Hostname: page-component-78c5997874-4rdpn Total loading time: 0 Render date: 2024-11-05T14:37:36.477Z Has data issue: false hasContentIssue false
  • English
  • Français

Molecular characterization of oil palm Elaeis guineensis Jacq. of different origins for their utilization in breeding programmes

Published online by Cambridge University Press:  20 March 2014

Diana Arias ,
Iván Ochoa ,
Fernando Castro  and
Hernán Romero
Diana Arias
Affiliation:
Oil Palm Biology and Breeding Research Program, Colombian Oil Palm Research Center – Cenipalma, Street 21, No. 42-55, Bogota, Colombia
Iván Ochoa
Affiliation:
Breeding and Seed Production Program of Unipalma S.A. Cumaral, Meta, Hacienda Santa Barbara, Bogota, Colombia
Fernando Castro
Affiliation:
Breeding and Seed Production Program of Unipalma S.A. Cumaral, Meta, Hacienda Santa Barbara, Bogota, Colombia
Hernán Romero*
Affiliation:
Oil Palm Biology and Breeding Research Program, Colombian Oil Palm Research Center – Cenipalma, Street 21, No. 42-55, Bogota, Colombia Department of Biology, Faculty of Science, Universidad Nacional de Colombia, Bogota, Colombia
*
* Corresponding author. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Sustainable development of a breeding programme depends on having sufficient genetic variability to achieve genetic gains in each selection cycle. The aim of this study was to molecularly characterize families of the oil palm, Elaeis guineensis Jacq., of different origins using microsatellite molecular markers. The value of the observed heterozygosity was higher than that of the expected heterozygosity in all of the progenies. The coefficients (G ST= 0.207 and F ST= 0.174) and AMOVA showed genotypic differences among the evaluated families. Likewise, this was reflected in the groups obtained by the dendrogram and principal coordinate analyses. This difference could have evolved due to the enrichment of some of the families with germplasm from different origins. Therefore, genetic relationships estimated from molecular data would be convenient to select families more distant from each group and palms more distant from each family selected to reserve genetic variability. This information will guide us in the decision-making process when planning breeding programmes focused on crosses to develop new populations with an acceptable broad genetic base and adaptability. In this way, sources of resistance to biotic and abiotic factors can be identified for the development of new varieties with competitive advantages for the sector.

Keywords

expected heterozygositygenetic differentiationmicrosatellitemolecular data
Type
Research Article
Information
Plant Genetic Resources , Volume 12 , Issue 3 , December 2014 , pp. 341 - 348
Copyright
Copyright © NIAB 2014 

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.)

References

Barcelos, E, Amblard, P, Berthaud, J, and Seguin, M (2002) Genetic diversity and relationship in American and African oil palm as revealed by RFLP and AFLP molecular markers. Pesquisa Agropecuaria Brasileira 37: 1105–1114.Google Scholar
Beirnaert, A (1933) Les base de la sélection du palmier á huile. Agron Colon 135–146.Google Scholar
Billotte, N, Risterucci, AM, Barcelos, E, Noyer, JL, Amblard, P and Baurens, FC (2001) Development, characterization, and across-taxa utility of oil palm (Elaeis guineensis Jacq.) microsatellite markers. Genome 44: 413–425.Google Scholar
Billotte, N, Marseillac, N, Risterucci, AM, Adon, B, Brottier, P, Baurens, FC, Singh, R, Herrán, A, Asmady, H, Billot, C, Amblard, P, Durand-Gasselin, T, Courtois, B, Asmono, D, Cheah, SC, Rohde, W, Ritter, E and Charrier, A (2005) Microsatellite-based high density linkage map in oil palm (Elaeis guineensis Jacq.). Theoretical and Applied Genetics 110: 754–765.Google Scholar
Castro, F and Corley, RHV (2007) Advances in the Research and Development program of Unipalma D × P seeds. PALMAS 28: 227–240.Google Scholar
Cochard, B, Adon, B, Rekima, S, Billotte, N, Desmier de Chenon, R, Koutou, A, Nouy, B, Omoré, A, Purba, AR, Glazsmann, JC and Noyer, JL (2009) Geographic and genetic structure of African oil palm diversity suggests new approaches to breeding. Tree genetics & genomes 5: 493–504.Google Scholar
Corley, RHV and Tinker, PB (2003) The Oil Palm. 562 pp. Oxford, UK: Blackwell Publishing.Google Scholar
Corley, RHV and Castro, F (2004) The Unipalma oil palm breeding program. PALMAS 25: 311–325.Google Scholar
Durand-Gasselin, T, Kouamé, R, Cochard, B, Adon, B and Amblard, P (2000) Diffusion vériétale du palmier à huile (Elaeis guineensis Jacq.). Oléagineux Corps Gras Lipides 7: 207–214.Google Scholar
Dumortier, F (2003) Breeding for high yielding progenies at Dami OPRS. In: Proc. Agric. Conf. Palm oil: The Power-House for the Global Oils & Fats Economy, pp. 51–74, Malaysian Palm Oil Board, Kuala Lumpur.Google Scholar
Excoffier, L and Heckel, G (2006) Computer programs for population genetics data analysis: a survival guide. Nature Reviews Genetics 7: 745–758.Google Scholar
FAOSTAT (2010) Food and Agriculture Organization of the United Nations – for a world without hunger. Available at http://faostat.fao.org (accessed 19 October 2012).Google Scholar
Gascon, J-P and de Berchoux, C (1964) Caractéristique de la production d'Elaeis guineensis (Jacq.) de diverses origines et de leurs croisements. Application à la sélection du palmier à huile. Oléagineux 19: 75–84.Google Scholar
Goudet, J (2002) Institute of Ecology. Biology Building, UNIL software (FSTAT). Version 2.9.3.2. Available at http://www2.unil.ch/popgen/softwares/fstat.htm (accessed 19 April 2012).Google Scholar
Hardon, J (1970) Inbreeding in population of the oil palm (Elaeis guineensis Jacq.) and its effects on selection. Oléagineux 25: 449–456.Google Scholar
Hayati, A, Wickneswari, R, Maizura, I and Rajanaidu, N (2004) Genetic diversity of oil palm (Elaeis guineensis Jacq.) germplasm collections from Africa: implications from improvement and conservation of genetic resources. Theoretical and Applied Genetics 108: 1274–1284.Google Scholar
Kalia, RK, Rai, MK, Kalia, S, Singh, R and Dhawan, AK (2011) Microsatellite markers: an overview of the recent progress in plants. Euphytica 177: 309–334.Google Scholar
Kularatne, RS, Shah, FH and Rajanaidu, N (2001) The evaluation of genetic diversity of Deli dura and African oil palm germplasm collection by AFLP technique. Trop Agric Res 13: 1–12.Google Scholar
Laurentin, H (2009) Data analysis for molecular characterization of plant genetic resources. Genetic Resources and Crop Evolution 56: 277–292.Google Scholar
Maizura, I, Rajanaidu, N, Zakri, A and Cheah, S (2006) Assessment of genetic diversity in oil palm (Elaeis guineensis Jacq.) using restriction fragment length polymorphism (RFLP). Genetic Resources and Crop Evolution 53: 187–195.Google Scholar
Mayes, S, Jack, PL and Corley, RHV (2000) The use molecular markers to investigate the genetic structure of an oil palm breeding programme. Heredity 85: 288–293.CrossRefGoogle ScholarPubMed
Nei, M (1972) Genetic distance between populations. American Naturalist 106: 283–292.Google Scholar
Nei, M (1978) Estimation of average heterozygosity and genetic distance from a small number of individuals. Genetics 89: 583–590.Google Scholar
Nei, M (1987) Molecular Evolutionary Genetics. 128 pp. New York: Colombia University Press.Google Scholar
Nei, M and Li, WH (1979) Mathematical model for studying genetic variation in terms of restriction endonucleases. Proceedings of the National Academy of Science 76: 5269–5273.Google Scholar
Norziha, A, Rafii, M, Maizura, I and Ghizan, S (2008) Genetic variation among oil palm parent genotypes and their progenies based on microsatellite markers. Journal of oil palm Research 20: 533–541.Google Scholar
Ooi, SC (1975) Variability in the Deli dura breeding population of the oil palm (Elaeis guineensis Jacq.). II Within bunch components of yield. Malaysian Agricultural Research 50: 20–30.Google Scholar
Peakall, R and Smouse, P (2006) Genetic analysis in Excel. Population genetic software for teaching and research (GenALEx). Version 6.1. Available at http://biology.anu.edu.au/GenAlEx/Download.html (accessed 19 April 2012).Google Scholar
Perrier, X and Jacquemoud-Collet, JP (2006) Software (DARwin). Available at http://darwin.cirad.fr./darwin.Google Scholar
Purba, AR, Noyer, JL, Baudouin, L, Perrier, X, Hamon, S and Lagoda, PJL (2000) A new aspect of genetic diversity of Indonesian oil palm (Elaies guineensis Jacq.) revealed by isoenzyme and AFLP markers and its consequences for breeding. Theoretical and Applied Genetics 101: 956–961.Google Scholar
Rohlf, FJ (2000) NTSYSpc: Numerical Taxonomy and Multivariate Analysis System. Version 2.11L . Setauket, New York: Exeter Software.Google Scholar
Rosenquist, E (1986) The genetic base of oil palm breeding populations. In Proc. Int. Workshop Oil palm germplasm and utilisation, pp. 27–56, Palm Oil Res Inst Malaysia, Kuala Lumpur.Google Scholar
Singh, R, Mohd, N, Ting, N, Rosli, R, Tan, S, Leslie, E, Ithnin, M and Cheah, S (2008) Exploiting an oil palm EST database for the development of gene-derived SSR markers and their exploitation for assessment of genetic diversity. Biologia 63: 227–235.Google Scholar
Weir, BS and Cockerham, CC (1984) Estimating F-statistics for the analysis of population structure. Evolution 38: 1358–1370.Google Scholar