Pieter-Jan Volders

An update on LNCipedia: a database for annotated human lncRNA sequences

The human genome is pervasively transcribed, producing thousands of non-coding RNA transcripts. The majority of these transcripts are long non-coding RNAs (lncRNAs) and novel lncRNA genes are being identified at rapid pace. To streamline these efforts, we created LNCipedia, an online repository of lncRNA transcripts and annotation. Here, we present LNCipedia 3.0 (http://www.lncipedia.org), the latest version of the publicly available human lncRNA database. Compared to the previous version of LNCipedia, the database grew over five times in size, gaining over 90 000 new lncRNA transcripts. Assessment of the protein-coding potential of LNCipedia entries is improved with state-of-the art methods that include large-scale reprocessing of publicly available proteomics data. As a result, a high-confidence set of lncRNA transcripts with low coding potential is defined and made available for download. In addition, a tool to assess lncRNA gene conservation between human, mouse and zebrafish has been implemented.

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to keep their miRNA annotation up-to-date, reannotate analytical miRNA platforms and link published results with outdated annotation to the latest miRBase release.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

RNAcentral: a comprehensive database of non-coding RNA sequences

Abstract RNAcentral is a database of non-coding RNA (ncRNA) sequences that aggregates data from specialised ncRNA resources and provides a single entry point for accessing ncRNA sequences of all ncRNA types from all organisms. Since its launch in 2014, RNAcentral has integrated twelve new resources, taking the total number of collaborating database to 22, and began importing new types of data, such as modified nucleotides from MODOMICS and PDB. We created new species-specific identifiers that refer to unique RNA sequences within a context of single species. The website has been subject to continuous improvements focusing on text and sequence similarity searches as well as genome browsing functionality. All RNAcentral data is provided for free and is available for browsing, bulk downloads, and programmatic access at http://rnacentral.org/.RNAcentral is a database of non-coding RNA (ncRNA) sequences that aggregates data from specialised ncRNA resources and provides a single entry point for accessing ncRNA sequences of all ncRNA types from all organisms. Since its launch in 2014, RNAcentral has integrated twelve new resources, taking the total number of collaborating database to 22, and began importing new types of data, such as modified nucleotides from MODOMICS and PDB. We created new species-specific identifiers that refer to unique RNA sequences within a context of single species. The website has been subject to continuous improvements focusing on text and sequence similarity searches as well as genome browsing functionality. All RNAcentral data is provided for free and is available for browsing, bulk downloads, and programmatic access at http://rnacentral.org/.

The Notch driven long non-coding RNA repertoire in T-cell acute lymphoblastic leukemia

Genetic studies in T-cell acute lymphoblastic leukemia have uncovered a remarkable complexity of oncogenic and loss-of-function mutations. Amongst this plethora of genetic changes, NOTCH1 activating mutations stand out as the most frequently occurring genetic defect, identified in more than 50% of T-cell acute lymphoblastic leukemias, supporting a role as an essential driver for this gene in T-cell acute lymphoblastic leukemia oncogenesis. In this study, we aimed to establish a comprehensive compendium of the long non-coding RNA transcriptome under control of Notch signaling. For this purpose, we measured the transcriptional response of all protein coding genes and long non-coding RNAs upon pharmacological Notch inhibition in the human T-cell acute lymphoblastic leukemia cell line CUTLL1 using RNA-sequencing. Similar Notch dependent profiles were established for normal human CD34+ thymic T-cell progenitors exposed to Notch signaling activity in vivo. In addition, we generated long non-coding RNA expression profiles (array data) from ex vivo isolated Notch active CD34+ and Notch inactive CD4+CD8+ thymocytes and from a primary cohort of 15 T-cell acute lymphoblastic leukemia patients with known NOTCH1 mutation status. Integration of these expression datasets with publicly available Notch1 ChIP-sequencing data resulted in the identification of long non-coding RNAs directly regulated by Notch activity in normal and malignant T cells. Given the central role of Notch in T-cell acute lymphoblastic leukemia oncogenesis, these data pave the way for the development of novel therapeutic strategies that target hyperactive Notch signaling in human T-cell acute lymphoblastic leukemia.

Identification of long non-coding RNAs involved in neuronal development and intellectual disability

Recently, exome sequencing led to the identification of causal mutations in 16–31% of patients with intellectual disability (ID), leaving the underlying cause for many patients unidentified. In this context, the noncoding part of the human genome remains largely unexplored. For many long non-coding RNAs (lncRNAs) a crucial role in neurodevelopment and hence the human brain is anticipated. Here we aimed at identifying lncRNAs associated with neuronal development and ID. Therefore, we applied an integrated genomics approach, harnessing several public epigenetic datasets. We found that the presence of neuron-specific H3K4me3 confers the highest specificity for genes involved in neurodevelopment and ID. Based on the presence of this feature and GWAS hits for CNS disorders, we identified 53 candidate lncRNA genes. Extensive expression profiling on human brain samples and other tissues, followed by Gene Set Enrichment Analysis indicates that at least 24 of these lncRNAs are indeed implicated in processes such as synaptic transmission, nervous system development and neurogenesis. The bidirectional or antisense overlapping orientation relative to multiple coding genes involved in neuronal processes supports these results. In conclusion, we identified several lncRNA genes putatively involved in neurodevelopment and CNS disorders, providing a resource for functional studies.

ViVar: A Comprehensive Platform for the Analysis and Visualization of Structural Genomic Variation

Structural genomic variations play an important role in human disease and phenotypic diversity. With the rise of high-throughput sequencing tools, mate-pair/paired-end/single-read sequencing has become an important technique for the detection and exploration of structural variation. Several analysis tools exist to handle different parts and aspects of such sequencing based structural variation analyses pipelines. A comprehensive analysis platform to handle all steps, from processing the sequencing data, to the discovery and visualization of structural variants, is missing. The ViVar platform is built to handle the discovery of structural variants, from Depth Of Coverage analysis, aberrant read pair clustering to split read analysis. ViVar provides you with powerful visualization options, enables easy reporting of results and better usability and data management. The platform facilitates the processing, analysis and visualization, of structural variation based on massive parallel sequencing data, enabling the rapid identification of disease loci or genes. ViVar allows you to scale your analysis with your work load over multiple (cloud) servers, has user access control to keep your data safe and is easy expandable as analysis techniques advance. URL: https://www.cmgg.be/vivar/

Genome wide expression profiling of p53 regulated miRNAs in neuroblastoma

Restoration of the antitumor activity of p53 could offer a promising approach for the treatment of neuroblastoma. MicroRNAs (miRNAs) are important mediators of p53 activity, but their role in the p53 response has not yet been comprehensively addressed in neuroblastoma. Therefore, we set out to characterize alterations in miRNA expression that are induced by p53 activation in neuroblastoma cells. Genome-wide miRNA expression analysis showed that miR-34a-5p, miR-182-5p, miR-203a, miR-222-3p, and miR-432-5p are upregulated following nutlin-3 treatment in a p53 dependent manner. The function of miR-182-5p, miR-203a, miR-222-3p, and miR-432-5p was analyzed by ectopic overexpression of miRNA mimics. We observed that these p53-regulated miRNAs inhibit the proliferation of neuroblastoma cells to varying degrees, with the most profound growth inhibition recorded for miR-182-5p. Overexpression of miR-182-5p promoted apoptosis in some neuroblastoma cell lines and induced neuronal differentiation of NGP cells. Using Chromatin Immunoprecipitation-qPCR (ChIP-qPCR), we did not observe direct binding of p53 to MIR182, MIR203, MIR222, and MIR432 in neuroblastoma cells. Taken together, our findings yield new insights in the network of p53-regulated miRNAs in neuroblastoma.

Long noncoding RNA signatures define oncogenic subtypes in T-cell acute lymphoblastic leukemia

Long noncoding RNA signatures define oncogenic subtypes in T-cell acute lymphoblastic leukemia

Noncoding after All: Biases in Proteomics Data Do Not Explain Observed Absence of lncRNA Translation Products

Over the past decade, long noncoding RNAs (lncRNAs) have emerged as novel functional entities of the eukaryotic genome. However, the scientific community remains divided over the amount of true noncoding transcripts among the large number of unannotated transcripts identified by recent large scale and deep RNA-sequencing efforts. Here, we systematically exclude possible technical reasons underlying the absence of lncRNA-encoded proteins in mass spectrometry data sets, strongly suggesting that the large majority of lncRNAs is indeed not translated.

Long non-coding RNAs in cutaneous melanoma: clinical perspectives

Metastatic melanoma of the skin has a high mortality despite the recent introduction of targeted therapy and immunotherapy. Long non-coding RNAs (lncRNAs) are defined as transcripts of more than 200 nucleotides in length that lack protein-coding potential. There is growing evidence that lncRNAs play an important role in gene regulation, including oncogenesis. We present 13 lncRNA genes involved in the pathogenesis of cutaneous melanoma through a variety of pathways and molecular interactions. Some of these lncRNAs are possible biomarkers or therapeutic targets for malignant melanoma.