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Background The main limitations in the analysis of viral metagenomes are perhaps the high genetic variability and the lack of information in extant databases. To address these issues, several bioinformatic tools have been specifically designed or adapted for metagenomics by improving read assembly and creating more sensitive methods for homology detection. This study compares the performance of different available assemblers and taxonomic annotation software using simulated viral-metagenomic data. Results We simulated two 454 viral metagenomes using genomes from NCBI's RefSeq database based on the list of actual viruses found in previously published metagenomes. Three different assembly strategies, spanning six assemblers, were tested for performance: overlaplayout- consensus algorithms Newbler, Celera and Minimo; de Bruijn graphs algorithms Velvet and MetaVelvet; and read probabilistic model Genovo. The performance of the assemblies was measured by the length of resulting contigs (using N50), the percentage of reads assembled and the overall accuracy when comparing against corresponding reference genomes. Additionally, the number of chimeras per contig and the lowest common ancestor were estimated in order to assess the effect of assembling on taxonomic and functional annotation. The functional classification of the reads was evaluated by counting the reads that correctly matched the functional data previously reported for the original genomes and calculating the number of over-represented functional categories in chimeric contigs. The sensitivity and specificity of tBLASTx, PhymmBL and the k-mer frequencies were measured by accurate predictions when comparing simulated reads against the NCBI Virus genomes RefSeq database. Conclusions Assembling improves functional annotation by increasing accurate assignations and decreasing ambiguous hits between viruses and bacteria. However, the success is limited by the chimeric contigs occurring at all taxonomic levels. The assembler and its parameters should be selected based on the focus of each study. Minimo's non-chimeric contigs and Genovo's long contigs excelled in taxonomy assignation and functional annotation, respectively. tBLASTx stood out as the best approach for taxonomic annotation for virus identification. PhymmBL proved useful in datasets in which no related sequences are present as it uses genomic features that may help identify distant taxa. The k-frequencies underperformed in all viral datasets. [ABSTRACT FROM AUTHOR]

The oral cavity of humans is inhabited by hundreds of bacterial species and some of them have a key role in the development of oral diseases, mainly dental caries and periodontitis. We describe for the first time the metagenome of the human oral cavity under health and diseased conditions, with a focus on supragingival dental plaque and cavities. Direct pyrosequencing of eight samples with different oral-health status produced 1 Gbp of sequence without the biases imposed by PCR or cloning. These data show that cavities are not dominated by Streptococcus mutans (the species originally identified as the ethiological agent of dental caries) but are in fact a complex community formed by tens of bacterial species, in agreement with the view that caries is a polymicrobial disease. The analysis of the reads indicated that the oral cavity is functionally a different environment from the gut, with many functional categories enriched in one of the two environments and depleted in the other. Individuals who had never suffered from dental caries showed an over-representation of several functional categories, like genes for antimicrobial peptides and quorum sensing. In addition, they did not have mutans streptococci but displayed high recruitment of other species. Several isolates belonging to these dominant bacteria in healthy individuals were cultured and shown to inhibit the growth of cariogenic bacteria, suggesting the use of these commensal bacterial strains as probiotics to promote oral health and prevent dental caries. [ABSTRACT FROM AUTHOR]

BRCA1 has been linked to the genetic susceptibility of a majority of familial breast and ovarian cancers. Several lines of evidence indicate that BRCA1 is a tumor suppressor and its expression is downregulated in sporadic breast and ovarian cancer cases. Therefore, the identification of genes involved in the regulation of BRCA1 gene expression might lead to new insights into the pathogenesis and treatment of these tumors. Peroxisome proliferator-activated receptor gamma (PPAR?) is a member of the nuclear receptor superfamily that has well-established roles in the regulation of adipocyte development and glucose homeostasis. More recently, it has been shown that ligands of PPAR? have a potent antitumorigenic activity in breast cancer cells. In the present study we have found that two distinct ligands of PPAR?; 15-deoxy-?-12,14-prostaglandin J2 (15dPG-J2) and rosiglitazone, increase the levels of BRCA1 protein in human MCF-7 breast cancer cells. Immunofluorescence microscopy analysis showed that, after treatment with 15dPG-J2, the BRCA1 protein is mainly localized in the nucleus. Functional analysis by transient transfection of different 5'-flanking region fragments, as well as gel mobility shift assays and mutagenic analysis, suggests that the effects of 15dPG-J2 and rosiglitazone are mediated through a functional DR1 located between the nucleotides -241 and -229, which is a canonical PPAR? type response element. Our data suggest that PPAR? is a crucial gene regulating BRCA1 gene expression and might therefore be important for the BRCA1 regulatory pathway involved in the pathogenesis of sporadic breast and ovarian cancer.Oncogene (2003) 22, 5446-5450. doi:10.1038/sj.onc.1206824 [ABSTRACT FROM AUTHOR]

A correction to an article on genomes of soft-shell and green sea turtles published in a previous issue of the journal is presented.

Lactococcus garvieae is the etiological agent of lactococcosis disease, affecting many cultured fish species worldwide. In addition, this bacterium is currently considered a potential zoonotic microorganism since it is known to cause several opportunistic human infections. Here we present the draft genome sequence of the L. garvieae strain UNIUD074. [ABSTRACT FROM AUTHOR]

The Open Targets Platform (https://www.targetvalidation.org/) provides users with a queryable knowledgebase and user interface to aid systematic target identification and prioritisation for drug discovery based upon underlying evidence. It is publicly available and the underlying code is open source. Since our last update two years ago, we have had 10 releases to maintain and continuously improve evidence for target-disease relationships from 20 different data sources. In addition, we have integrated new evidence from key datasets, including prioritised targets identified from genome-wide CRISPR knockout screens in 300 cancer models (Project Score), and GWAS/UK BioBank statistical genetic analysis evidence from the Open Targets Genetics Portal. We have evolved our evidence scoring framework to improve target identification. To aid the prioritisation of targets and inform on the potential impact of modulating a given target, we have added evaluation of post-marketing adverse drug reactions and new curated information on target tractability and safety. We have also developed the user interface and backend technologies to improve performance and usability. In this article, we describe the latest enhancements to the Platform, to address the fundamental challenge that developing effective and safe drugs is difficult and expensive., (© The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research.)

CRISPR genetic screens in cancer cell models are a powerful tool to elucidate oncogenic mechanisms and to identify promising therapeutic targets. The Project Score database (https://score.depmap.sanger.ac.uk/) uses genome-wide CRISPR-Cas9 dropout screening data in hundreds of highly annotated cancer cell models to identify genes required for cell fitness and prioritize novel oncology targets. The Project Score database currently allows users to investigate the fitness effect of 18 009 genes tested across 323 cancer cell models. Through interactive interfaces, users can investigate data by selecting a specific gene, cancer cell model or tissue type, as well as browsing all gene fitness scores. Additionally, users can identify and rank candidate drug targets based on an established oncology target prioritization pipeline, incorporating genetic biomarkers and clinical datasets for each target, and including suitability for drug development based on pharmaceutical tractability. Data are freely available and downloadable. To enhance analyses, links to other key resources including Open Targets, COSMIC, the Cell Model Passports, UniProt and the Genomics of Drug Sensitivity in Cancer are provided. The Project Score database is a valuable new tool for investigating genetic dependencies in cancer cells and the identification of candidate oncology targets., (© The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research.)

The Ensembl project (http://www.ensembl.org) is a system for genome annotation, analysis, storage and dissemination designed to facilitate the access of genomic annotation from chordates and key model organisms. It provides access to data from 87 species across our main and early access Pre! websites. This year we introduced three newly annotated species and released numerous updates across our supported species with a concentration on data for the latest genome assemblies of human, mouse, zebrafish and rat. We also provided two data updates for the previous human assembly, GRCh37, through a dedicated website (http://grch37.ensembl.org). Our tools, in particular the VEP, have been improved significantly through integration of additional third party data. REST is now capable of larger-scale analysis and our regulatory data BioMart can deliver faster results. The website is now capable of displaying long-range interactions such as those found in cis-regulated datasets. Finally we have launched a website optimized for mobile devices providing views of genes, variants and phenotypes. Our data is made available without restriction and all code is available from our GitHub organization site (http://github.com/Ensembl) under an Apache 2.0 license., (© The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.)

The mammalian radiation has corresponded with rapid changes in noncoding regions of the genome, but we lack a comprehensive understanding of regulatory evolution in mammals. Here, we track the evolution of promoters and enhancers active in liver across 20 mammalian species from six diverse orders by profiling genomic enrichment of H3K27 acetylation and H3K4 trimethylation. We report that rapid evolution of enhancers is a universal feature of mammalian genomes. Most of the recently evolved enhancers arise from ancestral DNA exaptation, rather than lineage-specific expansions of repeat elements. In contrast, almost all liver promoters are partially or fully conserved across these species. Our data further reveal that recently evolved enhancers can be associated with genes under positive selection, demonstrating the power of this approach for annotating regulatory adaptations in genomic sequences. These results provide important insight into the functional genetics underpinning mammalian regulatory evolution., (Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.)

Activation of peroxisome proliferator-activated receptor gamma (PPARgamma) has been found to induce cell death in a variety of cells. In this regard, we reported recently that 15-deoxy-Delta-(12,14)-prostaglandin J2 (15dPG-J2), a specific ligand of the nuclear receptor PPARgamma, inhibits proliferation and induces cellular differentiation and apoptosis in the breast cancer cell line MCF-7. In addition to PPARgamma activation other proteins, such as NF-kappaB and AP1, have been shown to be targets of 15dPG-J2. However, the mechanism by which 15dPG-J2 triggers cell death is still elusive. Our results demonstrate that 15dPG-J2 initiates breast cancer cell death via a very rapid and severe impairment of mitochondrial function, as revealed by a drop in mitochondrial membrane potential (DeltaPsi(m)), generation of reactive oxygen species (ROS) and a decrease in oxygen consumption. In addition, 15dPG-J2 can also activate an intrinsic apoptotic pathway involving phosphatidyl serine externalization, caspase activation and cytochrome c release. Bcl-2 over-expression and zVADfmk, albeit preventing caspase activation, have no effect on 15dPG-J2-mediated mytochondrial dysfunction and loss of cell viability. In contrast, the addition of radical scavengers or rotenone, which prevent 15dPG-J2-induced ROS production, block the loss of cell viability induced by this prostaglandin. Finally, 15dPG-J2-induced cell death appears to involve disruption of the microtubule cytoskeletal network. Together, these results suggest that PG-J2-induced mitochondrial dysfunction and ROS production inevitably leads to death, with or without caspases.