项目名称: 木薯块根淀粉性状的候选基因关联分析
项目编号: No.31501355
项目类型: 青年科学基金项目
立项/批准年度: 2016
项目学科: 食品科学、农学基础与作物学
项目作者: 王明
作者单位: 中国热带农业科学院热带作物品种资源研究所
项目金额: 20万元
中文摘要: 木薯是我国最具开发前景的能源作物,而木薯块根的淀粉含量和淀粉组分(直链和支链淀粉含量、直链淀粉/支链淀粉比例)是影响木薯乙醇产率和产业化应用的重要因素。利用丰富的自然群体资源和公开的基因信息,基于连锁不平衡的关联分析方法,可以突破常规连锁作图定位中亲本数量和遗传背景的局限,发掘得到更多的等位变异信息。本项目拟用候选基因关联分析法研究木薯淀粉含量和淀粉组分,利用木薯国家种质圃350份木薯种质资源材料构建自然群体,克隆控制木薯淀粉含量和淀粉组分的关键基因,比较这些基因的等位变异及核苷酸多态性;结合自然群体中的淀粉表型,在种质材料中检测候选基因对淀粉性状的表型效应,挖掘引起木薯淀粉含量和淀粉组分变异的关键基因位点并将其转化为功能标记,为木薯分子育种提供材料信息和技术支持,也为分子标记辅助选择培育优良加工型木薯品种提供理论及实践依据。
中文关键词: 木薯;淀粉;候选基因;关联分析;功能标记
英文摘要: Cassava is one of the most prospective energy crops, while both starch content and component (amylose and amylopectin content, amylose and amylopectin ratio) in cassava are important factors affecting ethanol production and industrial application. With abundant natural resources and disclosure information on the related genes, association analysis method based on linkage disequilibrium, could break through the limitations in numbers of parents and genetic background among conventional linkage mapping. And association analysis could explore more information on allelic variation. Using association analysis of candidate genes, cassava starch contents and components will be studied in this project. Natural population will be constructed using 350 accessions from National Cassava Germplasm Repertory. Those key genes controlling starch content and component will be cloned. Allelic variation and nucleotide polymorphism in natural populations will be analyzed. Together with starch phenotype in natural population, phenotypic effects on starch traits for candidate genes in materials will be detected. Those key locus causing variations of starch content and component will be mined, and be transformed into functional markers. These will provide material information and technical support for cassava molecular breeding, but also provide the theory and practice basis on molecular marker assisted selection in cassava breeding for excellent varieties of processing types.
英文关键词: Cassava;Starch;Candidate genes;association analysis;Functional marker