A Reference Transcript Database for improved analysis of RNA-seq data from barley

术语“基因表达”是指基因产生蛋白质的生物过程。在真核生物中，基因表达是复杂的。基因的DNA序列首先通过转录过程复制成前体信使RNA（pre-mRNA），并且前体mRNA经历几个加工步骤以形成成熟信使RNA（mRNA），其是合成相应蛋白质的模板。转录后加工步骤可以从相同基因产生不同的mRNA转录物（即转录物同种型），有效地调节个体转录物丰度和潜在的蛋白质功能。具有来自单个基因的多个转录物同种型在以下方面是有问题的：1）定义单个转录物同种型的表达水平以及它们在不同条件下如何变化，以及2）确定它们的特征-例如它们是否编码蛋白质同种型。由于基因表达数据被广泛用于推导生物学推断，例如，通过根据共同的表达模式对基因进行分组，如果不考虑替代转录物的相对丰度，将必然产生错误的结论。在这个项目中，我们专注于开发一种资源/工具，可以准确检测和定量大麦中的mRNA转录异构体。该工具将能够在个体转录水平上对基因表达的动态变化进行高分辨率分析，并且作为一个公认的和可访问的参考，将有助于统一和构建整个研究社区的此类分析。科学家们用来将基因与功能联系起来的主要方法之一是监测基因表达的模式：即基因在何时何地开启或关闭，以及在什么水平上开启或关闭。目前的方法通过计数对应于特定样品中给定mRNA相对于整个mRNA群体的非常特异性序列的出现频率并将这些计数转化为相对丰度水平来提供基因表达的总体测量。然而，这些方法不能区分个体同种型变体的丰度，特别是那些决定蛋白质水平、结构和活性的变体。我们称之为“参考转录数据库”或RTD的工具。RTD实际上是存在于来自单个生物体的不同范围的组织中的所有转录物同种型的文库。通过在基因表达研究中使用RTD，我们可以识别和确定不同的转录异构体的丰度容易和快速，这些可以用于随后的功能analysis.We将这个项目集中在作物，大麦，一个模型的小粒小麦族谷物，包括小麦和黑麦。RTD将允许在受到一系列条件或处理的植物的转录水平上容易地分析对全局和特定基因表达的影响，从而提高我们社区探索和理解广泛生物过程的能力。RTD将由詹姆斯赫顿研究所的大麦和计算科学小组进行更新和长期维护。

The term 'gene expression' refers to the biological process by which a gene gives rise to a protein. In eukaryotes, gene expression is complex. The DNA sequence of the gene is first copied into a precursor messenger RNA (pre-mRNA) by the process of transcription and the pre-mRNA subjected to several processing steps to form a mature messenger RNA (mRNAs) that is the template for synthesis of the corresponding protein. The post-transcriptional processing steps can generate different mRNA transcripts from the same gene (i.e. transcript isoforms), effectively modulating individual transcript abundance and potentially protein function. Having multiple transcript isoforms from a single gene is problematic in terms of 1) defining the expression levels of individual transcript isoforms and how they change under different conditions, and 2) determining their characteristics - such as whether they encode protein isoforms or not. As gene expression data is widely used to derive biological inference, for example, by grouping genes according to common patterns of expression, failure to take account of the relative abundance of alternative transcripts will unavoidably generate false conclusions. In this project, we focus on the development of a resource/tool that will allow the accurate detection and quantification of mRNA transcript isoforms in barley. The tool will enable high resolution analysis of dynamic changes in gene expression at the individual transcript level and as a recognised and accessible reference will help unify and structure such analyses across a research community. One of the main approaches scientists use to associate genes with functions is to monitor patterns of gene expression: i.e. where and when genes are switched on or off, and at what level. Current approaches provide an overall measure of gene expression by counting the frequency of occurrence of very specific sequences that correspond to a given mRNA relative to the whole population of mRNAs in a particular sample and transforming these counts into relative abundance levels. However these methods are unable to distinguish the abundance of individual isoform variants, in particular those that determine protein levels, structures and activities. We call the tool a 'Reference Transcript Database' or RTD. The RTD is effectively a library of all of the transcript isoforms that exist in a diverse range of tissues from a single organism. By using the RTD in gene expression studies we can identify and determine the abundance of different transcript isoforms easily and quickly, and these can be used in subsequent functional analyses.We focus this project on the crop plant, barley, a model for the small grain Triticeae cereals that include wheat and rye. The RTD will allow effects on global and specific gene expression to be easily analysed at the transcript level in plants subjected to a range of conditions or treatments, improving our community's ability to explore and understand a wide range of biological processes. The RTD will be refreshed and maintained longer term by the barley and computational sciences groups at the James Hutton Institute.