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类和小鼠（C57BL/6NJ）组织和原代细胞系中生成精细结构的RNA图谱，通过确定其翻译产物的证据是否可以被识别来评估新转录本的生物学重要性。从分析的每个样本中，我们建议在生物重复中分离长（约200个核苷酸）和短（约200个核苷酸）RNA。这些样品的基于illumina的图谱最初将使用(1)核糖体（r-）RNA耗尽长总RNA的RNA测序（-seq）生成。(2)烟草酸性焦磷酸酶（TAP）预处理短RNA的RNA-seq分析(3)总RNA基因表达的对端Cap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部分生成上述文库。长RNA-Seq数据将被提炼成由剪接、聚腺苷酸位点、新生基因和转录本组成的功能元件。短RNA数据将被提取成代表短RNA的5'端至读取长度的组群。将对PE-CAGE数据进行分析，形成簇，表示连接到转录体内部标签的转录体的5'端。重要的是，将使用非参数不可复制检测率（nplDR）脚本评估每个元素的可重复性。总的来说，这些数据将允许检测

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.