BREAD: Platform, Pipeline, and Analytical Tools for Next Generation Genotyping to Serve Breeding Efforts in Africa

主要研究者：Edward Buckler（康奈尔大学/美国农业部农业研究所，美国）托马斯·哈希（ICRISAT-Patancheru，Hyderabad，India），Stephen Kresovich（美国南卡罗来纳州大学），Sharon Mitchell（美国康奈尔大学）和Kassa Semagn（CIMMYT-肯尼亚内罗毕）特蕾莎·富尔顿（美国康奈尔大学）植物育种的先进策略正在迅速从操纵少数主要基因或基因组区域的分子育种方法发展到复杂的，协调的方法，包括跨许多基因组区域的同时选择（全基因组或基因组选择）。植物分子育种的未来（从关键地方品种的保护到有针对性的杂交部署）必须整合和挖掘庞大的数据集，并采用数学模型来预测哪些基因型在特定环境中表现良好。然后，这些信息将用于帮助育种者和农民确定最佳的亲本组合，并选择后代基因型（针对特定的目标环境），以最少的有限资源使用最有效地最大限度地提高农业产量（产量和质量）。这种独特的机会是建立在廉价的高标记密度基因分型，高质量的表型，以及适当的数学模型的预测和实验设计的支柱。这项研究工作计划解决与应用高通量高密度基因分型和开发一个可操作的“模型”，为广泛的作物相关的技术问题。该项目将开发和优化下一代测序技术，作为对撒哈拉以南非洲（SSA）和世界其他半干旱热带地区农民重要的玉米和高粱品种的高通量基因分型检测。该项目将利用下一代测序技术，结合高水平的多路复用和非常便宜的样品制备方法，建立一个平台，为每个人提供10万至100万个标记，成本大大低于目前的现场和实验室成本。该平台将为从DNA制备到生物信息学分析的整个流程提供强大的协议，这对基因组选择至关重要。此外，这些方法将被推广，因此在未来任何物种的任何大量个体都可以同样容易地进行基因分型。降低基因分型成本并增加其对所有作物的适用性将使植物育种者能够利用基因组选择来促进作物改良。基因组选择有可能显着提高发展中国家每年农业生产力的增长率。在这一协调项目中，工作重点是解决关键技术组成部分，使世界一半人口能够获得先进的方法，使更好的作物品种专门适应具有挑战性的环境和生产系统。该项目将通过项目网站提供协议，通过NCBI Short Read Archive进行测序，并通过Panzea和Gramene网站提供多样性数据。此外，该项目将通过在肯尼亚和印度举行的两次专题讨论会和培训单元，向康奈尔大学的研究人员提供培训。

PI: Edward Buckler (Cornell University/USDA-ARS, USA)Co-PIs: C. Thomas Hash (ICRISAT-Patancheru, Hyderabad, India), Stephen Kresovich (University of South Carolina, USA), Sharon Mitchell (Cornell University, USA), and Kassa Semagn (CIMMYT-Nairobi, Kenya)Senior Personnel: Theresa Fulton (Cornell University, USA)Advanced strategies of plant breeding are rapidly evolving from molecular breeding methods that manipulate a few major genes or genomic regions to complex, coordinated methods that incorporate simultaneous selection across many genomic regions (genome-wide or genomic selection). The future of plant molecular breeding (from conservation of key landraces to targeted hybrid deployment) must integrate and mine huge data sets and employ mathematical models that can predict which genotypes will perform well in specific environments. This information will then be used to help breeders and farmers identify the optimal parental combinations and select progeny genotypes (for a particular target environment) that most efficiently maximize agricultural output (yield and quality) with minimal use of constrained resources. This unique opportunity is founded on the pillars of inexpensive high marker density genotyping, high quality phenotyping, and appropriate mathematical models for prediction and experimental design. This research effort is planned to solve the technical problems associated with applying high-throughput high density genotyping and developing an operational "model" for a wide range of crops. The project will exploit and optimize next generation sequencing technologies as high-throughput genotyping assays for maize and sorghum varieties important to farmers in sub-Saharan Africa (SSA) and other semi-arid, tropical regions of the world. Using next generation sequencing technologies combined with high levels of multiplexing and very inexpensive sample preparation methods, the project will establish a platform to provide 100,000-1 million markers per individual for a cost substantially below current field and laboratory costs. This platform will produce robust protocols for the entire pipeline, from DNA preparation to bioinformatic analyses, which are essential for genomic selection. Moreover, these approaches will be generalized so in the future any large number of individuals of any species can be genotyped with equal ease. Reducing the genotyping costs and increasing its applicability to all crops will enable plant breeders to employ genomic selection to facilitate crop improvement.Genomic selection has the potential to significantly increase the rate of gain in agricultural productivity per year in the developing world. In this coordinated project, efforts focus on solving key technology components necessary to give half the world's population access to advanced approaches for making better crop varieties specifically tailored to challenging environments and production systems. This project will make protocols available through the project website, sequencing reads through NCBI Short Read Archive, and diversity data through the Panzea and Gramene websites. Additionally, the project will provide training to researchers at Cornell and through two symposia and training modules held in Kenya and India.