Skip to main navigation menu Skip to main content Skip to site footer
Plant Science Today (PST)

Research Articles

Early Access

Evaluation of selected Andaman Tall coconut (Cocos nucifera L.) population for uniformity, stability and genetic variation using microsatellite markers

DOI
https://doi.org/10.14719/pst.12824
Submitted
19 November 2025
Published
15-06-2026
Versions

Abstract

Tall coconut genotypes of Andaman were investigated using phenotypic traits and molecular marker analysis to determine genetic consistency. A set of 35 Andaman Tall coconut genotypes was subjected to molecular analysis using fourteen SSR primers. Uniform banding profiles were obtained with 10 out of 14 primers, while four primers exhibited polymorphism, indicating a relatively high level of genetic similarity with moderate genetic variation among the genotypes. Cluster analysis grouped the genotypes into three major clusters, with twelve genotypes in Cluster I, twenty-one in Cluster II and two in Cluster III. From the present study, it is inferred that seed nuts should preferably be collected from mother palms exhibiting consistent and stable phenotypic traits across seasons and from isolated or controlled pollination setups (interse mating), to maintain true-to-type progenies and preserve genetic uniformity. The findings of this study demonstrate that SSR-based molecular markers can serve as an effective tool for identifying genetically true-to-type mother palms for coconut varietal improvement programmes.

References

  1. 1. Arunachalam V, Jerard BA, Elangovan M, Ratnambal MJ, Dhanapal R, Rizal S, et al. Unexploited diversity in coconut palm (Cocos nucifera L.). Plant Genet Resour Newsl. 2001;127:39–43.
  2. 2. Benjamin P, Cesar O, Rigoberto H, Alba M, Daniel D, Mariano M, et al. Module 4: Germplasm conservation. 2008.
  3. 3. Deborah A, Karamura D. Numerical taxonomic studies of the East African highland bananas in Uganda. PhD [thesis]. Reading (UK): University of Reading; 1998.
  4. 4. Zhang J, Jiang Y, Wang Y, Guo Y, Long H, Deng G, et al. Molecular markers and cytogenetics to characterize a wheat-Dasypyrum villosum 3V(3D) substitution line conferring resistance to stripe rust. PLoS One. 2018;13(8):e0202033. https://doi.org/10.1371/journal.pone.0202033
  5. 5. Lai K, Lorenc MT, Lee HC, Berkman PJ, Bayer PE, Visendi P, et al. Identification and characterization of more than 4 million intervarietal SNPs across the group 7 chromosomes of bread wheat. Plant Biotechnol J. 2015;13(1):97–104. https://doi.org/10.1111/pbi.12240
  6. 6. Tanksley SD, Young ND, Paterson AH, Bonierbale MW. RFLP mapping in plant breeding: new tools for an old science. Nat Biotechnol. 1989;7:257–64. https://doi.org/10.1038/nbt0389-257
  7. 7. Lynch M, Milligan BG. Analysis of population genetic structure with RAPD markers. Mol Ecol. 1994;3:91–9. https://doi.org/10.1111/j.1365-294X.1994.tb00109.x
  8. 8. Akkaya MS, Bhagwat AA, Cregan PB. Length polymorphisms of simple sequence repeat DNA in soybean. Genetics. 1992;132:1131–9. https://doi.org/10.1093/genetics/132.4.1131
  9. 9. Reddy MP, Sarla N, Siddiq EA. Inter simple sequence repeat (ISSR) polymorphism and its application in plant breeding. Euphytica. 2002;128:9–17. https://doi.org/10.1023/A:1020691618797
  10. 10. Jorde LB, Watkins WS, Bamshad MJ, Dixon ME, Ricker CE, Seielstad MT, et al. The distribution of human genetic diversity: a comparison of mitochondrial, autosomal and Y-chromosome data. Am J Hum Genet. 2000;66(3):979–88. https://doi.org/10.1086/302825
  11. 11. Goldstein JA, Blaisdell JA, Limdi NA. A potentially deleterious new CYP2C9 polymorphism identified in an African American patient with major hemorrhage on warfarin therapy. Blood Cells Mol Dis. 2009;42(2):155–8. https://doi.org/10.1016/j.bcmd.2008.10.011
  12. 12. Jamali SH, Cockram J, Hickey LT. Insights into deployment of DNA markers in plant variety protection and registration. Theor Appl Genet. 2019;132:1911–29. https://doi.org/10.1007/s00122-019-03348-7
  13. 13. Ratnambal MJ, Nair MK, Muraleedharan K, Kumaran PM, Bhaskara Rao EVV, Pillai RV. Coconut descriptors. Kasaragod: CPCRI; 1995.
  14. 14. Rajesh MK, Jerard BA, Preethi P, Thomas RJ, Fayas TP, Rachana KE, et al. Development of a RAPD-derived SCAR marker associated with tall-type palm trait in coconut. Sci Hortic. 2013;150:312–6. https://doi.org/10.1016/j.scienta.2012.11.023
  15. 15. Lewis PO, Zaykin D. Genetic Data Analysis (GDA): computer program for the analysis of allelic data. Version 1.1 (d16c). Storrs (CT): University of Connecticut; 2002.
  16. 16. Panse VG, Sukhatme PV. Statistical methods for agricultural workers. 3rd ed. New Delhi: ICAR; 1969.
  17. 17. Zavinon F, Adoukonou-Sagbadja H, Keilwagen J, Lehnert H, Ordon F, Perovic D. Genetic diversity and population structure in Beninese pigeon pea (Cajanus cajan) landraces revealed by SSR and genome-wide SNP markers. Genet Resour Crop Evol. 2020;67(1):191–208. https://doi.org/10.1007/s10722-019-00864-9
  18. 18. Teulat B, Aldam C, Trehin R, Lebrun P, Barker JHA, Arnold GM, et al. Analysis of genetic diversity in coconut (Cocos nucifera L.) populations using SSR and AFLP markers. Theor Appl Genet. 2000;100(5):764–71. https://doi.org/10.1007/s001220051350
  19. 19. Perera L, Russell JR, Provan J, Powell W. Levels and distribution of genetic diversity of coconut (Cocos nucifera L. var. typica) from Sri Lanka assessed by microsatellite markers. Euphytica. 2001;122(2):381–9. https://doi.org/10.1023/A:1012987224319
  20. 20. Rajesh MK, Nagarajan P, Jerard BA, Arunachalam V, Dhanapal R. Microsatellite variability of coconut genotypes from Andaman and Nicobar Islands. Curr Sci. 2008;94:12.
  21. 21. Ribeiro FE, Baudouin L, Lebrun P, Chaves LJ, Brondani C, Zucchi MI, et al. Population structure of Brazilian tall coconut (Cocos nucifera L.) by microsatellite markers. Genet Mol Biol. 2010;33(4):696–702. https://doi.org/10.1590/S1415-47572010005000077
  22. 22. Geethanjali S, Rukmani JA, Rajakumar D, Kadirvel P, Viswanathan PL. Genetic diversity, population structure and association analysis in coconut (Cocos nucifera L.) using SSR markers. Plant Genet Resour. 2018;16(2):156–68. https://doi.org/10.1017/S1479262117000119
  23. 23. Preethi P, Rahman S, Naganeeswaran S, Sabana AA, Gangaraj KP, Jerard BA, et al. Development of EST-SSR markers for genetic diversity analysis in coconut. Mol Biol Rep. 2020;47(12):9385–97. https://doi.org/10.1007/s11033-020-05981-8
  24. 24. Loiola CM, Azevedo AON, Diniz LE, Aragao WM, Azevedo CDDO, Santos PHA, et al. Genetic relationships among tall coconut palm accessions of ICG-LAC using microsatellite markers. PLoS One. 2016;11(3):e0151309. https://doi.org/10.1371/journal.pone.0151309
  25. 25. Martinez RT, Baudouin L, Berger A, Dollet M. Characterization of genetic diversity in tall coconut of the Dominican Republic using microsatellite markers. Tree Genet Genomes. 2010;6:73–81. https://doi.org/10.1007/s11295-009-0229-6
  26. 26. Rivera R, Edwards KJ, Barker JHA, Arnold GM, Ayad G, Hodgkin T, et al. Isolation and characterization of polymorphic microsatellites in Cocos nucifera L. Genome. 1999;42:668–75. https://doi.org/10.1139/g98-170
  27. 27. Perera L, Russell JR, Provan J, Powell W. Microsatellite DNA markers for evaluating genetic diversity of coconut. Genome. 2000;43(1):15–21. https://doi.org/10.1139/g99-079
  28. 28. Meerow AW, Wisser RJ, Brown SJ, Kuhn DN, Schnell RJ, Broschat TK. Analysis of genetic diversity and population structure within Florida coconut germplasm using microsatellite markers. Theor Appl Genet. 2003;106(4):715–26. https://doi.org/10.1007/s00122-002-1121-z
  29. 29. Devakumar K, Jayadev K, Rajesh MK, Chandrasekhar A, Manimekalai R, Kumaran PM, et al. Assessment of genetic diversity of Indian coconut accessions using microsatellite markers. Plant Genet Resour Newsl. 2006;145:38–45.
  30. 30. Hamrick JL, Godt MJW. Allozyme diversity in plant species. In: Brown AHD, Clegg MT, Kahler AL, Weir BS, editors. Plant population genetics, breeding and genetic resources. Sunderland (MA): Sinauer Associates; 1989. p. 43–63.
  31. 31. Liu FM, Zhang NN, Liu XJ, Yang ZJ, Jia HY, Xu DP. Genetic diversity and population structure of Dalbergia odorifera using microsatellite markers. Genes. 2019;10(4):281. https://doi.org/10.3390/genes10040281
  32. 32. Perera KC, Chandrika, Perera KLN, Dasanayaka N. Genetic diversity of Sri Lanka yellow dwarf coconut as revealed by microsatellite markers. Trop Agric Res. 2013;26(1):131. https://doi.org/10.4038/tar.v26i1.8078
  33. 33. Feng ML, Li J, Tang LX. Correlation analysis between climatic factors and flowering and pollination characteristics of aromatic coconut. Southwest China J Agric Sci. 2015;28(4):1780–3.
  34. 34. Wright S. The interpretation of population structure by F-statistics with special regard to systems of mating. Evolution. 1965;19:395–420. https://doi.org/10.1111/j.1558-5646.1965.tb01731.x
  35. 35. Weir BS, Cockerham CC. Estimating F-statistics for the analysis of population structure. Evolution. 1984;38:1358–70. https://doi.org/10.1111/j.1558-5646.1984.tb05657.x
  36. 36. Hartl DL, Clark AG. Principles of population genetics. 3rd ed. Sunderland (MA): Sinauer Associates; 1997.

Downloads

Download data is not yet available.