Covariance Analysis, a New Approach for Relative Quantification Competitive PCR in Evaluation of Rumen Anaerobic Fungal Populations
Advances in Bioscience and Bioengineering
Volume 2, Issue 5, December 2014, Pages: 44-50
Received: Dec. 8, 2014;
Accepted: Dec. 23, 2014;
Published: Jan. 4, 2015
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Mohammad Hadi Sekhavati, Department of Animal Science, Ferdowsi University of Mashhad, Iran
Mahdi Elahi Torshizi, Department of Animal Science, Mashhad Branch, Islamic Azad University, Mashhad, Iran
Mahyar Heydarpour, CABG genomics group, Brigham & Women's Hospital, Harvard Medical School, USA
Adham Fani Maleki, Embryonic and Stem Cell Biology and Biotechnology Research Group, Institute of Biotechnology, Ferdowsi University of Mashhad, Iran
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Quantitative competitive polymerase chain reaction (QC-PCR) technique is playing an important role in nucleic acid quantification. This paper describes a new statistical approach for data analyzing in relative quantitative competitive PCR assays. In order to test the accuracy of this statistical model for quantifying anaerobic rumen fungi, samples of rumen fluid were collected from six fistulated Holstein steers which were fed in two different diets groups (soybean meal diet and canola meal diet). Competitor intensity signal (CIS) and efficiency of PCR (EFF) were assumed as two covariates in ANCOVA method. The assumptions for using of these two covariates were tested. A high positive correlation between the mean of the template intensity signal (TIS) through serial dilutions showed an appropriate efficiency of the competitive PCR assays. Results showed that the accuracy of data analyzing for relative quantification anaerobic fungi was considerable improved in ANCOVA model in comparison with ANOVA method and also the power of test is much greater. So, it seems that considering of the CIS and EFF as two co-variables was suitable.
Analysis of Covariance (ANCOVA), Competitor Intensity Signal (CIS), Efficiency of PCR (EFF), Template Intensity Signal (TIS)
To cite this article
Mohammad Hadi Sekhavati,
Mahdi Elahi Torshizi,
Adham Fani Maleki,
Covariance Analysis, a New Approach for Relative Quantification Competitive PCR in Evaluation of Rumen Anaerobic Fungal Populations, Advances in Bioscience and Bioengineering.
Vol. 2, No. 5,
2014, pp. 44-50.
W.M. Freeman, S.J. Walker, and K.E. Vrana, Quantitative RT-PCR: pitfalls and potential. Biotechniques 1999. 26 p. 112-125.
F. Watzinger, E. Hörth, and T. Lion, Quantification of mRNA expression by competitive PCR using non-homologous competitors containing a shifted restriction site. Nucleic Acids Research, 2001. 29 p. 52.
A. Gaiger, et al., Increase of bcr- abl chimeric mRNA expression in tumor cells of patients with chronic myeloid leukemia precedes disease progression. Blood 1995. 86 p. 2371.
Joblin, K., Isolation, enumeration, and maintenance of rumen anaerobic fungi in roll tubes. Applied and environmental microbiology, 1981. 42(6): p. 1119-1122.
Vu, H.L., et al., A method for quantification of absolute amounts of nucleic acids by (RT)–PCR and a new mathematical model for data analysis. Nucleic acids research, 2000. 28(7): p. e18-e18.
Zar, J.H., Biostatistical Analysis. Second Edition ed1984: Prentice Hall International, Inc.
Reilly, K. and G. Attwood, Detection of Clostridium proteoclasticumand Closely Related Strains in the Rumen by Competitive PCR. Applied and environmental microbiology, 1998. 64(3): p. 907-913.
G.W, S. and W.G. Cochran, Statistical Methods. Eighth edition ed1991: Iowa state university press/AMES
Zentilin, L. and M. Giacca, Competitive PCR for precise nucleic acid quantification. Nature protocols, 2007. 2(9): p. 2092-2104.
Robinson, P., et al., Some experimental design and statistical criteria for analysis of studies in manuscripts submitted for consideration for publication. Animal feed science and technology, 2006. 129(1): p. 1-11.
Boom, R., et al., Rapid and simple method for purification of nucleic acids. Journal of clinical microbiology, 1990. 28(3): p. 495-503.
Sekhavati, M.H., et al., Development and use of quantitative competitive PCR assays for relative quantifying rumen anaerobic fungal populations in both in vitro and in vivo systems. Mycol Res, 2009. 113(Pt 10): p. 1146-53.
SAS, S. and S.U.s. Guide, Version 9.1. SAS Institute Inc., Cary, NC, 2003.
J. Dubcovsky, http://www.plantsciences.ucdavis.edu/agr205/schedule.htm . Introduction to Analysis of covariance.