FuGePrior: A novel gene fusion prioritization algorithm based on accurate fusion structure analysis in cancer RNA-seq samples

Abstract Background Latest Next Generation Sequencing technologies opened the way to a novel era of genomic studies, allowing to gain novel insights into multifactorial pathologies as cancer. In particular gene fusion detection and comprehension have been deeply enhanced by these methods. However, state of the art algorithms for gene fusion identification are still challenging. Indeed, they identify huge amounts of poorly overlapping candidates and all the reported fusions should be considered for in lab validation clearly overwhelming wet lab capabilities. Results In this work we propose a novel methodological approach and tool named FuGePrior for the prioritization of gene fusions from paired-end RNA-Seq data. The proposed pipeline combines state of the art tools for chimeric transcript discovery and prioritization, a series of filtering and processing steps designed by considering modern literature on gene fusions and an analysis on functional reliability of gene fusion structure. Conclusions FuGePrior performance has been assessed on two publicly available paired-end RNA-Seq datasets: The first by Edgren and colleagues includes four breast cancer cell lines and a normal breast sample, whereas the second by Ren and colleagues comprises fourteen primary prostate cancer samples and their paired normal counterparts. FuGePrior results accounted for a reduction in the number of fusions output of chimeric transcript discovery tools that ranges from 65 to 75% depending on the considered breast cancer cell line and from 37 to 65% according to the prostate cancer sample under examination. Furthermore, since both datasets come with a partial validation we were able to assess the performance of FuGePrior in correctly prioritizing real gene fusions. Specifically, 25 out of 26 validated fusions in breast cancer dataset have been correctly labelled as reliable and biologically significant. Similarly, 2 out of 5 validated fusions in prostate dataset have been recognized as priority by FuGePrior tool

isomiR-SEA: An RNA-Seq analysis tool for miRNAs/isomiRs expression level profiling and miRNA-mRNA interaction sites evaluation

>Background: Massive parallel sequencing of transcriptomes, revealed the presence of many miRNAs and miRNAs variants named isomiRs with a potential role in several cellular processes through their interaction with a target mRNA. Many methods and tools have been recently devised to detect and quantify miRNAs from sequencing data. However, all of them are implemented on top of general purpose alignment methods, thus providing poorly accurate results and no information concerning isomiRs and conserved miRNA-mRNA interaction sites. >Results: To overcome these limitations we present a novel algorithm named isomiR-SEA, that is able to provide users with very accurate miRNAs expression levels and both isomiRs and miRNA-mRNA interaction sites precise classifications. Tags are mapped on the known miRNAs sequences thanks to a specialized alignment algorithm developed on top of biological evidence concerning miRNAs structure. Specifically, isomiR-SEA checks for miRNA seed presence in the input tags and evaluates, during all the alignment phases, the positions of the encountered mismatches, thus allowing to distinguish among the different isomiRs and conserved miRNA-mRNA interaction sites. >Conclusions: isomiR-SEA performances have been assessed on two public RNA-Seq datasets proving that the implemented algorithm is able to account for more reliable and accurate miRNAs expression levels with respect to those provided by two compared state of the art tools. Moreover, differently from the few methods currently available to perform isomiRs detection, the proposed algorithm implements the evaluation of isomiRs and conserved miRNA-mRNA interaction sites already in the first alignment phases, thus avoiding any additional filtering stages potentially responsible for the loss of useful information

An Exploratory Study on the Influence of Psychopathological Risk and Impulsivity on BMI and Perceived Quality of Life in Obese Patients

The present study aimed to assess the psychological profiles of adult male and female obese patients, as well as to verify the possible influence of their psychopathological risk and impulsivity on their body mass index (BMI) and perceived quality of life. A total of 64 obese subjects accessing a center for care of their obesity were assessed through anthropometric and psychometric measurements. All anthropometric measures in men were higher than in women, while in turn, women showed higher psychopathological symptoms. Furthermore, the symptoms of somatization and psychoticism were predictors for a higher BMI in men, but there was no effect of psychopathological symptoms on the perceived quality of life (QoL) of male subjects. Moreover, in women, somatization and attentional impulsivity were predictors for a higher BMI, whereas no correlation was found between their psychopathological risk and perceived QoL. The results of regression analysis underlined that somatization is a “core” psychopathological symptom in obese subjects regardless of their sex, which is a potential predictor for a higher BMI. The psychological difficulties of the subjects had no effect on their perceived QoL, suggesting that they find it difficult to reflect on the impact that obesity has on their life

On the relevance of a complete characterisation of miRNAs, isomiRs and miRNA-mRNA interaction sites through miRNA-specific alignment tools

The advent of NGS dramatically changed the characterisation of multifactorial pathologies such as cancer. The high molecular variability of cancer makes essential the identification of biomarkers able to explain the differences among cancer sub-types, allowing physicians to provide patients with suitable therapies. In this context, miRNAs are considered adequate biomarkers and miRNAs profiling from miRNA-sequencing is widely used. However, state of the art tools performing miRNAs reads mapping rely on general-purpose alignment algorithms. On the other side, researches carried out in the last decade led to the identification of many miRNAs specific features that are not exploited by miRNAs aligner. Moreover, the role of miRNAs variants called ‘isomiRs’ is still an open issue. IsomiRs impact miRNA targets affinity characterization and their analysis enables a more accurate evaluation of miRNA expression profiles. In light of these considerations, there is need of algorithmic methodologies able to provide users with a complete and accurate picture of the whole miRNAs, isomiRs and interaction sites spectrum. We report the impact of the application of such methodology on 23 human miRNA-Seq datasets from GEO, for which the overall isomiRs expression level and the characteristics of the interaction sites has been evaluated. As a result, 40% of the 189M miRNAs mapped reads showed a miRNA exact sequence, whereas 50% are characterized by a sequence accounting for 3’ isomiRs and the remaining reads possess sequences compatible with 5’ and SNP isomiRs or combinations of them. Furthermore, in the 2% of the cases some interaction sites are missed. Two other samples (hESCs and NSCs), recently analysed to confirm isomiRs importance, have been also studied in terms of isomiRs and interaction sites profiles, pointing out that such characteristics require a suitable methodology for miRNA sequences analysis because they cannot be appreciated from the overall miRNAs expression profile

Dynamic Gap Selector: A Smith Waterman Sequence Alignment Algorithm with Affine Gap Model Optimisation

Smith Waterman algorithm (S-W) is nowadays considered one of the best method to perform local alignments of biological sequences characterizing proteins, DNA and RNA molecules. Indeed, S-W is able to ensure better accuracy levels with respect to the heuristic alignment algorithms by extensively exploring all the possible alignment configurations between the sequences under examination. It has been proven that the first amino acid (AA) or nucleotide (NT) inserted/deleted (that identify a gap open) found during the alignment operations performed on sequences is more significant from a biological point of view than the subsequent ones (called gap extension), making the so called Affine Gap model a viable solution for biomolecules alignment. However, this version of S-W algorithm is expensive both in terms of computation as well as in terms of memory requirements with respect to others less demanding solutions such as the ones using a Linear Gap model. In order to overcome these drawbacks we have developed an optimised version of the S-Walgorithm based on Affine Gap model called Dynamic Gap Selector (DGS S-W). Differently from the standard S-W Affine Gap method, the proposed DGS S-W method reduces the memory requirements from 3*N*M to N*M where N and M represents the size of the compared sequences. In terms of computational costs, the proposed algorithm reduces by a factor of 2 the number of operations required by the standard Affine Gap model. DGS S-W method has been tested on two protein and one RNA sequences datasets, showing mapping scores very similar to those reached thanks to the classical S-W Affine Gap method and, at the same time, reduced computational costs and memory usag

miR-SEA: miRNA Seed Extension based Aligner Pipeline for NGS Expression Level Extraction

The advent of Next Generation Sequencing (NGS) technology has enabled a new major approach for micro RNAs (miRNAs) expression profiling through the so called RNA-Sequencing (RNA-Seq). Different tools have been developed in the last years in order to detect and quantify miRNAs, especially in pathological samples, starting from the big amount of data deriving from RNA sequencing. These tools, usually relying on general purpose alignment algorithms, are however characterized by different sensitivity and accuracy levels and in the most of the cases provide not overlapping predictions. To overcome these limitations we propose a novel pipeline for miRNAs detection and quantification in RNA-Seq sample, miRNA Seed Extension Aligner (miR-SEA), based on an experimental evidence concerning miRNAs structure. The proposed pipeline was tested on three Colorectal Cancer (CRC) RNA-Seq samples and the obtained results compared with those provided by two well-known miRNAs detection tools showing good ability in performing detection and quantification more adherent to miRNAs structur

A novel framework for chimeric transcript detection based on accurate gene fusion model

Next generation sequencing plays a key role in the detection of structural variations. Chimeric transcripts are relevant examples of such variations, as they are involved in several diseases. In this work, we propose an effective methodology for the detection of fused transcripts in RNA-Seq paired-end data. The proposed methodology is based on an accurate fusion model implemented by a set of filters reducing the impact of artifacts. Moreover, the methodology accounts for transcripts consistently expressing in the sample under study even if they are not annotated. The effectiveness of the proposed solution has been experimentally validated on of Chronic Myelogenous Leukemia (CML) samples, providing both the genes involved in the fusion and the exact chimeric sequence. \ua9 2011 IEEE

Mouse Panx1 Is Dispensable for Hearing Acquisition and Auditory Function

Panx1 forms plasma membrane channels in brain and several other organs, including the inner ear. Biophysical properties, activation mechanisms and modulators of Panx1 channels have been characterized in detail, however the impact of Panx1 on auditory function is unclear due to conflicts in published results. To address this issue, hearing performance and cochlear function of the Panx1−/− mouse strain, the first with a reported global ablation of Panx1, were scrutinized. Male and female homozygous (Panx1−/−), hemizygous (Panx1+/−) and their wild type (WT) siblings (Panx1+/+) were used for this study. Successful ablation of Panx1 was confirmed by RT-PCR and Western immunoblotting in the cochlea and brain of Panx1−/− mice. Furthermore, a previously validated Panx1-selective antibody revealed strong immunoreactivity in WT but not in Panx1−/− cochleae. Hearing sensitivity, outer hair cell-based “cochlear amplifier” and cochlear nerve function, analyzed by auditory brainstem response (ABR) and distortion product otoacoustic emission (DPOAE) recordings, were normal in Panx1+/− and Panx1−/− mice. In addition, we determined that global deletion of Panx1 impacts neither on connexin expression, nor on gap-junction coupling in the developing organ of Corti. Finally, spontaneous intercellular Ca2+ signal (ICS) activity in organotypic cochlear cultures, which is key to postnatal development of the organ of Corti and essential for hearing acquisition, was not affected by Panx1 ablation. Therefore, our results provide strong evidence that, in mice, Panx1 is dispensable for hearing acquisition and auditory function

FUNGI : FUsioN Gene Integration toolset

Motivation: Fusion genes are both useful cancer biomarkers and important drug targets. Finding relevant fusion genes is challenging due to genomic instability resulting in a high number of passenger events. To reveal and prioritize relevant gene fusion events we have developed FUsionN Gene Identification toolset (FUNGI) that uses an ensemble of fusion detection algorithms with prioritization and visualization modules. Results: We applied FUNGI to an ovarian cancer dataset of 107 tumor samples from 36 patients. Ten out of 11 detected and prioritized fusion genes were validated. Many of detected fusion genes affect the PI3K-AKT pathway with potential role in treatment resistance.Peer reviewe