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[This corrects the article DOI: 10.1371/journal.pone.0158724.].

The molecular classification of glioblastoma (GBM) based on gene expression might better explain outcome and response to treatment than clinical factors. Whole transcriptome sequencing using next-generation sequencing platforms is rapidly becoming accepted as a tool for measuring gene expression for both research and clinical use. Fresh frozen (FF) tissue specimens of GBM are difficult to obtain since tumor tissue obtained at surgery is often scarce and necrotic and diagnosis is prioritized over freezing. After diagnosis, leftover tissue is usually stored as formalin-fixed paraffin-embedded (FFPE) tissue. However, RNA from FFPE tissues is usually degraded, which could hamper gene expression analysis. We compared RNA-Seq data obtained from matched pairs of FF and FFPE GBM specimens. Only three FFPE out of eleven FFPE-FF matched samples yielded informative results. Several quality-control measurements showed that RNA from FFPE samples was highly degraded but maintained transcriptomic similarities to RNA from FF samples. Certain issues regarding mutation analysis and subtype prediction were detected. Nevertheless, our results suggest that RNA-Seq of FFPE GBM specimens provides reliable gene expression data that can be used in molecular studies of GBM if the RNA is sufficiently preserved.

Recent estimates of the global burden of fungal disease suggest that that their incidence has been drastically underestimated and that mortality may rival that of malaria or tuberculosis. Azoles are the principal class of antifungal drug and the only available oral treatment for fungal disease. Recent occurrence and increase in azole resistance is a major concern worldwide. Known azole resistance mechanisms include over-expression of efflux pumps and mutation of the gene encoding the target protein cyp51a, however, for one of the most important fungal pathogens of humans, Aspergillus fumigatus, much of the observed azole resistance does not appear to involve such mechanisms. Here we present evidence that azole resistance in A. fumigatus can arise through mutation of components of mitochondrial complex I. Gene deletions of the 29.9KD subunit of this complex are azole resistant, less virulent and exhibit dysregulation of secondary metabolite gene clusters in a manner analogous to deletion mutants of the secondary metabolism regulator, LaeA. Additionally we observe that a mutation leading to an E180D amino acid change in the 29.9 KD subunit is strongly associated with clinical azole resistant A. fumigatus isolates. Evidence presented in this paper suggests that complex I may play a role in the hypoxic response and that one possible mechanism for cell death during azole treatment is a dysfunctional hypoxic response that may be restored by dysregulation of complex I. Both deletion of the 29.9 KD subunit of complex I and azole treatment alone profoundly change expression of gene clusters involved in secondary metabolism and immunotoxin production raising potential concerns about long term azole therapy.

UNLABELLED: Next-generation sequencing technologies expedited research to develop efficient computational tools for the identification of structural variants (SVs) and their use to study human diseases. As deeper data is obtained, the existence of higher complexity SVs in some genomes becomes more evident, but the detection and definition of most of these complex rearrangements is still in its infancy. The full characterization of SVs is a key aspect for discovering their biological implications. Here we present a pipeline (PeSV-Fisher) for the detection of deletions, gains, intra- and inter-chromosomal translocations, and inversions, at very reasonable computational costs. We further provide comprehensive information on co-localization of SVs in the genome, a crucial aspect for studying their biological consequences. The algorithm uses a combination of methods based on paired-reads and read-depth strategies. PeSV-Fisher has been designed with the aim to facilitate identification of somatic variation, and, as such, it is capable of analysing two or more samples simultaneously, producing a list of non-shared variants between samples. We tested PeSV-Fisher on available sequencing data, and compared its behaviour to that of frequently deployed tools (BreakDancer and VariationHunter). We have also tested this algorithm on our own sequencing data, obtained from a tumour and a normal blood sample of a patient with chronic lymphocytic leukaemia, on which we have also validated the results by targeted re-sequencing of different kinds of predictions. This allowed us to determine confidence parameters that influence the reliability of breakpoint predictions. AVAILABILITY: PeSV-Fisher is available at http://gd.crg.eu/tools.

Despite intense interest, methods that provide enhanced sensitivity and specificity in parallel measurements of candidate protein biomarkers in numerous samples have been lacking. We present herein a multiplex proximity ligation assay with readout via realtime PCR or DNA sequencing (ProteinSeq). We demonstrate improved sensitivity over conventional sandwich assays for simultaneous analysis of sets of 35 proteins in 5 µl of blood plasma. Importantly, we observe a minimal tendency to increased background with multiplexing, compared to a sandwich assay, suggesting that higher levels of multiplexing are possible. We used ProteinSeq to analyze proteins in plasma samples from cardiovascular disease (CVD) patient cohorts and matched controls. Three proteins, namely P-selectin, Cystatin-B and Kallikrein-6, were identified as putative diagnostic biomarkers for CVD. The latter two have not been previously reported in the literature and their potential roles must be validated in larger patient cohorts. We conclude that ProteinSeq is promising for screening large numbers of proteins and samples while the technology can provide a much-needed platform for validation of diagnostic markers in biobank samples and in clinical use.