整合基因组范围代谢网络模型和转录组数据的毛竹生物质代谢通路研究

Moso bamboo is peculiar to a kind of bamboo in china, which has some advantages, such as widely distribution, most planting areas (accounting for over two-thirds of totally planting areas in china), and highly economic value. In the wake of the completion of moso genome sequencing, moso bamboo has become one of the significant subject in the aspect of developing and utilizing the biomass energy. Because it is difficult to form the integrated realization based on scattered and huge information, a systematic method will be need in order to better understand the metabolic features of moso bamboo biomass. GSMN method starts from genomic data, and then builds the relationship among gene, protein and reaction from low to high. GSMN will simulate metabolic characteristics of moso bamboo as authentic as possible through translating the scattered DNA information to a simulated function network by using computer. To build moso bamboo GSMN with highly accuracy, the construction for moso bamboo is not only ability to using the genome of moso bamboo, but also to integrating the various transcriptome of moso bamboo. More importantly, in this project, we will focus on analysis and prediction about metabolic pathways and essential elements for biomass synthesis of moso bamboo, and predicted the varying patterns of biomass synthesis in different condition. This study will provide the guidance of molecule experiments and lay the foundation for subsequent genetic engineering of bamboo.

毛竹是我国特有且分布范围最广、面积最大、经济价值最高的竹种。随着毛竹基因组测序完成，毛竹在生物质能源开发利用方面的优势日趋凸显。但要从零散且数量巨大的数据中形成整体认识，则需要一套系统学的研究方法。基因组范围代谢网络（GSMN）是以系统生物学为研究策略，以生物质代谢通路为主要研究对象，从基因组数据出发，通过基因-蛋白-反应，从低到高映射，将生物体零散的DNA信息翻译成一个较为准确模拟细胞代谢的计算机功能网络。毛竹GSMN的构建不仅利用毛竹基因组数据，而且还整合毛竹转录组数据，最大限度确保模型的准确可靠。基于毛竹GSMN，本项目将重点分析、预测参与其生物质相关的代谢通路和关键因子、揭示代谢通路特点和预测不同条件下生物质相关代谢的变化规律，这不仅为竹类植物的遗传改良及基因发掘研究提供了模型支持，而且对未来禾本科作物的品种改良、能源作物的遗传解析提供了重要的借鉴意义。

毛竹基因组序列草图及其功能基因组注释与分析平台的完成，为竹类植物后基因组学研究奠定了坚实的基础。在毛竹功能基因组研究中，全基因组代谢网络是研究其生长、发育等过程中的重要调控网络。本项目收集了全部已发表的毛竹转录组数据78份并加测了毛竹不同组织样品26份，采用系统生物学方法和CFinder等软件，构建了毛竹全基因组代谢网络（phGSMN），研究毛竹生物质代谢及其对胁迫作用应答的分子基础。通过比较分析快速生长期与材质生长期的多样本phGSMN，构建毛竹快速生长期的特异转录调控网络，解析网络各节点之间的相互作用关系，重点研究快速生长时期次生细胞壁生物合成和脱水胁迫等代谢过程中转录调控网络。最后，应用转录组数据和phGSMN全新构建了phGSMN平台，实现相关数据的便捷查询和使用，为后续实验验证提供数据支持。