Detection and absolute quantification of betasatellites associated with okra yellow vein mosaic disease by qPCR

Abstract

Okra yellow vein mosaic disease (OYVMD) causes serious loss in okra production in Sri Lanka. Therefore, screening of resistant okra verities is an essential need to control the dis ease. As the available qualitative and semi-quantitative methods failed to detect latent infec tion the present study aimed to develop a quantitative PCR (qPCR) assay to detect and quan tify one of the OYVMD causing agent, symptom modulating satellite molecules. A pair of primers targeting a portion of βC1 gene of BYVMBs was designed and used to quantify of BYVMBs by absolute quantification method using SYBR Green I chemistry. Standard curves were prepared using series of dilutions of known copy number plasmids carrying target se quence. The mean amplification efficiency was 95% and the coefficient of determination was 0.994. The method was tested to find out the relation between symptoms and betasatellite ti tre in range of severity of OYVMD symptoms; the betasatellite titre increased with increasing severity. Interestingly, the method was able to detect BYVMBs present in apparently healthy plants growing in an infected field at a concentration which was not able to detect in end point PCR. Betasatellite titre was also measured in different ages of leaves and different posi tions. On average, the betasatellite titre in younger leaves was higher than in mature leaves and there were no significant variations in betasatellite titre in different position in each leaf. The assay was also tested as a tool to screen for resistant okra varieties; among the eight vari eties tested no BYVMBs were detected in variety Maha F1. Varieties TV8 and MI5 had sig nificantly higher copy number than rest of the varieties. The qPCR protocol described in this study is a useful method to detect and quantify BYVMBs in okra, especially for plant sam ples with betasatellite Journal Pre-proof titre lower than the detection limit of conventional methods.