Computational and analytical framework for small RNA profiling by high-throughput sequencing

The advent of high-throughput sequencing (HTS) methods has enabled direct approaches to quantitatively profile small RNA populations. However, these methods have been limited by several factors, including representational artifacts and lack of established statistical methods of analysis. Furthermore, massive HTS data sets present new problems related to data processing and mapping to a reference genome. Here, we show that cluster-based sequencing-by-synthesis technology is highly reproducible as a quantitative profiling tool for several classes of small RNA from Arabidopsis thaliana. We introduce the use of synthetic RNA oligoribonucleotide standards to facilitate objective normalization between HTS data sets, and adapt microarray-type methods for statistical analysis of multiple samples. These methods were tested successfully using mutants with small RNA biogenesis (miRNA-defective dcl1 mutant and siRNA-defective dcl2 dcl3 dcl4 triple mutant) or effector protein (ago1 mutant) deficiencies. Computational methods were also developed to rapidly and accurately parse, quantify, and map small RNA data.     

Activity profiling of barley vacuolar processing enzymes provides new insights into the plant and cyst nematode interaction

Vacuolar processing enzymes (VPEs) play an important role during regular growth and development and defence responses. Despite substantial attempts to understand the molecular basis of plant–cyst nematode interaction, the mechanism of VPEs functioning during this interaction remains unknown. The second-stage Heterodera filipjevi juvenile penetrates host roots and induces the formation of a permanent feeding site called a syncytium. To investigate whether infection with H. filipjevi alters plant host VPEs, the studies were performed in Hordeum vulgare roots and leaves on the day of inoculation and at 7, 14 and 21 days post-inoculation (dpi). Implementing molecular, biochemical and microscopic methods we identified reasons for modulation of barley VPE activity during interaction with H. filipjevi. Heterodera filipjevi parasitism caused a general decrease of VPE activity in infected roots, but live imaging of VPEs showed that their activity is up-regulated in syncytia at 7 and 14 dpi and down-regulated at 21 dpi. These findings were accompanied by tissue-specific VPE gene expression patterns. Expression of the barley cystatin HvCPI-4 gene was stimulated in leaves but diminished in roots upon infestation. External application of cyclotides that can be produced naturally by VPEs elicits in pre-parasitic juveniles vesiculation of their body, enhanced formation of granules, induction of exploratory behaviour (stylet thrusts and head movements), production of reactive oxygen species (ROS) and final death by methuosis. Taken together, down-regulation of VPE activity through nematode effectors promotes the nematode invasion rates and leads to avoidance of the induction of the plant proteolytic response and death of the invading juveniles.     

Novel insights into the calcium action in cherry fruit development revealed by high-throughput mapping

Plant Molecular Biology - This work provides the first system-wide datasets concerning metabolic changes in calcium-treated fruits, which reveal that exogenously applied calcium may specifically...     

Ribozymes: recent advances in the development of RNA tools

The discovery 20 years ago that some RNA molecules, called ribozymes, are able to catalyze chemical reactions was a breakthrough in biology. Over the last two decades numerous natural RNA motifs endowed with catalytic activity have been described. They all fit within a few well-defined types that respond to a specific RNA structure. The prototype catalytic domain of each one has been engineered to generate trans-acting ribozymes that catalyze the site-specific cleavage of other RNA molecules. On the 20th anniversary of ribozyme discovery we briefly summarize the main features of the different natural catalytic RNAs. We also describe progress towards developing strategies to ensure an efficient ribozyme-based technology, dedicating special attention to the ones aimed to achieve a new generation of therapeutic agents.     

Deep-lipidotyping by mass spectrometry: recent technical advances and applications

In-depth structural characterization of lipids is an essential component of lipidomics. There has been a rapid expansion of mass spectrometry methods that are capable of resolving lipid isomers at various structural levels over the past decade. These developments finally make deep-lipidotyping possible, which provides new means to study lipid metabolism and discover new lipid biomarkers. In this review, we discuss recent advancements in tandem mass spectrometry (MS/MS) methods for identification of complex lipids beyond the species (known headgroup information) and molecular species (known chain composition) levels. These include identification at the levels of carbon-carbon double bond (C=C) location and sn-position, as well as characterization of acyl chain modifications. We also discuss the integration of isomer-resolving MS/MS methods with different lipid analysis workflows and their applications in lipidomics. The results showcase the distinct capabilities of deep-lipidotyping in untangling the metabolism of individual isomers and sensitive phenotyping by using relative fractional quantitation of the isomers.     

Experience sampling methodology in mental health research: new insights and technical developments

In the mental health field, there is a growing awareness that the study of psychiatric symptoms in the context of everyday life, using experience sampling methodology (ESM), may provide a powerful and necessary addition to more conventional research approaches. ESM, a structured self‐report diary technique, allows the investigation of experiences within, and in interaction with, the real‐world context. This paper provides an overview of how zooming in on the micro‐level of experience and behaviour using ESM adds new insights and additional perspectives to standard approaches. More specifically, it discusses how ESM: a) contributes to a deeper understanding of psychopathological phenomena, b) allows to capture variability over time, c) aids in identifying internal and situational determinants of variability in symptomatology, and d) enables a thorough investigation of the interaction between the person and his/her environment and of real‐life social interactions. Next to improving assessment of psychopathology and its underlying mechanisms, ESM contributes to advancing and changing clinical practice by allowing a more fine‐grained evaluation of treatment effects as well as by providing the opportunity for extending treatment beyond the clinical setting into real life with the development of ecological momentary interventions. Furthermore, this paper provides an overview of the technical details of setting up an ESM study in terms of design, questionnaire development and statistical approaches. Overall, although a number of considerations and challenges remain, ESM offers one of the best opportunities for personalized medicine in psychiatry, from both a research and a clinical perspective.     

Direct mutation analysis by high-throughput sequencing: from germline to low-abundant, somatic variants

DNA mutations are the source of genetic variation within populations. The majority of mutations with observable effects are deleterious. In humans mutations in the germ line can cause genetic disease. In somatic cells multiple rounds of mutations and selection lead to cancer. The study of genetic variation has progressed rapidly since the completion of the draft sequence of the human genome. Recent advances in sequencing technology, most importantly the introduction of massively parallel sequencing (MPS), have resulted in more than a hundred-fold reduction in the time and cost required for sequencing nucleic acids. These improvements have greatly expanded the use of sequencing as a practical tool for mutation analysis. While in the past the high cost of sequencing limited mutation analysis to selectable markers or small forward mutation targets assumed to be representative for the genome overall, current platforms allow whole genome sequencing for less than $5000. This has already given rise to direct estimates of germline mutation rates in multiple organisms including humans by comparing whole genome sequences between parents and offspring. Here we present a brief history of the field of mutation research, with a focus on classical tools for the measurement of mutation rates. We then review MPS, how it is currently applied and the new insight into human and animal mutation frequencies and spectra that has been obtained from whole genome sequencing. While great progress has been made, we note that the single most important limitation of current MPS approaches for mutation analysis is the inability to address low-abundance mutations that turn somatic tissues into mosaics of cells. Such mutations are at the basis of intra-tumor heterogeneity, with important implications for clinical diagnosis, and could also contribute to somatic diseases other than cancer, including aging. Some possible approaches to gain access to low-abundance mutations are discussed, with a brief overview of new sequencing platforms that are currently waiting in the wings to advance this exploding field even further.