Zipper plot : visualizing transcriptional activity of genomic regions

Background: Reconstructing transcript models from RNA-sequencing (RNA-seq) data and establishing these as independent transcriptional units can be a challenging task. Current state-of-the-art tools for long non-coding RNA (lncRNA) annotation are mainly based on evolutionary constraints, which may result in false negatives due to the overall limited conservation of lncRNAs. Results: To tackle this problem we have developed the Zipper plot, a novel visualization and analysis method that enables users to simultaneously interrogate thousands of human putative transcription start sites (TSSs) in relation to various features that are indicative for transcriptional activity. These include publicly available CAGE-sequencing, ChIP-sequencing and DNase-sequencing datasets. Our method only requires three tab-separated fields (chromosome, genomic coordinate of the TSS and strand) as input and generates a report that includes a detailed summary table, a Zipper plot and several statistics derived from this plot. Conclusion: Using the Zipper plot, we found evidence of transcription for a set of well-characterized lncRNAs and observed that fewer mono-exonic lncRNAs have CAGE peaks overlapping with their TSSs compared to multi-exonic lncRNAs. Using publicly available RNA-seq data, we found more than one hundred cases where junction reads connected protein-coding gene exons with a downstream mono-exonic lncRNA, revealing the need for a careful evaluation of lncRNA 5′-boundaries. Our method is implemented using the statistical programming language R and is freely available as a webtool

Long non-coding RNAs as novel components in the TP53 pathway

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SMARTer single cell total RNA-sequencing

Single cell RNA sequencing methods have been increasingly used to understand cellular heterogeneity. Nevertheless, most of these methods suffer from one or more limitations, such as focusing only on polyadenylated RNA, sequencing of only the 3' end of the transcript, an exuberant fraction of reads mapping to ribosomal RNA, and the unstranded nature of the sequencing data. Here, we developed a novel single cell strand-specific total RNA library preparation method addressing all the aforementioned shortcomings. Our method was validated on a microfluidics system using three different cancer cell lines undergoing a chemical or genetic perturbation and on two other cancer cell lines sorted in microplates. We demonstrate that our total RNA-seq method detects an equal or higher number of genes compared to classic polyA[+] RNA-seq, including novel and non-polyadenylated genes. The obtained RNA expression patterns also recapitulate the expected biological signal. Inherent to total RNA-seq, our method is also able to detect circular RNAs. Taken together, SMARTer single cell total RNA sequencing is very well suited for any single cell sequencing experiment in which transcript level information is needed beyond polyadenylated genes

SMARTer single cell total RNA sequencing

Single cell RNA sequencing methods have been increasingly used to understand cellular heterogeneity. Nevertheless, most of these methods suffer from one or more limitations, such as focusing only on polyadenylated RNA, sequencing of only the 3' end of the transcript, an exuberant fraction of reads mapping to ribosomal RNA, and the unstranded nature of the sequencing data. Here, we developed a novel single cell strand-specific total RNA library preparation method addressing all the aforementioned shortcomings. Our method was validated on a microfluidics system using three different cancer cell lines undergoing a chemical or genetic perturbation and on two other cancer cell lines sorted in microplates. We demonstrate that our total RNA-seq method detects an equal or higher number of genes compared to classic polyA[+] RNA-seq, including novel and non-polyadenylated genes. The obtained RNA expression patterns also recapitulate the expected biological signal. Inherent to total RNA-seq, our method is also able to detect circular RNAs. Taken together, SMARTer single cell total RNA sequencing is very well suited for any single cell sequencing experiment in which transcript level information is needed beyond polyadenylated genes

TBX2 is a neuroblastoma core regulatory circuitry component enhancing MYCN/FOXM1 reactivation of DREAM targets

Chromosome 17q gains are almost invariably present in high-risk neuroblastoma cases. Here, we perform an integrative epigenomics search for dosage-sensitive transcription factors on 17q marked by H3K27ac defined super-enhancers and identify TBX2 as top candidate gene. We show that TBX2 is a constituent of the recently established core regulatory circuitry in neuroblastoma with features of a cell identity transcription factor, driving proliferation through activation of p21-DREAM repressed FOXM1 target genes. Combined MYCN/TBX2 knockdown enforces cell growth arrest suggesting that TBX2 enhances MYCN sustained activation of FOXM1 targets. Targeting transcriptional addiction by combined CDK7 and BET bromodomain inhibition shows synergistic effects on cell viability with strong repressive effects on CRC gene expression and p53 pathway response as well as several genes implicated in transcriptional regulation. In conclusion, we provide insight into the role of the TBX2 CRC gene in transcriptional dependency of neuroblastoma cells warranting clinical trials using BET and CDK7 inhibitors

LncRNAs as novel players in neuroblastoma tumor biology

In neuroblastoma, several protein coding genes are established as key players in the tumorigenesis and pathogenesis, such as ALK, MYCN and PHOX2B. These proteins regulate a plethora of other genes, however, little is known about their non-coding targets. Based on the combination of RNA sequencing data of 497 primary tumor samples and model systems for MYCN, ALK and PHOX2B, we could demonstrate that each of these key neuroblastoma genes regulate a core set of lincRNAs, some of which were associated with certain disease stages or survival. Furthermore, we analyzed the data to find lincRNAs that modulate the effect or are in charge of the regulation of these genes. Through a state-of-the-art computational workflow, various lincRNAs were identified as a functional member of the networks surrounding these key genes. Both approaches allowed us to establish a core set of lincRNAs with a potential implication in this pediatric malignancy. To confirm one of these results, we have experimentally validated our top candidate, a neuroblastoma specific lincRNA with an association with PHOX2B and overall survival. NESPR (NEuroblastoma Specific Phox2B Regulatory rna) is located in the genomic region of PHOX2B and is a member of the noradrenergic core regulatory circuit (CRC) in charge of neuroblastoma cell identity. Through antisense oligonucleotide (ASO) mediated downregulation of NESPR, we evaluated its functional role and revealed a link between expression patterns of NESPR and PHOX2B. Next to PHOX2B, 780 other genes were perturbed, including members of the noradrenergic and mesenchymal CRC. Reduced levels of NESPR also resulted in a decreased growth rate and subsequently apoptosis. The suspected mechanism through which NESPR operates involves the formation of chromatin structures to regulate PHOX2B expression. However, activity independent of PHOX2B has been identified through ChIRP sequencing, where motif enrichments of GATA3 and ISL1, two transcription factors of the noradrenergic CRC, were found. The results from these studies suggest that key neuroblastoma genes regulate a set of lincRNAs, which can play a role in neuroblastoma initiation and pathogenesis. Through experimental validation of one of the candidate genes, we confirmed its suspected functional activity in this pediatric malignancy. However, further experiments are essential to confirm functionality of the other lincRNAs contained in our core set