A phylogeny-driven genomic encyclopaedia of Bacteria and Archaea.

Sequencing of bacterial and archaeal genomes has revolutionized our understanding of the many roles played by microorganisms. There are now nearly 1,000 completed bacterial and archaeal genomes available, most of which were chosen for sequencing on the basis of their physiology. As a result, the perspective provided by the currently available genomes is limited by a highly biased phylogenetic distribution. To explore the value added by choosing microbial genomes for sequencing on the basis of their evolutionary relationships, we have sequenced and analysed the genomes of 56 culturable species of Bacteria and Archaea selected to maximize phylogenetic coverage. Analysis of these genomes demonstrated pronounced benefits (compared to an equivalent set of genomes randomly selected from the existing database) in diverse areas including the reconstruction of phylogenetic history, the discovery of new protein families and biological properties, and the prediction of functions for known genes from other organisms. Our results strongly support the need for systematic 'phylogenomic' efforts to compile a phylogeny-driven 'Genomic Encyclopedia of Bacteria and Archaea' in order to derive maximum knowledge from existing microbial genome data as well as from genome sequences to come.

Gene rearrangements in hormone receptor negative breast cancers revealed by mate pair sequencing.

BACKGROUND: Chromosomal rearrangements in the form of deletions, insertions, inversions and translocations are frequently observed in breast cancer genomes, and a subset of these rearrangements may play a crucial role in tumorigenesis. To identify novel somatic chromosomal rearrangements, we determined the genome structures of 15 hormone-receptor negative breast tumors by long-insert mate pair massively parallel sequencing. RESULTS: We identified and validated 40 somatic structural alterations, including the recurring fusion between genes DDX10 and SKA3 and translocations involving the EPHA5 gene. Other rearrangements were found to affect genes in pathways involved in epigenetic regulation, mitosis and signal transduction, underscoring their potential role in breast tumorigenesis. RNA interference-mediated suppression of five candidate genes (DDX10, SKA3, EPHA5, CLTC and TNIK) led to inhibition of breast cancer cell growth. Moreover, downregulation of DDX10 in breast cancer cells lead to an increased frequency of apoptotic nuclear morphology. CONCLUSIONS: Using whole genome mate pair sequencing and RNA interference assays, we have discovered a number of novel gene rearrangements in breast cancer genomes and identified DDX10, SKA3, EPHA5, CLTC and TNIK as potential cancer genes with impact on the growth and proliferation of breast cancer cells.

GenePRIMP: a gene prediction improvement pipeline for prokaryotic genomes.

We present 'gene prediction improvement pipeline' (GenePRIMP; http://geneprimp.jgi-psf.org/), a computational process that performs evidence-based evaluation of gene models in prokaryotic genomes and reports anomalies including inconsistent start sites, missed genes and split genes. We found that manual curation of gene models using the anomaly reports generated by GenePRIMP improved their quality, and demonstrate the applicability of GenePRIMP in improving finishing quality and comparing different genome-sequencing and annotation technologies.

Genome-wide sequencing for the identification of rearrangements associated with Tourette syndrome and obsessive-compulsive disorder.

BACKGROUND: Tourette Syndrome (TS) is a neuropsychiatric disorder in children characterized by motor and verbal tics. Although several genes have been suggested in the etiology of TS, the genetic mechanisms remain poorly understood. METHODS: Using cytogenetics and FISH analysis, we identified an apparently balanced t(6,22)(q16.2;p13) in a male patient with TS and obsessive-compulsive disorder (OCD). In order to map the breakpoints and to identify additional submicroscopic rearrangements, we performed whole genome mate-pair sequencing and CGH-array analysis on DNA from the proband. RESULTS: Sequence and CGH array analysis revealed a 400 kb deletion located 1.3 Mb telomeric of the chromosome 6q breakpoint, which has not been reported in controls. The deletion affects three genes (GPR63, NDUFA4 and KLHL32) and overlaps a region previously found deleted in a girl with autistic features and speech delay. The proband's mother, also a carrier of the translocation, was diagnosed with OCD and shares the deletion. We also describe a further potentially related rearrangement which, while unmapped in Homo sapiens, was consistent with the chimpanzee genome. CONCLUSIONS: We conclude that genome-wide sequencing at relatively low resolution can be used for the identification of submicroscopic rearrangements. We also show that large rearrangements may escape detection using standard analysis of whole genome sequencing data. Our findings further provide a candidate region for TS and OCD on chromosome 6q16.

Next generation RNA-sequencing in prognostic subsets of chronic lymphocytic leukemia.

Advances in next-generation RNA-sequencing have revealed the complexity of transcriptomes by allowing both coding and noncoding(nc)RNAs to be analyzed. However, limited data exist regarding the whole transcriptional landscape of chronic lymphocytic leukemia(CLL). In this pilot-study, we evaluated RNA-sequencing in CLL by comparing two subsets which carry almost identical or "stereotyped" B-cell receptors with distinct clinical outcome, that is the poor-prognostic subset #1 (n 5 4) and the more favorable-prognostic subset #4(n 5 4). Our analysis revealed that 156 genes (e.g. LPL, WNT9A) and 76 ncRNAs, (e.g. SNORD48, SNORD115) were differentially expressed between the subsets. This technology also enabled us to identify numerous subset-specific splice variants (n 5 406), which were predominantly expressed in subset #1, including a splice-isoform of MSI2 with a novel start exon. A further important application of RNA-sequencing was for mutation detection and revealed 16­30 missense mutations per sample; notably many of these changes were found in genes with a strong potential for involvement in CLL pathogenesis, e.g., ATM and NOTCH2.This study not only demonstrates the effectiveness of RNA-sequencing for identifying mutations, quantifying gene expression and detecting splicing events, but also highlights the potential such global approaches have to significantly advance our understanding of the molecular mechanisms behind CLL development.

Proteome survey reveals modularity of the yeast cell machinery.

Protein complexes are key molecular entities that integrate multiple gene products to perform cellular functions. Here we report the first genome-wide screen for complexes in an organism, budding yeast, using affinity purification and mass spectrometry. Through systematic tagging of open reading frames (ORFs), the majority of complexes were purified several times, suggesting screen saturation. The richness of the data set enabled a de novo characterization of the composition and organization of the cellular machinery. The ensemble of cellular proteins partitions into 491 complexes, of which 257 are novel, that differentially combine with additional attachment proteins or protein modules to enable a diversification of potential functions. Support for this modular organization of the proteome comes from integration with available data on expression, localization, function, evolutionary conservation, protein structure and binary interactions. This study provides the largest collection of physically determined eukaryotic cellular machines so far and a platform for biological data integration and modelling.

Estimating DNA coverage and abundance in metagenomes using a gamma approximation.

MOTIVATION: Shotgun sequencing generates large numbers of short DNA reads from either an isolated organism or, in the case of metagenomics projects, from the aggregate genome of a microbial community. These reads are then assembled based on overlapping sequences into larger, contiguous sequences (contigs). The feasibility of assembly and the coverage achieved (reads per nucleotide or distinct sequence of nucleotides) depend on several factors: the number of reads sequenced, the read length and the relative abundances of their source genomes in the microbial community. A low coverage suggests that most of the genomic DNA in the sample has not been sequenced, but it is often difficult to estimate either the extent of the uncaptured diversity or the amount of additional sequencing that would be most efficacious. In this work, we regard a metagenome as a population of DNA fragments (bins), each of which may be covered by one or more reads. We employ a gamma distribution to model this bin population due to its flexibility and ease of use. When a gamma approximation can be found that adequately fits the data, we may estimate the number of bins that were not sequenced and that could potentially be revealed by additional sequencing. We evaluated the performance of this model using simulated metagenomes and demonstrate its applicability on three recent metagenomic datasets. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Integration of phenotypic metadata and protein similarity in Archaea using a spectral bipartitioning approach.

In order to simplify and meaningfully categorize large sets of protein sequence data, it is commonplace to cluster proteins based on the similarity of those sequences. However, it quickly becomes clear that the sequence flexibility allowed a given protein varies significantly among different protein families. The degree to which sequences are conserved not only differs for each protein family, but also is affected by the phylogenetic divergence of the source organisms. Clustering techniques that use similarity thresholds for protein families do not always allow for these variations and thus cannot be confidently used for applications such as automated annotation and phylogenetic profiling. In this work, we applied a spectral bipartitioning technique to all proteins from 53 archaeal genomes. Comparisons between different taxonomic levels allowed us to study the effects of phylogenetic distances on cluster structure. Likewise, by associating functional annotations and phenotypic metadata with each protein, we could compare our protein similarity clusters with both protein function and associated phenotype. Our clusters can be analyzed graphically and interactively online.

OnTheFly: a tool for automated document-based text annotation, data linking and network generation.

UNLABELLED: OnTheFly is a web-based application that applies biological named entity recognition to enrich Microsoft Office, PDF and plain text documents. The input files are converted into the HTML format and then sent to the Reflect tagging server, which highlights biological entity names like genes, proteins and chemicals, and attaches to them JavaScript code to invoke a summary pop-up window. The window provides an overview of relevant information about the entity, such as a protein description, the domain composition, a link to the 3D structure and links to other relevant online resources. OnTheFly is also able to extract the bioentities mentioned in a set of files and to produce a graphical representation of the networks of the known and predicted associations of these entities by retrieving the information from the STITCH database. AVAILABILITY: http://onthefly.embl.de, http://onthefly.embl.de/FAQ.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

jClust: a clustering and visualization toolbox.

UNLABELLED: jClust is a user-friendly application which provides access to a set of widely used clustering and clique finding algorithms. The toolbox allows a range of filtering procedures to be applied and is combined with an advanced implementation of the Medusa interactive visualization module. These implemented algorithms are k-Means, Affinity propagation, Bron-Kerbosch, MULIC, Restricted neighborhood search cluster algorithm, Markov clustering and Spectral clustering, while the supported filtering procedures are haircut, outside-inside, best neighbors and density control operations. The combination of a simple input file format, a set of clustering and filtering algorithms linked together with the visualization tool provides a powerful tool for data analysis and information extraction. AVAILABILITY: http://jclust.embl.de/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The complete genome sequence of Staphylothermus marinus reveals differences in sulfur metabolism among heterotrophic Crenarchaeota.

BACKGROUND: Staphylothermus marinus is an anaerobic, sulfur-reducing peptide fermenter of the archaeal phylum Crenarchaeota. It is the third heterotrophic, obligate sulfur reducing crenarchaeote to be sequenced and provides an opportunity for comparative analysis of the three genomes. RESULTS: The 1.57 Mbp genome of the hyperthermophilic crenarchaeote Staphylothermus marinus has been completely sequenced. The main energy generating pathways likely involve 2-oxoacid:ferredoxin oxidoreductases and ADP-forming acetyl-CoA synthases. S. marinus possesses several enzymes not present in other crenarchaeotes including a sodium ion-translocating decarboxylase likely to be involved in amino acid degradation. S. marinus lacks sulfur-reducing enzymes present in the other two sulfur-reducing crenarchaeotes that have been sequenced -- Thermofilum pendens and Hyperthermus butylicus. Instead it has three operons similar to the mbh and mbx operons of Pyrococcus furiosus, which may play a role in sulfur reduction and/or hydrogen production. The two marine organisms, S. marinus and H. butylicus, possess more sodium-dependent transporters than T. pendens and use symporters for potassium uptake while T. pendens uses an ATP-dependent potassium transporter. T. pendens has adapted to a nutrient-rich environment while H. butylicus is adapted to a nutrient-poor environment, and S. marinus lies between these two extremes. CONCLUSION: The three heterotrophic sulfur-reducing crenarchaeotes have adapted to their habitats, terrestrial vs. marine, via their transporter content, and they have also adapted to environments with differing levels of nutrients. Despite the fact that they all use sulfur as an electron acceptor, they are likely to have different pathways for sulfur reduction.

Annotation of metagenome short reads using proxygenes.

MOTIVATION: A typical metagenome dataset generated using a 454 pyrosequencing platform consists of short reads sampled from the collective genome of a microbial community. The amount of sequence in such datasets is usually insufficient for assembly, and traditional gene prediction cannot be applied to unassembled short reads. As a result, analysis of such datasets usually involves comparisons in terms of relative abundances of various protein families. The latter requires assignment of individual reads to protein families, which is hindered by the fact that short reads contain only a fragment, usually small, of a protein. RESULTS: We have considered the assignment of pyrosequencing reads to protein families directly using RPS-BLAST against COG and Pfam databases and indirectly via proxygenes that are identified using BLASTx searches against protein sequence databases. Using simulated metagenome datasets as benchmarks, we show that the proxygene method is more accurate than the direct assignment. We introduce a clustering method which significantly reduces the size of a metagenome dataset while maintaining a faithful representation of its functional and taxonomic content.

Identification of tightly regulated groups of genes during Drosophila melanogaster embryogenesis.

Time-series analysis of whole-genome expression data during Drosophila melanogaster development indicates that up to 86% of its genes change their relative transcript level during embryogenesis. By applying conservative filtering criteria and requiring 'sharp' transcript changes, we identified 1534 maternal genes, 792 transient zygotic genes, and 1053 genes whose transcript levels increase during embryogenesis. Each of these three categories is dominated by groups of genes where all transcript levels increase and/or decrease at similar times, suggesting a common mode of regulation. For example, 34% of the transiently expressed genes fall into three groups, with increased transcript levels between 2.5-12, 11-20, and 15-20 h of development, respectively. We highlight common and distinctive functional features of these expression groups and identify a coupling between downregulation of transcript levels and targeted protein degradation. By mapping the groups to the protein network, we also predict and experimentally confirm new functional associations.

Systematic association of genes to phenotypes by genome and literature mining.

One of the major challenges of functional genomics is to unravel the connection between genotype and phenotype. So far no global analysis has attempted to explore those connections in the light of the large phenotypic variability seen in nature. Here, we use an unsupervised, systematic approach for associating genes and phenotypic characteristics that combines literature mining with comparative genome analysis. We first mine the MEDLINE literature database for terms that reflect phenotypic similarities of species. Subsequently we predict the likely genomic determinants: genes specifically present in the respective genomes. In a global analysis involving 92 prokaryotic genomes we retrieve 323 clusters containing a total of 2,700 significant gene-phenotype associations. Some clusters contain mostly known relationships, such as genes involved in motility or plant degradation, often with additional hypothetical proteins associated with those phenotypes. Other clusters comprise unexpected associations; for example, a group of terms related to food and spoilage is linked to genes predicted to be involved in bacterial food poisoning. Among the clusters, we observe an enrichment of pathogenicity-related associations, suggesting that the approach reveals many novel genes likely to play a role in infectious diseases.

STRING: known and predicted protein-protein associations, integrated and transferred across organisms.

A full description of a protein's function requires knowledge of all partner proteins with which it specifically associates. From a functional perspective, 'association' can mean direct physical binding, but can also mean indirect interaction such as participation in the same metabolic pathway or cellular process. Currently, information about protein association is scattered over a wide variety of resources and model organisms. STRING aims to simplify access to this information by providing a comprehensive, yet quality-controlled collection of protein-protein associations for a large number of organisms. The associations are derived from high-throughput experimental data, from the mining of databases and literature, and from predictions based on genomic context analysis. STRING integrates and ranks these associations by benchmarking them against a common reference set, and presents evidence in a consistent and intuitive web interface. Importantly, the associations are extended beyond the organism in which they were originally described, by automatic transfer to orthologous protein pairs in other organisms, where applicable. STRING currently holds 730,000 proteins in 180 fully sequenced organisms, and is available at http://string.embl.de/.

Genome-wide profiling of genetic synthetic lethality identifies CDK12 as a novel determinant of PARP1/2 inhibitor sensitivity.

Small-molecule inhibitors of PARP1/2, such as olaparib, have been proposed to serve as a synthetic lethal therapy for cancers that harbor BRCA1 or BRCA2 mutations. Indeed, in clinical trials, PARP1/2 inhibitors elicit sustained antitumor responses in patients with germline BRCA gene mutations. In hypothesizing that additional genetic determinants might direct use of these drugs, we conducted a genome-wide synthetic lethal screen for candidate olaparib sensitivity genes. In support of this hypothesis, the set of identified genes included known determinants of olaparib sensitivity, such as BRCA1, RAD51, and Fanconi's anemia susceptibility genes. In addition, the set included genes implicated in established networks of DNA repair, DNA cohesion, and chromatin remodeling, none of which were known previously to confer sensitivity to PARP1/2 inhibition. Notably, integration of the list of candidate sensitivity genes with data from tumor DNA sequencing studies identified CDK12 deficiency as a clinically relevant biomarker of PARP1/2 inhibitor sensitivity. In models of high-grade serous ovarian cancer (HGS-OVCa), CDK12 attenuation was sufficient to confer sensitivity to PARP1/2 inhibition, suppression of DNA repair via homologous recombination, and reduced expression of BRCA1. As one of only nine genes known to be significantly mutated in HGS-OVCa, CDK12 has properties that should confirm interest in its use as a biomarker, particularly in ongoing clinical trials of PARP1/2 inhibitors and other agents that trigger replication fork arrest.

Sequence based analysis of U-2973, a cell line established from a double-hit B-cell lymphoma with concurrent MYC and BCL2 rearrangements.

BACKGROUND: Double-hit lymphoma is a complex and highly aggressive sub-type of B-cell lymphoma, which has recently been classified and is an area of active research interest due to the poor prognosis for patients with this disease. It is characterized by the presence of both an activating MYC chromosomal translocation and a simultaneous additional oncogenic translocation, often of the BCL2 gene. Recently, a cell line was established from a patient with this complex lymphoma and analyzed using conventional tools revealing it contains both MYC and BCL2 translocation events. FINDINGS: In this work, we reanalyzed the genome of the cell line using next generation whole genome sequencing technology in order to catalogue translocations, insertions and deletions which may contribute to the pathology of this lymphoma type. CONCLUSIONS: We describe the cell line in much greater detail, and pinpoint the exact locations of the chromosomal breakpoints. We also find several rearrangements within cancer-associated genes, which were not found using conventional tools, suggesting that high throughput sequencing may reveal novel targets for therapy, which could be used concurrently with existing treatments.

Medusa: A tool for exploring and clustering biological networks.

BACKGROUND: Biological processes such as metabolic pathways, gene regulation or protein-protein interactions are often represented as graphs in systems biology. The understanding of such networks, their analysis, and their visualization are today important challenges in life sciences. While a great variety of visualization tools that try to address most of these challenges already exists, only few of them succeed to bridge the gap between visualization and network analysis. FINDINGS: Medusa is a powerful tool for visualization and clustering analysis of large-scale biological networks. It is highly interactive and it supports weighted and unweighted multi-edged directed and undirected graphs. It combines a variety of layouts and clustering methods for comprehensive views and advanced data analysis. Its main purpose is to integrate visualization and analysis of heterogeneous data from different sources into a single network. CONCLUSIONS: Medusa provides a concise visual tool, which is helpful for network analysis and interpretation. Medusa is offered both as a standalone application and as an applet written in Java. It can be found at: https://sites.google.com/site/medusa3visualization.

Novel insights into the diversity of catabolic metabolism from ten haloarchaeal genomes.

BACKGROUND: The extremely halophilic archaea are present worldwide in saline environments and have important biotechnological applications. Ten complete genomes of haloarchaea are now available, providing an opportunity for comparative analysis. METHODOLOGY/PRINCIPAL FINDINGS: We report here the comparative analysis of five newly sequenced haloarchaeal genomes with five previously published ones. Whole genome trees based on protein sequences provide strong support for deep relationships between the ten organisms. Using a soft clustering approach, we identified 887 protein clusters present in all halophiles. Of these core clusters, 112 are not found in any other archaea and therefore constitute the haloarchaeal signature. Four of the halophiles were isolated from water, and four were isolated from soil or sediment. Although there are few habitat-specific clusters, the soil/sediment halophiles tend to have greater capacity for polysaccharide degradation, siderophore synthesis, and cell wall modification. Halorhabdus utahensis and Haloterrigena turkmenica encode over forty glycosyl hydrolases each, and may be capable of breaking down naturally occurring complex carbohydrates. H. utahensis is specialized for growth on carbohydrates and has few amino acid degradation pathways. It uses the non-oxidative pentose phosphate pathway instead of the oxidative pathway, giving it more flexibility in the metabolism of pentoses. CONCLUSIONS: These new genomes expand our understanding of haloarchaeal catabolic pathways, providing a basis for further experimental analysis, especially with regard to carbohydrate metabolism. Halophilic glycosyl hydrolases for use in biofuel production are more likely to be found in halophiles isolated from soil or sediment.