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中文摘要
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描述(申请人提供):创新的高通量全基因组方法和技术的发展,如RNA-SEQ和CHIP-SEQ,使识别和分析所有编码和非编码RNA以及绘制表观遗传标记和转录因子结合位点图成为可能。然而,RNA-Seq通常是使用从细胞或组织中分离的总RNA来执行的,这种分析将产生稳定水平的RNA的特征,但不会告知特定的基因表达变化是否是由于转录改变和/或RNA稳定性改变。最近,已经发展了许多不同的方法来估计基因组序列的新生转录,如Gro-Seq,Net-Seq,以及通过代谢标记和分离新生RNA。我们将在这一R01应用程序中进一步开发和验证两种方法,我们认为这两种方法为现有技术增加了重要的新能力,用于全面和高通量地探索人类细胞中的基因表达特征。BruChase-Seq是基于溴追逐标记和深度测序相结合的方法,直接测量所有初级和成熟的mRNA以及非编码RNA的合成和降解动力学,并确定所有内含子序列的剪接动力学。BRIV-Seq在Bru标记之前通过紫外光引入随机的转录阻断损伤,识别转录起始位点(TSS),可能的增强子元件,并通过稳定如果完全转录可能不稳定的转录本,从而允许更敏感的检测。这些进展中的每一项都有可能极大地扩展当前的基因组注释,方法是对已知基因进行额外的功能评估,显示基因部分如何独立发挥作用,以及识别神秘的基因间元件。
英文摘要
DESCRIPTION (provided by applicant): The development of innovative high throughput genome-wide methodologies and technologies such as RNA-Seq and ChIP-Seq have made it possible to identify and analyze all coding and non-coding RNAs as well as map epigenetic marks and transcription factor binding sites. However, RNA-Seq is typically performed using total RNA isolated from cells or tissues and such analysis will generate signatures of steady-state levels of RNA but will not inform on whether particular gene expression alterations are due to altered transcription and/or altered RNA stability. Recently, a number of different approaches have been developed to estimate nascent transcription of genomic sequences such as GRO-Seq, NET-Seq and by metabolic labeling and isolated of nascent RNA. We will in this R01 application further develop and validate two approaches that we believe add important new capabilities to existing techniques for the comprehensive and high throughput exploration of gene expression signatures in human cells. BruChase-Seq is based on bromouridine pulse-chase labeling coupled to deep sequencing directly measuring the kinetics of synthesis and degradation of all primary and mature mRNAs and non-coding RNAs as well as determines splicing kinetics of all intron sequences. BrUV-Seq introduces random transcription-blocking lesions by UV light prior to BrU-labeling, identifying transcription start sites (TSS), putative enhancer elements and by stabilizing transcripts that might be labile if completely transcribed allowing their more sensitive detection. Each of these advances has the potential to greatly expand current genomic annotations by assigning additional functional assessments to known genes, showing how the parts of genes act independently, and identifying cryptic intergenic elements.
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