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Classification Of The Malaysian Banana Varieties Using Retrotransposon Markers


Teo, Chee How (2002) Classification Of The Malaysian Banana Varieties Using Retrotransposon Markers. Masters thesis, Universiti Putra Malaysia.


Retrotransposons are the most common class of eukaryotic transposable elements that make up over 50% of nuclear DNA found in many plants with large and complex genomes. The long terminal repeat (LTR) retrotransposons have a high degree of autonomy and encode at least five distinct protein components, which are required for their movement in the genome. We have exploited the repetitive, dispersed nature of many LTR-containing retrotransposon families for the visualization of genomic polymorphism (genome constitution) and the visualization of varieties polymorphism (varieties classification). The IRAP-PCR (Inter- Retrotransposon Amplified Polymorphism-Polymerase Chain Reaction) markers are generated by the proximity of two LTRs or reverse transcriptase CRT) genes using outward-facing primers annealing to LTR target sequence. This method could distinguish between banana genome constitution (A and B genome) and varieties. This method can track new insertion of retrotransposon in banana tissue culture materials. The evolution of Malaysian bananas can also be tracked using this phylogenetic analysis. Since the method is PCR-based, it may allow the detection and isolation of the active, newly inserted retrotransposon copies easily, by analyzing the subsequent generations within an otherwise genetically homogeneous material. This method is applicable to other plants with dispersed families of LTR retrotransposons where either the LTR or nearby internal sequences are known.

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Additional Metadata

Item Type: Thesis (Masters)
Subject: Bananas - Malaysia
Subject: Food technology
Call Number: FSMB 2002 8
Chairman Supervisor: Tan Siang Ree, PhD
Divisions: Faculty of Food Science and Technology
Depositing User: Mohd Nezeri Mohamad
Date Deposited: 19 Jul 2011 06:54
Last Modified: 19 Jul 2011 06:54
URI: http://psasir.upm.edu.my/id/eprint/11859
Statistic Details: View Download Statistic

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