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Molecular detection of Mycoplasma gallisepticum by real time PCR


Citation

Farhana Yasmin, and Ideris, Aini and Omar, Abdul Rahman and Bejo, Mohd Hair and Tan, Sheau Wei and Tan, C. G. and Islam, R. and Ahmad, K. (2014) Molecular detection of Mycoplasma gallisepticum by real time PCR. Jurnal Veterinar Malaysia, 26 (1&2). pp. 1-7. ISSN 9128-2506

Abstract

Mycoplasma gallisepticum (MG) causes chronic respiratory disease leading to huge economic losses to the poultry industry worldwide. Early and efficient detection is therefore crucial in reducing the loss sustained by poultry farmers and poultry industry at large. Three main approaches are used for the diagnosis of MG: isolation and identification, serology and molecular detection method. Recently, real time polymerase chain reaction has been developed for the detection of infectious organisms, but so far only a limited number of diagnostic real time PCRs have been proposed for MG. This study was carried out to develop a SYBR green real time PCR assay for the detection of MG using primer set specific to the gapA gene. The primer set was able to amplify the expected DNA fragment of 505 bp. The assay was found to be specific and highly sensitive in detecting MG as indicated by its ability to detect between 260 ng/μl to 26 pg/μl DNA template. In conclusion, this study successfully developed a specific and sensitive real time PCR assay for the rapid detection of MG compared to conventional PCR method. Although the cost to carry out real time PCR is more expensive, it is a more specific, sensitive, and rapid method for detection of MG as compared with conventional PCR.


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Additional Metadata

Item Type: Article
Divisions: Faculty of Veterinary Medicine
Institute of Bioscience
Publisher: Veterinary Association Malaysia
Keywords: Mycoplasma gallisepticum; PCR; SYBR green real time PCR; GapA gene
Depositing User: Umikalthom Abdullah
Date Deposited: 13 Nov 2009 06:35
Last Modified: 30 Sep 2015 02:34
URI: http://psasir.upm.edu.my/id/eprint/2441
Statistic Details: View Download Statistic

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