Microsatellite analysis to evaluate the seedling and mature of oil palm populations (Elaeis guineensis Jacq.) to Ganoderma boninense resistance

• Published in: Kuwait journal of science 2021-07, Vol.48 (3)
• Main Authors: Hayati, Rahmah, Lisnawita, Lisnawita, Munir, Erman, Basyuni, Mohammad
• Format: Article
• Language: English
• ISSN: 2307-4108; 2307-4116
• DOI: 10.48129/kjs.v48i3.9382

To conduct efficient disease screening, the differentiation of the palm tree (Elaeis guineensis Jacq.) to Ganoderma boninense resistance populations is critical. Differentiation can be done by analyzing the genetic structures of the two populations and comparing their seedling and matures. This article presents the results of studying four selected stably amplified polymorphic of codominant microsatellite data to estimate the differentiation between eight E. guineensis populations from different types of inoculated or symptoms of Ganoderma from North Sumatera, Indonesia. The DNA extraction was carried out based on the CTAB method with a little modification. The forward and reverse primers, i.e., P4(EGIFR), P6(EG01), P7(EG02), and P9(EG03), were used in a polymerase chain reaction (PCR). The detection of the results of amplification was performed using molecular weight analysis on UVITEC-1D software. To determine the microsatellite analysis, the data of genes were used to perform with the GENALEX ver 6.502 and MVSP ver 3.2 software. Four of the loci have polymorphism for all types of seedling and mature species of E. guineensis. The polymorphism information content was calculated as PIC=0.70. The genetic differentiation among populations was highest (Fst > 0.25), showed a high genetic divergence. The calculation of Fst by population revealed that the highest Fst was largely due to suggesting diversifying selection in gene flow and resistance selection. The molecular of analysis variance (AMOVA) was showed a significant (5%) differentiation among individuals (100%) between eight types of population. A clustering by UPGMA analysis, based on squared Euclidean and Datalog (10), transformed genetic distances and revealed was a significant difference cluster in the seedling and mature populations.