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2.
Nucleic Acids Res ; 47(16): e93, 2019 09 19.
Artigo em Inglês | MEDLINE | ID: mdl-31216024

RESUMO

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.


Assuntos
Sequenciamento de Nucleotídeos em Larga Escala/métodos , RNA Circular/análise , RNA Mensageiro/análise , RNA Ribossômico/análise , Análise de Célula Única/métodos , Benchmarking , Linhagem Celular Tumoral , Biblioteca Gênica , Humanos , Técnicas Analíticas Microfluídicas , Poli A/genética , Poli A/metabolismo , RNA Circular/genética , RNA Mensageiro/genética , RNA Ribossômico/genética , Análise de Sequência de RNA/estatística & dados numéricos
3.
Sci Rep ; 9(1): 5685, 2019 04 05.
Artigo em Inglês | MEDLINE | ID: mdl-30952905

RESUMO

Long intergenic non-coding RNAs (lincRNAs) are emerging as integral components of signaling pathways in various cancer types. In neuroblastoma, only a handful of lincRNAs are known as upstream regulators or downstream effectors of oncogenes. Here, we exploit RNA sequencing data of primary neuroblastoma tumors, neuroblast precursor cells, neuroblastoma cell lines and various cellular perturbation model systems to define the neuroblastoma lincRNome and map lincRNAs up- and downstream of neuroblastoma driver genes MYCN, ALK and PHOX2B. Each of these driver genes controls the expression of a particular subset of lincRNAs, several of which are associated with poor survival and are differentially expressed in neuroblastoma tumors compared to neuroblasts. By integrating RNA sequencing data from both primary tumor tissue and cancer cell lines, we demonstrate that several of these lincRNAs are expressed in stromal cells. Deconvolution of primary tumor gene expression data revealed a strong association between stromal cell composition and driver gene status, resulting in differential expression of these lincRNAs. We also explored lincRNAs that putatively act upstream of neuroblastoma driver genes, either as presumed modulators of driver gene activity, or as modulators of effectors regulating driver gene expression. This analysis revealed strong associations between the neuroblastoma lincRNAs MIAT and MEG3 and MYCN and PHOX2B activity or expression. Together, our results provide a comprehensive catalogue of the neuroblastoma lincRNome, highlighting lincRNAs up- and downstream of key neuroblastoma driver genes. This catalogue forms a solid basis for further functional validation of candidate neuroblastoma lincRNAs.


Assuntos
Neuroblastoma/genética , RNA Longo não Codificante/genética , Linhagem Celular Tumoral , Tecnologia de Impulso Genético/métodos , Perfilação da Expressão Gênica/métodos , Humanos , Células-Tronco Neurais/fisiologia , Análise de Sequência de RNA/métodos , Transdução de Sinais/genética , Fatores de Transcrição/genética
4.
Nat Commun ; 9(1): 4866, 2018 11 19.
Artigo em Inglês | MEDLINE | ID: mdl-30451831

RESUMO

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.


Assuntos
Neoplasias Encefálicas/genética , Proteína Forkhead Box M1/genética , Regulação Neoplásica da Expressão Gênica , Proteínas Interatuantes com Canais de Kv/genética , Proteína Proto-Oncogênica N-Myc/genética , Neuroblastoma/genética , Proteínas Repressoras/genética , Proteínas com Domínio T/genética , Antineoplásicos/farmacologia , Azepinas/farmacologia , Neoplasias Encefálicas/tratamento farmacológico , Neoplasias Encefálicas/metabolismo , Neoplasias Encefálicas/patologia , Linhagem Celular Tumoral , Sobrevivência Celular/efeitos dos fármacos , Quinases Ciclina-Dependentes/genética , Quinases Ciclina-Dependentes/metabolismo , Variações do Número de Cópias de DNA , Epigênese Genética , Proteína Forkhead Box M1/metabolismo , Células HEK293 , Histonas/genética , Histonas/metabolismo , Humanos , Proteínas Interatuantes com Canais de Kv/metabolismo , Proteína Proto-Oncogênica N-Myc/metabolismo , Neuroblastoma/tratamento farmacológico , Neuroblastoma/metabolismo , Neuroblastoma/patologia , Organoides/efeitos dos fármacos , Organoides/metabolismo , Organoides/patologia , Panobinostat/farmacologia , Fenilenodiaminas/farmacologia , Pirimidinas/farmacologia , Proteínas Repressoras/metabolismo , Transdução de Sinais , Proteínas com Domínio T/metabolismo , Triazóis/farmacologia , Proteína Supressora de Tumor p53/genética , Proteína Supressora de Tumor p53/metabolismo , Quinase Ativadora de Quinase Dependente de Ciclina
5.
BMC Bioinformatics ; 18(1): 231, 2017 May 02.
Artigo em Inglês | MEDLINE | ID: mdl-28464823

RESUMO

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.


Assuntos
Genômica/métodos , RNA Longo não Codificante/genética , Análise de Sequência de RNA/métodos , Software , Imunoprecipitação da Cromatina , Humanos , Sítio de Iniciação de Transcrição
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