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A High-Density SNP Genotyping Array for Rice Biology and Molecular Breeding

A high-density single nucleotide polymorphism (SNP) array is critically important for geneticists and molecu- lar breeders. With the accumulation of huge amounts of genomic re-sequencing data and available technologies for accurate SNP detection, it is possible to design high-density and high-qualit...

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Bibliographic Details
Published in:Molecular plant 2014-03, Vol.7 (3), p.541-553
Main Authors: Chen, Haodong, Xie, Weibo, He, Hang, Yu, Huihui, Chen, Wei, Li, Jing, Yu, Renbo, Yao, Yue, Zhang, Wenhui, He, Yuqing, Tang, Xiaoyan, Zhou, Fasong, Deng, Xing Wang, Zhang, Qifa
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Language:English
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Summary:A high-density single nucleotide polymorphism (SNP) array is critically important for geneticists and molecu- lar breeders. With the accumulation of huge amounts of genomic re-sequencing data and available technologies for accurate SNP detection, it is possible to design high-density and high-quality rice SNP arrays. Here we report the devel- opment of a high-density rice SNP array and its utility. SNP probes were designed by screening more than 10 000 000 SNP loci extracted from the re-sequencing data of 801 rice varieties and an array named RiceSNP50 was produced on the Illumina Infinium platform. The array contained 51 478 evenly distributed markers, 68% of which were within genic regions. Several hundred rice plants with parent/F1 relationships were used to generate a high-quality cluster file for accurate SNP calling. Application tests showed that this array had high genotyping accuracy, and could be used for dif- ferent objectives. For example, a core collection of elite rice varieties was clustered with fine resolution. Genome-wide association studies (GWAS) analysis correctly identified a characterized QTL. Further, this array was successfully used for variety verification and trait introgression. As an accurate high-throughput genotyping tool, RiceSNP50 will play an important role in both functional genomics studies and molecular breeding.
ISSN:1674-2052
1752-9867
DOI:10.1093/mp/sst135