Combining maxRatio analysis with real-time PCR and its potential application for the prediction of Meloidogyne incognita in field samples.
Diagnosing and quantifying plant-parasitic nematodes is critical for efficient nematode management. Several studies have been performed intending to demonstrate nematode quantification via real-time quantitative PCR. However, most of the studies used dilution of DNA templates to make standard curves, while few studies used samples with different nematode numbers to make the standard curve, resulting in a high standard error. The objective of the present study was to develop a high quality standard curve using samples containing different numbers of the root-knot nematode Meloidogyne incognita and evaluate the results of real time qPCR with maxRatio analysis. The results showed that a high quality standard curve was obtained with different nematode numbers using specific primers and cycle threshold (Ct)-PCR (R²=0.9962, P<0.001, n=9). With the maxRatio analysis, the fractional cycle number (FCN)-PCR cycle curve and adjusted FCN (FCNadj)-PCR cycle curve had similar patterns as those of the Ct-PCR cycle curve. For quantification of nematodes in field soil samples, qPCR estimations with a FCNadj-PCR cycle standard curve was very close to microscope counting of second-stage juveniles (R²=0.9064, P<0.001, n=10), qPCR estimations with a FCN-PCR cycle standard curve was comparably good (R²=0.8509, P<0.001, n=10), and the biases with a Ct-PCR cycle standard curve were large (R²=0.7154, P<0.001, n=10). Moreover, we found that the concentration of Triton X-100 had less of an effect on FCN as compared to Ct, with delta FCN 0.52, and delta Ct 3.94 at 0.8% Triton. The present study suggests, that combined with maxRatio methods, real time qPCR could be a practical approach for quantifying M. incognita in field samples.
College of Life Sciences, Tianjin 300071, Nankai University, China.
Yu-Long
YL
Zhao
Wei-Bin
WB
Ruan
Le
L
Yu
Jing-Yi
JY
Zhang
Jin-Miao
JM
Fu
Eric B
EB
Shain
Xi-Tai
XT
Huang
Jing-Guo
JG
Wang