Genomic differences detected in the oil palm truncated leaf syndrome (TLS) ramets (elaeis guineensis Jacq.) using the representational difference analysis (RDA) approach

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Abstract

Truncated Leaf Syndrome (TLS) is a commonly found abnormality amongst tissue cultured plantlets of oil palm (Elaeis guineensis Jacq.) which, if severe, will eventually lead to the death of the ramets. It was hypothesised that this phenotype could be due to genetic variability. As such, Genomic Representational Difference Analysis (G-RDA) was carried out to identify potential markers that can be used in tissue culture process for early determination of TLS ramets. A total of 18 unique sequences were successfully obtained. Primers were designed and verification of G-RDA products through polymerase chain reaction (PCR) analyses and sequence comparison was carried out using 12 clones of TLS and normal oil palm ramets. Two out of 18 set of primers [F4(6)-1181Bgl and F4(10)-1181Bgl] were identified as potential markers and further verified by PCR and Southern analyses. The primer set F4(6)-1181Bgl was only able to distinguish between TLS and normal ramet of only one genotype (Yangambi) with the presence of expected band in TLS but was absent in normal ramet. The primer set F4(10)-1181Bgl showed the presence of multiple banding pattern in the genotype of La Me and Yangambi. Analysis of the multiple band sequences revealed that those sequences represent multiple regions within the same genome, they are potentially polymorphic markers. The two primer sets mentioned above could be classified as potential genotype specific primers as it is only functional in selected genotype. Further verification with extensive number of samples is needed to elucidate the potential of the above two primer sets to be used as markers across all genotypes of oil palm.

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Silvarajoo, K., Namasivayam, P., Ho, C. L., & Alwee, S. S. R. S. (2018). Genomic differences detected in the oil palm truncated leaf syndrome (TLS) ramets (elaeis guineensis Jacq.) using the representational difference analysis (RDA) approach. Journal of Oil Palm Research, 30(2), 219–235. https://doi.org/10.21894/jopr.2018.0016

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