ParMap, an algorithm for the identification of small genomic insertions and deletions in nextgen sequencing data

<p>Abstract</p> <p>Background</p> <p>Next-generation sequencing produces high-throughput data, albeit with greater error and shorter reads than traditional Sanger sequencing methods. This complicates the detection of genomic variations, especially, small insertions and deletions.</p> <p>Findings</p> <p>Here we describe ParMap, a statistical algorithm for the identification of complex genetic variants, such as small insertion and deletions, using partially mapped reads in nextgen sequencing data.</p> <p>Conclusions</p> <p>We report ParMap's successful application to the mutation analysis of chromosome X exome-captured leukemia DNA samples.</p

VHE γ\gamma-ray observations of Markarian 501

Markarian 501, a nearby (z=0.033) X-ray selected BL Lacertae object, is a well established source of Very High Energy (VHE, E>=300 GeV) gamma rays. Dramatic variability in its gamma-ray emission on time-scales from years to as short as two hours has been detected. Multiwavelength observations have also revealed evidence that the VHE gamma-ray and hard X-ray fluxes may be correlated. Here we present results of observations made with the Whipple Collaboration's 10 m Atmospheric Cerenkov Imaging Telescope during 1999 and discuss them in the context of observations made on Markarian 501 during the period from 1996-1998

A Platform-Independent Method for Detecting Errors in Metagenomic Sequencing Data: DRISEE

We provide a novel method, DRISEE (duplicate read inferred sequencing error estimation), to assess sequencing quality (alternatively referred to as “noise” or “error”) within and/or between sequencing samples. DRISEE provides positional error estimates that can be used to inform read trimming within a sample. It also provides global (whole sample) error estimates that can be used to identify samples with high or varying levels of sequencing error that may confound downstream analyses, particularly in the case of studies that utilize data from multiple sequencing samples. For shotgun metagenomic data, we believe that DRISEE provides estimates of sequencing error that are more accurate and less constrained by technical limitations than existing methods that rely on reference genomes or the use of scores (e.g. Phred). Here, DRISEE is applied to (non amplicon) data sets from both the 454 and Illumina platforms. The DRISEE error estimate is obtained by analyzing sets of artifactual duplicate reads (ADRs), a known by-product of both sequencing platforms. We present DRISEE as an open-source, platform-independent method to assess sequencing error in shotgun metagenomic data, and utilize it to discover previously uncharacterized error in de novo sequence data from the 454 and Illumina sequencing platforms

On the power and the systematic biases of the detection of chromosomal inversions by paired-end genome sequencing

One of the most used techniques to study structural variation at a genome level is paired-end mapping (PEM). PEM has the advantage of being able to detect balanced events, such as inversions and translocations. However, inversions are still quite difficult to predict reliably, especially from high-throughput sequencing data. We simulated realistic PEM experiments with different combinations of read and library fragment lengths, including sequencing errors and meaningful base-qualities, to quantify and track down the origin of false positives and negatives along sequencing, mapping, and downstream analysis. We show that PEM is very appropriate to detect a wide range of inversions, even with low coverage data. However, % of inversions located between segmental duplications are expected to go undetected by the most common sequencing strategies. In general, longer DNA libraries improve the detectability of inversions far better than increments of the coverage depth or the read length. Finally, we review the performance of three algorithms to detect inversions -SVDetect, GRIAL, and VariationHunter-, identify common pitfalls, and reveal important differences in their breakpoint precisions. These results stress the importance of the sequencing strategy for the detection of structural variants, especially inversions, and offer guidelines for the design of future genome sequencing projects

U87MG Decoded: The Genomic Sequence of a Cytogenetically Aberrant Human Cancer Cell Line

U87MG is a commonly studied grade IV glioma cell line that has been analyzed in at least 1,700 publications over four decades. In order to comprehensively characterize the genome of this cell line and to serve as a model of broad cancer genome sequencing, we have generated greater than 30× genomic sequence coverage using a novel 50-base mate paired strategy with a 1.4kb mean insert library. A total of 1,014,984,286 mate-end and 120,691,623 single-end two-base encoded reads were generated from five slides. All data were aligned using a custom designed tool called BFAST, allowing optimal color space read alignment and accurate identification of DNA variants. The aligned sequence reads and mate-pair information identified 35 interchromosomal translocation events, 1,315 structural variations (>100 bp), 191,743 small (<21 bp) insertions and deletions (indels), and 2,384,470 single nucleotide variations (SNVs). Among these observations, the known homozygous mutation in PTEN was robustly identified, and genes involved in cell adhesion were overrepresented in the mutated gene list. Data were compared to 219,187 heterozygous single nucleotide polymorphisms assayed by Illumina 1M Duo genotyping array to assess accuracy: 93.83% of all SNPs were reliably detected at filtering thresholds that yield greater than 99.99% sequence accuracy. Protein coding sequences were disrupted predominantly in this cancer cell line due to small indels, large deletions, and translocations. In total, 512 genes were homozygously mutated, including 154 by SNVs, 178 by small indels, 145 by large microdeletions, and 35 by interchromosomal translocations to reveal a highly mutated cell line genome. Of the small homozygously mutated variants, 8 SNVs and 99 indels were novel events not present in dbSNP. These data demonstrate that routine generation of broad cancer genome sequence is possible outside of genome centers. The sequence analysis of U87MG provides an unparalleled level of mutational resolution compared to any cell line to date

Obesity Takes Its Toll on Visceral Pain: High-Fat Diet Induces Toll-Like Receptor 4- Dependent Visceral Hypersensitivity

Exposure to high-fat diet induces both, peripheral and central alterations in TLR4 expression. Moreover, functional TLR4 is required for the development of high-fat diet-induced obesity. Recently, central alterations in TLR4 expression have been associated with the modulation of visceral pain. However, it remains unknown whether there is a functional interaction between the role of TLR4 in diet-induced obesity and in visceral pain. In the present study we investigated the impact of long-term exposure to high-fat diet on visceral pain perception and on the levels of TLR4 and Cd11b (a microglial cell marker) protein expression in the prefrontal cortex (PFC) and hippocampus. Peripheral alterations in TLR4 were assessed following the stimulation of spleenocytes with the TLR4-agonist LPS. Finally, we evaluated the effect of blocking TLR4 on visceral nociception, by administering TAK-242, a selective TLR4-antagonist. Our results demonstrated that exposure to high-fat diet induced visceral hypersensitivity. In parallel, enhanced TLR4 expression and microglia activation were found in brain areas related to visceral pain, the PFC and the hippocampus. Likewise, peripheral TLR4 activity was increased following long-term exposure to high-fat diet, resulting in an increased level of pro-inflammatory cytokines. Finally, TLR4 blockage counteracted the hyperalgesic phenotype present in mice fed on high-fat diet. Our data reveal a role for TLR4 in visceral pain modulation in a model of diet-induced obesity, and point to TLR4 as a potential therapeutic target for the development of drugs to treat visceral hypersensitivity present in pathologies associated to fat diet consumption

Population genetic analysis of bi-allelic structural variants from low-coverage sequence data with an expectation-maximization algorithm

Background Population genetics and association studies usually rely on a set of known variable sites that are then genotyped in subsequent samples, because it is easier to genotype than to discover the variation. This is also true for structural variation detected from sequence data. However, the genotypes at known variable sites can only be inferred with uncertainty from low coverage data. Thus, statistical approaches that infer genotype likelihoods, test hypotheses, and estimate population parameters without requiring accurate genotypes are becoming popular. Unfortunately, the current implementations of these methods are intended to analyse only single nucleotide and short indel variation, and they usually assume that the two alleles in a heterozygous individual are sampled with equal probability. This is generally false for structural variants detected with paired ends or split reads. Therefore, the population genetics of structural variants cannot be studied, unless a painstaking and potentially biased genotyping is performed first. Results We present svgem, an expectation-maximization implementation to estimate allele and genotype frequencies, calculate genotype posterior probabilities, and test for Hardy-Weinberg equilibrium and for population differences, from the numbers of times the alleles are observed in each individual. Although applicable to single nucleotide variation, it aims at bi-allelic structural variation of any type, observed by either split reads or paired ends, with arbitrarily high allele sampling bias. We test svgem with simulated and real data from the 1000 Genomes Project. Conclusions svgem makes it possible to use low-coverage sequencing data to study the population distribution of structural variants without having to know their genotypes. Furthermore, this advance allows the combined analysis of structural and nucleotide variation within the same genotype-free statistical framework, thus preventing biases introduced by genotype imputation

Proteolysis of proBDNF Is a Key Regulator in the Formation of Memory

It is essential to understand the molecular processes underlying long-term memory to provide therapeutic targets of aberrant memory that produce pathological behaviour in humans. Under conditions of recall, fully-consolidated memories can undergo reconsolidation or extinction. These retrieval-mediated memory processes may rely on distinct molecular processes. The cellular mechanisms initiating the signature molecular events are not known. Using infusions of protein synthesis inhibitors, antisense oligonucleotide targeting brain-derived neurotrophic factor (BDNF) mRNA or tPA-STOP (an inhibitor of the proteolysis of BDNF protein) into the hippocampus of the awake rat, we show that acquisition and extinction of contextual fear memory depended on the increased and decreased proteolysis of proBDNF (precursor BDNF) in the hippocampus, respectively. Conditions of retrieval that are known to initiate the reconsolidation of contextual fear memory, a BDNF-independent memory process, were not correlated with altered proBDNF cleavage. Thus, the processing of BDNF was associated with the acquisition of new information and the updating of information about a salient stimulus. Furthermore, the differential requirement for the processing of proBDNF by tPA in distinct memory processes suggest that the molecular events actively engaged to support the storage and/or the successful retrieval of memory depends on the integration of ongoing experience with past learning

The role of non-medical therapeutic approaches in the rehabilitation of Complex Regional Pain Syndrome

Purpose of the review: Non-medical therapeutic approaches are fundamental to the management of Complex Regional Pain Syndrome (CRPS) in order to promote the best outcome for patients. This review focuses on three key approaches underpinning CRPS rehabilitation, namely: physiotherapy and occupational therapy, psychological approaches and education and self-management. Recent Findings: Recently published European standards outline the quality of therapeutic care that people with CRPS must receive. Early initiated therapy is essential to optimise outcomes, underpinned by patient education. Therapists should promote early movement of the affected limb and encourage re-engagement with usual activities as immobilisation is known to have negative outcomes. There is evidence to support the possible long-term benefit of graded motor imagery and mirror therapy. Psychological assessment should include identification of depression and post-traumatic stress disorder, as treatment of these conditions may improve the trajectory of CRPS. Novel therapies include neurocognitive approaches and those addressing spatial bias, both of which should provide a focus for future research.Summary: There exists a broad range of non-medical therapeutic approaches to rehabilitation for CPRS that are thought to be important. However, the evidence for their efficacy is limited. Further research using standardised outcomes would be helpful in developing targeted therapies for the future