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玉米全基因组转录起始位点鉴定

Genome-Wide TSS Identification in Maize.

作者信息

Mejia-Guerra María Katherine, Li Wei, Doseff Andrea I, Grotewold Erich

机构信息

Department of Molecular Genetics, Center for Applied Plant Sciences (CAPS), The Ohio State University, Columbus, OH, USA.

Institute of Genomic Diversity, Cornell University, Ithaca, NY, USA.

出版信息

Methods Mol Biol. 2018;1830:239-256. doi: 10.1007/978-1-4939-8657-6_14.

Abstract

Regulation of gene expression is a fundamental biological process that relies on transcription factors (TF) recognizing specific cis motifs in the regulatory regions of the genes that they control. In most eukaryotic organisms, cis-regulatory elements are significantly enriched around the transcription start site (TSS). However, different from other genic features, TSSs need to be experimentally determined, becoming then important components of genome annotations. One of the methods for experimentally determining TSSs at the genome-wide level is CAGE (cap analysis of gene expression). This chapter describes how to prepare a CAGE library for sequencing, starting with RNA extraction, library construction, and quality controls before proceed to sequencing in the Illumina platform. We then describe how to use a computational pipeline to determine, from the alignment of CAGE tags, the genome-wide location of TSSs, followed with statistical approaches required to cluster TSSs that operate as transcriptional units, and to determine core promoter properties such as shape. The analyses described here focus on maize, since its large and yet deficiently annotated genome creates some unique challenges, but with some modifications can be easily adopted for other organisms as well.

摘要

基因表达调控是一个基本的生物学过程,它依赖于转录因子(TF)识别它们所控制基因的调控区域中的特定顺式基序。在大多数真核生物中,顺式调控元件在转录起始位点(TSS)周围显著富集。然而,与其他基因特征不同,TSS需要通过实验确定,因此成为基因组注释的重要组成部分。在全基因组水平上实验确定TSS的方法之一是CAGE(基因表达的帽分析)。本章描述了如何制备用于测序的CAGE文库,从RNA提取、文库构建和质量控制开始,然后在Illumina平台上进行测序。然后,我们描述了如何使用计算流程从CAGE标签的比对中确定全基因组范围内TSS的位置,接着是对作为转录单元的TSS进行聚类以及确定核心启动子特性(如形状)所需的统计方法。这里描述的分析主要集中在玉米上,因为其庞大且注释不足的基因组带来了一些独特的挑战,但经过一些修改后也可以很容易地应用于其他生物。

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