Transcriptome profiling by high throughput RNA Sequencing

描述（由申请人提供）：大规模并行cDNA测序（RNA-seq）的最新进展为转录组的综合分析铺平了道路，转录组是一组所有RNA分子，包括一个或多个细胞群体中的mRNA、rRNA、tRNA和其他非编码RNA。RNA-Seq可以识别转录边界的精确位置，显示外显子是如何连接的，并揭示转录区域的序列变异。总而言之，RNA-Seq是第一种基于测序的方法，其允许以非常高通量和定量的方式调查整个转录组，提供用于注释的单碱基分辨率和基因组规模的数字基因表达水平。然而，该技术正在积极开发中，并且在文库制备过程中存在几个酶促步骤，其可能导致序列依赖性偏倚，阻碍基因组区域之间的比较并不利地影响transriptome分析。用于在RNA-Seq中添加衔接子序列的连接酶具有基于结构的偏好，产生第一cDNA链的逆转录酶易于复制错误和重排，并且用于扩增的聚合酶在接近富含GC / AT的区域时经常出错。该项目的目标是创建一个文库制备试剂盒，用于制作用于深度测序的最小偏差，高度索引的RNA-Seq文库，其构建方式允许转录组图谱容易和公平地查询。我们的建议是开发技术，以无偏见的，高通量的方式研究转录组，这将使未来的临床应用成为现实，并推动比较组织疾病谱的研究，进一步解锁转录调控。

DESCRIPTION (provided by applicant): Recent advances in massively parallel cDNA sequencing (RNA-seq) have paved the way for comprehensive analysis of the transcriptome, a set of all RNA molecules including mRNA, rRNA, tRNA and other non-coding RNAs in one or more populations of cells. RNA-Seq can identify the precise location of transcription boundaries, show how exons are connected and reveal sequence variations in transcribed regions. Taken together, RNA-Seq is the first sequencing based method that allows the entire transciptome to be surveyed in a very high- throughput and quantitative manner, offering both single-base resolution for annotation and digital gene expression levels at the genome scale. However, this technology is under active development and there are several enzymatic steps during library preparation that can contribute to sequence dependent bias, hindering comparisons between genomic regions and adversely affecting transriptome profiling. Ligases used to add on adapter sequences in RNA- Seq have structure based preferences, reverse transcriptases that make the first cDNA strand are prone to copy errors and rearrangements, and polymerases used for amplification often stumble when approaching GC / AT rich regions. The goal of this project is to create a library preparation kit for making minimally biased, highly indexed RNA-Seq libraries for deep sequencing that are constructed in a way to allow transcriptome profiles to be easily and fairly interrogated. Our proposal to develop technology to study the transcriptome in an unbiased, high-throughput manner should make future clinical applications a reality and propel research in comparative tissue disease profiles, further un-locking transcriptional regulation.