The Rice 3000 Genomes Project Data.

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Rice, <em>Oryza sativa L.</em>, is the staple food for half the worlds 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.<br>
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.<br>
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 <em>O. sativa</em>. 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.<br>
Keywords: Oryza sativa, genetic resources, genome diversity, next generation sequencing<br>
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The 3000 rice genomes sequence data are now completely uploaded into the INSDC databases (the Sequence Read Archives (SRA) at EBI, DDBJ and NCBI), and available for easy download from the links noted below, rather than from GigaDB. NB - the mapping of each file as previously stored in GigaDB to the relevant location on the EBI FTP server can be found in the file seq_file_mapping_to_SRA.txt.<br>
<br>Please choose the appropriate geographical location:<br>
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Europe: EBI - PRJEB6180<br>
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USA: NCBI - PRJEB6180 <br>
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Asia: DDBJ - ERP005654<br>

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<br>Any inquires can be directed to any /all of the following members of the consortium:<br>
Gengyun Zhang BGI, Shenzhen, China<br>
Zhikang Li Chinese Academy of Agricultural Sciences, Beijing, China<br>
Tian-Qing Zheng Chinese Academy of Agricultural Sciences, Beijing, China<br>
Kenneth L. McNally International Rice Research Institute, Metro Manila, Philippines
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水稻（Oryza sativa L.）是全球半数人口的主粮。到2030年，水稻产量需至少提升25%以跟上人口增长的步伐。为缓解气候变化与可耕地流失的影响、保障全球粮食供应，亟需加速水稻遗传改良的遗传增益进程。

本数据集收录了一项国际合作重测序项目的数据，该项目对来自89个国家的3000份核心水稻种质资源进行测序，成果作为全球公共科研资源开放共享。该3000份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%。

本数据可为通过各类生物信息学及/或遗传学方法大规模挖掘调控重要水稻性状的新等位基因提供研究基础，同时也有助于从更高细节层面解析栽培稻（O. sativa）的基因组多样性。随着本测序数据的正式发布，项目组呼吁全球水稻科研共同体以此为依托，搭建全球公共水稻遗传/基因组数据库与信息平台，以推动水稻育种技术革新，助力未来水稻遗传改良工作。

关键词：栽培稻（Oryza sativa）、遗传资源、基因组多样性、下一代测序（next generation sequencing）

3000份水稻基因组序列数据现已全部上传至国际核酸序列数据库联盟（INSDC）的相关数据库，包括欧洲生物信息研究所（EBI）、日本DNA数据库（DDBJ）与美国国家生物技术信息中心（NCBI）的序列读取存档（Sequence Read Archives, SRA），用户可通过下文标注的链接直接下载，无需通过GigaDB获取。注：原存储于GigaDB的各文件与EBI FTP服务器对应位置的映射关系，可在seq_file_mapping_to_SRA.txt文件中查询。

请选择对应地理区域：
欧洲：EBI - PRJEB6180
美国：NCBI - PRJEB6180
亚洲：DDBJ - ERP005654

如有任何咨询，可联系该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
肯尼思·L·麦克纳利 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“水稻3000基因组项目”的基因组数据，发布于2014年5月27日，包含来自89个国家的3000份水稻种质资源的重测序数据，平均测序深度为14X，覆盖率和映射率分别达94.0%和92.5%。这些数据旨在支持水稻重要表型的等位基因发现、基因组多样性研究，并为全球水稻育种提供公共基础资源。