In silico single nucleotide polymorphism discovery and application to marker-assisted selection in soybean |
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Authors: | Tanapon Chaisan Kyujung Van Moon Young Kim Kyung Do Kim Beom-Soon Choi and Suk-Ha Lee |
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Institution: | (1) Department of Plant Science and Research Institute for Agriculture and Life Sciences, Seoul National University, San 56-1, Sillim-dong, Gwanak-gu, Seoul, 151-921, Republic of Korea;(2) National Instrumentation Center for Environmental Management, Seoul National University, Seoul, 151-921, Korea;(3) Plant Genomics and Breeding Institute, Seoul National University, Seoul, 151-921, Korea; |
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Abstract: | The general approach to discovering single nucleotide polymorphisms (SNPs) requires locus-specific PCR amplification. To enhance
the efficiency of SNP discovery in soybean, we used in silico analysis prior to re-sequencing as it is both rapid and inexpensive.
In silico analysis was performed to detect putative SNPs in expressed sequence tag (EST) contigs assembled using publicly
available ESTs from 18 different soybean genotypes. SNP validation by direct sequencing of six soybean cultivars and a wild
soybean genotype was performed with PCR primers designed from EST contigs aligned with at least 5 out of 18 soybean genotypes.
The efficiency of SNP discovery among the confirmation genotypes was 81.2%. Furthermore, the efficiency of SNP discovery between
Pureunkong and Jinpumkong 2 genotypes was 47.4%, a great improvement on our previous finding based on direct sequencing (22.3%).
Using SNPs between Pureunkong and Jinpumkong 2 in EST contigs, which were linked to target traits, we were able to genotype
90 recombinant inbred lines by high-resolution melting (HRM) analysis. These SNPs were mapped onto the expected locations
near quantitative trait loci for water-logging tolerance and seed pectin concentration. Thus, our protocol for HRM analysis
can be applied successfully not only to genetic diversity studies, but also to marker-assisted selection (MAS). Our study
suggests that a combination of in silico analysis and HRM can reduce the cost and labor involved in developing SNP markers
and genotyping SNPs. The markers developed in this study can also easily be applied to MAS if the markers are associated with
the target traits. |
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