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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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Authors
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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Abstract
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.
Keywords
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, Mahyar Heydarpour, 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. doi: 10.11648/j.abb.20140205.11
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