BREAD ABRDC: Development of Essential Genetic and

小米是一种对东非粮食安全具有战略意义的粮食作物。这种粮食营养价值高，可以在干旱环境中生长，因此对小农的生计很重要。该地区的一个主要农业目标是通过减少或消除影响谷子生长的病害，培育产量更高的谷子品种。稻瘟病菌是影响谷子产量达80%的致病菌，是影响谷子的主要病害之一。为了了解如何控制疾病爆发，该项目使用基因组测序作为一种强大的方法来确定真菌的精确菌株，并研究真菌如何在植物中引起疾病症状。对采集自肯尼亚、坦桑尼亚、乌干达和埃塞俄比亚的稻瘟病菌株进行序列分析，将提供有关东非病原菌遗传多样性的信息，并为确定导致谷子感染的因素提供资源。从这种方法获得的知识对于制定有效的疾病管理战略至关重要。此外，对小谷子寄主的序列分析将阐明为什么一些品种比其他品种更抗稻瘟病。产生的资源还将被用作培训东非本科生和研究生生物信息学的工具，生物信息学是将信息转化为改进育种策略所必需的一种专业知识。该项目的具体目标是：(1)生成异源四倍体小米基因组（1C=1.8 Gb）的80X PacBio序列，生成高质量的基因组组装（1C=1.8 Gb）；(2)对200株东非稻瘟菌Magnaporthe oryzae分离株（其中24株采集于10年前）进行重新测序，以确定该稻瘟菌随时间和地理区域的多样性和进化。利用已知效应物的共同特征（分泌和高多态性水平），利用效应物预测管道对blast基因组序列进行挖掘，以鉴定候选效应基因；(3)利用RNA-Seq分析blast-finger millet相互作用转录组，以鉴定在感染早期诱导的基因。编码分泌蛋白的基因将从RNA-Seq实验中鉴定，并与使用效应预测管道鉴定的基因交叉参考。将差异表达的寄主基因在相容和不相容相互作用之间进行比较，并与水稻稻瘟病感染早期阶段差异表达的基因进行比较。(4)使用双轮robin设计，建立来自21个不同亲本的约4000个ril的巢式关联图谱。该群体将代表首个捕获谷子种质资源中存在的大量多样性的图谱资源，并具有较高的数量性状位点检测能力。

Finger millet is a grain crop of strategic importance to food security in Eastern Africa. The grain has high nutritional value, can grow in arid environments and thus is important to the livelihood of smallholder farmers. A major agricultural goal in the region is to develop higher yielding varieties of finger millet through reducing or eliminating diseases that impact growth of the plant. Blast fungus is a pathogen that reduces yield up to 80% and is one of the main diseases affecting finger millet. To understand how to control disease outbreaks, this project uses genomic sequencing as a powerful approach to identify precise strains of the fungus and to study how the fungus causes disease symptoms in the plant. Sequence analyses of blast strains collected in Kenya, Tanzania, Uganda and Ethiopia will provide information on the genetic diversity of the pathogen in Eastern Africa, and provide a resource to identify the factors that are responsible for infection of finger millet. The knowledge from this approach is essential to develop efficient disease management strategies. Furthermore, sequence analyses of the finger millet host will clarify why some cultivars are more resistant to blast than others. The generated resources will also be used as a vehicle to train undergraduate and graduate students in Eastern Africa in bioinformatics, an expertise that is essential to translate the information to improve breeding strategies. The specific aims of the project are to (1) Generate 80X PacBio sequence for the allotetraploid finger millet genome (1C=1.8 Gb) to generate a high quality genome assembly (1C=1.8 Gb); (2) Resequence 200 Eastern African isolates of the finger millet blast fungus Magnaporthe oryzae, including 24 that were collected 10 years ago, to determine the diversity and evolution of this finger millet pathogen both over time and across geographic regions. The blast genome sequences will be mined to identify candidate effector genes using an effector prediction pipeline that incorporates common characteristics of known effectors (secretion and high polymorphism levels;(3) Analyze the blast-finger millet interaction transcriptome using RNA-Seq to identify genes that are induced at early stages of infection. Genes encoding secreted proteins will be identified from the RNA-Seq experiment and cross-referenced to those identified using the effector prediction pipeline. Host genes that are differentially expressed will be compared between compatible and incompatible interactions, and with genes that are differentially expressed during early stages of blast infection in rice, and(4) Develop a nested association mapping panel of some 4000 RILs derived from 21 diverse parents using a double round robin design. This population will represent the first mapping resource that captures substantial diversity present in finger millet germplasm and has a high quantitative trait loci detection power.