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Identification of Domesticated Silkworm Varieties Using a Whole Genome Single Nucleotide Polymorphisms-based Decision Tree
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전장유전체 SNP 기반 decision tree를 이용한 누에 품종 판별

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Type
Academic journal
Author
Jong Woo Park (국립농업과학원) Jeong Sun Park (전남대학교) Chan Young Jeong (국립농업과학원) Hyeok Gyu Kwon (국립농업과학원) Sang Kuk Kang (국립농업과학원) Seong-Wan Kim (국립농업과학원) Nam-Suk Kim (국립농업과학원) Kee Young Kim (국립농업과학원) Iksoo Kim (전남대학교)
Journal
Korean Society Of Life Science Journal of Life Science Vol.32 No.12 KCI Accredited Journals
Published
2022.12
Pages
947 - 955 (9page)

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Identification of Domesticated Silkworm Varieties Using a Whole Genome Single Nucleotide Polymorphisms-based Decision Tree
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Silkworms, which have recently shown promise as functional health foods, show functional differences between varieties; therefore, the need for variety identification is emerging. In this study, we analyzed the whole silkworm genome to identify 10 unique silkworm varieties (Baekhwang, Baekok, Daebaek, Daebak, Daehwang, Goldensilk, Hansaeng, Joohwang, Kumkang, and Kumok) using single nucleotide polymorphisms (SNP) present in the genome as biomarkers. In addition, nine SNPs were selected to discriminate between varieties by selecting SNPs specific to each variety. We subsequently created a decision tree capable of cross-verifying each variety and classifying the varieties through sequential analysis. Restriction fragment length polymorphism (RFLP) was used for SNP867 and SNP9183 to differentiate between the varieties of Daehwang and Goldensilk and between Kumkang and Daebak, respectively. A tetra-primer amplification refractory (T-ARMS) mutation was used to analyze the remaining SNPs. As a result, we could isolate the same group or select an individual variety using the nine unique SNPs from SNP780 to SNP9183. Furthermore, nucleotide sequence analysis for the region confirmed that the alleles were identical. In conclusion, our results show that combining SNP analysis of the whole silkworm genome with the decision tree is of high value as a discriminative marker for classifying silkworm varieties.
#Markers #silkworm varieties #SNP #T-ARMS

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References (26)

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Ahn, H. Y., Cha, J. Y., Park, K. R., Kim, Y. R. and Cho, Y. S. 2013. Improvement effect of fermented silkworm (Bombyx mori L.) power against orotic acid-induced fatty liver in rats. J. Life Sci. 23, 789-795. google schola Bolger, A. M., Lohse, M. and Usadel, B. 2014. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114-2120. google schola Bosco, D., Loria, A., Sartor, C. and Cenis, J. L. 2006. PCR-RFLP identification of Bemisia tabaci biotypes in the Mediterranean Basin. Phytoparasitica 34, 243-251. google schola Danecek, P., Auton, A., Abecasis, G., Albers, C. A., Banksn, E., DePristo, M. A., Handsaker, R. E., Lunter, G., Marth, G. T., Sherry, S. T., McVean, G. and Durbin, R. 2011. The variant call format and VCFtools. Bioinformatics 27, 2156-2158. google schola Groeneveld, L. F., Lenstra, J. A., Eding, H., Toro, M. A., Scherf, B., Pilling, D., Negrini, R., Finlay, E. K., Jianlin, H., Groeneveld, E., Weigend, S. and Globaldiv, C. 2010. Genetic diversity in farm animals-a review. Anim. Genet. 41, 6-31. google schola

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