PLANT DISEASE DIAGNOSIS - The Epidemiology of Plant Diseases - page 25

Quantification of a real-time PCR product revolves around the concept of Ct
values (Higuchi et al., 1993). Fluorescence values recorded during each cycle
represent the amount of product amplified until that point in the PCR reaction. The
template DNA present at the start of the reaction is directly proportional to the
cycles for fluorescence and is first recorded as being statistically significant above
the baseline (Gibson et al., 1996). This fractional cycle number value is known as
the Ct value and always occurs in the exponential phase of the reaction. The two
most widely used methods for quantifying an unknown sample using Ct values
obtained from an amplification plot (Giulietti et al., 2001) are the standard curve
method and the comparative threshold method. In the former, a standard curve is
prepared by plotting Ct values against the log of template DNA. Depending on the
template used, an absolute or relative standard curve can be prepared. Because of the
complication associated with an absolute standard curve, a relative standard curve
has often been the method of choice. In a relative standard curve, a dilution series of
one of the samples being compared is usually used as the template. Quantities of
target 'unknown' samples are extrapolated from the standard curve and expressed in
terms of arbitrary units. In the comparative threshold method, only relative
quantification can be performed. In this method, arithmetic formulae are used to
calculate relative expression levels; these are then compared with a calibrator, which
can be one of the samples being compared, for example, the untreated control.
By using probes with different fluorescent reporter dyes, amplification of two or
more PCR products representing different organisms, polymorphisms or SNPs can
be detected in a single PCR reaction (McCartney et al., 2003). Real-time PCR has
been deployed for the detection of human pathogens, scanning SNPs associated with
human diseases and resistance to anti-microbial agents, and detecting genetically
modified foods and other agricultural products. This technique is not used routinely
in plant pathogen detection assays; however certain detection assays for research
purposes have been developed for fungi (Bohm et al., 1999; Fraaije et al., 2001,
2002), bacteria (Schaad et al., 1999; Schaad and Frederick, 2002), viroids (Mumford
et al., 2000) and viruses (Boonham et al., 2000).
Different molecular marker systems have become available during the last two
decades to deal with all aspects of molecular biology applications, such as crop
improvement, genotyping and diagnostics of pathogens. In recent years, there has
been an emphasis on the development of newer and more efficient molecular marker
systems involving inexpensive non-gel-based assays with high throughput detection
systems. Availability of Single Nucleotide Polymorphisms (SNPs) is one such
development of new generation molecular markers used for individual genotyping.
RFLPs, RAPDs and SSRs which were the markers of choice during the last two
decades, need gel-based assays and are, therefore, time-consuming and expensive.
SNPs, in contrast, represent sites where the DNA sequence differs by a single base
and can be detected by different non-gel-based methods (Gupta et al., 2001). Single
nucleotide polymorphism has been shown to be the most abundant, so that at least
one million SNPs should be available, only in the non-repetitive transcribed region
of the human genome (Wang et al., 1998a). According to recent estimates, one SNP
is known to occur in every 100-300 bp in any genome, much higher in order of
magnitude than that of SSRs, thus making SNPs the most abundant molecular