Gert Van Peer

The need for transparency and good practices in the qPCR literature

Two surveys of over 1,700 publications whose authors use quantitative real-time PCR (qPCR) reveal a lack of transparent and comprehensive reporting of essential technical information. Reporting standards are significantly improved in publications that cite the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines, although such publications are still vastly outnumbered by those that do not.

miRBase Tracker: keeping track of microRNA annotation changes

Since 2002, information on individual microRNAs (miRNAs), such as reference names and sequences, has been stored in miRBase, the reference database for miRNA annotation. As a result of progressive insights into the miRNome and its complexity, miRBase underwent addition and deletion of miRNA records, changes in annotated miRNA sequences and adoption of more complex naming schemes over time. Unfortunately, miRBase does not allow straightforward assessment of these ongoing miRNA annotation changes, which has resulted in substantial ambiguity regarding miRNA identity and sequence in public literature, in target prediction databases and in content on various commercially available analytical platforms. As a result, correct interpretation, comparison and integration of miRNA study results are compromised, which we demonstrate here by assessing the impact of ignoring sequence annotation changes. To address this problem, we developed miRBase Tracker (www.mirbasetracker.org), an easy-to-use online database that keeps track of all historical and current miRNA annotation present in the miRBase database. Three basic functionalities allow researchers to keep their miRNA annotation up-to-date, reannotate analytical miRNA platforms and link published results with outdated annotation to the latest miRBase release. We expect miRBase Tracker to increase the transparency and annotation accuracy in the field of miRNA research. Database URL: www.mirbasetracker.org

MicroRNA-128-3p is a novel oncomiR targeting PHF6 in T-cell acute lymphoblastic leukemia

T-cell acute lymphoblastic leukemia arises from the leukemic transformation of developing thymocytes and results from cooperative genetic lesions. Inactivation of the PHF6 gene is frequently observed in T-cell acute lymphoblastic leukemia, suggesting an important tumor suppressive role for PHF6 in the pathobiology of this leukemia. Although the precise function of PHF6 is still unknown, this gene is most likely involved in chromatin regulation, a strongly emerging theme in T-cell acute lymphoblastic leukemia. In this context, our previous description of a cooperative microRNA regulatory network controlling several well-known T-cell acute lymphoblastic leukemia tumor suppressor genes, including PHF6, is of great importance. Given the high frequency of PHF6 lesions in T-cell acute lymphoblastic leukemia and the integration of PHF6 in this microRNA regulatory network, we aimed to identify novel oncogenic microRNAs in T-cell acute lymphoblastic leukemia which suppress PHF6. To this end, we performed an unbiased PHF6 3′UTR-microRNA library screen and combined the results with microRNA profiling data of samples from patients with T-cell acute lymphoblastic leukemia and normal thymocyte subsets. We selected miR-128-3p as a candidate PHF6-targeting, oncogenic microRNA and demonstrated regulation of PHF6 expression upon modulation of this microRNA in T-cell acute lymphoblastic leukemia cell lines. In vivo evidence of an oncogenic role of this microRNA in T-cell acute lymphoblastic leukemia was obtained through accelerated leukemia onset in a NOTCH1-induced T-cell acute lymphoblastic leukemia mouse model upon miR-128-3p over-expression. We conclude that miR-128-3p is a strong novel candidate oncogenic microRNA in T-cell acute lymphoblastic leukemia which targets the PHF6 tumor suppressor gene.

Expressed Repeat Elements Improve RT-qPCR Normalization across a Wide Range of Zebrafish Gene Expression Studies

The selection and validation of stably expressed reference genes is a critical issue for proper RT-qPCR data normalization. In zebrafish expression studies, many commonly used reference genes are not generally applicable given their variability in expression levels under a variety of experimental conditions. Inappropriate use of these reference genes may lead to false interpretation of expression data and unreliable conclusions. In this study, we evaluated a novel normalization method in zebrafish using expressed repetitive elements (ERE) as reference targets, instead of specific protein coding mRNA targets. We assessed and compared the expression stability of a number of EREs to that of commonly used zebrafish reference genes in a diverse set of experimental conditions including a developmental time series, a set of different organs from adult fish and different treatments of zebrafish embryos including morpholino injections and administration of chemicals. Using geNorm and rank aggregation analysis we demonstrated that EREs have a higher overall expression stability compared to the commonly used reference genes. Moreover, we propose a limited set of ERE reference targets (hatn10, dna15ta1 and loopern4), that show stable expression throughout the wide range of experiments in this study, as strong candidates for inclusion as reference targets for qPCR normalization in future zebrafish expression studies. Our applied strategy to find and evaluate candidate expressed repeat elements for RT-qPCR data normalization has high potential to be used also for other species.

miSTAR : miRNA target prediction through modeling quantitative and qualitative miRNA binding site information in a stacked model structure

Abstract In microRNA (miRNA) target prediction, typically two levels of information need to be modeled: the number of potential miRNA binding sites present in a target mRNA and the genomic context of each individual site. Single model structures insufficiently cope with this complex training data structure, consisting of feature vectors of unequal length as a consequence of the varying number of miRNA binding sites in different mRNAs. To circumvent this problem, we developed a two-layered, stacked model, in which the influence of binding site context is separately modeled. Using logistic regression and random forests, we applied the stacked model approach to a unique data set of 7990 probed miRNA–mRNA interactions, hereby including the largest number of miRNAs in model training to date. Compared to lower-complexity models, a particular stacked model, named miSTAR (miRNA stacked model target prediction; www.mi-star.org), displays a higher general performance and precision on top scoring predictions. More importantly, our model outperforms published and widely used miRNA target prediction algorithms. Finally, we highlight flaws in cross-validation schemes for evaluation of miRNA target prediction models and adopt a more fair and stringent approach.

A high-throughput 3 ' UTR reporter screening identifies microRNA interactomes of cancer genes

Introduction Despite the established contribution of deregulated microRNA (miRNA) function to carcinogenesis, relatively few miRNA-cancer gene interactions have been validated, making it difficult to appreciate the true complexity of miRNA-cancer gene regulatory networks. Results In this effort, we identify miRNA interactomes of 17 well-established cancer genes, involved in various cancer types, through a miRNome-wide 3’ UTR reporter screening. Using a novel and performant strategy for high-throughput screening data analysis, we identify 390 interactions, quadrupling the size of the known miRNA interactome for the cancer genes under investigation. Clear enrichments of established and predicted interactions underscore the validity of the interactome data set. Interactomes appear to be primarily driven by canonical binding site interactions. Nonetheless, non-canonical binding sites, such as offset 6mer and seed-mismatched or G:U wobble sites, also have regulatory activity, albeit clearly less pronounced. Furthermore, we observe enhanced regulation in the presence of 3’ supplementary pairing for both canonical and non-canonical binding sites. Conclusions Altogether, the cancer gene-miRNA interactome data set represents a unique resource that will aid in the unraveling of regulatory miRNA networks and the dynamic regulation of key protein-coding cancer genes. In addition, it uncovers aspects of the functional miRNA binding site’s architecture and the relative contributions of different binding site types.

Localization and Expression of Nuclear Factor of Activated T-Cells 5 in Myoblasts Exposed to Pro-inflammatory Cytokines or Hyperosmolar Stress and in Biopsies from Myositis Patients

Aims: Regeneration in skeletal muscle relies on regulated myoblast migration and differentiation, in which the transcription factor nuclear factor of activated T-cells 5 (NFAT5) participates. Impaired muscle regeneration and chronic inflammation are prevalent in myositis. Little is known about the impact of inflammation on NFAT5 localization and expression in this group of diseases. The goal of this study was to investigate NFAT5 physiology in unaffected myoblasts exposed to cytokine or hyperosmolar stress and in myositis. Methods: NFAT5 intracellular localization and expression were studied in vitro using a cell culture model of myositis. Myoblasts were exposed to DMEM solutions enriched with pro-inflammatory cytokines IFN-γ with IL-1β or hyperosmolar DMEM obtained by NaCl supplementation. NFAT5 localization was visualized using immunohistochemistry (IHC) and Western blotting (WB) in fractionated cell lysates. NFAT5 expression was assessed by WB and RT-qPCR. In vivo localization and expression of NFAT5 were studied in muscle biopsies of patients diagnosed with polymyositis (n = 6), dermatomyositis (n = 10), inclusion body myositis (n = 11) and were compared to NFAT5 localization and expression in non-myopathic controls (n = 13). Muscle biopsies were studied by means of quantitative IHC and WB of total protein extracts. Results: In unaffected myoblasts, hyperosmolar stress ensues in NFAT5 nuclear translocation and increased NFAT5 mRNA and protein expression. In contrast, pro-inflammatory cytokines did not lead to NFAT5 nuclear translocation nor increased expression. Cytokines IL-1β with IFN-γ induced colocalization of NFAT5 with histone deacetylase 6 (HDAC6), involved in cell motility. In muscle biopsies from dermatomyositis and polymyositis patients, NFAT5 colocalized with HDAC6, while in IBM, this was often absent. Conclusions: Our data suggest impaired NFAT5 localization and expression in unaffected myoblasts in response to inflammation. This disturbed myogenic NFAT5 physiology could possibly explain deleterious effects on muscle regeneration in myositis.