Genome-Wide Analysis of Root Traits

PIS：Philip Benfey(杜克大学生物学)，John Heller(杜克大学数学)，Jonathan Lynch(宾夕法尼亚州立大学园艺)，Joshua Weitz(佐治亚理工学院生物学)；高级人员：Herbert Edelsbrunner(杜克大学计算机科学)，Leon Kochian(康奈尔-美国农业部-博伊斯·汤普森研究所)，Daniel Williams(北卡罗来纳中央大学生物学)这个项目的长期目标是使用基因组方法来确定控制作物根系分枝模式的基因。根在土壤中的分支方式被称为植物的“根系结构”，它在不同的植物之间有很大的不同。众所周知，这些差异会影响植物获得水分和养分的能力。由于许多植物必须应对营养和水分有限的环境，因此根系结构是植物如何适应环境的核心特征。对根系结构的更好理解解决了植物生物学面临的两大挑战--如何以可持续的方式养活迅速增长的世界人口，以及如何应对全球气候变化。糟糕的土壤肥力和环境压力抑制了世界许多地区的作物产量，许多模型预测，这些压力在未来几十年将会增加。在大多数发展中国家，集约化灌溉和施肥在环境上是不可持续的，在经济上也是不可行的。因此，确定构成根系结构的基因可能对农业和世界粮食安全具有深远的意义。令人惊讶的是，人们对构成根系结构的个体特征知之甚少。有两个主要问题限制了对根系构型遗传基础的理解：1)缺乏经济有效的非侵入性成像方法；2)缺乏足够的手段来描述根系构型的复杂空间结构。该项目将使用两种非侵入性成像技术来获取不同环境条件下水稻和玉米根系生长的图像。根系统的反应将与在类似条件下生长在土壤中的反应进行比较。将开发描述生长的根系的数学方法和比较不同的根系体系结构的模拟。将利用水稻和玉米的特殊群体来识别根构型特征的数量性状基因座(QTL)，并将努力分离对植物育种具有重要意义的基因。这项工作的更广泛影响部分源于这项研究的本质，即它本质上是跨学科的，因此在不同水平(本科生、研究生、博士后)的培训将把定量方法与应用于实验生物学相结合。将与北卡罗来纳中央大学(NCCU)的教职员工合作开发一门课程，重点是了解复杂的遗传特征。NCCU是一所历史悠久的黑人大学(HBCU)，距离杜克大学校园5英里。这门课程将使用植物和人类疾病的例子来告知和教育本科生分析复杂的遗传特征所涉及的问题，以及目前可用于识别这些特征的基因的尖端技术和计算方法。对于选修过这门课程的合格学生，将提供研究实习机会。将开发一个网站来传播这一项目的结果，并描述研究人员和饲养者感兴趣的方法和结果。该网站将可通过http://www.biology.duke.edu/benfeylab/.访问

PIs: Philip Benfey (Duke - Biology), John Harer (Duke - Mathematics), Jonathan Lynch (Penn State - Horticulture), Joshua Weitz (Georgia Tech - Biology); Senior Personnel: Herbert Edelsbrunner (Duke - Computer Science), Leon Kochian (Cornell-USDA-Boyce Thompson Institute), Daniel Williams (North Carolina Central University - Biology)The long-term goal of this project is to use genomic approaches to identify the genes that control the branching patterns of crop roots. How roots branch in soil is known as the plant's 'root system architecture' and it varies dramatically from plant to plant. These differences are known to impact the plant's ability to acquire water and nutrients. Since many plants have to deal with environments in which nutrients and water are limiting, the root system architecture is a central feature of how plants adapt to their environment. A better understanding of root system architecture addresses two of the major challenges confronting plant biology - how to feed a burgeoning world population in a sustainable manner and how to cope with global climate change. Poor soil fertility and environmental stress suppress crop yields in many parts of the world, and many models predict these stresses will increase in coming decades. Intensive irrigation and fertilization are not environmentally sustainable, nor economically viable in most developing countries. Thus, identifying the genes that underlie root system architecture could have a profound significance for agriculture and world food security. Surprisingly, little is known about the individual traits that comprise root system architecture. There are two principal issues that have restricted the understanding of the genetic basis of root system architecture: 1) the lack of cost-effective methods for non-invasively imaging growing roots and 2) the lack of adequate means of describing the complex spatial structure of root system architecture. Two non-invasive imaging technologies will be used in this project to acquire images of growing rice and maize roots under different environmental conditions. Response of root systems will be compared to responses when grown in soil under similar conditions. Mathematical approaches to describing growing root systems and simulations for comparing different root system architectures will be developed. Quantitative trait loci (QTL) for root architecture traits will be identified using special populations of rice and maize and efforts will be initiated toward isolating genes of significance to plant breeding.The broader impacts of this work stem, in part, from the nature of this research that it is inherently interdisciplinary, thus training at various levels (undergraduate, graduate, post-doctoral) will integrate quantitative approaches with applications to experimental biology. A course will be developed in collaboration with faculty at North Carolina Central University (NCCU) that focuses on understanding complex genetic traits. NCCU is a historically black university (HBCU) located 5 miles from the Duke campus. The course will use examples from plants as well as human disease to inform and educate undergraduates as to the issues involved in analyzing complex genetic traits and the cutting edge technologies and computational approaches now available for identifying the genes responsible for these traits. For qualified students who have taken this course, research internships will be provided. A website will be developed to disseminate the results from this project, as well as to describe methods and results of interest to researchers and breeders. The web site will be accessible at http://www.biology.duke.edu/benfeylab/.