Plant-RRBS, a bisulfite and next-generation sequencing-based methylome profiling method enriching for coverage of cytosine positions

Background: Cytosine methylation in plant genomes is important for the regulation of gene transcription and transposon activity. Genome-wide methylomes are studied upon mutation of the DNA methyltransferases, adaptation to environmental stresses or during development. However, from basic biology to breeding programs, there is a need to monitor multiple samples to determine transgenerational methylation inheritance or differential cytosine methylation. Methylome data obtained by sodium hydrogen sulfite (bisulfite)-conversion and next-generation sequencing (NGS) provide genome- wide information on cytosine methylation. However, a profiling method that detects cytosine methylation state dispersed over the genome would allow high-throughput analysis of multiple plant samples with distinct epigenetic signatures. We use specific restriction endonucleases to enrich for cytosine coverage in a bisulfite and NGS-based profiling method, which was compared to whole-genome bisulfite sequencing of the same plant material. Methods: We established an effective methylome profiling method in plants, termed plant-reduced representation bisulfite sequencing (plant-RRBS), using optimized double restriction endonuclease digestion, fragment end repair, adapter ligation, followed by bisulfite conversion, PCR amplification and NGS. We report a performant laboratory protocol and a straightforward bioinformatics data analysis pipeline for plant-RRBS, applicable for any reference-sequenced plant species. Results: As a proof of concept, methylome profiling was performed using an Oryza sativa ssp. indica pure breeding line and a derived epigenetically altered line (epiline). Plant-RRBS detects methylation levels at tens of millions of cytosine positions deduced from bisulfite conversion in multiple samples. To evaluate the method, the coverage of cytosine positions, the intra-line similarity and the differential cytosine methylation levels between the pure breeding line and the epiline were determined. Plant-RRBS reproducibly covers commonly up to one fourth of the cytosine positions in the rice genome when using MspI-DpnII within a group of five biological replicates of a line. The method predominantly detects cytosine methylation in putative promoter regions and not-annotated regions in rice. Conclusions: Plant-RRBS offers high-throughput and broad, genome- dispersed methylation detection by effective read number generation obtained from reproducibly covered genome fractions using optimized endonuclease combinations, facilitating comparative analyses of multi-sample studies for cytosine methylation and transgenerational stability in experimental material and plant breeding populations

A molecular insight into algal-oomycete warfare : cDNA analysis of Ectocarpus siliculosus infected with the basal oomycete Eurychasma dicksonii

Peer reviewedPublisher PD

Review of current Severe Accident Management (SAM) approaches for Nuclear Power Plants in Europe

The Fukushima accidents highlighted that both the in-depth understanding of such sequences and the development or improvement of adequate Severe Accident Management (SAM) measures are essential in order to further increase the safety of the nuclear power plants operated in Europe. To support this effort, the CESAM (Code for European Severe Accident Management) R&D project, coordinated by GRS, started in April 2013 for 4 years in the 7th EC Framework Programme of research and development of the European Commission. It gathers 18 partners from 12 countries: IRSN, AREVA NP SAS and EDF (France), GRS, KIT, USTUTT and RUB (Germany), CIEMAT (Spain), ENEA (Italy), VUJE and IVS (Slovakia), LEI (Lithuania), NUBIKI (Hungary), INRNE (Bulgaria), JSI (Slovenia), VTT (Finland), PSI (Switzerland), BARC (India) plus the European Commission Joint Research Center (JRC). The CESAM project focuses on the improvement of the ASTEC (Accident Source Term Evaluation Code) computer code. ASTEC,, jointly developed by IRSN and GRS, is considered as the European reference code since it capitalizes knowledge from the European R&D on the domain. The project aims at its enhancement and extension for use in severe accident management (SAM) analysis of the nuclear power plants (NPP) of Generation II-III presently under operation or foreseen in near future in Europe, spent fuel pools included. In the frame of the CESAM project one of the tasks consisted in the preparation of a report providing an overview of the Severe Accident Management (SAM) approaches in European Nuclear Power Plants to serve as a basis for further ASTEC improvements. This report draws on the experience in several countries from introducing SAMGs and on substantial information that has become available within the EU “stress test”. To disseminate this information to a broader audience, the initial CESAM report has been revised to include only public available information. This work has been done with the agreement and in collaboration with all the CESAM project partners. The result of this work is presented here.JRC.F.5-Nuclear Reactor Safety Assessmen

MetWAMer: eukaryotic translation initiation site prediction

<p>Abstract</p> <p>Background</p> <p>Translation initiation site (TIS) identification is an important aspect of the gene annotation process, requisite for the accurate delineation of protein sequences from transcript data. We have developed the MetWAMer package for TIS prediction in eukaryotic open reading frames of non-viral origin. MetWAMer can be used as a stand-alone, third-party tool for post-processing gene structure annotations generated by external computational programs and/or pipelines, or directly integrated into gene structure prediction software implementations.</p> <p>Results</p> <p>MetWAMer currently implements five distinct methods for TIS prediction, the most accurate of which is a routine that combines weighted, signal-based translation initiation site scores and the contrast in coding potential of sequences flanking TISs using a perceptron. Also, our program implements clustering capabilities through use of the <it>k</it>-medoids algorithm, thereby enabling cluster-specific TIS parameter utilization. In practice, our static weight array matrix-based indexing method for parameter set lookup can be used with good results in data sets exhibiting moderate levels of 5'-complete coverage.</p> <p>Conclusion</p> <p>We demonstrate that improvements in statistically-based models for TIS prediction can be achieved by taking the class of each potential start-methionine into account pending certain testing conditions, and that our perceptron-based model is suitable for the TIS identification task. MetWAMer represents a well-documented, extensible, and freely available software system that can be readily re-trained for differing target applications and/or extended with existing and novel TIS prediction methods, to support further research efforts in this area.</p

ISOL@: an Italian SOLAnaceae genomics resource

BACKGROUND: Present-day '-omics' technologies produce overwhelming amounts of data which include genome sequences, information on gene expression (transcripts and proteins) and on cell metabolic status. These data represent multiple aspects of a biological system and need to be investigated as a whole to shed light on the mechanisms which underpin the system functionality.The gathering and convergence of data generated by high-throughput technologies, the effective integration of different data-sources and the analysis of the information content based on comparative approaches are key methods for meaningful biological interpretations.In the frame of the International Solanaceae Genome Project, we propose here ISOLA, an Italian SOLAnaceae genomics resource. RESULTS: ISOLA (available at http://biosrv.cab.unina.it/isola) represents a trial platform and it is conceived as a multi-level computational environment.ISOLA currently consists of two main levels: the genome and the expression level. The cornerstone of the genome level is represented by the Solanum lycopersicum genome draft sequences generated by the International Tomato Genome Sequencing Consortium. Instead, the basic element of the expression level is the transcriptome information from different Solanaceae species, mainly in the form of species-specific comprehensive collections of Expressed Sequence Tags (ESTs).The cross-talk between the genome and the expression levels is based on data source sharing and on tools that enhance data quality, that extract information content from the levels' under parts and produce value-added biological knowledge. CONCLUSIONS: ISOLA is the result of a bioinformatics effort that addresses the challenges of the post-genomics era. It is designed to exploit '-omics' data based on effective integration to acquire biological knowledge and to approach a systems biology view. Beyond providing experimental biologists with a preliminary annotation of the tomato genome, this effort aims to produce a trial computational environment where different aspects and details are maintained as they are relevant for the analysis of the organization, the functionality and the evolution of the Solanaceae family

A new look at the LTR retrotransposon content of the chicken genome

BACKGROUND: LTR retrotransposons contribute approximately 10 % of the mammalian genome, but it has been previously reported that there is a deficit of these elements in the chicken relative to both mammals and other birds. A novel LTR retrotransposon classification pipeline, LocaTR, was developed and subsequently utilised to re-examine the chicken LTR retrotransposon annotation, and determine if the proposed chicken deficit is biologically accurate or simply a technical artefact. RESULTS: Using LocaTR 3.01 % of the chicken galGal4 genome assembly was annotated as LTR retrotransposon-derived elements (nearly double the previous annotation), including 1,073 that were structurally intact. Element distribution is significantly correlated with chromosome size and is non-random within each chromosome. Elements are significantly depleted within coding regions and enriched in gene sparse areas of the genome. Over 40 % of intact elements are found in clusters, unrelated by age or genera, generally in poorly recombining regions. The transcription of most LTR retrotransposons were suppressed or incomplete, but individual domain and full length retroviral transcripts were produced in some cases, although mostly with regularly interspersed stop codons in all reading frames. Furthermore, RNAseq data from 23 diverse tissues enabled greater characterisation of the co-opted endogenous retrovirus Ovex1. This gene was shown to be expressed ubiquitously but at variable levels across different tissues. LTR retrotransposon content was found to be very variable across the avian lineage and did not correlate with either genome size or phylogenetic position. However, the extent of previous, species-specific LTR retrotransposon annotation appears to be a confounding factor. CONCLUSIONS: Use of the novel LocaTR pipeline has nearly doubled the annotated LTR retrotransposon content of the chicken genome compared to previous estimates. Further analysis has described element distribution, clustering patterns and degree of expression in a variety of adult tissues, as well as in three embryonic stages. This study also enabled better characterisation of the co-opted gamma retroviral envelope gene Ovex1. Additionally, this work suggests that there is no deficit of LTR retrotransposons within the Galliformes relative to other birds, or to mammalian genomes when scaled for the three-fold difference in genome size

An improved microRNA annotation of the canine genome

The domestic dog, Canis familiaris, is a valuable model for studying human diseases. The publication of the latest Canine genome build and annotation, CanFam3.1 provides an opportunity to enhance our understanding of gene regulation across tissues in the dog model system. In this study, we used the latest dog genome assembly and small RNA sequencing data from 9 different dog tissues to predict novel miRNAs in the dog genome, as well as to annotate conserved miRNAs from the miRBase database that were missing from the current dog annotation. We used both miRCat and miRDeep2 algorithms to computationally predict miRNA loci. The resulting, putative hairpin sequences were analysed in order to discard false positives, based on predicted secondary structures and patterns of small RNA read alignments. Results were further divided into high and low confidence miRNAs, using the same criteria. We generated tissue specific expression profiles for the resulting set of 811 loci: 720 conserved miRNAs, (207 of which had not been previously annotated in the dog genome) and 91 novel miRNA loci. Comparative analyses revealed 8 putative homologues of some novel miRNA in ferret, and one in microbat. All miRNAs were also classified into the genic and intergenic categories, based on the Ensembl RefSeq gene annotation for CanFam3.1. This additionally allowed us to identify four previously undescribed MiRtrons among our total set of miRNAs. We additionally annotated piRNAs, using proTRAC on the same input data. We thus identified 263 putative clusters, most of which (211 clusters) were found to be expressed in testis. Our results represent an important improvement of the dog genome annotation, paving the way to further research on the evolution of gene regulation, as well as on the contribution of post-transcriptional regulation to pathological conditions

Comparative genomics of the major parasitic worms

Parasitic nematodes (roundworms) and platyhelminths (flatworms) cause debilitating chronic infections of humans and animals, decimate crop production and are a major impediment to socioeconomic development. Here we report a broad comparative study of 81 genomes of parasitic and non-parasitic worms. We have identified gene family births and hundreds of expanded gene families at key nodes in the phylogeny that are relevant to parasitism. Examples include gene families that modulate host immune responses, enable parasite migration though host tissues or allow the parasite to feed. We reveal extensive lineage-specific differences in core metabolism and protein families historically targeted for drug development. From an in silico screen, we have identified and prioritized new potential drug targets and compounds for testing. This comparative genomics resource provides a much-needed boost for the research community to understand and combat parasitic worms