An accurate and efficient method for large-scale SSR genotyping and applications. Issue 10 (10th February 2017)

• Record Type: Journal Article
• Authors: Li, Lun; Fang, Zhiwei; Zhou, Junfei; Chen, Hong; Hu, Zhangfeng; Gao, Lifen; Chen, Lihong; Ren, Sheng; Ma, Hongyu; Lu, Long; Zhang, Weixiong; Peng, Hai
• Is Part Of: Nucleic acids research. Volume 45:Issue 10(2017)
• Page Start: e88
• Page End: e88
• Publication Date: 2017-02-10
• Subjects: Nucleic acids -- Periodicals; Molecular biology -- Periodicals; 572.805
• DOI: 10.1093/nar/gkx093
• Languages: English
• ISSNs: 0305-1048

Abstract

Abstract: Accurate and efficient genotyping of simple sequence repeats (SSRs) constitutes the basis of SSRs as an effective genetic marker with various applications. However, the existing methods for SSR genotyping suffer from low sensitivity, low accuracy, low efficiency and high cost. In order to fully exploit the potential of SSRs as genetic marker, we developed a novel method for SSR genotyping, named as AmpSeq-SSR, which combines multiplexing polymerase chain reaction (PCR), targeted deep sequencing and comprehensive analysis. AmpSeq-SSR is able to genotype potentially more than a million SSRs at once using the current sequencing techniques. In the current study, we simultaneously genotyped 3105 SSRs in eight rice varieties, which were further validated experimentally. The results showed that the accuracies of AmpSeq-SSR were nearly 100 and 94% with a single base resolution for homozygous and heterozygous samples, respectively. To demonstrate the power of AmpSeq-SSR, we adopted it in two applications. The first was to construct discriminative fingerprints of the rice varieties using 3105 SSRs, which offer much greater discriminative power than the 48 SSRs commonly used for rice. The second was to map Xa21, a gene that confers persistent resistance to rice bacterial blight. We demonstrated that genome-scale fingerprints of an organism can be efficiently constructed and candidate genes, such as Xa21 in rice, can be accurately and efficiently mapped using an innovative strategy consisting of multiplexing PCR, targeted sequencing and computational analysis. While the work we present focused on rice, AmpSeq-SSR can be readily extended to animals and micro-organisms.