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Genomewide selection in oil palm: increasing selection gain per unit time and cost with small populations

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Abstract

Oil palm (Elaeis guineensis Jacq.) requires 19 years per cycle of phenotypic selection. The use of molecular markers may reduce the generation interval and the cost of oil-palm breeding. Our objectives were to compare, by simulation, the response to phenotypic selection, marker-assisted recurrent selection (MARS), and genomewide selection with small population sizes in oil palm, and assess the efficiency of each method in terms of years and cost per unit gain. Markers significantly associated with the trait were used to calculate the marker scores in MARS, whereas all markers were used (without significance tests) to calculate the marker scores in genomewide selection. Responses to phenotypic selection and genomewide selection were consistently greater than the response to MARS. With population sizes of N = 50 or 70, responses to genomewide selection were 4–25% larger than the corresponding responses to phenotypic selection, depending on the heritability and number of quantitative trait loci. Cost per unit gain was 26–57% lower with genomewide selection than with phenotypic selection when markers cost US $1.50 per data point, and 35–65% lower when markers cost $0.15 per data point. With population sizes of N = 50 or 70, time per unit gain was 11–23 years with genomewide selection and 14–25 years with phenotypic selection. We conclude that for a realistic yet relatively small population size of N = 50 in oil palm, genomewide selection is superior to MARS and phenotypic selection in terms of gain per unit cost and time. Our results should be generally applicable to other tree species that are characterized by long generation intervals, high costs of maintaining breeding plantations, and small population sizes in selection programs.

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References

  • Bernardo R (2002) Breeding for quantitative traits in plants. Stemma Press, Woodbury

    Google Scholar 

  • Bernardo R (2004) What proportion of declared QTL in plants are false? Theor Appl Genet 109:419–424

    Article  PubMed  CAS  Google Scholar 

  • Bernardo R, Charcosset A (2006) Usefulness of gene information in marker-assisted recurrent selection: a simulation appraisal. Crop Sci 46:614–621

    Article  Google Scholar 

  • Bernardo R, Yu J (2007) Prospects for genomewide selection for quantitative traits in maize. Crop Sci 47:1082–1090

    Article  Google Scholar 

  • Bernardo R, Moreau L, Charcosset A (2006) Number and fitness of selected individuals in marker-assisted and phenotypic recurrent selection. Crop Sci 46:1972–1980

    Article  Google Scholar 

  • Billotte N, Marseillac N, Risterucci A-M, Adon B, Brottier P, Baurens F-C, Singh R, Herrán A, Asmady H, Billot C, Amblard P, Durand-Gasselin T, Courtois B, Asmono D, Cheah SC, Rohde W, Ritter E, Charrier A (2005) Microsatellite-based high density linkage map in oil palm (Elaeis guineensis Jacq.). Theor Appl Genet 110:754–765

    Article  PubMed  CAS  Google Scholar 

  • Chua KL, Singh R, Cheah SC (2001) Construction of oil palm (Elaeis guineensis Jacq.) linkage maps using AFLP markers. In: Cutting-edge technologies for sustained competitiveness (Agriculture), Proc 2001 PIPOC Int Palm Oil Cong, 20–22 August 2001, Mutiara Kuala Lumpur, Malaysia, pp 461–467

  • Corley RHV, Tinker PB (2003) The oil palm, 4th edn. Blackwell Publishing, Oxford

    Google Scholar 

  • Eathington SR, Crosbie TM, Edward MD, Reiter RS, Bull JK (2007) Molecular markers in a commercial breeding program. Crop Sci 47:S154–S163 (published online 18 Dec 2007). http://crop.scijournals.org/cgi/content/full/47/Supplement_3/S-154

    Google Scholar 

  • Edwards M, Johnson L (1994) RFLPs for rapid recurrent selection. In: Analysis of molecular marker data. Joint Plant Breeding Symposium Series. Am Soc Hort Sci, CSSA, Madison, WI, pp 33–40

  • Hallauer AR (1990) Methods used in developing maize inbreds. Maydica 35:1–16

    Google Scholar 

  • Hospital F, Moreau L, Lacoudre F, Charcosset A, Gallais A (1997) More on the efficiency of marker-assisted selection. Theor Appl Genet 95:1181–1189

    Article  Google Scholar 

  • Johnson L (2001) Marker assisted sweet corn breeding: a model for specialty crops. Proc Corn Sorghum Ind Res Conf 56:25–30

    Google Scholar 

  • Johnson R (2004) Marker-assisted selection. Plant Breed Rev 24(1):293–309

    Google Scholar 

  • Johnson GR, Mumm RH (1996) Marker assisted maize breeding. Proc Corn Sorghum Ind Res Conf 51:75–84

    Google Scholar 

  • Kilian A, Huttner E, Wenzl P, Jaccoud D, Carling J, Caig V, Evers M, Heller-Uszynska K, Uszynski G, Cayla C, Patarapuwadol S, Xia L, Yang S, Thomson B (2005) The fast and the cheap: SNP and DArT-based whole genome profiling for crop improvement. In: Tuberosa R, Phillips RL, Gale M (eds) Proc Int Cong “In the Wake of the Double Helix: From the Green Revolution to the Gene Revolution,” 27–31 May 2003, Bologna, pp 443–461

  • Koebner R (2003) MAS in cereals: green for maize, amber for rice, still red for wheat and barley. In: Marker assisted selection: a fast track to increase genetic gain in plant and animal breeding? 17–18 October 2003, Turin, Italy. FAO, Rome. http://www.fao.org/biotech/docs/Koebner.pdf (September 8, 2007)

  • Lande R, Thompson R (1990) Efficiency of marker-assisted selection in the improvement of quantitative traits. Genetics 124:743–756

    PubMed  CAS  Google Scholar 

  • Mayes S, Jack PL, Marshall DF, Corley RHV (1997) Construction of a RFLP genetic linkage map for oil pal (Elaeis guineensis Jacq.). Genome 40:116–122

    Article  CAS  PubMed  Google Scholar 

  • Meuwissen THE, Hayes BJ, Goddard ME (2001) Prediction of total genetic value using genome-wide dense marker maps. Genetics 157:1819–1829

    PubMed  CAS  Google Scholar 

  • Mielke T (2007) Oil world annual 2007. ISTA Mielke Gmbh, Hamburg

    Google Scholar 

  • Rance KA, Mayes S, Price Z, Jack PL, Corley RHV (2001) Quantitative trait loci for yield components in oil palm (Elaeis guineensis Jacq.). Theor Appl Genet 103:1302–1310

    Article  CAS  Google Scholar 

  • Schaeffer LR (2006) Strategy for applying genome-wide selection in dairy cattle. J Anim Breed Genet 123:218–223

    Article  PubMed  CAS  Google Scholar 

  • Soh AC, Lee CH, Yong YY, Chin CW, Tan YP, Rajanaidu N, Phuah PK (1990) The precision of oil palm breeding trials in Malaysia. In: Soh AC, Rajanaidu N, Hasan Basri MN (eds) Int Symp. application of statistics to perennial tree crops research. Palm Oil Res Inst Malaysia, Kuala Lumpur, pp 41–50

    Google Scholar 

  • Yusof B (2007) Palm oil production through sustainable plantations. Eur J Lipid Sci Tech 109:289–295

    Article  CAS  Google Scholar 

Download references

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Correspondence to R. Bernardo.

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Communicated by M. Kearsey.

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Wong, C.K., Bernardo, R. Genomewide selection in oil palm: increasing selection gain per unit time and cost with small populations. Theor Appl Genet 116, 815–824 (2008). https://doi.org/10.1007/s00122-008-0715-5

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  • DOI: https://doi.org/10.1007/s00122-008-0715-5

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