Hostname: page-component-586b7cd67f-g8jcs Total loading time: 0 Render date: 2024-11-25T15:54:44.114Z Has data issue: false hasContentIssue false
  • English
  • Français

Genetic diversity, population structure and association analysis in coconut (Cocos nucifera L.) germplasm using SSR markers

Published online by Cambridge University Press:  10 April 2017

S. Geethanjali ,
J. Anitha Rukmani ,
D. Rajakumar ,
P. Kadirvel  and
P.L. Viswanathan
S. Geethanjali*
Affiliation:
Coconut Research Station, Tamil Nadu Agricultural University, Aliyarnagar-642101, Coimbatore, India
J. Anitha Rukmani
Affiliation:
Coconut Research Station, Tamil Nadu Agricultural University, Aliyarnagar-642101, Coimbatore, India Department of Oilseeds, Tamil Nadu Agricultural University, Coimbatore-641003, India
D. Rajakumar
Affiliation:
Coconut Research Station, Tamil Nadu Agricultural University, Aliyarnagar-642101, Coimbatore, India
P. Kadirvel
Affiliation:
ICAR-Indian Institute of Oilseeds Research, Rajendranagar, Hyderabad-500030, India
P.L. Viswanathan
Affiliation:
Department of Oilseeds, Tamil Nadu Agricultural University, Coimbatore-641003, India
*
*Corresponding author. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

A world-wide coconut germplasm collection (79 genotypes) was analyzed for genetic diversity and population structure based on 48 simple sequence repeat (SSR) loci. The genotypes displayed moderately high amount of genetic diversity, which was strongly structured according to geographical origins. Number of SSR alleles ranged from 2 to 7 with an average of 4.1 per locus. Gene diversity (expected heterozygosity) estimates ranged from 0.162 to 0.811 with a mean of 0.573. Polymorphism information content values ranged from 0.149 to 0.785 with an average of 0.522. Hierarchical clustering analysis grouped the genotypes into two major clusters with two sub-groups in each, which corresponded with the geographic origins. The first cluster comprised of ‘Tall’ genotypes originated from Indo-Atlantic and South Asia regions. The second cluster comprised mostly of ‘Dwarf’ genotypes and some Tall genotypes which originated from Indo-Pacific and South-East Asia regions. Model-based clustering by STRUCTURE analysis also supported the presence of clear genetic structuring in the collection with two major populations (K = 2) and four sub-populations (K = 4). The proportion of SSR locus-pairs in linkage disequilibrium was low (2.4%). Association analysis in a subset of 44 genotypes detected a single SSR locus, CnCir73 (chromosome 1) putatively associated with fruit yield component traits, which corresponded with a previously mapped quantitative trait locus in coconut.

Keywords

hierarchical clusteringlinkage disequilibriummicrosatellite markersplantation crop
Type
Research Article
Information
Plant Genetic Resources , Volume 16 , Issue 2 , April 2018 , pp. 156 - 168
Copyright
Copyright © NIAB 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

†

Current address: Centre for Plant Breeding and Genetics, Tamil Nadu Agricultural University, Coimbatore-641003, India.

References

Abdurakhmonov, IY and Abdukarimov, A (2008) Application of association mapping to understanding the genetic diversity of plant germplasm resources. International Journal of Plant Genomics 2008: 574927. doi: 10.1155/2008/574927.Google Scholar
Agrama, HA, Eizenga, GC and Yan, W (2007) Association mapping of yield and its components in rice cultivars. Molecular Breeding 19: 341–356.CrossRefGoogle Scholar
Angeles, JGC, Laurena, AC and Tecson-Mendoza, EM (2005) Extraction of genomic DNA from the lipid, polysaccharide and polyphenol-rich coconut (Cocos nucifera L.). Plant Molecular Biology Reporter 23(3): 297–298.Google Scholar
Ashburner, GR, Thompson, WK and Halloran, GM (1997) RAPD analysis of south Pacific coconut palm populations. Crop Science 37: 992–997.Google Scholar
Balakrishnan, NP and Nair, RB (1979) Wild populations of Areca and Cocos in Andaman and Nicobar Islands. Indian Journal of Forestry 2: 350–363.Google Scholar
Baudouin, L and Lebrun, P (2002) The development of microsatellite kit and dedicated software for use with coconuts. BUROTROP Bulletin 17: 16–20.Google Scholar
Baudouin, L, Lebrun, P, Konan, JL, Ritter, E, Berger, A and Billotte, N (2006) QTL analysis of fruit components in the progeny of a Rennell Island Tall coconut (Cocos nucifera L.) individual. Theoretical and Applied Genetics 112: 258–268.CrossRefGoogle ScholarPubMed
Bradbury, PJ, Zhang, Z, Kroon, DE, Casstevens, TM, Ramdoss, Y and Buckler, ES (2007) TASSEL: software for association mapping of complex traits in diverse samples. Bioinformatics 23: 2633–2635.CrossRefGoogle ScholarPubMed
Cardeña, R, Ashburner, GR and Oropeza, C (2003) Identification of RAPDs associated with resistance to lethal yellowing of the coconut (Cocos nucifera L.) palm. Scientia Horticulturae 98: 257–263.CrossRefGoogle Scholar
Daher, RF, Pereira, MG, Tupinambá, EA, Amaral Junior, AT, Aragao, WM, Ribeiro, FE, Oliveira, LO and Sakiyama, NS (2002) Assessment of coconut tree genetic divergence by compound sample RAPD marker analysis. Crop Breeding and Applied Biotechnology 2(3): 431–438.Google Scholar
Dasanayaka, PN, Everard, JMDT, Karunanayaka, EH and Nandadasa, HG (2009) Analysis of coconut (Cocos nucifera L.) diversity using microsatellite markers with emphasis on management and utilization of genetic resources. Journal of the National Science Foundation of Sri Lanka 37(2): 99–109.Google Scholar
Deva Kumar, K, Thomas, RJ, Nair, RV, Jerard, AB, Rajesh, MK, Jacob, PM, Jayadev, K and Parthasarathy, VA (2011) Analysis of population structure and genetic relatedness among root (wilt) disease-resistant and susceptible west coast Tall coconut palms (Cocos nucifera) using microsatellite markers. The Indian Journal of Agricultural Sciences 81(6): 487–493.Google Scholar
Earl, DA and vonHoldt, BM (2012) STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method. Conservation Genetics Resources 4(2): 359–361.CrossRefGoogle Scholar
Evanno, G, Regnaut, S and Goudet, J (2005) Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Molecular Ecology 14: 2611–2620.Google Scholar
FAOSTAT (2012) http://faostat.fao.org.Google Scholar
Font i Forcada, C, Oraguzie, N, Reyes-ChinWo, S, Espiau, MT, Socias i Company, R and Fernández i Martí, A (2015) Identification of genetic loci associated with quality traits in almond via association mapping. PLoS ONE 10(6): e0127656. doi: 10.1371/journal.pone.0127656.Google Scholar
Franco, J, Crossa, J, Taba, S and Shands, H (2005) A sampling strategy for conserving genetic diversity when forming core subsets. Crop Science 45: 1035–1044.CrossRefGoogle Scholar
Geethanjali, S, Rajkumar, D and Shoba, N (2014) Correlation and path coefficient analysis in coconut (Cocos nucifera L.). Electronic Journal of Plant Breeding 5(4): 702–707.Google Scholar
Gunn, BF, Baudouin, L and Olsen, KM (2011) Independent origins of cultivated coconut (Cocos nucifera L.) in the old world tropics. PLoS ONE 6(6): e21143 doi: 10.1371/journal.pone.0021143.CrossRefGoogle ScholarPubMed
Hamrick, JL and Godt, MJW (1990) Plant Population Genetics, Breeding, and Genetic Resources. Sunderland, MA: Sinauer. pp. 43–63.Google Scholar
Hamrick, JL and Godt, MJW (1996) Effects of life history traits on genetic diversity in plant species. Philosophical Transactions of Royal Society of London B 351: 1291–1298.Google Scholar
Harries, HC (1978) The evolution, dissemination and classification of Cocos nucifera L. The Botanical Review 44: 265–320.Google Scholar
Hartl, DL and Clark, AG (1997) Principles of Population Genetics. Sunderland, MA: Sinauer.Google Scholar
Herrán, A, Estioko, L, Becker, D, Rodriguez, MJB, Rohde, W and Ritter, E (2000) Linkage mapping and QTL analysis in coconut (Cocos nucifera L.). Theoretical and Applied Genetics 101: 292–300.Google Scholar
Iquira, E, Humira, S and François, B (2015) Association mapping of QTLs for Sclerotinia stem rot resistance in a collection of soybean plant introductions using a genotyping by sequencing (GBS) approach. BMC Plant Biology 15. DOI 10.1186/s12870–014–0408-y.Google Scholar
Jobson, JD (1992) Applied Multivariate Data Analysis, vol. II. Categorical and multivariate methods. New York: Springer.CrossRefGoogle Scholar
Lance, GN and Williams, WT (1967) A general theory of classificatory sorting strategies 1. Hierarchical systems. The Computer Journal 9: 373–380.Google Scholar
Lebrun, P, N'cho, YP, Seguin, M, Grivet, L and Baudouin, L (1998) Genetic diversity in coconut (Cocos nucifera L.) revealed by restriction fragment length polymorphism (RFLP) markers. Euphytica 101: 103–108.Google Scholar
Lebrun, P, Grivet, L and Baudouin, L (1999) Use of RFLP markers to study the diversity of the coconut palm. In: Oropeza, C, Verdeil, JL, Ashburner, GR, Cardeña, R, Santamaría, JM (eds) Current Advances in Coconut Biotechnology. Netherlands: Springer, pp. 73–87.Google Scholar
Lebrun, P, Baudouin, L, Bourdeix, R, Konan, JL, Barker, JH, Aldam, C, Herrán, A and Ritter, E (2001) Construction of a linkage map of the Rennell Island Tall coconut type (Cocos nucifera L.) and QTL analysis for yield characters. Genome 44: 962–970.Google Scholar
Liu, K and Muse, SV (2005) PowerMarker-an integrated analysis environment for genetic marker analysis. Bioinformatics 21(9): 2128–2129.Google Scholar
Liu, X, Tang, H, Li, D and Hou, L (2011) Genetic diversity of coconut cultivars in China by microsatellite (SSR) markers. Molecular Plant Breeding 2(12): 83–91.Google Scholar
Loiola, CM, Azevedo, AON, Diniz, LEC, Aragão, WM, Azevedo, CDDO, Santos, PHAD, Ramos, HCC, Pereira, MG and Ramos, SRR (2016) Genetic relationships among Tall coconut palm (Cocos nucifera L.) genotypes of the International Coconut Genebank for Latin America and the Caribbean (ICG-LAC), evaluated using microsatellite markers (SSRs). PLoS ONE 11(3): e0151309. doi: 10.1371/journal.pone.0151309.CrossRefGoogle Scholar
Manimekalai, R and Nagarajan, P (2006) Assessing genetic relationships among coconut (Cocos nucifera L.) genotypes using inter simple sequence repeat markers. Scientia Horticulturae 108: 49–54.CrossRefGoogle Scholar
Martinez, RT, Baudouin, L, Berger, A and Dollet, M (2010) Characterization of the genetic diversity of the Tall coconut (Cocos nucifera L.) in the Dominican Republic using microsatellite (SSR) markers. Tree Genetics & Genomes 6: 73–81.Google Scholar
Mauro-Herrera, M, Meerow, AW, Borrone, JW, Kuhn, DN and Schnell, RJ (2007) Usefulness of WRKY gene-derived markers for assessing genetic population structure: an example with Florida coconut cultivars. Scientia Horticulturae 115: 19–26.Google Scholar
Meerow, AW, Wisser, RJ, Brown, JS, Kuhn, DN, Schnell, RJ and Broschat, TK (2003) Analysis of genetic diversity and population structure within Florida coconut (Cocos nucifera L.) germplasm using microsatellite DNA, with special emphasis on the Fiji Dwarf cultivar. Theoretical and Applied Genetics 106: 715–726.Google Scholar
Odong, TL, van Heerwaarden, J, Jansen, J, van Hintum, TJL and van Eeuwijk, FA (2011) Determination of genetic structure of germplasm collections: are traditional hierarchical clustering methods appropriate for molecular marker data? Theoretical and Applied Genetics 123: 195–205.Google Scholar
Panaud, O, Chen, X and McCouch, SR (1996) Development of microsatellite markers and characterization of simple sequence length polymorphism (SSLP) in rice (Oryza sativa L.). Molecular and General Genetics 252: 597–607.Google Scholar
Panda, KC (1982) Coconut types of Orissa. Indian Coconut Journal 13: 10–18.Google Scholar
Parthasarathy, VA, Geethalakshmi, P and Niral, V (2004) Analysis of coconut cultivars and hybrids using isozyme polymorphism. Acta Botanica Croatica 63: 69–74.Google Scholar
Perera, L, Russell, JR, Provan, J, McNicol, JW and Powell, W (1998) Evaluating genetic relationship between indigenous coconut (Cocos nucifera L.) genotypes from Sri Lanka by means of AFLP profiling. Theoretical and Applied Genetics 96: 545–550.Google Scholar
Perera, L, Russell, JR, Provan, J and Powell, W (2000) Use of microsatellite DNA markers to investigate the level of genetic diversity and population genetic structure of coconut (Cocos nucifera L.). Genome 43: 15–21.Google Scholar
Perera, L, Russell, JR, Provan, J and Powell, W (2001) Levels and distribution of genetic diversity of coconut (Cocos nucifera L., var. Typica form typica) from Sri Lanka assessed by microsatellite markers. Euphytica 122: 381–389.Google Scholar
Perrier, X and Jacquemoud-Collet, JP (2006) DARwin software. Available at http://darwin.cirad.fr/ Google Scholar
Pritchard, JK, Stephens, M, Rosenberg, NA and Donelly, P (2000) Association mapping in structured populations. The American Journal of Human Genetics 37: 170–181.Google Scholar
Rajesh, MK, Arunachalam, V, Nagarajan, P, Lebrun, P, Samsudeen, K and Thamban, C (2008a) Genetic survey of 10 Indian coconut landraces by simple sequence repeats (SSRs). Scientia Horticulturae 118: 282–287.Google Scholar
Rajesh, MK, Nagarajan, P, Jerard, BA, Arunachalam, V and Dhanapal, R (2008b) Microsatellite variability of coconut genotypes (Cocos nucifera L.) from Andaman and Nicobar Islands. Current Science 94: 12.Google Scholar
Ratnambal, MJ, Nair, MK, Muralidharan, K, Kumaran, PM, Bhaskara Rao, EVV and Pillai, RV (1995) Coconut Descriptors. Part I. Kasaragod, India: Central Plantation Crops Research Institute.Google Scholar
Ribeiro, FE, Baudouin, L, Lebrun, P, Chaves, LJ, Brondani, C, Zucchi, MI and Vencovsky, R (2010) Population structures of Brazilian Tall coconut (Cocos nucifera L.) by microsatellite markers. Genetics and Molecular Biology 33(4): 696–702.Google Scholar
Riedel, M, Riederer, M, Becker, D, Herrán, A, Kullaya, A, Arana-López, G, Peña-Rodríguez, L, Billotte, N, Sniady, V, Rohde, W and Ritter, E (2009) Cuticular wax composition in Cocos nucifera L.: physicochemical analysis of wax components and mapping of their QTLs onto the coconut molecular linkage map. Tree Genetics & Genomes 5: 53–69.CrossRefGoogle Scholar
Rivera, R, Edwards, KJ, Barker, JH, Arnold, GM, Ayad, G, Hodgkin, T and Karp, A (1999) Isolation and characterization of polymorphic microsatellites in Cocos nucifera L. Genome 42: 668–675.Google Scholar
Shalini, KV, Manjunatha, S, Lebrun, P, Berger, A, Baudouin, L, Pirany, N, Ranganath, RM and Prasad, DT (2007) Identification of molecular markers associated with mite resistance in coconut (Cocos nucifera L.). Genome 50: 35–42.Google Scholar
Sokal, RR and Michener, CD (1958) A statistical method for evaluating systematic relationships. University of Kansas Science Bulletin 38: 1409–1438.Google Scholar
Storey, JD and Tibshirani, R (2003) Statistical significance for genome wide studies. Proceedings of National Academy of Sciences USA 100(16): 9440–9445.Google Scholar
Sugimura, Y, Itano, U, Salud, CD, Otsuji, K and Yamaguchi, H (1997) Biometric analysis of diversity of coconut palm: cultivar classification by botanical and agronomical traits. Euphytica 98: 29–35.Google Scholar
Tautz, D (1989) Hypervariability of simple sequences as a general source of polymorphic DNA markers. Nucleic Acids Research 17: 6463–6471.Google Scholar
Teulat, B, Aldam, C, Trehin, R, Lebrun, P, Barker, JHA, Arnold, GM, Karp, A, Baudouin, L and Rognon, F (2000) An analysis of genetic diversity in coconut (Cocos nucifera) populations from across the geographic range using sequence-tagged microsatellites (SSRs) and AFLPs. Theoretical and Applied Genetics 100: 764–771.CrossRefGoogle Scholar
Upadhyay, A, Jayadev, K, Manimekalai, R and Parthasarathy, VA (2004) Genetic relationship and diversity in Indian coconut genotypes based on RAPD markers. Scientia Horticulturae 99: 353–362.CrossRefGoogle Scholar
Ward, JH (1963) Hierarchical groupings to optimize an objective function. Journal of the American Statistical Association 58: 236–244.Google Scholar
Xiao, Y, Luo, Y, Yang, Y, Fan, H, Xia, W, Mason, AS, Zhao, S, Sager, R and Qiao, F (2013) Development of microsatellite markers in Cocos nucifera and their application in evaluating the level of genetic diversity of Cocos nucifera . Plant Omics Journal 6(3): 193–200.Google Scholar
Xia, W, Xiao, Y, Liu, Z, Luo, Y, Mason, AS, Fan, H, Yang, Y, Zhao, S and Peng, M (2014) Development of gene-based simple sequence repeat markers for association analysis in Cocos nucifera . Molecular Breeding 34: 525–535.Google Scholar
Zizumbo-Villarreal, D and Piñero, D (1998) Pattern of morphological variation and diversity of Cocos nucifera (Arecaceae) in Mexico. American Journal of Botany 85(6): 855–865.Google Scholar
Supplementary material: File

Geethanjali supplementary material

Tables S1-S2

Download Geethanjali supplementary material(File)
File 174.6 KB