The Rice 3000 Genomes Project Data

Rice, Oryza sativa L., is the staple food for half the world’s population. By 2030, rice production must increase by at least 25% to keep pace with population growth. Accelerated genetic gains in rice improvement are needed to mitigate the effects of climate change and loss of arable land and to ensure global food supply. Here, we include data from an international effort resequencing a core collection of 3,000 rice accessions from 89 countries as a global public good. The 3,000 sequenced rice genomes had an average sequencing depth of 14X, average genome coverage and mapping rates of 94.0% and 92.5%, respectively. This data provides a foundation for large-scale discovery of novel alleles for important rice phenotypes using various bioinformatics and/or genetic approaches. It also serves to understand at a higher level of detail the genomic diversity within O. sativa. With the release of the sequencing data, the project calls for the global rice community to take advantage of this data as a foundation for establishing a global, public rice genetic/genomic database and information platform for advancing rice breeding technology for future rice improvement. Keywords: Oryza sativa, genetic resources, genome diversity, next generation sequencing Any inquires can be directed to any /all of the following members of the consortium: Gengyun Zhang BGI, Shenzhen, China Zhikang Li Chinese Academy of Agricultural Sciences, Beijing, China Tian-Qing Zheng Chinese Academy of Agricultural Sciences, Beijing, China Kenneth L. McNally International Rice Research Institute, Metro Manila, Philippines

水稻（Oryza sativa L.）是全球半数人口的主粮。至2030年，水稻产量需至少提升25%方能匹配人口增长需求。为缓解气候变化与耕地流失带来的影响、保障全球粮食供应，亟需加速水稻遗传改良的遗传增益。本数据集收录了一项国际合作项目的重测序数据：该项目针对来自89个国家的3000份核心水稻种质资源开展重测序，所得数据作为全球公共共享资源对外发布。3000份已测序水稻基因组的平均测序深度为14X，平均基因组覆盖度与比对率分别为94.0%和92.5%。本数据集为通过各类生物信息学及/或遗传学方法大规模发掘重要水稻表型的新等位基因提供了研究基础，同时也可为更精细解析栽培稻的基因组多样性提供支撑。随着本测序数据的正式发布，本项目呼吁全球水稻科研共同体以此为基础，搭建全球公共的水稻遗传/基因组数据库与信息平台，以推动未来水稻育种改良技术的发展。关键词：栽培稻（Oryza sativa）、遗传资源、基因组多样性、下一代测序。任何咨询可联系本联盟的以下任意或全部成员：张耕耘（深圳华大基因（BGI），中国深圳）、黎志康（中国农业科学院，中国北京）、郑天清（中国农业科学院，中国北京）、Gengyun Zhang、Zhikang Li、Tian-Qing Zheng、Kenneth L. McNally（国际水稻研究所，菲律宾马尼拉大都会）

搜集汇总

背景与挑战

背景概述

该数据集是'3000 Rice Genomes Project'的基因组数据，发布于2014年，包含来自89个国家的3000个水稻种质资源的重测序数据，平均测序深度为14X，覆盖率和映射率较高。数据旨在为水稻表型新等位基因发现和基因组多样性研究提供基础，支持全球水稻育种改进，可通过INSDC数据库公开获取。