Deep Transcriptional Profiling of Rice Using Signature Sequencing

水稻是重要的作物，养活了世界上一半以上的人口，也是美国具有重要经济意义的谷类作物的典范。最近获得的基因组序列有助于水稻基因的功能分析和分子研究。然而，这些基因中的大多数还只是通过计算而不是实验方法来定义的;计算基因预测可能无法识别染色体序列中的所有RNA转录本。 该项目将使用一种称为“大规模并行签名测序”（MPSS）的转录谱分析技术来表征水稻转录本的多样性和表达模式。确定水稻基因组中基因表达的模式和水平将促进我们对水稻分子生物学和控制重要农艺性状的遗传因素的理解。对水稻的这种分析对其他经济上重要的谷物如玉米、小麦、高粱和大麦的改良具有广泛的实际意义，因为这些物种中存在的几乎所有基因都可能在水稻中具有同源物。MPSS数据将用于识别计算方法遗漏的基因，并将提供验证许多先前预测但从未实验证实的基因的数据。MPSS将用于评估在以下条件下的基因表达：-在不同的未处理的水稻组织和这些组织在寒冷，干旱和盐胁迫下的子集。在感病和抗病植株的真菌或细菌感染的水稻组织中。将在感染或耐药反应期间测定一系列时间点。在“籼稻"背景和籼粳杂交种中，该实验将测量两个水稻品种之间基因表达的差异，其中基因组序列是可用的。通过MPSS技术鉴定的新转录本将通过微阵列分析和通过测序超过500个新转录本来验证。所有这些数据（MPSS，微阵列和转录本的序列验证）将通过项目网页公开提供。 该网站将包括查询和分析工具，以方便公众使用水稻MPSS数据，并将显示水稻MPSS签名的丰度和染色体位置。该网站将类似于我们为双子叶植物模式拟南芥开发的网站（http：//www.dbi.udel.edu/mpss）。

Rice is important both as a crop plant that feeds more than half of the world's population and as a model for cereal crops of great economic importance in the US. The recent availability of the genomic sequence facilitates functional analysis and molecular studies of the rice genes. However, most of these genes are as yet defined only by computational and not experimental approaches; computational gene predictions may not identify all RNA transcripts within the chromosomal sequence. This project will use a transcriptional profiling technology called "massively parallel signature sequencing" (MPSS) to characterize the diversity and expression patterns of rice transcripts. Defining the patterns and levels of gene expression in the rice genome will advance our understanding of rice molecular biology and genetic factors controlling important agronomical traits. This analysis of rice has broad practical implications for the improvement of other economically important cereals, such as corn, wheat, sorghum and barley, because nearly all genes present in these species are likely to have homologs in rice. The MPSS data will be used to identify genes missed by computational approaches and will provide data that validate many genes previously predicted but never confirmed experimentally. MPSS will be used to assess gene expression under the following conditions: -In diverse untreated rice tissues and a subset of these tissues under cold, drought and salt stress.-In fungal- or bacterial-infected rice tissues in both susceptible and resistant plants. A series of timepoints will be assayed during the infection or resistance response.-In an 'Indica' rice background and in a hybrid of Indica x Japonica; this experiment will measure differences in gene expression between the two rice varieties for which genomic sequence is available.The novel transcripts identified by the MPSS technology will be validate by microarray analysis and by sequencing more than 500 novel transcripts. All of these data (MPSS, microarray, and sequence validation of transcripts) will be made publicly available through a project webpage. This web site will include query and analysis tools to facilitate public use of the rice MPSS data and will display the abundance and chromosomal locations of rice MPSS signatures. This website will be similar to that which we have developed for the model dicot, Arabidopsis (http://www.dbi.udel.edu/mpss).