Computational Approaches for Mining GRO-Seq Data to Identify and Characterize Active Enhancers.

Computational Approaches for Mining GRO-Seq Data to Identify and Characterize Active Enhancers.
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挖掘 GRO-Seq 数据以识别和表征活性增强子的计算方法。

DOI:
10.1007/978-1-4939-4035-6_10
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发表时间:
2017
期刊:
Methods in molecular biology (Clifton, N.J.)
影响因子:
--
通讯作者:
Kraus WL
Kraus WL
中科院分区:
其他
文献类型:
--
作者:
Nagari A;Murakami S;Malladi VS;Kraus WL

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转录增强子是与转录因子结合的DNA调控元件,其作用是正向调节近端或远端靶基因的表达。增强子具有许多已通过基因组分析发现的特征。最近的研究表明,活性增强子招募RNA聚合酶II (Pol II)并进行转录,产生增强子RNA (eRNAs)。GRO-seq是一种鉴定基因组中所有活性转录RNA聚合酶的位置和方向的方法,是监测新生增强子转录的有力方法。此外,增强子转录的独特模式可用于在缺乏有关潜在转录因子的任何信息的情况下识别增强子。在这里,我们描述了使用GRO-seq数据识别和分析活性增强子所需的计算方法,包括数据预处理、比对和转录本调用。此外,我们描述了挖掘GRO-seq的协议和计算管道,以识别活性增强子,以及转录的已知转录因子结合位点。此外,我们还讨论了将基于gro -seq的增强子数据与其他基因组数据(包括靶基因表达和功能)整合的方法。最后,我们描述了分子生物学分析,可用于确认和进一步探索已通过基因组分析确定的增强子的功能。总之,这些方法应该允许用户识别和探索新的细胞类型特异性增强子的特征和生物学功能。
Transcriptional enhancers are DNA regulatory elements that are bound by transcription factors and act to positively regulate the expression of nearby or distally-located target genes. Enhancers have many features that have been discovered using genomic analyses. Recent studies have shown that active enhancers recruit RNA polymerase II (Pol II) and are transcribed, producing enhancer RNAs (eRNAs). GRO-seq, a method for identifying the location and orientation of all actively transcribing RNA polymerases across the genome, is a powerful approach for monitoring nascent enhancer transcription. Furthermore, the unique pattern of enhancer transcription can be used to identify enhancers in the absence of any information about the underlying transcription factors. Here we describe the computational approaches required to identify and analyze active enhancers using GRO-seq data, including data pre-processing, alignment, and transcript calling. In addition, we describe protocols and computational pipelines for mining GRO-seq to identify active enhancers, as well as known transcription factor binding sites that are transcribed. Furthermore, we discuss approaches for integrating GRO-seq-based enhancer data with other genomic data, including target gene expression and function. Finally, we describe molecular biology assays that can be used to confirm and explore further the function of enhancers that have been identified using genomic assays. Together, these approaches should allow the user to identify, and explore the features and biological functions of new cell type-specific enhancers.