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Sulfurospirillum halorespirans is a bacterium that couples the reductive dehalogenation of chlorinated ethenes to growth. This process is called organohalide respiration (OHR), which can be of importance for bioremediation. Here, we report the complete genome of S. halorespirans, the second one of an organohalide-respiring Epsilonproteobacterium after that of Sulfurospirillum multivorans. With both genomes at hand, we were able to ascertain that the genomic region encoding OHR proteins in Epsilonproteobacteria differs from that found in organohalide-respiring bacteria (OHRB) affiliated to other phyla and that the production of a unique cobamide, norpseudo-B12, might not be limited to the model organism S. multivorans. The OHR region is virtually identical in both organisms with differences only in the gene sequence of the key enzyme of OHR, the PCE reductive dehalogenase (PceA), and in regulatory regions. This is of interest, since the availability of natural, closely related variants opens an avenue to study the poorly understood OHRB, which withstand systematic genetic manipulation so far.

BackgroundPrenatal and early postnatal exposures to environmental factors are considered responsible for the increasing prevalence of allergic diseases. Although there is some evidence for allergy-promoting effects in children due to exposure to plasticizers like phthalates, findings of previous studies are inconsistent and lack mechanistic information.ObjectiveWe investigated the effect of maternal phthalate exposure on asthma development in the subsequent generations and their underlying mechanisms including epigenetic alterations.MethodsPhthalate metabolites were measured within the prospective mother-child cohort LINA and correlated with asthma development in the children. A murine trans-generational asthma model was used to identify involved pathways.ResultsIn LINA maternal urinary concentrations of mono-n-butyl phthalate, a metabolite of butyl benzyl phthalate (BBP), were associated with an increased asthma risk in the children. Using a murine trans-generational asthma model, we demonstrate a direct effect of BBP on asthma severity in the offspring with a persistently increased airway inflammation up to the F2 generation. This disease-promoting effect was mediated by a BBP-induced global DNA hypermethylation in CD4+ T cells of the offspring as treatment with a DNA demethylating agent alleviated exacerbation of allergic airway inflammation. 13 transcriptionally down-regulated genes linked to promoter or enhancer hypermethylation were identified. Among these, the GATA-3 repressor Zfpm1 emerged as a potential mediator of the enhanced susceptibility for Th2-driven allergic asthma.ConclusionThese data provide strong evidence that maternal BBP exposure increases the risk for allergic airway inflammation in the offspring by modulating the expression of genes involved in Th2 differentiation via epigenetic alterations.

Interleukin-6 (IL-6)-activated Signal Transducer and Activator of Transcription 3 (STAT3) facilitates survival in the multiple myeloma cell line INA-6 and therefore represents an oncogenic key player. However, the biological mechanisms are still not fully understood. In previous studies we identified microRNA-21 as a STAT3 target gene with strong anti-apoptotic potential, suggesting that noncoding RNAs have an impact on the pathogenesis of human multiple myeloma. Here, we describe five long noncoding RNAs (lncRNAs) induced by IL-6-activated STAT3, which we named STAiRs. While STAiRs 1, 2 and 6 remain unprocessed in the nucleus and show myeloma-specific expression, STAiRs 15 and 18 are spliced and broadly expressed. Especially STAiR2 and STAiR18 are promising candidates. STAiR2 originates from the first intron of a tumor suppressor gene. Our data support a mutually exclusive expression of either STAiR2 or the functional tumor suppressor in INA-6 cells and thus a contribution of STAiR2 to tumorigenesis. Furthermore, STAiR18 was shown to be overexpressed in every tested tumor entity, indicating its global role in tumor pathogenesis. Taken together, our study reveals a number of STAT3-induced lncRNAs suggesting that the interplay between the coding and noncoding worlds represents a fundamental principle of STAT3-driven cancer development in multiple myeloma and beyond.

Pseudoalteromonas phage vB_PspS-H40/1 is a lytic phage that infects Pseudoalteromonas sp. strain H40. Both, the phage and its host were isolated in the 1970s from seawater samples collected from the North Sea near the island of Helgoland, Germany. The phage particle has an icosahedral capsid with a diameterof ~43 to 45 nm and a long non-contractile tail of ~68 nm in length, a typical morphology for members of the Siphoviridae family. The linear dsDNA genome of Pseudoalteromonas phage vB_PspS-H40/1 has a sequence length of 45,306 bp and a GC content of 40.6%. The genome has a modular structure and contains a high proportion of sequence information for hypothetical proteins, typically seen in phagegenome sequences. This is the first report of the complete genome sequence of this lytic phage, which has been frequently used since the 1990s as biological tracer in hydrogeological transport studies.

The exposome encompasses an individual's exposure to exogenous chemicals, as well as endogenous chemicals that are produced or altered in response to external stressors. While the exposome concept has been established for human health, its principles can be extended to include broader ecological issues. The assessment of exposure is tightly interlinked with hazard assessment. Here, we explore if mechanistic understanding of the causal links between exposure and adverse effects on human health and the environment can be improved by integrating the exposome approach with the adverse outcome pathway (AOP) concept that structures and organizes the sequence of biological events from an initial molecular interaction of a chemical with a biological target to an adverse outcome. Complementing exposome research with the AOP concept may facilitate a mechanistic understanding of stress-induced adverse effects, examine the relative contributions from various components of the exposome, determine the primary risk drivers in complex mixtures, and promote an integrative assessment of chemical risks for both human and environmental health.

The European Centre for the Ecotoxicology and Toxicology of Chemicals (ECETOC) organised a workshop to discuss the state-of-the-art research on noncoding RNAs (ncRNAs) as biomarkers in regulatory toxicology and as analytical and therapeutic agents. There was agreement that ncRNA expression profiling data requires careful evaluation to determine the utility of specific ncRNAs as biomarkers. To advance the use of ncRNA in regulatory toxicology, the following research priorities were identified: (1) Conduct comprehensive literature reviews to identify possibly suitable ncRNAs and areas of toxicology where ncRNA expression profiling could address prevailing scientific deficiencies. (2) Develop consensus on how to conduct ncRNA expression profiling in a toxicological context. (3) Conduct experimental projects, including, e.g., rat (90-day) oral toxicity studies, to evaluate the toxicological relevance of the expression profiles of selected ncRNAs. Thereby, physiological ncRNA expression profiles should be established, including the biological variability of healthy individuals. To substantiate the relevance of key ncRNAs for cell homeostasis or pathogenesis, molecular events should be dose-dependently linked with substance-induced apical effects. Applying a holistic approach, knowledge on ncRNAs, ‘omics and epigenetics technologies should be integrated into adverse outcome pathways to improve the understanding of the functional roles of ncRNAs within a regulatory context.

Genetics of gene expression (eQTLs or expression QTLs) has proved an indispensable tool for understanding biological pathways and pathomechanisms of trait associated SNPs. However, power of most genome-wide eQTL studies is still limited. We performed a large eQTL study in peripheral blood mononuclear cells of 2,112 individuals increasing the power to detect trans-effects genome-wide. Going beyond univariate SNP-transcript associations, we analyse relations of eQTLs to biological pathways, polygenetic effects of expression regulation, trans-clusters, and enrichment of co-localised functional elements. We found eQTLs for about 85% of analysed genes, 18% of genes were trans-regulated. Local eSNPs were enriched up to a distance of 5 Mb to the transcript challenging typically implemented ranges of cis-regulations. Pathway enrichment within regulated genes of GWAS-related eSNPs supported functional relevance of identified eQTLs. We demonstrate that nearest genes of GWAS-SNPs might frequently be misleading functional candidates. We identified novel trans-clusters of potential functional relevance for GWAS-SNPs of several phenotypes including obesity-related traits, HDL-cholesterol levels, and haematological phenotypes. We used chromatin immunoprecipitation data for demonstrating biological effects. Yet, we show for strongly heritable transcripts that still little trans-chromosomal heritability is explained by all identified trans-eSNPs, however, our data suggests that most cis-heritability of these transcripts seems explained. Dissection of co-localised functional elements indicated a prominent role of SNPs in loci of pseudogenes and non-coding RNAs for the regulation of coding genes. In summary, our study substantially increases the catalogue of human eQTLs and improves our understanding of the complex genetic regulation of gene-expression, pathways and disease-related processes.

The T helper cell subsets Th1, Th2, Th17, and Treg play an important role in immune cell homeostasis, in host defense, and in immunological disorders. Recently, much attention has been paid to Th17 cells which seem to play an important role in the early phase of the adoptive immune response and autoimmune disease. When generating Th17 cells under in vitro conditions the amount of IL-17A producing cells hardly exceeds 20% while the nature of the remaining T cells is poorly characterized. As engagement of the aryl hydrocarbon receptor (AHR) has also been postulated to modulate the differentiation of T helper cells into Th17 cells with regard to the IL-17A expression we ask how far do Th17 polarizing conditions in combination with ligand induced AHR activation have an effect on the production of other T helper cell cytokines. We found that a high proportion of T helper cells cultured under Th17 polarizing conditions are IL-8 and IL-9 single producing cells and that AHR activation results in an upregulation of IL-8 and a downregulation of IL-9 production. Thus, we have identified IL-8 and IL-9 producing T helper cells which are subject to regulation by the engagement of the AHR.

Microarrays are widely used in gene expression studies, and custom expression microarrays are popularto monitor expression changes of a customer-defined set of genes. However, the complexity of transcriptomesuncovered recently make custom expression microarray design a non-trivial task. Pervasivetranscription and alternative processing of transcripts generate a wealth of interweaved transcripts thatrequires well-considered probe design strategies and is largely neglected in existing approaches.We developed the web server CEM-Designer that facilitates microarray platform independent designof custom expression microarrays for complex transcriptomes. CEM-Designer covers (i) the collectionand generation of a set of unique target sequences from different sources and (ii) the selection of a set ofsensitive and specific probes that optimally represents the target sequences. Probe design itself is left tothird party software to ensure that probes meet provider-specific constraints.CEM-Designer is available at http://designpipeline.bioinf.uni-leipzig.de.

Eulimnogammarus verrucosus is an amphipod endemic to the unique ecosystem of Lake Baikal and serves as an emerging model in ecotoxicological studies. We report here on a survey sequencing of its genome as a first step to establish sequence resources for this species. From a single lane of paired-end sequencing data, we estimated the genome size as nearly 10 Gb and we obtained an overview of the repeat content. At least two-thirds of the genome are non-unique DNA, and a third of the genomic DNA is composed of just five families of repetitive elements, including low-complexity sequences. Attempts to use off-the-shelf assembly tools failed on the available low-coverage data both before and after removal of highly repetitive components. Using a seed-based approach we nevertheless assembled short contigs covering 33 pre-microRNAs and the homeodomain-containing exon of nine Hox genes. The absence of clear evidence for paralogs implies that a genome duplication did not contribute to the large genome size. We furthermore report the assembly of the mitochondrial genome using a new, guided “crystallization” procedure. The initial results presented here set the stage for a more complete sequencing and analysis of this large genome.

Background The genome is pervasively transcribed but most transcripts do not code for proteins, constituting non-protein coding RNAs. Despite increasing numbers of functional reports of individual long noncoding RNAs (lncRNAs), assessing the extent of functionality among the non-coding transcriptional output of mammalian cells remains intricate. In the protein coding world, transcripts differentially expressed in the context of processes essential for the survival of multicellular organisms have been instrumental for the discovery of functionally relevant proteins and their deregulation is frequently associated with diseases. We therefore systematically identify lncRNAs expressed differentially in response to oncologically relevant processes, cell-cycle, p53-, and STAT3 pathway, using tiling arrays. Results We find that up to 80% of the pathway-triggered transcriptional response can be non-coding. Among these we identify very large macroRNAs with pathway-specific expression patterns and demonstrate that these are likely continuous transcripts. MacroRNAs contain elements conserved in mammals and sauropsids, which in part exhibit conserved RNA secondary structure. Comparing evolutionary rates of a macroRNA to adjacent protein coding genes suggests a local action of the transcript. Finally, in different grades of astrocytoma, a tumor disease unrelated to the initially used cell lines, macroRNAs are differentially expressed. Conclusions It has been shown previously that the majority of expressed non-ribosomal transcripts are non-coding. We now conclude that differential expression triggered by signaling pathways gives rise to a similar abundance of non-coding content. It is thus unlikely that the prevalence of non-coding transcripts in the cell is a trivial consequence of leaky or random transcription events.

Numerous high-throughput sequencing studies have focused on detecting conventionally spliced mRNAs in RNA-seq data. However, non-standard RNAs arising through gene fusion, circularization or trans-splicing are often neglected. We introduce a novel, unbiased algorithm to detect splice junctions from single-end cDNA sequences. In contrast to other methods, our approach accommodates multi-junction structures. Our method compares favorably with competing tools for conventionally spliced mRNAs and, with a gain of up to 40% of recall, systematically outperforms them on reads with multiple splits, trans-splicing and circular products. The algorithm is integrated into our mapping tool segemehl (http://www.bioinf.uni-leipzig.de/Software/segemehl/).

With the advent of high throughput and high dimensional metabolomics data the question of the appropriate interpretationand integration with other omics data became pivotal. Here we focus on the human model system since it is the best characterized model system and thereby can be seen as a benchmark for the direction of developments for other species. In addition the basics on which the selection and the mode how metabolomics data can be combined with other omics data are reviewed. Genome, transcriptome and proteome data are discussed in respect to their inherent characteristics in terms of measurement, data features, coverage and their relatedness to metabolome data. Due to its recently gained importance we also review the specific features of serum metabolomics. On the metabolome side we discuss the emerging relevance of flux and the often neglected tight interconnectedness of small molecules with signaling pathways. The contribution of metabolome data to integrated pathway analyses is so far based on either only the combination, intrinsic correlation or detection of overrepresentation. In order to overcome the shortcomings of these approaches data interpretation should be performed by making use of a detailed pathway topology. This functional integration is crucial for the intended comprehensive phenotyping and demands for specific precautionary means of data assessment and data evaluation.

With B30 000 deaths annually in the United States, prostate cancer (PCa) is a major oncologic disease. Here we show that the microRNAs miR-130a, miR-203 and miR-205 jointly interfere with the two major oncogenic pathways in prostate carcinoma and are downregulated in cancer tissue. Using transcriptomics we show that the microRNAs repress several gene products known to be overexpressed in this cancer. Argonaute 2 (AGO2) co-immunoprecipitation, reporter assays and western blot analysis demonstrate that the microRNAs directly target several components of the mitogen-activated protein kinase (MAPK) and androgen receptor (AR) signaling pathways, among those several AR coregulators and HRAS (Harvey rat sarcoma viral oncogene homolog), and repress signaling activity. Both pathways are central for the development of the primary tumor and in particular the progression to its incurable castration-resistant form. Reconstitution of the microRNAs in LNCaP PCa cells induce morphological changes, which resemble the effect of androgen deprivation, and jointly impair tumor cell growth by induction of apoptosis and cell cycle arrest. We therefore propose that these microRNAs jointly act as tumor suppressors in prostate carcinoma and might interfere with progression to castration resistance.

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Motivation: Tiling arrays have been a mainstay of unbiased genome-wide transcriptomics over the last decade. Currently available approaches to identify expressed or differentially expressed segments in tiling array data are limited in the recovery of the underlying gene structures and require several parameters that are intensity-related or partly dataset-specific. Results: We have developed TileShuffle, a statistical approach that identifies transcribed and differentially expressed segments as significant differences from the background distribution while considering sequence-specific affinity biases and cross-hybridization. It avoids dataset-specific parameters in order to provide better comparability of different tiling array datasets, based on different technologies or array designs. TileShuffle detects highly and differentially expressed segments in biological data with significantly lower false discovery rates under equal sensitivities than commonly used methods. Also, it is clearly superior in the recovery of exon–intron structures. It further provides window z-scores as a normalized and robust measure for visual inspection.

Currently used clinico-pathological parameters are insufficient for a reliable prediction of metastatic risk and disease-free survival (DFS) of patients with clear-cell renal cell carcinoma (ccRCC). To identify prognostic genes, the expression profiles of primary ccRCC obtained from patients with different DFS — eight synchronously, nine metachronously, and seven not metastasized tumors — were determined by genome-wide expression analyses. Synchronously and metachronously metastasized primary ccRCC differed in the expression of 167 genes. Thirty-six of these genes were also differentially expressed in synchronously vs. metachronously developed pulmonary metastases analyzed in a previous study. Due to their DFS-associated deregulation that is concordant in metastases and primary ccRCC these genes are potentially functionally involved in metastatic tumor growth and are also prognostically useful.A prognostic impact was confirmed for the genes CD31, EDNRB, and TSPAN7 at the mRNA level (n=86), and for TSPAN7 at the protein level (n=106). Patients with a higher gene expression of EDNRB or TSPAN7, or with TSPAN7-positive vessels in both cores investigated on tissue microarrays had a significantly longer DFS and tumor-specific survival (TSS). Patients with a higher CD31 gene expression showed a significantly longer TSS. EDNRB was an independent prognostic marker for the DFS. CD31, EDNRB, and TSPAN7 had an independent impact on the TSS.In summary, comparative analysis of primary tumors and metastases is appropriate to identify independent prognostic markers in ccRCC. Gene expression of CD31 and EDNRB, and endothelial TSPAN7 protein level are potentially useful to improve outcome prediction due to their independent prognostic impact.

Rapid improvements in high-throughput experimental technologies make it nowadays possible to study the expression, as well as changes in expression, of whole transcriptomes under different environmental conditions in a detailed view. We describe current approaches to identify genome-wide functional RNA transcripts (experimentally as well as computationally), and focus on computational methods that may be utilized to disclose their function. While genome databases offer a wealth of information about known and putative functions for protein-coding genes, functional information for novel non-coding RNA genes is almost nonexistent. This is mainly explained by the lack of established software tools to efficiently reveal the function and evolutionary origin of non-coding RNA genes. Here, we describe in detail computational approaches one may follow to annotate and classify an RNA transcript.

Motivation: Long non-coding RNAs (lncRNAs) resemble protein-coding mRNAs but do not encode proteins. Most lncRNAs are under lower sequence constraints than protein-coding genes and lack conserved secondary structures, making it hard to predict them computationally. Results: We introduce an approach to predict spliced lncRNAs in vertebrate genomes combining comparative genomics and machine learning. It is based on detecting signatures of characteristic splice site evolution in vertebrate whole genome alignments. First, we predict individual splice sites, then assemble compatible sites into exon candidates, and finally predict multi-exon transcripts. Using a novel method to evaluate typical splice site substitution patterns that explicitly takes the species phylogeny into account, we show that individual splice sites can be accurately predicted. Since our approach relies only on predicted splice sites, it can uncover both coding and non-coding exons. We show that our predicted exons and partial transcripts are mostly non-coding and lack conserved secondary structures. These exons are of particular interest, since existing computational approaches cannot detect them. Transcriptome sequencing data indicate tissue-specific expression patterns of predicted exons and there is evidence that increasing sequencing depth and breadth will validate additional predictions. We also found a significant enrichment of predicted exons that form multi-exon transcript parts, and we experimentally validate such a novel multi-exon gene. Overall, we obtain 336 novel multi-exon transcript predictions from human intergenic regions. Our results indicate the existence of novel human transcripts that are conserved in evolution and our approach contributes to the completion of the human transcript catalog.

We report the generation and analysis of functional data from multiple, diverse experiments performed on a targeted 1% of the human genome as part of the pilot phase of the ENCODE Project. These data have been further integrated and augmented by a number of evolutionary and computational analyses. Together, our results advance the collective knowledge about human genome function in several major areas. First, our studies provide convincing evidence that the genome is pervasively transcribed, such that the majority of its bases can be found in primary transcripts, including non-protein-coding transcripts, and those that extensively overlap one another. Second, systematic examination of transcriptional regulation has yielded new understanding about transcription start sites, including their relationship to specific regulatory sequences and features of chromatin accessibility and histone modification. Third, a more sophisticated view of chromatin structure has emerged, including its inter-relationship with DNA replication and transcriptional regulation. Finally, integration of these new sources of information, in particular with respect to mammalian evolution based on inter- and intra-species sequence comparisons, has yielded new mechanistic and evolutionary insights concerning the functional landscape of the human genome. Together, these studies are defining a path for pursuit of a more comprehensive characterization of human genome function.

Recent experimental and computational studies have provided overwhelming evidence for a plethora of diverse transcripts that are unrelated to protein-coding genes. One subclass consists of those RNAs that require distinctive secondary structure motifs to exert their biological function and hence exhibit distinctive patterns of sequence conservation characteristic for positive selection on RNA secondary structure. The deep-sequencing of 12 drosophilid species coordinated by the NHGRI provides an ideal data set of comparative computational approaches to determine those genomic loci that code for evolutionarily conserved RNA motifs. This class of loci includes the majority of the known small ncRNAs as well as structured RNA motifs in mRNAs. We report here on a genome-wide survey using RNAz.

Udgivelsesdato: 2007-Jun, Functional RNA structures play an important role both in the context of noncoding RNA transcripts as well as regulatory elements in mRNAs. Here we present a computational study to detect functional RNA structures within the ENCODE regions of the human genome. Since structural RNAs in general lack characteristic signals in primary sequence, comparative approaches evaluating evolutionary conservation of structures are most promising. We have used three recently introduced programs based on either phylogenetic-stochastic context-free grammar (EvoFold) or energy directed folding (RNAz and AlifoldZ), yielding several thousand candidate structures (corresponding to approximately 2.7% of the ENCODE regions). EvoFold has its highest sensitivity in highly conserved and relatively AU-rich regions, while RNAz favors slightly GC-rich regions, resulting in a relatively small overlap between methods. Comparison with the GENCODE annotation points to functional RNAs in all genomic contexts, with a slightly increased density in 3'-UTRs. While we estimate a significant false discovery rate of approximately 50%-70% many of the predictions can be further substantiated by additional criteria: 248 loci are predicted by both RNAz and EvoFold, and an additional 239 RNAz or EvoFold predictions are supported by the (more stringent) AlifoldZ algorithm. Five hundred seventy RNAz structure predictions fall into regions that show signs of selection pressure also on the sequence level (i.e., conserved elements). More than 700 predictions overlap with noncoding transcripts detected by oligonucleotide tiling arrays. One hundred seventy-five selected candidates were tested by RT-PCR in six tissues, and expression could be verified in 43 cases (24.6%).