Landscape of transcription in human and mouse

该项目的总体目标是使用各种高通量测序平台在人和鼠(C57BL/6NJ)组织和原代细胞系中生成精细结构的RNA图谱，通过确定是否可以确定其翻译产物的证据来评估新转录物的生物学意义。从每个被分析的样本中，我们建议从生物副本中分离长(&gt；200个核苷酸)和短(&lt；200个核苷酸)RNA。这些样本的Illumina图谱最初将使用(1)核糖体(r-)RNA耗尽的长总RNA的RNA测序(-seq)来生成。(2)烟草酸性焦磷酸酶(TAP)处理过的短RNA的RNA-SEQ；(3)总RNA的基因表达对端帽分析(PE-CAGE)。此外，对于原代细胞系的一个子集，我们将从核和细胞质亚细胞组分中生成上述文库。长的RNA-Seq数据将被蒸馏成功能元件，由剪接连接、多腺苷酸位点和从头基因和转录本组成。短RNA数据将被蒸馏成代表直到读取长度的短RNA的5‘端的重叠群。将分析PECAGE数据以形成代表转录本的5‘端的簇，该转录本链接到转录本主体内部的标签。重要的是，将使用非参数不可重现检测率(NplDR)脚本评估每个元素的重复性。总而言之，这些数据将允许检测 新的转录区和关于转录本的启动子区域和亚细胞驻留的支持性信息。总而言之，这些数据将被用来生成非编码和蛋白质编码转录本的模型，并区分复杂座位上的异构体，这是获得哺乳动物转录本的全面视图所必需的。对于这些样本的子集，我们将同时收集人类捐赠者的基因组序列，以提供一个参考图谱，该图谱将被用于对照RNA数据进行映射，并得出关于等位基因特异性表达和RNA编辑的信息。未加注释的转录模型将使用远程(PacBio/454)测序进行测试。最后，进行蛋白质组学分析，并将结果与未注释的转录本进行比较。

The overall goal of this project is to generate fine-structure RNA maps in human and mouse (C57BL/6NJ) tissues and primary cell lines using a variety of high-throughput sequencing platforms, to evaluate the biological importance of novel transcripts by determining if evidence of their translated products can be identified. From each sample analyzed, we propose to isolate long (>200 nucleotides) and short (< 200 nucleotides) RNA in biological duplicate. Illumina-based maps for these samples will initially be generated using (1) RNA sequencing (-seq) of ribosomal (r-)RNA depleted long total RNA. (2) RNA-seq of tobacco acid pyrophosphatase (TAP) pre-treated short RNA (3) Pair-end Cap Analysis of Gene Expression (PE-CAGE) of total RNA. Additionally, for a subset of primary cell lines we will generate the above libraries from nuclear and cytoplasmic subcellular fractions. Long RNA-Seq data will be distilled down into functional elements consisting of splice junctions, polyadenylatio sites and de novo genes and transcripts. The short RNA data will be distilled into contigs representing the 5' ends of short RNAs up to the read length. PE-CAGE data will be analyzed to form clusters representing the 5' ends of transcripts linked to a tag internal to the transcript body. Importantly, each element will be assessed for reproducibility using a nonparametric Irreproducible Detection Rate (nplDR) script. Collectively, these data will allow for the detection of novel transcribed regions and supportive information as to the location of promoter regions and subcellular residence of transcripts. In aggregate, these data will be used to generate models of both noncoding and protein coding transcripts and to distinguish isoforms at complex loci necessary to obtain a comprehensive view of mammalian transcriptomes. For a subset of these samples we will simultaneously collect the genome sequence of the human donors to provide a reference map that will be used to map the RNA data against and derive information concerning allele-specific expression and RNA editing. Unannotated transcript models will be tested using long-range (PacBio/454) sequencing. Lastly, proteogenomic analysis will be done and the results compared against the unannotated transcripts.