文献类型： 外文期刊
作者： Yan, Jun 1 ; Zou, Dong 2 ; Li, Chen 6 ; Zhang, Zhang 2 ; Song, Shuhui 2 ; Wang, Xiangfeng 1 ;
作者机构： 1.China Agr Univ, Coll Agron & Biotechnol, Dept Crop Genom & Bioinformat, Beijing 100094, Peoples R China
2.China Natl Ctr Bioinformat, Beijing 100101, Peoples R China
3.Chinese Acad Sci, Natl Genom Data Ctr, Beijing Inst Genom, Beijing 100101, Peoples R China
4.Chinese Acad Sci, CAS Key Lab Genome Sci & Informat, Beijing Inst Genom, Beijing 100101, Peoples R China
5.Univ Chinese Acad Sci, Beijing 100101, Peoples R China
6.Guangdong Acad Agr Sci, Rice Res Inst, Guangzhou 510640, Peoples R China
关键词： Rice; SNP; Database; HapMap; Panel
期刊名称：GENOMICS PROTEOMICS & BIOINFORMATICS （ 影响因子：7.691； 五年影响因子：11.12 ）
ISSN： 1672-0229
年卷期： 2020 年 18 卷 2 期
页码：
收录情况： SCI
摘要： The information commons for rice (IC4R) database is a collection of 18 million single nucleotide polymorphisms (SNPs) identified by resequencing of 5152 rice accessions. Although IC4R offers ultra-high density rice variation map, these raw SNPs are not readily usable for the public. To satisfy different research utilizations of SNPs for population genetics, evolutionary analysis, association studies, and genomic breeding in rice, raw genotypic data of these 18 million SNPs were processed by unified bioinformatics pipelines. The outcomes were used to develop a daughter database of IC4R - SnpReady for Rice (SR4R). SR4R presents four reference SNP panels, including 2,097,405 hapmapSNPs after data filtration and genotype imputation, 156,502 tagSNPs selected from linkage disequilibrium-based redundancy removal, 1180 fixedSNPs selected from genes exhibiting selective sweep signatures, and 38 barcodeSNPs selected from DNA fingerprinting simulation. SR4R thus offers a highly efficient rice variation map that combines reduced SNP redundancy with extensive data describing the genetic diversity of rice populations. In addition, SR4R provides rice researchers with a web interface that enables them to browse all four SNP panels, use online toolkits, as well as retrieve the original data and scripts for a variety of population genetics analyses on local computers. SR4R is freely available to academic users at http://sr4r.ic4r.org/.
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