Evidence of a Large Novel Gene Pool Associated with Prokaryotic Genomic Islands

Microbial genes that are “novel” (no detectable homologs in other species) have become of increasing interest as environmental sampling suggests that there are many more such novel genes in yet-to-be-cultured microorganisms. By analyzing known microbial genomic islands and prophages, we developed criteria for systematic identification of putative genomic islands (clusters of genes of probable horizontal origin in a prokaryotic genome) in 63 prokaryotic genomes, and then characterized the distribution of novel genes and other features. All but a few of the genomes examined contained significantly higher proportions of novel genes in their predicted genomic islands compared with the rest of their genome (Paired t test = 4.43E-14 to 1.27E-18, depending on method). Moreover, the reverse observation (i.e., higher proportions of novel genes outside of islands) never reached statistical significance in any organism examined. We show that this higher proportion of novel genes in predicted genomic islands is not due to less accurate gene prediction in genomic island regions, but likely reflects a genuine increase in novel genes in these regions for both bacteria and archaea. This represents the first comprehensive analysis of novel genes in prokaryotic genomic islands and provides clues regarding the origin of novel genes. Our collective results imply that there are different gene pools associated with recently horizontally transmitted genomic regions versus regions that are primarily vertically inherited. Moreover, there are more novel genes within the gene pool associated with genomic islands. Since genomic islands are frequently associated with a particular microbial adaptation, such as antibiotic resistance, pathogen virulence, or metal resistance, this suggests that microbes may have access to a larger “arsenal” of novel genes for adaptation than previously thought

Comparative transcriptome analysis of Arabidopsis thaliana infested by diamond back moth (Plutella xylostella) larvae reveals signatures of stress response, secondary metabolism, and signalling

Background: Plants are exposed to attack from a large variety of herbivores. Feeding insects can induce substantial changes of the host plant transcriptome. Arabidopsis thaliana has been established as a relevant system for the discovery of genes associated with response to herbivory, including genes for specialized (i.e. secondary) metabolism as well as genes involved in plant-insect defence signalling. Results Using a 70-mer oligonulceotide microarray covering 26,090 gene-specific elements, we monitored changes of the Arabidopsis leaf transcriptome in response to feeding by diamond back moth (DBM; Plutella xylostella) larvae. Analysis of samples from a time course of one hour to 24 hours following onset of DBM feeding revealed almost three thousand (2,881) array elements (including 2,671 genes with AGI annotations) that were differentially expressed (>2-fold; p[t-test] < 0.05) of which 1,686 also changed more than twofold in expression between at least two time points of the time course with p(ANOVA) < 0.05. While the majority of these transcripts were up-regulated within 8 h upon onset of insect feeding relative to untreated controls, cluster analysis identified several distinct temporal patterns of transcriptome changes. Many of the DBM-induced genes fall into ontology groups annotated as stress response, secondary metabolism and signalling. Among DBM-induced genes associated with plant signal molecules or phytohormones, genes associated with octadecanoid signalling were clearly overrepresented. We identified a substantial number of differentially expressed genes associated with signal transduction in response to DBM feeding, and we compared there expression profiles with those of previously reported transcriptome responses induced by other insect herbivores, specifically Pieris rapae, Frankliniella occidentalis, Bemisia tabaci,Myzus persicae, and Brevicoryne brassicae. Conclusion Arabidopsis responds to feeding DBM larvae with a drastic reprogramming of the transcriptome, which has considerable overlap with the response induced by other insect herbivores. Based on a meta-analysis of microarray data we identified groups of transcription factors that are either affected by multiple forms of biotic or abiotic stress including DBM feeding or, alternatively, were responsive to DBM herbivory but not to most other forms of stress.Botany, Department ofForest Sciences, Department ofForestry, Faculty ofScience, Faculty ofStatistics, Department ofReviewedFacult

Comparative transcriptome analysis of <it>Arabidopsis thaliana </it>infested by diamond back moth (<it>Plutella xylostella</it>) larvae reveals signatures of stress response, secondary metabolism, and signalling

Abstract Background Plants are exposed to attack from a large variety of herbivores. Feeding insects can induce substantial changes of the host plant transcriptome. Arabidopsis thaliana has been established as a relevant system for the discovery of genes associated with response to herbivory, including genes for specialized (i.e. secondary) metabolism as well as genes involved in plant-insect defence signalling. Results Using a 70-mer oligonulceotide microarray covering 26,090 gene-specific elements, we monitored changes of the Arabidopsis leaf transcriptome in response to feeding by diamond back moth (DBM; Plutella xylostella) larvae. Analysis of samples from a time course of one hour to 24 hours following onset of DBM feeding revealed almost three thousand (2,881) array elements (including 2,671 genes with AGI annotations) that were differentially expressed (>2-fold; p[t-test] Pieris rapae, Frankliniella occidentalis, Bemisia tabaci,Myzus persicae, and Brevicoryne brassicae. Conclusion Arabidopsis responds to feeding DBM larvae with a drastic reprogramming of the transcriptome, which has considerable overlap with the response induced by other insect herbivores. Based on a meta-analysis of microarray data we identified groups of transcription factors that are either affected by multiple forms of biotic or abiotic stress including DBM feeding or, alternatively, were responsive to DBM herbivory but not to most other forms of stress.</p

Predictors of the Risk of Mortality in Neurofibromatosis 2

To evaluate clinical and molecular predictors of the risk of mortality in people with neurofibromatosis 2 (NF2), we analyzed the mortality experience of 368 patients from 261 families in the United Kingdom NF2 registry, using the Cox proportional-hazards model and the jackknife method. Age at diagnosis, intracranial meningiomas, and type of treatment center were informative predictors of the risk of mortality. In Cox models, the relative risk of mortality increased 1.13-fold per year decrease in age at diagnosis (95% confidence interval [CI] 1.08–1.18) and was 2.51-fold greater in people with meningiomas compared with those without meningiomas (95% CI 1.38–4.57). The relative risk of mortality in patients treated at specialty centers was 0.34 compared with those treated at nonspecialty centers (95% CI 0.12–0.98). In a separate model, the relative risk of mortality in people with constitutional NF2 missense mutations was very low compared with those with other types of mutations (nonsense or frameshift mutations, splice-site mutations, and large deletions), but the CI could not be well quantified because there was only one death among people with missense mutations. We conclude that age at diagnosis, the strongest single predictor of the risk of mortality, is a useful index for patient counseling and clinical management (as are intracranial meningiomas). To ensure optimal care, we recommend that people with NF2 be referred to specialty treatment centers

Proportion of Novel Genes in Genomic Islands (Red Bars) versus the Rest of the Genome (Blue Bars) according to a COG-Based Analysis

<p>Proportions of novel genes are calculated as a percentage of all genes within islands or outside of islands, respectively, for each genome (listed on the x axis). A paired <i>t</i> test indicates that significantly more genes in islands versus non-islands do not have a COG classification (<i>p</i> = 1.20E-18). This phenomenon is uniform across prokaryotic lineages and domains. Similar results are also observed if different datasets are analyzed, or different methods for identifying novel genes are used (<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.0010062#pgen-0010062-t003" target="_blank">Table 3</a>).</p

Proportion of Novel Genes in Genomic Islands (Red Bars) versus the Rest of the Genome (Blue Bars) according to a SUPERFAMILY-Based Analysis

<p>Proportions of novel genes are calculated as a percentage of all genes within islands or outside of islands, respectively, for each genome (listed on the x axis). A paired <i>t</i> test indicates that significantly higher proportions of genes in islands (red bars) versus outside islands (non-islands; purple bars) do not have a SUPERFAMILY prediction (potential novel genes; <i>p</i> = 4.43E-14).</p

ArrayPipe: a flexible processing pipeline for microarray data

A number of microarray analysis software packages exist already; however, none combines the user-friendly features of a web-based interface with potential ability to analyse multiple arrays at once using flexible analysis steps. The ArrayPipe web server (freely available at www.pathogenomics.ca/arraypipe) allows the automated application of complex analyses to microarray data which can range from single slides to large data sets including replicates and dye-swaps. It handles output from most commonly used quantification software packages for dual-labelled arrays. Application features range from quality assessment of slides through various data visualizations to multi-step analyses including normalization, detection of differentially expressed genes, andcomparison and highlighting of gene lists. A highly customizable action set-up facilitates unrestricted arrangement of functions, which can be stored as action profiles. A unique combination of web-based and command-line functionality enables comfortable configuration of processes that can be repeatedly applied to large data sets in high throughput. The output consists of reports formatted as standard web pages and tab-delimited lists of calculated values that can be inserted into other analysis programs. Additional features, such as web-based spreadsheet functionality, auto-parallelization and password protection make this a powerful tool in microarray research for individuals and large groups alike

Conifer defence against insects: microarray gene expression profiling of Sitka spruce (Picea sitchensis) induced by mechanical wounding or feeding by spruce budworms (Choristoneura occidentalis) or white pine weevils (Pissodes strobi) reveals large

Conifers are resistant to attack from a large number of potential herbivores or pathogens. Previous molecular and biochemical characterization of selected conifer defence systems support a model of multigenic, constitutive and induced defences that act on invading insects via physical, chemical, biochemical or ecological (multitrophic) mechanisms. However, the genomic foundation of the complex defence and resistance mechanisms of conifers is largely unknown. As part of a genomics strategy to characterize inducible defences and possible resistance mechanisms of conifers against insect herbivory, we developed a cDNA microarray building upon a new spruce (Picea spp.) expressed sequence tag resource. This first-generation spruce cDNA microarray contains 9720 cDNA elements representing c. 5500 unique genes. We used this array to monitor gene expression in Sitka spruce (Picea sitchensis) bark in response to herbivory by white pine weevils (Pissodes strobi, Curculionidae) or wounding, and in young shoot tips in response to western spruce budworm (Choristoneura occidentalis, Lepidopterae) feeding. Weevils are stem-boring insects that feed on phloem, while budworms are foliage feeding larvae that consume needles and young shoot tips. Both insect species and wounding treatment caused substantial changes of the host plant transcriptome detected in each case by differential gene expression of several thousand array elements at 1 or 2 d after the onset of treatment. Overall, there was considerable overlap among differentially expressed gene sets from these three stress treatments. Functional classification of the induced transcripts revealed genes with roles in general plant defence, octadecanoid and ethylene signalling, transport, secondary metabolism, and transcriptional regulation. Several genes involved in primary metabolic processes such as photosynthesis were down-regulated upon insect feeding or wounding, fitting with the concept of dynamic resource allocation in plant defence. Refined expression analysis using gene-specific primers and real-time PCR for selected transcripts was in agreement with microarray results for most genes tested. This study provides the first large-scale survey of insect-induced defence transcripts in a gymnosperm and provides a platform for functional investigation of plant-insect interactions in spruce. Induction of spruce genes of octadecanoid and ethylene signalling, terpenoid biosynthesis, and phenolic secondary metabolism are discussed in more detail