Absolute quantification of cassava brown streak virus mRNA by real-time qPCR
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Shirima, R.R., Maeda, D.G., Kanju, E., Ceasar, G., Tibazarwa, F.I. & Legg, J. (2017). Absolute quantification of cassava brown streak virus mRNA by real-time qPCR. Journal of Virological Methods, 245, 1-13.
Permanent link to cite or share this item: http://hdl.handle.net/10568/80816
Cassava brown streak disease (CBSD) is the most important virus disease of cassava and a major food security threat in Africa. Yearly economic losses of up to $100 million USD have been attributed to CBSD. The lack of information on plant-virus interactions has restricted progress in breeding for CBSD resistance. Virus quantiﬁcation is becoming a major tool for the quick and reliable assessment of plant host resistance. Therefore, a protocol for speciﬁc absolute quantiﬁcation of Cassava brown streak virus (CBSV) and Ugandan cassava brown streak virus (UCBSV) was developed. CBSV and UCBSV coat protein (CP) speciﬁc standard templates: CBSV (pFer2, 826 bp) and UCBSV (pUF1-R1-1, 732) respectively were generated and maintained in a TA cloning vector. These were used to construct standard curves using a TaqMan qPCR assay. Standard curves with acceptable ampliﬁcation efﬁciencies (90–105%) and coefﬁcients of determination (R2) greater than 0.99 were obtained. Infected cassava plants were sampled from a screenhouse and the ﬁeld and used to validate this assay. Results obtained by testing several screenhouse and ﬁeld samples revealed consistent absolute quantiﬁcation assays for different CBSV and UCBSV isolates. This study presents the ﬁrst protocol for absolute quantiﬁcation of CBSVs and is expected to accelerate screening for CBSD resistance and hence breeding for CBSD resistance. The use of the method presented here should improve the clarity of virus quantiﬁcation data as the results obtained are not inﬂuenced by varietal, host, seasonal or environmental conditions. Screening efﬁciency will also be greatly improved as there is no need for the use of reference genes consequently allowing for a larger number of samples to be analyzed. This will increase experimental precision in a timely and cost effective manner.
Investors/sponsorsBill & Melinda Gates Foundation
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