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Genetic diversity and population structure among accessions of Perilla frutescens (L.) Britton in East Asia using new developed microsatellite markers

Abstract

SSRs were successfully isolated from the Perilla crop in our current study, and used to analyze Perilla accessions from East Asia. Analyses of the clear genetic diversity and relationship for Perilla crop still remain insufficient. In this study, 40 new simple sequence repeat (SSR) primer sets were developed from RNA sequences using transcriptome analysis. These new SSR markers were applied to analyze the diversity, relationships, and population structure among 35 accessions of the two cultivated types of Perilla crop and their weedy types. A total of 220 alleles were identified at all loci, with an average of 5.5 alleles per locus and a range between 2 and 10 alleles per locus. The MAF (major allele frequency) per locus varied from 0.229 to 0.943, with an average of 0.466. The average polymorphic information content (PIC) value was 0.603, ranging from 0.102 to 0.837. The genetic diversity (GD) ranged from 0.108 to 0.854, with an average of 0.654. Based on population structure analysis, all accessions were divided into three groups: Group I, Group II and the admixed group. This study demonstrated the utility of new SSR analysis for the study of genetic diversity and population structure among 35 Perilla accessions. The GD of each locus for accessions of cultivated var. frutescens, weedy var. frutescens, cultivated var. crispa, and weedy var. crispa were 0.415, 0.606, 0.308, and 0.480, respectively. Both weedy accessions exhibited higher GD and PIC values than their cultivated types in East Asia. The new SSR primers of Perilla species reported in this study may provide potential genetic markers for population genetics to enhance our understanding of the genetic diversity, genetic relationship and population structure of the cultivated and weedy types of P. frutescens in East Asia. In addition, new Perilla SSR primers developed from RNA-seq can be used in the future for cultivar identification, conservation of Perilla germplasm resources, genome mapping and tagging of important genes/QTLs for Perilla breeding programs.

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References

  • Bostein D, White RL, Skolnick M, Davis RW (1980) Construction of a genetic linkage map in man using restriction fragment length polymorphisms. Am J Genet 32:314–331

    Google Scholar 

  • Dice LR (1945) Measures of the amount of ecologic association between species. Ecology 26:297–302

    Article  Google Scholar 

  • Evanno G, Regnaut S, Goudet J (2005) Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol Ecol 14:2611–2620

    CAS  Article  Google Scholar 

  • Fukushima A, Nakamura M, Suzuki H, Saito K, Yamazaki M (2015) High-throughput sequencing and de novo assembly of red and green forms of the Perilla frutescens var. crispa Transcriptome. PLoS ONE 10(6):e0129154. https://doi.org/10.1371/journal.pone.0129154

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  • Hamza S, Hamida WB, Rebaϊ A, Harrabi M (2004) SSR-based genetic diversity assessment among Tunisian winter barley and relationship with morphological traits. Euphytica 135:107–118

    CAS  Article  Google Scholar 

  • Hancock JF (1992) Plant evolution and the origin of crop species. Prentice Hall, Englewood Cliffs

    Google Scholar 

  • Jochen CR, Hamrit S, Heckenberger M, Schipprack W, Maurer HP, Bohn M, Melchinger AE (2005) Genetic structure and diversity of European flint maize populations determined with SSR analyses of individuals and bulks. Theor Appl Genet 111:906–913

    Article  Google Scholar 

  • Kwon SJ, Lee JK, Kim NS, Yu JW, Dixit A, Cho EG, Park YJ (2005) Isolation and characterization of SSR markers in Perilla frutescens Britt. Mol Ecol Notes 5:454–456

    Article  Google Scholar 

  • Ladizinsky G (1998) Plant evolution under domestication. Chapman & Hall Published, Raleigh

    Book  Google Scholar 

  • Lee JK, Kim NS (2007) Genetic diversity and relationships of cultivated and weedy types of Perilla frutescens collected from East Asia revealed by SSR markers. Korean J Breed Sci 39:491–499

    Google Scholar 

  • Lee JK, Ohnishi O (2001) Geographic differentiation of morphological characters among Perilla crops and their weedy types in East Asia. Breed Sci 51:247–255

    Article  Google Scholar 

  • Lee JK, Ohnishi O (2003) Genetic relationships among cultivated types of Perilla frutescens and their weedy types in East Asia revealed by AFLP markers. Genet Resour Crop Evol 50:65–74

    CAS  Article  Google Scholar 

  • Lee JK, Nitta M, Kim NS, Park CH, Yoon KM, Shin YB, Ohnishi O (2002) Genetic diversity of Perilla and related weedy types in Korea determined by AFLP analyses. Crop Sci 42:2161–2166

    CAS  Article  Google Scholar 

  • Lee JK, Kwon SJ, Park BJ, Kim MJ, Park YJ, Ma KH, Lee SY, Kim JH (2007) Analysis of genetic diversity and Relationships of cultivated and weedy types of Perilla frutescens collected from Korea by using microsatellite markers. Korean J Genet 29:81–89

    CAS  Google Scholar 

  • Li HL (1969) The vegetables of ancient China. Econ Bot 23:235–260

    Article  Google Scholar 

  • Liu K, Muse SV (2005) PowerMarker: an integrated analysis environment for genetic marker analysis. Bioinformatics 21:2128–2129

    CAS  Article  Google Scholar 

  • Ma SJ, Sa KJ, Hong TK, Lee JK (2017) Genetic diversity and population structure analysis in Perilla frutescens from Northern areas of China based on simple sequence repeats. Genet Mol Res 16(3):gmr16039746. https://doi.org/10.4238/gmr16039746

    Article  Google Scholar 

  • Makino T (1961) Makino’s new illustrated flora of Japan. Hokuryukan, Tokyo (in Japanese)

    Google Scholar 

  • Mutz KO, Heilkenbrinker A, Lonne M, Walter JG, Stahl F (2012) Transcriptome analysis using next-generation sequencing. Curr Opin Biotechnol 24:22–30

    Article  Google Scholar 

  • Ni J, Colowit PM, Mackill DJ (2002) Evaluation of Genetic Diversity in Rice Subspecies Using SSR Markers. Crop Sci 42:601–607

    CAS  Article  Google Scholar 

  • Nitta M (2001) Origin Perilla crops and their weedy type. Ph.D. Thesis, Kyoto University, Kyoto, p. 78

  • Nitta M, Ohnishi O (1999) Genetic relationships among two Perilla crops, shiso and egoma, and the weedy type revealed by RAPD markers. Jpn J Genet 74:43–48

    CAS  Google Scholar 

  • Nitta M, Lee JK, Ohnishi O (2003) Asian Perilla crops and their weedy forms: their cultivation, utilization and genetic relationships. Econ Bot 57:245–253

    Article  Google Scholar 

  • Nitta M, Lee JK, Kang CW, Katsuta M, Yasumoto S, Liu D, Nagamine T, Ohnishi O (2005) The distribution of Perilla species. Genet Resour Crop Evol 52:797–8044

    Article  Google Scholar 

  • Park YJ, Dixit A, Ma KH, Lee JK, Lee MH, Chung CS, Nitta M, Okuno K, Kim TS, Cho EG, Rao VR (2008) Evaluation of genetic diversity and relationships within an on-farm collection of Perilla frutescens (L.) Britt. using SSR markers. Genet Resour Crop Evol 55:523–535

    CAS  Article  Google Scholar 

  • Park YJ, Lee JK, Kim NS (2009) Simple sequence repeat polymorphisms (SSRPs) for evaluation of molecular diversity and germplasm classification of minor crops. Molecules 14:4546–4569

    CAS  Article  Google Scholar 

  • Powell W, Morgante M, Andre C, Hanafey M, Vogel J, Tingey S, Rafalski A (1996) The comparison of RFLP, RAPD, AFLP and SSR (SSR) markers for germplasm analysis. Mol Breed 2:225–238

    CAS  Article  Google Scholar 

  • Prasad M, Varshney RK, Roy JK, Balyan HS, Gupta PK (2000) The use of microsatellites for detecting DNA polymorphism, genotype identification and genetic diversity in wheat. Theor Appl Genet 100:584–592

    CAS  Google Scholar 

  • Pritchard JK, Wen W (2003) Documentation for STRUCTURE software: Version 2

  • Rohlf FJ (1998) NTSYS-pc: numerical taxonomy and multivariate analysis system. Version: 2.02. Exter Software, Setauket

    Google Scholar 

  • Sa KJ, Park JY, Park KJ, Lee JK (2010) Analysis of genetic diversity and relationships among waxy maize inbred lines in Korea using SSR markers. Genes Genomics 32:375–384

    Article  Google Scholar 

  • Sa KJ, Kim JA, Lee JK (2012) Comparison of seed characteristics between the cultivated and the weedy types of Perilla species. Hort Environ Biotechnol 53(4):310–315

    Article  Google Scholar 

  • Sa KJ, Choi SH, Ueno M, Park KC, Park YJ, Ma KH, Lee JK (2013) Identification of genetic variations of cultivated and weedy types of Perilla species in Korea and Japan using morphological and SSR markers. Genes Genomics 35:649–659

    CAS  Article  Google Scholar 

  • Sa KJ, Choi SH, Ueno M, Lee JK (2015) Genetic diversity and population structure in cultivated and weedy types of Perilla in East Asia and other countries as revealed by SSR markers. Hortic Environ Biotechnol 56(4):524–534

    Article  Google Scholar 

  • Schontz D, Rether B (1999) Genetic variability in foxtail millet, Setaria italica (L.) P. Beauv.: identification and classification of lines with RAPD markers. Plant Breed 118:190–192

    Article  Google Scholar 

  • Tong W, Kwon SJ, Lee JS, Choi IK, Park YJ, Choi SH, Sa KJ, Kim BW, Lee JK (2015) Gene set by de novo assembly of Perilla species and expression profiling between P. frutescens (L.) var. frutescens and var. crispa. Gene 559:155–163

    CAS  Article  Google Scholar 

  • Wang R, Yu Y, Zhao J, Shi Y, Song Y, Wang T, Li Y (2008) Population structure and linkage disequilibrium of a mini core set of maize inbred lines in China. Theor Appl Genet 117:1141–1153

    CAS  Article  Google Scholar 

  • Wang L, Wang Z, Chen J, Liu C, Zhu W, Wang L, Meng L (2015) De novo transcriptome assembly and development of novel microsatellite markers for the traditional chinese medicinal herb, Veratrilla baillonii franch (Gentianaceae). Evol Bioinform 11(S1):39–45. https://doi.org/10.4137/EBO.S20942

    CAS  Article  Google Scholar 

  • Xia XC, Reif JC, Melchinger AE, Frisch M, Hoisington DA, Beck K, Pixley K, Warburton ML (2005) Genetic diversity among CIMMYT maize inbred lines investigated with SSR markers: II. Subtropical, tropical midaltitude, and highland maize inbred lines and their relationships with elite U.S. and European maize. Crop Sci 45:2573–2582

    CAS  Article  Google Scholar 

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Acknowledgements

This study was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science, and Technology (#2016R1D1A1B01006461).

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Correspondence to Ju Kyong Lee.

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Kyu Jin Sa declares that he has no conflict of interest. Ik-Young Choi declares that he has no conflict of interest. Kyong-Cheul Park declares that he has no conflict of interest. Ju Kyong Lee declares that he has no conflict of interest.

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This article does not contain any studies with human subjects or animals performed by any of the above authors.

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Sa, K.J., Choi, IY., Park, KC. et al. Genetic diversity and population structure among accessions of Perilla frutescens (L.) Britton in East Asia using new developed microsatellite markers. Genes Genom 40, 1319–1329 (2018). https://doi.org/10.1007/s13258-018-0727-8

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  • DOI: https://doi.org/10.1007/s13258-018-0727-8

Keywords

  • Perilla frutescens
  • Oil crop
  • Chinese medicine or vegetable crop
  • Genetic diversity and relationship
  • Microsatellites
  • RNA-seq