数字植物：科学内涵、瓶颈及发展策略

朱新广; 常天根; 宋青峰; 常硕其; 王重荣; 张国庆; 郭亚; 周少川

doi:10.12211/2096-8280.2020-018

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数字植物：科学内涵、瓶颈及发展策略

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- 数字植物：科学内涵、瓶颈及发展策略
- ePlant: scientific connotations, bottlenecks, and development strategies
- 合成生物学 2020年1卷第3期页码：285-297
- 作者机构：
  
  1.植物分子遗传国家重点实验室，中国科学院分子植物科学卓越创新中心，中国科学院上海生命科学研究院植物生理生态研究所，上海 200032
  2.杂交水稻国家重点实验室，湖南杂交水稻研究中心，湖南长沙 410125
  3.广东省水稻育种新技术重点实验室，广东农业科学院水稻研究所，广东广州 510640
  4.中国科学院上海营养与健康研究所，中国科学院-马普学会计算生物学伙伴研究所，中国科学院计算生物学重点实验室，上海 200031
  5.江南大学，江苏无锡 214122
- 作者简介：
  
  [ "朱新广，（1974—），男，博士，研究员，研究方向为光合作用系统生物学和合成生物学。E-mail:zhuxg@sippe.ac.cn" ]
- 基金信息：
  
  中国科学院先导专项(XDB27020105;XDA08020301);国家自然科学基金(30970213;31870214);国家重点基础研究发展计划(2015CB150104);国家高技术研究发展计划(2014AA101601);国家重点研发计划(2019YFA0904600);广东省应用型科技专项(2015B 020231001)
- DOI：10.12211/2096-8280.2020-018
  中图分类号： Q94
- 收稿：2020-03-06，
  
  修回：2020-04-22，
  
  纸质出版：2020-06-30
- 稿件说明：
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朱新广, 常天根, 宋青峰, 常硕其, 王重荣, 张国庆, 郭亚, 周少川. 数字植物：科学内涵、瓶颈及发展策略[J]. 合成生物学, 2020, 1(3): 285-297

ZHU Xinguang, CHANG Tiangen, SONG Qingfeng, CHANG Shuoqi, WANG Chongrong, ZHANG Guoqing, GUO Ya, ZHOU Shaochuan. ePlant： scientific connotations, bottlenecks, and development strategies[J]. Synthetic Biology Journal, 2020, 1(3): 285-297
朱新广, 常天根, 宋青峰, 常硕其, 王重荣, 张国庆, 郭亚, 周少川. 数字植物：科学内涵、瓶颈及发展策略[J]. 合成生物学, 2020, 1(3): 285-297 DOI： 10.12211/2096-8280.2020-018.

ZHU Xinguang, CHANG Tiangen, SONG Qingfeng, CHANG Shuoqi, WANG Chongrong, ZHANG Guoqing, GUO Ya, ZHOU Shaochuan. ePlant： scientific connotations, bottlenecks, and development strategies[J]. Synthetic Biology Journal, 2020, 1(3): 285-297 DOI： 10.12211/2096-8280.2020-018.

摘要

当前，各类组学技术、基因组编辑技术及超性能计算能力的飞速发展正使得植物科学从描述性、定性研究向精细定量研究乃至理性设计的转变。在这个过程中，数字植物的研究应运而生。数字植物通过对植物生长发育过程多尺度、多生理生化现象的系统定量模拟，以实现植物整个生命周期的“数字化”。数字植物将为定量植物科学研究、植物设计及改造提供理论工具。数字植物的发展将支持新代谢通路、基因调控网络的设计，乃至植物理想基因系统的设计，从而为以提升作物产量和优化作物品质为目标的植物合成生物学提供设计工具。本文在分析当前构建数字植物遇到的瓶颈的基础上，提出发展数字植物所需要的关键措施，即：构建植物生长发育基本模型；获得同化物在各器官间分配的代谢数据；创建模块模型耦联方法；建立数字植物研究公共平台；发展表型数据与机理模型相结合的方法；以水稻为模式植物，开展数字植物指导的分子设计育种；建立支持数字植物的人才培养及储备策略。利用数字植物定量模拟和设计植物是未来植物合成生物学发展的趋势，数字植物指导下的作物栽培和育种也是精准农业和智慧农业的必然要求。

Abstract

Plant systems and synthetic biology has gained more and more attention in recent years as a result of the rapid advances in genomics

proteomics

metabolomics

epigenomics and genome editing technologies. Plant systems and synthetic biology for quantitative studies of plant systems differs from traditional plant science that mainly focuses on descriptive and qualitative studies of plant systems. In addition

plant systems and synthetic biology also emphasizes the design and creation of new biochemical pathways

regulatory circuits

signaling pathways

and even biological structures that are not exist in native plants hosts for desired properties.

A number of mega projects in plant synthetic biology have been initiated in recent years

all with a common goal of boosting crop yield and developing technologies for Green Revolution of agriculture. With these projects

it was evident that to maximize the benefit of plant synthetic biology

we ought to develop a robust system model for plant growth and development: ePlant

which includes the simulation not only for molecular

biochemical

physiological

and physical processes in different organs of a plant

but also for interaction between plant and environment as highlighted by the system of soil

root

plant and air. The ePlant model needs to be developed using a divide-and-conquer approach followed by the modular construction

and once developed

it can be used as a major tool for basic research in plant science

studies for interaction among genes

environment and management practices

identification of new options to engineer crops for desired properties

and finally design of ideotypes desired for crop breeding.

To expedite the development of ePlant model

we propose a number of priorities and strategies

which include developing basic models for plant growth and development

collecting systems data related to partitioning of similarities among different organs

creating new methods to integrate modules at different temporal and spatial scales

building up public online platforms to support the development of ePlant

developing algorithms to support effective integration of ePlant models with phenomics data

and finally forming policies to nurture the development of communities on plant systems modeling.

We emphasize a strong demand for an online platform or portal to support the development of ePlant models and their applications. This platform needs to include not only the basic models

data supporting model development and application and high-performance super-computing resources to enable the models' widely applications by the plant science research community. We also advocate for using rice as the model species to construct such an ePlant

considering the large quantities of studies on rice genomics

genetics

physiology

breeding and agronomics

which will expedite the development

validation and application of ePlant models. After ePlant model developed for rice (eRice)

we can use it to guide dissection of mechanism underlying high yield formation in current rice lines

to design ideotypes for super-high-yield rice breeding

and to format optimal agronomic practices.

关键词

Keywords

references

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