Methods to study splicing from high-throughput RNA Sequencing data

The development of novel high-throughput sequencing (HTS) methods for RNA (RNA-Seq) has provided a very powerful mean to study splicing under multiple conditions at unprecedented depth. However, the complexity of the information to be analyzed has turned this into a challenging task. In the last few years, a plethora of tools have been developed, allowing researchers to process RNA-Seq data to study the expression of isoforms and splicing events, and their relative changes under different conditions. We provide an overview of the methods available to study splicing from short RNA-Seq data. We group the methods according to the different questions they address: 1) Assignment of the sequencing reads to their likely gene of origin. This is addressed by methods that map reads to the genome and/or to the available gene annotations. 2) Recovering the sequence of splicing events and isoforms. This is addressed by transcript reconstruction and de novo assembly methods. 3) Quantification of events and isoforms. Either after reconstructing transcripts or using an annotation, many methods estimate the expression level or the relative usage of isoforms and/or events. 4) Providing an isoform or event view of differential splicing or expression. These include methods that compare relative event/isoform abundance or isoform expression across two or more conditions. 5) Visualizing splicing regulation. Various tools facilitate the visualization of the RNA-Seq data in the context of alternative splicing. In this review, we do not describe the specific mathematical models behind each method. Our aim is rather to provide an overview that could serve as an entry point for users who need to decide on a suitable tool for a specific analysis. We also attempt to propose a classification of the tools according to the operations they do, to facilitate the comparison and choice of methods.Comment: 31 pages, 1 figure, 9 tables. Small corrections adde

Ovarian cancer immunotherapy: opportunities, progresses and challenges

Due to the low survival rates from invasive ovarian cancer, new effective treatment modalities are urgently needed. Compelling evidence indicates that the immune response against ovarian cancer may play an important role in controlling this disease. We herein summarize multiple immune-based strategies that have been proposed and tested for potential therapeutic benefit against advanced stage ovarian cancer. We will examine the evidence for the premise that an effective therapeutic vaccine against ovarian cancer is useful not only for inducing remission of the disease but also for preventing disease relapse. We will also highlight the questions and challenges in the development of ovarian cancer vaccines, and critically discuss the limitations of some of the existing immunotherapeutic strategies. Finally, we will summarize our own experience on the use of patient-specific tumor-derived heat shock protein-peptide complex for the treatment of advanced ovarian cancer

A comprehensive assessment of N-terminal signal peptides prediction methods

Background: Amino-terminal signal peptides (SPs) are short regions that guide the targeting of secretory proteins to the correct subcellular compartments in the cell. They are cleaved off upon the passenger protein reaching its destination. The explosive growth in sequencing technologies has led to the deposition of vast numbers of protein sequences necessitating rapid functional annotation techniques, with subcellular localization being a key feature. Of the myriad software prediction tools developed to automate the task of assigning the SP cleavage site of these new sequences, we review here, the performance and reliability of commonly used SP prediction tools. Results: The available signal peptide data has been manually curated and organized into three datasets representing eukaryotes, Gram-positive and Gram-negative bacteria. These datasets are used to evaluate thirteen prediction tools that are publicly available. SignalP (both the HMM and ANN versions) maintains consistency and achieves the best overall accuracy in all three benchmarking experiments, ranging from 0.872 to 0.914 although other prediction tools are narrowing the performance gap. Conclusion: The majority of the tools evaluated in this study encounter no difficulty in discriminating between secretory and non-secretory proteins. The challenge clearly remains with pinpointing the correct SP cleavage site. The composite scoring schemes employed by SignalP may help to explain its accuracy. Prediction task is divided into a number of separate steps, thus allowing each score to tackle a particular aspect of the prediction.12 page(s

Reproductive Behaviour Evolves Rapidly When Intralocus Sexual Conflict Is Removed

Background Intralocus sexual conflict can inhibit the evolution of each sex towards its own fitness optimum. In a previous study, we confirmed this prediction through the experimental removal of female selection pressures in Drosophila melanogaster, achieved by limiting the expression of all major chromosomes to males. Compared to the control populations (C1-4) where the genomes are exposed to selection in both sexes, the populations with male-limited genomes (ML1-4) showed rapid increases in male fitness, whereas the fitness of females expressing ML-evolved chromosomes decreased [1]. Methodology/Principal Findings Here we examine the behavioural phenotype underlying this sexual antagonism. We show that males expressing the ML genomes have a reduced courtship level but acquire the same number of matings. On the other hand, our data suggest that females expressing the ML genomes had reduced attractiveness, stimulating a lower rate of courtship from males. Moreover, females expressing ML genomes tend to display reduced yeast-feeding behaviour, which is probably linked to the reduction of their fecundity. Conclusion/Significance These results suggest that reproductive behaviour is shaped by opposing selection on males and females, and that loci influencing attractiveness and foraging were polymorphic for alleles with sexually antagonistic expression patterns prior to ML selection. Hence, intralocus sexual conflict appears to play a role in the evolution of a wide range of fitness-related traits and may be a powerful mechanism for the maintenance of genetic variation in fitness

Advanced glycoxidation and lipoxidation end products (AGEs and ALEs): an overview of their mechanisms of formation

Advanced lipoxidation end products (ALEs) and advanced glycation end products (AGEs) have a pathogenetic role in the development and progression of different oxidative-based diseases including diabetes, atherosclerosis, and neurological disorders. AGEs and ALEs represent a quite complex class of compounds that are formed by different mechanisms, by heterogeneous precursors and that can be formed either exogenously or endogenously. There is a wide interest in AGEs and ALEs involving different aspects of research which are essentially focused on set-up and application of analytical strategies (1) to identify, characterize, and quantify AGEs and ALEs in different pathophysiological conditions ; (2) to elucidate the molecular basis of their biological effects ; and (3) to discover compounds able to inhibit AGEs/ALEs damaging effects not only as biological tools aimed at validating AGEs/ALEs as drug target, but also as promising drugs. All the above-mentioned research stages require a clear picture of the chemical formation of AGEs/ALEs but this is not simple, due to the complex and heterogeneous pathways, involving different precursors and mechanisms. In view of this intricate scenario, the aim of the present review is to group the main AGEs and ALEs and to describe, for each of them, the precursors and mechanisms of formation

Strategies to Target Tumor Immunosuppression

The tumor microenvironment is currently in the spotlight of cancer immunology research as a key factor impacting tumor development and progression. While antigen-specific immune responses play a crucial role in tumor rejection, the tumor hampers these immune responses by creating an immunosuppressive microenvironment. Recently, major progress has been achieved in the field of cancer immunotherapy, and several groundbreaking clinical trials demonstrated the potency of such therapeutic interventions in patients. Yet, the responses greatly vary among individuals. This calls for the rational design of more efficacious cancer immunotherapeutic interventions that take into consideration the “immune signature” of the tumor. Multimodality treatment regimens that aim to enhance intratumoral homing and activation of antigen-specific immune effector cells, while simultaneously targeting tumor immunosuppression, are pivotal for potent antitumor immunity