Kay Nieselt

Pan-Tetris: an interactive visualisation for Pan-genomes

BackgroundLarge-scale genome projects have paved the way to microbial pan-genome analyses. Pan-genomes describe the union of all genes shared by all members of the species or taxon under investigation. They offer a framework to assess the genomic diversity of a given collection of individual genomes and moreover they help to consolidate gene predictions and annotations. The computation of pan-genomes is often a challenge, and many techniques that use a global alignment-independent approach run the risk of not separating paralogs from orthologs. Also alignment-based approaches which take the gene neighbourhood into account often need additional manual curation of the results. This is quite time consuming and so far there is no visualisation tool available that offers an interactive GUI for the pan-genome to support curating pan-genomic computations or annotations of orthologous genes.ResultsWe introduce Pan-Tetris, a Java based interactive software tool that provides a clearly structured and suitable way for the visual inspection of gene occurrences in a pan-genome table. The main features of Pan-Tetris are a standard coordinate based presentation of multiple genomes complemented by easy to use tools compensating for algorithmic weaknesses in the pan-genome generation workflow. We demonstrate an application of Pan-Tetris to the pan-genome of Staphylococcus aureus.ConclusionsPan-Tetris is currently the only interactive pan-genome visualisation tool. Pan-Tetris is available from http://bit.ly/1vVxYZT

Progression-Specific Genes Identified by Expression Profiling of Matched Ductal Carcinomas In situ and Invasive Breast Tumors, Combining Laser Capture Microdissection and Oligonucleotide Microarray Analysis

Becoming invasive is a crucial step in breast cancer oncogenesis. At this point, a lesion carries the potential for spreading and metastasis--a process, whose molecular characteristics still remain poorly understood. In this article, we describe a matched-pair analysis of ductal carcinoma in situ (DCIS) and invasive ductal carcinoma (IDC) of nine breast ductal carcinomas to identify novel molecular markers characterizing the transition from DCIS to IDC. The purpose of this study was to better understand the molecular biology of this transition and to identify candidate genes whose products might serve as prognostic markers and/or as molecular targets for treatment. To obtain cellular-based gene expression profiles from epithelial tumor cells, we combined laser capture microdissection with a T7-based two-round RNA amplification and Affymetrix oligonucleotide microarray analysis. Altogether, a set of 24 tumor samples was analyzed, comprised of nine matched DCIS/IDC and replicate DCIS/IDC preparations from three of the nine tumors. Cluster analysis on expression data shows the robustness and reproducibility of the techniques we established. Using multiple statistical methods, 546 significantly differentially expressed probe sets were identified. Eighteen candidate genes were evaluated by RT-PCR. Examples of genes already known to be associated with breast cancer invasion are BPAG1, LRRC15, MMP11, and PLAU. The expression of BPAG1, DACT1, GREM1, MEF2C, SART2, and TNFAIP6 was localized to epithelial tumor cells by in situ hybridization and/or immunohistochemistry, confirming the accuracy of laser capture microdissection sampling and microarray analysis.

Pre-Columbian mycobacterial genomes reveal seals as a source of New World human tuberculosis

Modern strains of Mycobacterium tuberculosis from the Americas are closely related to those from Europe, supporting the assumption that human tuberculosis was introduced post-contact. This notion, however, is incompatible with archaeological evidence of pre-contact tuberculosis in the New World. Comparative genomics of modern isolates suggests that M. tuberculosis attained its worldwide distribution following human dispersals out of Africa during the Pleistocene epoch, although this has yet to be confirmed with ancient calibration points. Here we present three 1,000-year-old mycobacterial genomes from Peruvian human skeletons, revealing that a member of the M. tuberculosis complex caused human disease before contact. The ancient strains are distinct from known human-adapted forms and are most closely related to those adapted to seals and sea lions. Two independent dating approaches suggest a most recent common ancestor for the M. tuberculosis complex less than 6,000 years ago, which supports a Holocene dispersal of the disease. Our results implicate sea mammals as having played a role in transmitting the disease to humans across the ocean.

Genome-wide comparison of medieval and modern Mycobacterium leprae

Leprosy: Ancient and Modern In medieval Europe, leprosy was greatly feared: Sufferers had to wear bells and were shunned and kept isolated from society. Although leprosy largely disappeared from Europe in the 16th century, elsewhere in the world almost a quarter of a million cases are still reported annually, despite the availability of effective drugs. Schuenemann et al. (p. 179, published online 13 June; see the 14 June News story by Gibbons, p. 1278) probed the origins of leprosy bacilli by using a genomic capture-based approach on DNA obtained from skeletal remains from the 10th to 14th centuries. Because the unique mycolic acids of this mycobacterium protect its DNA, for one Danish sample over 100-fold, coverage of the genome was possible. Sequencing suggests a link between the middle-eastern and medieval European strains, which falls in line with social historical expectations that the returning expeditionary forces of antiquity originally spread the pathogen. Subsequently, Europeans took the bacterium westward to the Americas. Overall, ancient and modern strains remain remarkably similar, with no apparent loss of virulence genes, indicating it was most probably improvements in social conditions that led to leprosys demise in Europe. Five European individuals who lived during the Middle Ages provide a look backward at leprosy. Leprosy was endemic in Europe until the Middle Ages. Using DNA array capture, we have obtained genome sequences of Mycobacterium leprae from skeletons of five medieval leprosy cases from the United Kingdom, Sweden, and Denmark. In one case, the DNA was so well preserved that full de novo assembly of the ancient bacterial genome could be achieved through shotgun sequencing alone. The ancient M. leprae sequences were compared with those of 11 modern strains, representing diverse genotypes and geographic origins. The comparisons revealed remarkable genomic conservation during the past 1000 years, a European origin for leprosy in the Americas, and the presence of an M. leprae genotype in medieval Europe now commonly associated with the Middle East. The exceptional preservation of M. leprae biomarkers, both DNA and mycolic acids, in ancient skeletons has major implications for palaeomicrobiology and human pathogen evolution.

High-Resolution Transcriptome Maps Reveal Strain-Specific Regulatory Features of Multiple Campylobacter jejuni Isolates

Campylobacter jejuni is currently the leading cause of bacterial gastroenteritis in humans. Comparison of multiple Campylobacter strains revealed a high genetic and phenotypic diversity. However, little is known about differences in transcriptome organization, gene expression, and small RNA (sRNA) repertoires. Here we present the first comparative primary transcriptome analysis based on the differential RNA–seq (dRNA–seq) of four C. jejuni isolates. Our approach includes a novel, generic method for the automated annotation of transcriptional start sites (TSS), which allowed us to provide genome-wide promoter maps in the analyzed strains. These global TSS maps are refined through the integration of a SuperGenome approach that allows for a comparative TSS annotation by mapping RNA–seq data of multiple strains into a common coordinate system derived from a whole-genome alignment. Considering the steadily increasing amount of RNA–seq studies, our automated TSS annotation will not only facilitate transcriptome annotation for a wider range of pro- and eukaryotes but can also be adapted for the analysis among different growth or stress conditions. Our comparative dRNA–seq analysis revealed conservation of most TSS, but also single-nucleotide-polymorphisms (SNP) in promoter regions, which lead to strain-specific transcriptional output. Furthermore, we identified strain-specific sRNA repertoires that could contribute to differential gene regulation among strains. In addition, we identified a novel minimal CRISPR-system in Campylobacter of the type-II CRISPR subtype, which relies on the host factor RNase III and a trans-encoded sRNA for maturation of crRNAs. This minimal system of Campylobacter, which seems active in only some strains, employs a unique maturation pathway, since the crRNAs are transcribed from individual promoters in the upstream repeats and thereby minimize the requirements for the maturation machinery. Overall, our study provides new insights into strain-specific transcriptome organization and sRNAs, and reveals genes that could modulate phenotypic variation among strains despite high conservation at the DNA level.

The dynamic architecture of the metabolic switch in Streptomyces coelicolor

BackgroundDuring the lifetime of a fermenter culture, the soil bacterium S. coelicolor undergoes a major metabolic switch from exponential growth to antibiotic production. We have studied gene expression patterns during this switch, using a specifically designed Affymetrix genechip and a high-resolution time-series of fermenter-grown samples.ResultsSurprisingly, we find that the metabolic switch actually consists of multiple finely orchestrated switching events. Strongly coherent clusters of genes show drastic changes in gene expression already many hours before the classically defined transition phase where the switch from primary to secondary metabolism was expected. The main switch in gene expression takes only 2 hours, and changes in antibiotic biosynthesis genes are delayed relative to the metabolic rearrangements. Furthermore, global variation in morphogenesis genes indicates an involvement of cell differentiation pathways in the decision phase leading up to the commitment to antibiotic biosynthesis.ConclusionsOur study provides the first detailed insights into the complex sequence of early regulatory events during and preceding the major metabolic switch in S. coelicolor, which will form the starting point for future attempts at engineering antibiotic production in a biotechnological setting.

Global transcriptional start site mapping using differential RNA sequencing reveals novel antisense RNAs in Escherichia coli.

While the model organism Escherichia coli has been the subject of intense study for decades, the full complement of its RNAs is only now being examined. Here we describe a survey of the E. coli transcriptome carried out using a differential RNA sequencing (dRNA-seq) approach, which can distinguish between primary and processed transcripts, and an automated prediction algorithm for transcriptional start sites (TSS). With the criterion of expression under at least one of three growth conditions examined, we predicted 14,868 TSS candidates, including 5,574 internal to annotated genes (iTSS) and 5,495 TSS corresponding to potential antisense RNAs (asRNAs). We examined expression of 14 candidate asRNAs by Northern analysis using RNA from wild-type E. coli and from strains defective for RNases III and E, two RNases reported to be involved in asRNA processing. Interestingly, nine asRNAs detected as distinct bands by Northern analysis were differentially affected by the rnc and rne mutations. We also compared our asRNA candidates with previously published asRNA annotations from RNA-seq data and discuss the challenges associated with these cross-comparisons. Our global transcriptional start site map represents a valuable resource for identification of transcription start sites, promoters, and novel transcripts in E. coli and is easily accessible, together with the cDNA coverage plots, in an online genome browser.

Mayday - integrative analytics for expression data

BackgroundDNA Microarrays have become the standard method for large scale analyses of gene expression and epigenomics. The increasing complexity and inherent noisiness of the generated data makes visual data exploration ever more important. Fast deployment of new methods as well as a combination of predefined, easy to apply methods with programmers access to the data are important requirements for any analysis framework. Mayday is an open source platform with emphasis on visual data exploration and analysis. Many built-in methods for clustering, machine learning and classification are provided for dissecting complex datasets. Plugins can easily be written to extend Maydays functionality in a large number of ways. As Java program, Mayday is platform-independent and can be used as Java WebStart application without any installation. Mayday can import data from several file formats, database connectivity is included for efficient data organization. Numerous interactive visualization tools, including box plots, profile plots, principal component plots and a heatmap are available, can be enhanced with metadata and exported as publication quality vector files.ResultsWe have rewritten large parts of Maydays core to make it more efficient and ready for future developments. Among the large number of new plugins are an automated processing framework, dynamic filtering, new and efficient clustering methods, a machine learning module and database connectivity. Extensive manual data analysis can be done using an inbuilt R terminal and an integrated SQL querying interface. Our visualization framework has become more powerful, new plot types have been added and existing plots improved.ConclusionsWe present a major extension of Mayday, a very versatile open-source framework for efficient micro array data analysis designed for biologists and bioinformaticians. Most everyday tasks are already covered. The large number of available plugins as well as the extension possibilities using compiled plugins and ad-hoc scripting allow for the rapid adaption of Mayday also to very specialized data exploration. Mayday is available at http://microarray-analysis.org.

Differential gene expression in peripheral blood of patients suffering from post-traumatic stress disorder

Differential gene expression in peripheral blood of patients suffering from post-traumatic stress disorder

Specific transcriptional changes in human fetuses with autosomal trisomies

Among full autosomal trisomies, only trisomies of chromosome 21 (Down syndrome), 18 (Edwards syndrome) and 13 (Patau syndrome) are compatible with postnatal survival. But the mechanisms, how a supernumerary chromosome disrupts the normal development and causes specific phenotypes, are still not fully explained. As an alternative to gene dosage effect due to the trisomic chromosome a genome-wide transcriptional dysregulation has been postulated. The aim of this study was to define the transcriptional changes in trisomy 13, 18, and 21 during early fetal development in order to obtain more insights into the molecular etiopathology of aneuploidy. Using oligonucleotide microarrays, we analyzed whole genome expression profiles in cultured amniocytes (AC) and chorionic villus cells (CV) from pregnancies with a normal karyotype and with trisomies of human chromosomes 13, 18 and 21. We observed a low to moderate up-regulation for a subset of genes of the trisomic chromosomes. Transcriptional levels of most of the genes on the supernumerary chromosome appeared similar to the respective chromosomal pair in normal karyotypes. A subset of chromosome 21 genes including the DSCR1 gene involved in fetal heart development was consistently up-regulated in different prenatal tissues (AC, CV) of trisomy 21 fetuses whereas only minor changes were found for genes of all other chromosomes. In contrast, in trisomy 18 vigorous downstream transcriptional changes were found. Global transcriptome analysis for autosomal trisomies 13, 18, and 21 supported a combination of the two major hypotheses.