbiont. Wolbachia protects Drosophila melanogaster against several viral infections and the strength of the protection varies between variants of this endosymbiont. Since Wolbachia is maternally transmitted, its fitness depends on the fitness of its host. Therefore, Wolbachia populations may be under selection when Drosophila is subjected to viral infection. Here we show that in D. melanogaster populations selected for increased survival upon infection with Drosophila C virus there is a strong selection coefficient for specific Wolbachia variants, leading to their fixation. Flies carrying these selected Wolbachia variants have higher survival and fertility upon viral infection when compared to flies with the other variants. These findings demonstrate how the interaction of a host with pathogens shapes the genetic composition of symbiont populations. Furthermore, host adaptation can result from the evolution of its symbionts, with host and symbiont functioning as a single evolutionary unit.Austrian Science Funds grant: (FWF P27630)

    PoPoolation DB: a user-friendly web-based database for the retrieval of natural polymorphisms in Drosophila

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    <p>Abstract</p> <p>Background</p> <p>The enormous potential of natural variation for the functional characterization of genes has been neglected for a long time. Only since recently, functional geneticists are starting to account for natural variation in their analyses. With the new sequencing technologies it has become feasible to collect sequence information for multiple individuals on a genomic scale. In particular sequencing pooled DNA samples has been shown to provide a cost-effective approach for characterizing variation in natural populations. While a range of software tools have been developed for mapping these reads onto a reference genome and extracting SNPs, linking this information to population genetic estimators and functional information still poses a major challenge to many researchers.</p> <p>Results</p> <p>We developed PoPoolation DB a user-friendly integrated database. Popoolation DB links variation in natural populations with functional information, allowing a wide range of researchers to take advantage of population genetic data. PoPoolation DB provides the user with population genetic parameters (Watterson's <it>Ξ </it>or Tajima's <it>π</it>), Tajima's D, SNPs, allele frequencies and indels in regions of interest. The database can be queried by gene name, chromosomal position, or a user-provided query sequence or GTF file. We anticipate that PoPoolation DB will be a highly versatile tool for functional geneticists as well as evolutionary biologists.</p> <p>Conclusions</p> <p>PoPoolation DB, available at <url>http://www.popoolation.at/pgt</url>, provides an integrated platform for researchers to investigate natural polymorphism and associated functional annotations from UCSC and Flybase genome browsers, population genetic estimators and RNA-seq information.</p

    Host range and Specificity of the Drosophila C Virus

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    Background: The Drosophila C virus (DCV) is a common and well-studied Drosophila pathogen. Although natural infections are known from Drosophila melanogaster and D. simulans, and artificial infections have been reported from several. Drosophila species and other insects, it remains unclear to date whether DCV infections also occur naturally in other Drosophila species. Methods/Principal Findings: Using reverse transcription PCR, we detected natural infections in six Drosophila species, which have not been previously known as natural hosts. By subsequent Sanger sequencing we compared DCV haplotypes among eight Drosophila host species. Our data suggest that cross-infections might be frequent both within and among species within the laboratory environment. Moreover, we find that some lines exhibit multiple infections with distinct DCV haplotypes. Conclusions: Our results suggest that the natural host range of DCV is much broader than previously assumed and that cross-infections might be a common phenomenon in the laboratory, even among different Drosophila hosts

    Adaptation of Drosophila to a novel laboratory environment reveals temporally heterogeneous trajectories of selected alleles

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    The genomic basis of adaptation to novel environments is a fundamental problem in evolutionary biology that has gained additional importance in the light of the recent global change discussion. Here, we combined laboratory natural selection (experimental evolution) in Drosophila melanogaster with genome‐wide next generation sequencing of DNA pools (Pool‐Seq) to identify alleles that are favourable in a novel laboratory environment and traced their trajectories during the adaptive process. Already after 15 generations, we identified a pronounced genomic response to selection, with almost 5000 single nucleotide polymorphisms (SNP; genome‐wide false discovery rates < 0.005%) deviating from neutral expectation. Importantly, the evolutionary trajectories of the selected alleles were heterogeneous, with the alleles falling into two distinct classes: (i) alleles that continuously rise in frequency; and (ii) alleles that at first increase rapidly but whose frequencies then reach a plateau. Our data thus suggest that the genomic response to selection can involve a large number of selected SNPs that show unexpectedly complex evolutionary trajectories, possibly due to nonadditive effects

    Genome-wide patterns of latitudinal differentiation among populations of Drosophila melanogaster from North America

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    Understanding the genetic underpinnings of adaptive change is a fundamental but largely unresolved problem in evolutionary biology. Drosophila melanogaster, an ancestrally tropical insect that has spread to temperate regions and become cosmopolitan, offers a powerful opportunity for identifying the molecular polymorphisms underlying clinal adaptation. Here, we use genome‐wide next‐ generation sequencing of DNA pools (‘pool‐seq’) from three populations collected along the North American east coast to examine patterns of latitudinal differentiation. Comparing the genomes of these populations is particularly interesting since they exhibit clinal variation in a number of important life history traits. We find extensive latitudinal differentiation, with many of the most strongly differentiated genes involved in major functional pathways such as the insulin/TOR, ecdysone, torso, EGFR, TGFÎČ/BMP, JAK/STAT, immunity and circadian rhythm pathways. We observe particularly strong differentiation on chromosome 3R, especially within the cosmopolitan inversion In(3R)Payne, which contains a large number of clinally varying genes. While much of the differentiation might be driven by clinal differences in the frequency of In(3R)P, we also identify genes that are likely independent of this inversion. Our results provide genome‐wide evidence consistent with pervasive spatially variable selection acting on numerous loci and pathways along the well‐ known North American cline, with many candidates implicated in life history regulation and exhibiting parallel differentiation along the previously investigated Australian cline
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