Background Nurr1 is a member of the nuclear receptor superfamily of transcription factors. The objective of the present study was to identify novel splicing variants of the gene in neuronal and non-neuronal tissues an...Background Nurr1 is a member of the nuclear receptor superfamily of transcription factors. The objective of the present study was to identify novel splicing variants of the gene in neuronal and non-neuronal tissues and determine their functions. Methods Reverse transcription-polymerase chain reaction (RT-PCR) analysis was used to screen for Nurr1 splice variants in the adult human central nervous system (CNS) and in other tissues such as lymphocytes,and liver,muscle,and kidney cells. Functional assays of the variants were performed by measuring Nurr1 response element (NuRE) transcriptional activity in vitro . Results In this study,the authors identified a novel splicing variant of Nurr1 within exon 5,found in multiple adult human tissues,including lymphocytes,and liver,muscle,and kidney cells,but not in the brain or spinal cord. Sequencing analysis showed the variant has a 75 bp deletion between nucleotides 1402 and 1476. A functional assay of the Nurr1-c splicing variant,performed by measuring NuRE transcriptional activity in vitro,detected a 39% lower level of luciferase (LUC) activity ( P <0.05).Conclusion A novel splicing variant of Nurr1 exists in human non-neuronal tissues and functional assays suggest that the variant may act as an alternate transcription regulator.展开更多
Background： Since the invention of next-generation RNA sequencing （RNA-seq） technologies, they have become a powerful tool to study the presence and quantity of RNA molecules in biological samples and have revoluti...Background： Since the invention of next-generation RNA sequencing （RNA-seq） technologies, they have become a powerful tool to study the presence and quantity of RNA molecules in biological samples and have revolutionized transcriptomic studies. The analysis of RNA-seq data at four different levels （samples, genes, transcripts, and exons） involve multiple statistical and computational questions, some of which remain challenging up to date. Results： We review RNA-seq analysis tools at the sample, gene, transcript, and exon levels from a statistical perspective. We also highlight the biological and statistical questions of most practical considerations. Conclusions： The development of statistical and computational methods for analyzing RNA-seq data has made significant advances in the past decade. However, methods developed to answer the same biological question often rely on diverse statistical models and exhibit different performance under different scenarios. This review discusses and compares multiple commonly used statistical models regarding their assumptions, in the hope of helping users select appropriate methods as needed, as well as assisting developers for future method development.展开更多
文摘Background Nurr1 is a member of the nuclear receptor superfamily of transcription factors. The objective of the present study was to identify novel splicing variants of the gene in neuronal and non-neuronal tissues and determine their functions. Methods Reverse transcription-polymerase chain reaction (RT-PCR) analysis was used to screen for Nurr1 splice variants in the adult human central nervous system (CNS) and in other tissues such as lymphocytes,and liver,muscle,and kidney cells. Functional assays of the variants were performed by measuring Nurr1 response element (NuRE) transcriptional activity in vitro . Results In this study,the authors identified a novel splicing variant of Nurr1 within exon 5,found in multiple adult human tissues,including lymphocytes,and liver,muscle,and kidney cells,but not in the brain or spinal cord. Sequencing analysis showed the variant has a 75 bp deletion between nucleotides 1402 and 1476. A functional assay of the Nurr1-c splicing variant,performed by measuring NuRE transcriptional activity in vitro,detected a 39% lower level of luciferase (LUC) activity ( P <0.05).Conclusion A novel splicing variant of Nurr1 exists in human non-neuronal tissues and functional assays suggest that the variant may act as an alternate transcription regulator.
文摘Background： Since the invention of next-generation RNA sequencing （RNA-seq） technologies, they have become a powerful tool to study the presence and quantity of RNA molecules in biological samples and have revolutionized transcriptomic studies. The analysis of RNA-seq data at four different levels （samples, genes, transcripts, and exons） involve multiple statistical and computational questions, some of which remain challenging up to date. Results： We review RNA-seq analysis tools at the sample, gene, transcript, and exon levels from a statistical perspective. We also highlight the biological and statistical questions of most practical considerations. Conclusions： The development of statistical and computational methods for analyzing RNA-seq data has made significant advances in the past decade. However, methods developed to answer the same biological question often rely on diverse statistical models and exhibit different performance under different scenarios. This review discusses and compares multiple commonly used statistical models regarding their assumptions, in the hope of helping users select appropriate methods as needed, as well as assisting developers for future method development.
