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In silico single nucleotide polymorphism discovery and application to marker-assisted selection in soybean

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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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Acknowledgments

This work was supported by a grant (no. CG3121) from the Crop Functional Genomics Center of the 21st Century Frontier Research Program funded by the Ministry of Education, Science and Technology, the Republic of Korea, and also supported by the Korea Rural Development Administration, BioGreen 21 Project 20080401034010, the Republic of Korea. We also thank the National Instrumentation Center for Environmental Management at Seoul National University in Korea.

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Authors and Affiliations

  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

    Tanapon Chaisan, Kyujung Van, Moon Young Kim, Kyung Do Kim & Suk-Ha Lee

  2. National Instrumentation Center for Environmental Management, Seoul National University, Seoul, 151-921, Korea

    Beom-Soon Choi

  3. Plant Genomics and Breeding Institute, Seoul National University, Seoul, 151-921, Korea

    Suk-Ha Lee

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  1. Tanapon Chaisan
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Correspondence to Suk-Ha Lee.

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Chaisan, T., Van, K., Kim, M.Y. et al. In silico single nucleotide polymorphism discovery and application to marker-assisted selection in soybean. Mol Breeding 29, 221–233 (2012). https://doi.org/10.1007/s11032-010-9541-y

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