132 REFERENCE GENE SCREENING FOR ANALYZING GENE EXPRESSION ACROSS FEMALE GOAT TISSUE

Quantitative RT-PCR (RT-qPCR) is an important method for investigating changes in mRNA expression levels in cells and tissues. Selection of the proper reference genes is very important when calibrating the results of RT-qPCR. Studies on the selection of reference genes in goat tissues are limited, despite the economic importance of their meat and dairy products. We applied absolute quantification using the standard curve method to the detection of the expression levels of 8 reference gene candidates (18S, TBP, YWHAZ, HMBS, ACTB, HPRT1, GAPDH, and EEF1A2) in 10 different tissue types (heart, liver, spleen, lung, kidney, stomach, uterus, ovary, small intestine, and muscle) sourced from a 5-month-old female Boer goat. All the experiments were performed using 3 biological replicates and technical triplicates of each cDNA sample. The optimal reference gene combination was selected according to the results determined by geNorm, NormFinder, and Bestkeeper software packages. The analyses showed that tissue is an important variability factor in gene expression stability. When all tissues were considered, 18S, TBP, and HMBS with the smallest paired variation coefficient is the optimal reference combination for calibrating RT-qPCR analysis of gene expression from goat tissues. The stability of each gene was evaluated, taking into account all of the data. The stability values (M) for these genes were 0.643/0.634/0.799, 0.156/0.467/0.584, and 0.396/0.445/0.566 by geNorm, NormFinder, and Bestkeeper, respectively. Dividing the dataset by different tissues, ACTB was the most stable in stomach, small intestine, and ovary, 18S in heart and spleen, HMBS in uterus and lung, TBP in liver, HPRT1 in kidney, and GAPDH in muscle. Overall, this study provided valuable information about the female goat reference genes that can be used in order to perform a proper normalisation when relative quantification by RT-qPCR studies is undertaken. This work was supported by National ‘863’ Program (2011AA100307-4), the Technology Innovation Project – Special Program and the Science and Technology Program of Anhui Province (11Z0101095 and 11010302108).