中国科学院昆明动物研究所机构知识库

环境选择压会促使群体的进化。相比于光合作用的自养植物，非光合作用植物从40支独立进化，在弱光条件下演化出独特的进化模式。为，了研究其中的分子进化机理，我们组装并解析了天麻基因组，也即迄今为止第一个非光合作用植物基因组。天麻在形态上出现了严重的根部退化和叶片的退化，在分子水平上，核基因组以及残留的叶绿体基因相关的光合作用基因出现了明显的选择放松信号，同时，在光合作用系统、叶片生长、质体分裂等方面也存在基因的缺失；天麻为了适应于真菌共生的独特模式，整个代谢通路进行了巨大重组，在碳代谢、氮代谢、生物节律、线粒体能量代谢、开花调控等方面都发生了不同程度的调控变化。天麻基因组不仅为我们揭示了非光合作用植物独特的进化模式，也为我们提供了一个新的真菌共生的研究模型。此外，天麻同时也是一种药用植物。目前，世界上50%的化药最初来源于植物。目前，合成生物学可以将植物中的相关合成基因导入到细菌中，合成目的化合物，多组学结合、上游数据与下游产业化结合发展成为当下药用植物研究趋势。而随着测序技术的发展和测序成本的降低，越来越多的研究者开始进行药用植物基因组学研究，近几年出现了不少数据“撞车”现象。因此，药用植物基因组亟待一个公共数据平台，为相关研究者提供信息全面的组学数据信息，达成数据实时共享与共赢合作，避免不必要的恶性竞争。在博士学习期间，我也负责搭建了全球第一个药用植物组学数据库（Herbal Medicine Omics Database， http://herbalplant.ynau.edu.cn/），涵盖了目前为止已发表的基因组、转录组、代谢组以及代谢通路数据初步实现百种中草药数据的共享、利用，满足有效成分合成生物学对关键合成酶的查找、定位功能，极大地促进相关研究工作效率的提升，实现数据纵向系统贯穿、横向分享分析，达到提高药用植物研究交流水平和数据共享的目的。

Strong environmental pressures drive population changes. In contrast to autotrophic plants, non-photosynthetic plants, which independently evolved over 40 times, display an evolutionary strategy of adaptation to a low-light, undergrowth environment. To facilitate analysis of the adaptive changes involved, here we present a de novo assembly of the genome of the perennial orchid Gastrodia elata. This first published genome of a non-photosynthetic plant reveals clear indications of losses of key genes and relaxation of selection in the plant’s photosynthetic, leaf development, and plastid division pathways. The orchid appears to have profoundly restructured basic metabolic pathways and changes in gene functions that enable it to participate in mycosymbiosis. Moreover, its carbohydrate and lipid metabolism pathways indicate adaptive shifts that enable nutrient exchange between the plant and mycosymbionts. Thus, the G. elata genome provides new insights into the molecular and evolutionary mechanisms underlying morphological and physiological adaptations associated with non-photosynthetic lifestyles and allow tests of a recently proposed host plant-fungus symbiosis model.Meanwhile, G. elata is also a kind of herbal medicine. In the world, more than 50% of drugs are derived from chemical compounds that have been isolated from various plants. With the development of sequencing technology and synthetic biology, we can obtain molecular information from the transcriptomic and genomic data of plants, and then utilize bacteria to synthesize desired chemical compounds. Increasing numbers of researchers have started to publish omics data for herbal plants. There has been concern that redundant data generation might occur, with some researchers expressing a desire for an all-inclusive reliable omics database for herbal medicine plants. Establishing such a database is of great importance to help the study of the biogenesis and functions of herbal medicine plants. To date, several pharmacology databases of herbal medicine have been published, but no omics database is currently available to the public. We have built the Herbal Medicine Omics Database (HMOD, Figure 1A, http://herbalplant.ynau.edu.cn/) to provide a reliable omics resource for all researchers. In this database, we have catalogued already published herbal medicine plant genomic, transcriptomic, pathways data and metabolomics information for use by the public, as well as unpublished transcriptomic and enzyme data identified from KEGG annotation. Moreover, a generic genome browser (Gbrowse) has been integrated to allowing the viewing of genome sequences. A BLAST tool is also provided in our database. To provide the latest advances and more analysis tools for herbal medicine plants, HMOD will be updated when new data are available (ftp://201.203.187.112:2222/).