Prediction of alternative isoforms from exon expression levels in RNA-Seq experiments

Alternative splicing, polyadenylation of pre-messenger RNA molecules and differential promoter usage can produce a variety of transcript isoforms whose respective expression levels are regulated in time and space, thus contributing specific biological functions. However, the repertoire of mammalian alternative transcripts and their regulation are still poorly understood. Second-generation sequencing is now opening unprecedented routes to address the analysis of entire transcriptomes. Here, we developed methods that allow the prediction and quantification of alternative isoforms derived solely from exon expression levels in RNA-Seq data. These are based on an explicit statistical model and enable the prediction of alternative isoforms within or between conditions using any known gene annotation, as well as the relative quantification of known transcript structures. Applying these methods to a human RNA-Seq dataset, we validated a significant fraction of the predictions by RT-PCR. Data further showed that these predictions correlated well with information originating from junction reads. A direct comparison with exon arrays indicated improved performances of RNA-Seq over microarrays in the prediction of skipped exons. Altogether, the set of methods presented here comprehensively addresses multiple aspects of alternative isoform analysis. The software is available as an open-source R-package called Solas at http://cmb.molgen.mpg.de/2ndGenerationSequencing/Solas/

Detection and Identification of Genome Editing in Plants: Challenges and Opportunities

Conventional genetic engineering techniques generate modifications in the genome via stable integration of DNA elements which do not occur naturally in this combination. Therefore, the resulting organisms and (most) products thereof can unambiguously be identified with event-specific PCR-based methods targeting the insertion site. New breeding techniques such as genome editing diversify the toolbox to generate genetic variability in plants. Several of these techniques can introduce single nucleotide changes without integrating foreign DNA and thereby generate organisms with intended phenotypes. Consequently, such organisms and products thereof might be indistinguishable from naturally occurring or conventionally bred counterparts with established analytical tools. The modifications can entirely resemble random mutations regardless of being spontaneous or induced chemically or via irradiation. Therefore, if an identification of these organisms or products thereof is demanded, a new challenge will arise for (official) seed, food, and feed testing laboratories and enforcement institutions. For detailed consideration, we distinguish between the detection of sequence alterations – regardless of their origin – the identification of the process that generated a specific modification and the identification of a genotype, i.e., an organism produced by genome editing carrying a specific genetic alteration in a known background. This article briefly reviews the existing and upcoming detection and identification strategies (including the use of bioinformatics and statistical approaches) in particular for plants developed with genome editing techniques

Overview and recommendations for the application of digital PCR

The digital Polymerase Chain Reaction (dPCR), for the detection and absolute quantification of DNA, is a relatively new technique but its application in analytical laboratories is steadily increasing. In contrast to quantitative real-time PCR, DNA (fragments) can be quantified without the need for standard curves. Using dPCR, the PCR mix containing the (target) DNA is partitioned – depending on the device used – currently into a maximum of 10,000,000 small compartments with a volume as low as a few picoliters. These can be either physically distinct compartments on a chip (referred to as chamber-based digital PCR [cdPCR]), or these compartments correspond to water-in-oil droplets (referred to as droplet digital [ddPCR]). Common to both approaches, once PCR has been carried out simultaneously in all compartments/droplets, the number of positive and negative signals for each partition is counted by fluorescence measurement. With this technique, an absolute quantification of DNA copy numbers can be performed with high precision and trueness, even for very low DNA copy numbers. Furthermore, dPCR is considered less susceptible than qPCR to PCR inhibitory substances that can be co-extracted during DNA extraction from different sources. Digital PCR has already been applied in various fields, for example for the detection and quantification of GMOs, species (animals, plants), human diseases, food viruses and bacteria including pathogens. When establishing dPCR in a laboratory, different aspects have to be considered. These include, but are not limited to, the adjustment of the type of the PCR master mix used, optimised primer and probe concentrations and signal separation of positive and negative compartments. This document addresses these and other aspects and provides recommendations for the transfer of existing real-time PCR methods into a dPCR format.JRC.F.5-Food and Feed Complianc

GMO Genetic Elements Thesaurus (GMO-GET) : a controlled vocabulary for the consensus designation of introduced or modified genetic elements in genetically modified organisms

Background: Various databases on genetically modified organisms (GMOs) exist, all with their specific focus to facilitate access to information needed for, e. g., the assistance in risk assessment, the development of detection and identification strategies or inspection and control activities. Each database has its unique approach towards the subject. Often these databases use different terminology to describe the GMOs. For adequate GMO addressing and identification and exchange of GMO-related information it is necessary to use commonly agreed upon concepts and terminology. Result: A hierarchically structured controlled vocabulary describing the genetic elements inserted into conventional GMOs, and GMOs developed by the use of gen(om)e-editing is presented: the GMO genetic element thesaurus (GMO-GET). GMO-GET can be used for GMO-related documentation, including GMO-related databases. It has initially been developed on the basis of two GMO databases, i.e. the Biosafety Clearing-House and the EUginius database. Conclusion: The use of GMO-GET will enable consistent and compatible information (harmonisation), also allowing an accurate exchange of information between the different data systems and thereby facilitating their interoperability. GMO-GET can also be used to describe genetic elements that are altered in organisms obtained through current targeted genome-editing techniques.</p

Interplay of Pneumococcal Hydrogen Peroxide and Host-Derived Nitric Oxide

Reactive oxygen and nitrogen species are released by immune-competent cells and contribute to cellular damage. On the other hand, certain pathogens, including Streptococcus pneumoniae, are known to produce hydrogen peroxide (H(2)O(2)), while production of nitrogen radicals by bacteria presumably occurs but has been poorly studied. We determined the relative contributions of bacterial versus host-derived oxygen and nitrogen radicals to cellular damage in pneumococcal infection. A special focus was placed on peroxynitrite as a hypothetical common product formed by the reaction of H(2)O(2) and NO. In microglial cultures, reduction of the formation of 3-nitrotyrosine and cellular damage required H(2)O(2)-deficient (ΔspxB or ΔcarB) pneumococci and inhibition of host NO synthesis with aminoguanidine. In infected C57BL/6 mice, neuronal loss and immunopositivity for nitrotyrosine in the dentate gyrus were markedly reduced with ΔspxB or ΔcarB bacterial mutants and in inducible nitric oxide synthase knockout mice. We conclude that although host and bacteria both produce oxygen and nitrogen radicals, the interplay of prokaryotic H(2)O(2) and eukaryotic NO is a major contributor to cellular damage in pneumococcal meningitis

Pneumolysin causes neuronal cell death through mitochondrial damage

Bacterial toxins such as pneumolysin are key mediators of cytotoxicity in infections. Pneumolysin is a pore-forming toxin released by Streptococcus pneumoniae, the major cause of bacterial meningitis. We found that pneumolysin is the pneumococcal factor that accounts for the cell death pathways induced by live bacteria in primary neurons. The pore-forming activity of pneumolysin is essential for the induction of mitochondrial damage and apoptosis. Pneumolysin colocalized with mitochondrial membranes, altered the mitochondrial membrane potential, and caused the release of apoptosis-inducing factor and cell death. Pneumolysin induced neuronal apoptosis without activating caspase-1, -3, or -8. Wild-type pneumococci also induced apoptosis without activation of caspase-3, whereas pneumolysin-negative pneumococci activated caspase-3 through the release of bacterial hydrogen peroxide. Pneumolysin caused upregulation of X-chromosome-linked inhibitor of apoptosis protein and inhibited staurosporine-induced caspase activation, suggesting the presence of actively suppressive mechanisms on caspases. In conclusion, our results indicate additional functions of pneumolysin as a mitochondrial toxin and as a determinant of caspase-independent apoptosis. Considering this, blocking of pneumolysin may be a promising cytoprotective strategy in pneumococcal meningitis and other infections

A high-resolution anatomical atlas of the transcriptome in the mouse embryo.

Ascertaining when and where genes are expressed is of crucial importance to understanding or predicting the physiological role of genes and proteins and how they interact to form the complex networks that underlie organ development and function. It is, therefore, crucial to determine on a genome-wide level, the spatio-temporal gene expression profiles at cellular resolution. This information is provided by colorimetric RNA in situ hybridization that can elucidate expression of genes in their native context and does so at cellular resolution. We generated what is to our knowledge the first genome-wide transcriptome atlas by RNA in situ hybridization of an entire mammalian organism, the developing mouse at embryonic day 14.5. This digital transcriptome atlas, the Eurexpress atlas (http://www.eurexpress.org), consists of a searchable database of annotated images that can be interactively viewed. We generated anatomy-based expression profiles for over 18,000 coding genes and over 400 microRNAs. We identified 1,002 tissue-specific genes that are a source of novel tissue-specific markers for 37 different anatomical structures. The quality and the resolution of the data revealed novel molecular domains for several developing structures, such as the telencephalon, a novel organization for the hypothalamus, and insight on the Wnt network involved in renal epithelial differentiation during kidney development. The digital transcriptome atlas is a powerful resource to determine co-expression of genes, to identify cell populations and lineages, and to identify functional associations between genes relevant to development and disease