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Analysis of Molecular Variance and Population Structure of Sesame (Sesamum indicum L.) Genotypes Using Simple Sequence Repeat Markers

  • Asekova, Sovetgul (Department of Southern Area Crop Science, National Institute of Crop Science, RDA) ;
  • Kulkarni, Krishnanand P. (School of Applied Biosciences, Kyungpook National University) ;
  • Oh, Ki Won (Research Policy Bureau, RDA) ;
  • Lee, Myung-Hee (Department of Southern Area Crop Science, National Institute of Crop Science, RDA) ;
  • Oh, Eunyoung (Department of Southern Area Crop Science, National Institute of Crop Science, RDA) ;
  • Kim, Jung-In (Department of Southern Area Crop Science, National Institute of Crop Science, RDA) ;
  • Yeo, Un-Sang (Department of Southern Area Crop Science, National Institute of Crop Science, RDA) ;
  • Pae, Suk-Bok (Department of Southern Area Crop Science, National Institute of Crop Science, RDA) ;
  • Ha, Tae Joung (Department of Southern Area Crop Science, National Institute of Crop Science, RDA) ;
  • Kim, Sung Up (Department of Southern Area Crop Science, National Institute of Crop Science, RDA)
  • Received : 2018.08.06
  • Accepted : 2018.09.04
  • Published : 2018.12.01

Abstract

Sesame (Sesamum indicum L.) is an important oilseed crop grown in tropical and subtropical areas. The objective of this study was to investigate the genetic relationships among 129 sesame landraces and cultivars using simple sequence repeat (SSR) markers. Out of 70 SSRs, 23 were found to be informative and produced 157 alleles. The number of alleles per locus ranged from 3 - 14, whereas polymorphic information content ranged from 0.33 - 0.86. A distance-based phylogenetic analysis revealed two major and six minor clusters. The population structure analysis using a Bayesian model-based program in STRUCTURE 2.3.4 divided 129 sesame accessions into three major populations (K = 3). Based on pairwise comparison estimates, Pop1 was observed to be genetically close to Pop2 with $F_{ST}$ value of 0.15, while Pop2 and Pop3 were genetically closest with $F_{ST}$ value of 0.08. Analysis of molecular variance revealed a high percentage of variability among individuals within populations (85.84%) than among the populations (14.16%). Similarly, a high variance was observed among the individuals within the country of origins (90.45%) than between the countries of origins. The grouping of genotypes in clusters was not related to their geographic origin indicating considerable gene flow among sesame genotypes across the selected geographic regions. The SSR markers used in the present study were able to distinguish closely linked sesame genotypes, thereby showing their usefulness in assessing the potentially important source of genetic variation. These markers can be used for future sesame varietal classification, conservation, and other breeding purposes.

Keywords

Acknowledgement

Supported by : Rural Development Administration (RDA)

References

  1. Ali GM, Yasumoto S, Seki-Katsuta M. 2007. Assessment of genetic diversity in sesame (Sesamum indicum L.) detected by Amplified Fragment Length Polymorphism markers. Electron. J. Biotechnol. 10: 12-23.
  2. Anilakumar KR, Pal A, Khanumand F, Bawa AS. 2010. Nutritional, medicinal and industrial uses of sesame (Sesamum indicum L.) seeds-An overview. Agriculturae Conspectus Scientificus. 75: 159-168.
  3. Barbosa CV, Silva AS, de Oliveira CV, Massa NM, de Sousa YR, da Costa WK, et al. 2017. Effects of sesame (Sesamum indicum L.) supplementation on creatine kinase, lactate dehydrogenase, oxidative stress markers, and aerobic capacity in semi-professional soccer players. Front. Physiol. 8: 196.
  4. Bhat KV, Babrekar PP, Lakhanpaul S. 1999. Study of genetic diversity in Indian and exotic sesame (Sesamum indicum L.) germplasm using Random Amplified Polymorphic DNA (RAPD) markers. Euphytica 110: 21-34. https://doi.org/10.1023/A:1003724732323
  5. Cho YI, Park JH, Lee CW, Ra WH, Chung JW, Lee JR, et al. 2011. Evaluation of the genetic diversity and population structure of sesame (Sesamum indicum L.) using microsatellite markers. Genes Genomics 33: 187-195. https://doi.org/10.1007/s13258-010-0130-6
  6. Cui C, Mei H, Liu Y, Zhang H, Zheng Y. 2017. Genetic diversity, population structure, and linkage disequilibrium of an association-mapping panel revealed by genomeide SNP markers in sesame. Front. Plant Sci. 8: 1189. https://doi.org/10.3389/fpls.2017.01189
  7. Dixit A, Jin MH, Chung JW, Yu JW, Chung HK, Ma KH, et al. 2005. Development of polymorphic microsatellite markers in sesame (Sesamum indicum L.). Mol. Ecol. Notes 5: 736-738. https://doi.org/10.1111/j.1471-8286.2005.01048.x
  8. Dossa K, Wei X, Zhang Y, Fonceka D, Yang W, Diouf D, et al. 2016. Analysis of genetic diversity and population structure of sesame accessions from Africa and Asia as major centers of its cultivation. Genes 7: 14. https://doi.org/10.3390/genes7040014
  9. Dossa K, Yu J, Liao B, Cisse N, Zhang X. 2017. Development of highly informative genome-wide single sequence repeat markers for breeding applications in sesame and construction of a web resource: SisatBase. Front. Plant Sci. 8: 1470. https://doi.org/10.3389/fpls.2017.01470
  10. Ercan AG, Taskin M, Turgut K. 2004. Analysis of genetic diversity in Turkish sesame (Sesamum indicum L.) populations using RAPD markers. Genet. Resour. Crop Evol. 51: 599-607. https://doi.org/10.1023/B:GRES.0000024651.45623.f2
  11. 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. https://doi.org/10.1111/j.1365-294X.2005.02553.x
  12. Excoffier L, Laval G, Schneider S. 2005. ARLEQUIN (version 3.0): an integrated software package for population genetics data analysis. Evol. Bioinform. Online 1: 47-50.
  13. Hanzawa F, Nomura S, Sakuma E, Uchida T, Ikeda S. 2013. Dietary sesame seed and its lignan, sesamin, increase tocopherol and phylloquinone concentrations in male rats. J. Nutr. 143: 1067-1073. https://doi.org/10.3945/jn.113.176636
  14. Hirata F, Fujita K, Ishikura Y, Hosoda K, Ishikawa T, Nakamura H. 1996. Hypocholesterolemic effect of sesame lignan in humans. Atherosclerosis 122: 135-136. https://doi.org/10.1016/0021-9150(95)05769-2
  15. Kalia RK, Rai MK, Kalia S, Singh R, Dhawan AK. 2011. Microsatellite markers: an overview of the recent progress in plants. Euphytica 177: 309-334. https://doi.org/10.1007/s10681-010-0286-9
  16. Kang CW, Kim SY, Lee SW, Mathur PN, Hodgkin T, Zhou MD, et al. 2006. Selection of a core collection of Korean germplasm by a stepwise clustering method. Breed. Sci. 56: 85-91. https://doi.org/10.1270/jsbbs.56.85
  17. Kim DH, Kashi Y, Zur G, Danin-Poleg Y, Lee SW, Shim KB, et al. 2001. Genetic relationships among sesame (Sesamum indicum) accessions using inter-simple sequence repeats (ISSR) markers. Korean J. Breed. Sci. 33: 257-269.
  18. Kim DH, Zur G, Danin-Poleg Y, Lee SW, Shim KB, Kang CW, et al. 2002. Genetic relationships of sesame germplasm collection as revealed by inter-simple sequence repeats. Plant Breed. 121: 259-262. https://doi.org/10.1046/j.1439-0523.2002.00700.x
  19. Lewontin RC. 1972. The apportionment of human diversity. p. 381-398. In: T. Dobzhansky, MK. Hecht, WC. Steere (eds.). Evolutionary Biology. Springer, Boston, MA.
  20. Lischer HEL, Excoffier L. 2012. PGDSpider: an automated data conversion tool for connecting population genetics and genomics programs. Bioinformatics 28: 298-299. https://doi.org/10.1093/bioinformatics/btr642
  21. Liu KJ, Muse SV. 2005. PowerMarker: an integrated analysis environment for genetic marker analysis. Bioinformatics 21: 2128-2129. https://doi.org/10.1093/bioinformatics/bti282
  22. Min S-K, Choi B, Park J-H, Chung J-W, Kim K-W, Park Y-J. 2016. Assessment of genetic diversity and population structure of the sub core set in sesame (Sesamum indicum) using SSR markers. J. Korean Soc. Int. Agric. 28: 73-83. https://doi.org/10.12719/KSIA.2016.28.1.73
  23. Mondal N, Bhat KV, Srivastave PS, Sen SK. 2015. Effects of domestication bottleneck and selection on fatty acid desaturases in Indian sesame germplasm. Plant Genet. Resour. 14: 81-90.
  24. Okello-Anyanga W, Hasel-Hohl K, Burg A, Gaubitzer S, Rubaihayo PR, Vollmann J, et al. 2017. Towards the selection of superior sesame lines based on genetic and phenotypic characterisation for Uganda. J. Agric. Sci. 9: 13-35.
  25. Pritchard JK, Stephens M, Donnelly P. 2000. Inference of population structure using multilocus genotype data. Genetics 155: 945-959.
  26. Rao PVR, Prasuna K, Anuradha G, Shividhya A, Reddy VLN, Shankar VG, et al. 2013. Molecular mapping and tagging of powdery mildew tolerance gene(s) in sesame (Sesamum indicum). Indian J. Agr. Sci. 83: 605-610.
  27. Rao VR, Hodgkin T. 2002. Genetic diversity and conservation and utilization of plant genetic resources. Plant Cell Tissue Organ Cult. 68: 1-19. https://doi.org/10.1023/A:1013359015812
  28. Rohlf FJ. 2001. NTSYS-pc version 2.11. Distribution by Exeter Software. Setauket, New York.
  29. Uchida T, Ichikawa T, Abe C, Yamashita K, Ikeda S. 2007. Dietary sesame seed decreases urinary excretion of alphaand gamma-tocopherol metabolites in rats. J. Nut. Sci. Vitaminol. 53: 372-376. https://doi.org/10.3177/jnsv.53.372
  30. Uncu AO, Gultekin V, Allmer J, Frary A, Doganlar S. 2015. Genomic simple sequence repeat markers reveal patterns of genetic relatedness and diversity in sesame. Plant Genome 8: 1-12.
  31. Wang L, Yu S, Tong C, Zhao Y, Liu Y, Song C, et al. 2014a. Genome sequencing of the high oil crop sesame provides insight into oil biosynthesis. BMC Genome Biol. 15: R39. https://doi.org/10.1186/gb-2014-15-2-r39
  32. Wang L, Han X, Zhang Y, Li D, Wei X, Ding X, et al. 2014b. Deep resequencing reveals allelic variation in Sesamum indicum. BMC Plant Biol. 14: 225. https://doi.org/10.1186/s12870-014-0225-3
  33. Wang L, Zhang Y, Zhu X, Zhu X, Li D, Zhang X, et al. 2017. Development of an SSR-based genetic map in sesame and identification of quantitative trait loci associated with charcoal rot resistance. Sci. Rep. 7: 8349. https://doi.org/10.1038/s41598-017-08858-2
  34. Wei W, Zhang Y, L ü H, Li D, Wang L, Zhang X, 2013. Association analysis for quality traits in a diverse panel of Chinese sesame (Sesamum indicum L.) germplasm. J. Integr. Plant Biol. 55: 745-758. https://doi.org/10.1111/jipb.12049
  35. Wei X, Wang L, Zhang Y, Qi X, Wang X, Ding X, et al. 2014. Development of simple sequence repeat (SSR) markers of sesame (Sesamum indicum) from a genome survey. Molecules 19: 5150-5162. https://doi.org/10.3390/molecules19045150
  36. Wei X, Zhu X, Yu J, Wang L, Zhang Y, Li D, et al. 2016. Identification of sesame genomic variations from genome comparison of landrace and variety. Front. Plant Sci. 7: 1169.
  37. Yeh FC, Yang RC, Boyle TJB. 1999. POPGENE version 1.32. Microsoft window-based freeware for population genetic analysis. University of Alberta and Centre for International Forestry Research, Edmonton, AB, Canada.
  38. Zhang H, Wei L, Miao H, Zhang T, Wang C. 2012. Development and validation of genic-SSR markers in sesame by RNA-seq. BMC Genomics 13: 316. https://doi.org/10.1186/1471-2164-13-316
  39. Zhang H, Miao H, Wang L, Qu L, Liu H, Wang Q, et al. 2013. Genome sequencing of the important oilseed crop Sesamum indicum L. Genome Biol. 14: 401. https://doi.org/10.1186/gb-2013-14-1-401