Joint NSF/ERA-CAPS: Collaborative Research: BEAN-ADAPT - Genetic Architecture of Rapid Evolutionary Adaptation to Changing Environments in Domesticated Phaseolus Bean Species

NSF/ERA-CAPS 联合：合作研究：BEAN-ADAPT - 驯化菜豆物种快速进化适应不断变化的环境的遗传结构

• 批准号: 1539838
• 负责人: Scott Jackson
• 金额: $ 74.29万
• 依托单位: University of Georgia Research Foundation Inc
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-05-15 至 2019-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1539838&HistoricalAwards=false
• 关键词: Joint; NSF; ERA; CAPS; Collaborative

PIs: Paul L. Gepts (University of California-Davis) and Scott A. Jackson (University of Georgia)ERA-CAPS Collaborators: Roberto Papa (Universita Politecnica delle Marche, Italy), Alisdair R. Fernie (Max-Planck-Institute of Molecular Plant Physiology, Germany), and Andreas Graner (Leibniz Institute of Plant Genetics and Crop Plant Research, Germany)Worldwide, legumes serve an important nutritional role as a source of protein, minerals, vitamins, and dietary fibers, and their ability to fix nitrogen (i.e. convert nitrogen in the atmosphere into a form that can be used by the plant) makes legumes natural contributors to sustainable agriculture. As domesticated crops, legumes have adapted to growth in many different environments, but the genetic basis for such adaptation is largely unknown. This project will take advantage of large gene bank collections of two legume species, common bean and runner bean, to discover the genes responsible for adaptation to new, changing, and variable environments. The results will allow better use of the genetic resources represented by these gene banks for improvement of legume crops. The project will include collaborators in the U.S., Colombia, Italy and Germany. Exchanges of students among the participating research groups will offer opportunities to learn new techniques and integrate information across the coordinating research efforts. In addition, outreach to undergraduates from the Southwest U.S. will provide exposure to hands-on research experiences in plant genomics. In this project, multi-location, multi-year field evaluations of large gene bank collections will be combined with high-throughput genomic tools to understand the genetic basis of adaptation in the legumes common bean (Phaseolus vulgaris) and runner bean (P. coccineus). Approximately 10,000 common bean and 1,000 runner bean accessions will be genotyped using a DNA sequencing approach and tested in contrasting environments and conditions in Europe (higher latitude) and South America (near the Equator) to associate genes with adaptation to environmental variables, such as day length, temperature, altitude, and rainfall. The two Phaseolus species have contrasting life histories, reproductive systems, and population structures, providing an opportunity to compare different adaptation paths. Sequence information will be complemented with transcriptomic and metabolomics profiling on a select subset of accessions to produce datasets that will be used to build models of how common bean adapted to new environments after its dispersal from two domestication centers in Mesoamerica and the Southern Andes. Prospectively, this information will be useful for developing new crop varieties adapted to changing or variable environments.

PI：Paul L. Gepts（加州大学戴维斯分校）和Scott A.杰克逊（格鲁吉亚大学）ERA-CAPS合作者：Roberto Papa（马尔凯理工大学，意大利），Alisdair R.费尔尼（马克斯-普朗克分子植物生理学研究所，德国）和Andreas Graner（Leibniz Institute of Plant Genetics and Crop Plant Research，德国）在世界范围内，豆类作为蛋白质、矿物质、维生素和膳食纤维的来源发挥着重要的营养作用，以及它们固氮的能力豆类作物的生物学特性（即将大气中的氮转化为植物可以利用的形式）使豆类成为可持续农业的天然贡献者。作为驯化作物，豆类已经适应了许多不同环境的生长，但这种适应的遗传基础在很大程度上是未知的。该项目将利用两种豆科植物（菜豆和菜豆）的大型基因库集合，发现负责适应新的，不断变化的和可变的环境的基因。研究结果将使这些基因库所代表的遗传资源更好地用于豆科作物的改良。该项目将包括美国的合作者，哥伦比亚、意大利和德国。 参与研究小组之间的学生交流将提供学习新技术和整合协调研究工作信息的机会。此外，来自美国西南部的本科生将接触到植物基因组学的实践研究经验。在该项目中，对大型基因库集合的多地点、多年实地评估将与高通量基因组工具相结合，以了解豆科植物菜豆（Phaseolus vulgaris）和红花菜豆（P. coccineus）适应的遗传基础。 将使用DNA测序方法对大约10，000份普通菜豆和1，000份红花菜豆种质进行基因分型，并在欧洲（高纬度）和南美洲（赤道附近）的对比环境和条件下进行测试，以将基因与适应环境变量（如白天长度，温度，海拔和降雨量）相关联。这两种菜豆具有截然不同的生活史、生殖系统和种群结构，为比较不同的适应途径提供了机会。序列信息将补充转录组学和代谢组学分析的一个选定的子集的加入，以产生数据集，将用于建立模型，如何适应新的环境后，从两个驯化中心在中美洲和南部安第斯山脉的普通豆。 这些信息将有助于开发适应不断变化或多变环境的新作物品种。