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Mapping of quantitative trait loci (QTLs) for oil yield using SSRs and gene-based markers in African oil palm (Elaeis guineensis Jacq.)

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Abstract

The identification of quantitative trait loci (QTLs) based on anchor markers, especially candidate genes that control a trait of interest, has been noted to increase the power of QTL detection. Since these markers can be scored as co-dominant data, they are also valuable for comparing and integrating the QTL linkage maps from diverse mapping populations. To estimate the position and effects of QTLs linked to oil yield traits in African oil palm, co-dominant microsatellites (SSR) and candidate gene-based sequence polymorphisms were applied to construct a linkage map for a progeny showing large differences in oil yield components. The progeny was genotyped for 97 SSR markers, 93 gene-linked markers, and 12 non-gene-linked SNP markers. From these, 190 segregating loci could be arranged into 31 linkage groups while 12 markers remained unmapped. Using the single marker linkage, interval mapping and multiple QTL methods, 16 putative QTLs on seven linkage groups affecting important oil yield related traits such as fresh fruit bunch yield (FFB), ratio of oil per fruit (OF), oil per bunch (OB), fruit per bunch (FB) and wet mesocarp per fruit (WMF) could be identified in the segregating population with estimated values for explained variance ranging from 12.4 % to 54.5 %. Markers designed from some candidate genes involved in lipid biosynthesis were found to be mapped near significant QTLs for various economic yield traits. Associations between QTLs and potential candidate genes are discussed.

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Acknowledgements

This research was supported by grants from the National Center for Genetic Engineering and Biotechnology (BIOTEC), National Science and Technology Development Agency, Ministry of Science and Technology (NSTDA), and the Center of Excellence on Agricultural Biotechnology, Science and Technology Postgraduate Education and Research Development Office, Office of Higher Education Commission, Ministry of Education. (AG-BIO/PERDO-CHE), Thailand. Sukanya Jeennor was supported by the Thailand Graduate Institute of Science and Technology (TGIST) from NSTDA. We thank Assoc. Prof. Julapark Chunwongse, Kasetsart University, for his critical comments. We also thank to the Univanich Palm Oil Public Company Limited, Krabi, Thailand for kindly providing plant samples and phenotypic data.

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  1. Center for Agricultural Biotechnology, Kasetsart University, Kampangsaen Campus, 73140, Nakhon Pathom, Thailand

    S. Jeennor & H. Volkaert

  2. Center of Excellence on Agricultural Biotechnology (AG-BIO/PERDO-CHE), Bangkok, 10900, Thailand

    S. Jeennor & H. Volkaert

  3. National Center for Genetic Engineering and Biotechnology, Thailand Science Park, Pathumthani, 12120, Thailand

    H. Volkaert

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Communicated by D. Grattapaglia

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Supplementary Table 1

List of candidate gene based markers and their linkage assignment. These genes are involved in lipid biosynthesis pathway and other related pathways. Some interesting transcription factors also mapped. The genotyping methods are detailed in Jeennor and Volkaert (2013). (PDF 34 kb)

Supplementary Table 2

List of non gene-linked SNP markers for oil palm developed from genomic fragment library of two progenies in mapping population. The detail of assay techniques used for detecting polymorphism in dura x pisifera parents and their genotype are shown (PDF 9 kb)

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Jeennor, S., Volkaert, H. Mapping of quantitative trait loci (QTLs) for oil yield using SSRs and gene-based markers in African oil palm (Elaeis guineensis Jacq.). Tree Genetics & Genomes 10, 1–14 (2014). https://doi.org/10.1007/s11295-013-0655-3

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