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Selection of reference genes for quantitative real-time PCR normalisation in adipose tissue, muscle, liver and mammary gland from ruminants

Published online by Cambridge University Press:  04 April 2013

M. Bonnet*
Affiliation:
INRA, UMR1213 Herbivores, F-63122 Saint-Genès-Champanelle, France VetAgro Sup, Élevage et production des ruminants, F-63370 Lempdes, France
L. Bernard
Affiliation:
INRA, UMR1213 Herbivores, F-63122 Saint-Genès-Champanelle, France VetAgro Sup, Élevage et production des ruminants, F-63370 Lempdes, France
S. Bes
Affiliation:
INRA, UMR1213 Herbivores, F-63122 Saint-Genès-Champanelle, France VetAgro Sup, Élevage et production des ruminants, F-63370 Lempdes, France
C. Leroux
Affiliation:
INRA, UMR1213 Herbivores, F-63122 Saint-Genès-Champanelle, France VetAgro Sup, Élevage et production des ruminants, F-63370 Lempdes, France
*
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Abstract

The reliability of reverse transcription quantitative real-time PCR (RT-qPCR) depends on normalising the mRNA abundance using carefully selected, stable reference genes. Our aim was to propose sets of reference genes for normalisation in bovine or caprine adipose tissue (AT), mammary gland, liver and muscle. All of these tissues contribute to nutrient partitioning and metabolism and, thus, to the profitability of ruminant productions (i.e. carcasses, meat and milk). In this study, eight commonly used reference genes that belong to different functional classes (CLN3, EIF3K, MRPL39, PPIA, RPLP0, TBP, TOP2B and UXT) were analysed using the geNorm procedure to determine the most stable reference genes in bovine and/or caprine tissues. Abundances and rankings of reference genes varied between tissues, species and the combination of tissues and/or species. Therefore, we proposed 29 sets of reference genes that differed depending on the tissue and/or species. As examples of the 29 sets, EIF3K, TOP2B and UXT were proposed as the most stable reference genes in bovine AT; UXT, EIF3K and RPLP0 were the most stable reference genes in bovine and caprine AT. The optimal number of reference genes for data normalisation was 3 for 27 of the proposed 29 sets. In two of the 29 sets, four to five reference genes were necessary for data normalisation when the number of studied tissues was increased. For example, UXT, EIF3K, TBP, TOP2B and CLN3 were required for data normalisation in bovine mammary gland, AT, muscle and liver. We have evaluated some of our proposed sets of reference genes for the normalisation of CD36 gene expression. Normalisation using the three most stable reference genes has revealed downregulation of CD36 gene expression in bovine mammary gland by a concentrate-based diet that is supplemented with sunflower oil and upregulation of CD36 gene expression in caprine liver by including a rapidly degradable starch in the diet. The dietary regulation of the gene expression of CD36 has been erased by normalisation with the least stable reference genes, which may result in misinterpretation of CD36 gene regulation. To conclude, our results provide valuable reference gene sets for other studies that aim to measure tissue and/or species-specific mRNA abundance in ruminants.

Type
Physiology and functional biology of systems
Copyright
Copyright © The Animal Consortium 2013 

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References

Bernard, L, Leroux, C, Rouel, J, Bonnet, M, Chilliard, Y 2012. Effect of the level and type of starchy concentrate on tissue lipid metabolism, gene expression and milk fatty acid secretion in Alpine goats receiving a diet rich in sunflower-seed oil. British Journal of Nutrition 107, 11471159.CrossRefGoogle Scholar
Bernard, L, Leroux, C, Bonnet, M, Rouel, J, Martin, P, Chilliard, Y 2005. Expression and nutritional regulation of lipogenic genes in mammary gland and adipose tissues of lactating goats. Journal of Dairy Research 72, 250255.Google Scholar
Bionaz, M, Loor, JJ 2007. Identification of reference genes for quantitative real-time PCR in the bovine mammary gland during the lactation cycle. Physiological Genomics 29, 312319.Google Scholar
Bonnet, M, Leroux, C, Chilliard, Y, Martin, P 2001. A fluorescent reverse transcription-polymerase chain reaction assay to quantify the lipoprotein lipase messenger RNA. Molecular and Cellular Probes 15, 187194.CrossRefGoogle ScholarPubMed
Bonnet, M, Delavaud, C, Bernard, L, Rouel, J, Chilliard, Y 2009. Sunflower-seed oil, rapidly-degradable starch, and adiposity up-regulate leptin gene expression in lactating goats. Domestic Animal Endocrinology 37, 93103.Google Scholar
Bonnet, M, Leroux, C, Faulconnier, Y, Hocquette, JF, Bocquier, F, Martin, P, Chilliard, Y 2000. Lipoprotein lipase activity and mRNA are up-regulated by refeeding in adipose tissue and cardiac muscle of sheep. Journal of Nutrition 130, 749756.CrossRefGoogle ScholarPubMed
Bonnet, M, Cassar-Malek, I, Bauchart, D, Chilliard, Y, Jurie, C, Thomas, ANormand, J 2011. Lipid supplementation and basal diet influence oxidative and lipogenic metabolism in muscle and adipose tissues in cattle. In Proceedings of the Eighth International Symposium on the Nutrition of Herbivores, 6th–9th September 2011, Aberystwyth, Wales, UK, p. 539.Google Scholar
Bonnet, M, Faulconnier, Y, Leroux, C, Jurie, C, Cassar-Malek, I, Bauchart, D, Boulesteix, P, Pethick, D, Hocquette, JF, Chilliard, Y 2007. Glucose-6-phosphate dehydrogenase and leptin are related to marbling differences among Limousin and Angus or Japanese Black × Angus steers. Journal of Animal Science 85, 28822894.Google Scholar
Bougarn, S, Cunha, P, Gilbert, FB, Meurens, F, Rainard, P 2011. Technical note: validation of candidate reference genes for normalization of quantitative PCR in bovine mammary epithelial cells responding to inflammatory stimuli. Journal of Dairy Science 94, 24252430.CrossRefGoogle ScholarPubMed
Bustin, SA 2000. Absolute quantification of mRNA using real-time reverse transcription polymerase chain reaction assays. Journal of Molecular Endocrinology 25, 169193.Google Scholar
Bustin, SA 2002. Quantification of mRNA using real-time reverse transcription PCR (RT-PCR): trends and problems. Journal of Molecular Endocrinology 29, 2339.CrossRefGoogle ScholarPubMed
Bustin, SA, Benes, V, Garson, JA, Hellemans, J, Huggett, J, Kubista, M, Mueller, R, Nolan, T, Pfaffl, MW, Shipley, GL, Vandesompele, J, Wittwer, CT 2009. The MIQE guidelines: minimum information for publication of quantitative real-time PCR experiments. Clinical Chemistry 55, 611622.Google Scholar
Cherfaoui, M, Durand, D, Bonnet, M, Cassar-Malek, I, Bauchart, D, Thomas, A, Gruffat, D 2012. Expression of enzymes and transcription factors involved in n-3 long chain PUFA biosynthesis in Limousin bull tissues. Lipids 47, 391401.Google Scholar
De Ketelaere, A, Goossens, K, Peelman, L, Burvenich, C 2006. Technical note: validation of internal control genes for gene expression analysis in bovine polymorphonuclear leukocytes. Journal of Dairy Science 89, 40664069.Google Scholar
Erkens, T, Van Poucke, M, Vandesompele, J, Goossens, K, Van Zeveren, A, Peelman, LJ 2006. Development of a new set of reference genes for normalization of real-time RT-PCR data of porcine backfat and longissimus dorsi muscle, and evaluation with PPARGC1A. BMC Biotechnology 6, 41.Google Scholar
Faulconnier, Y, Chilliard, Y, Torbati, MB, Leroux, C 2011. The transcriptomic profiles of adipose tissues are modified by feed deprivation in lactating goats. Comparative Biochemistry and Physiology Part D Genomics Proteomics 6, 139149.Google Scholar
Faulconnier, Y, Bonnet, M, Bocquier, F, Leroux, C, Chilliard, Y 2001. Effects of photoperiod and feeding level on adipose tissue and muscle lipoprotein lipase activity and mRNA level in dry non-pregnant sheep. British Journal of Nutrition 85, 299306.CrossRefGoogle ScholarPubMed
Finot, L, Marnet, PG, Dessauge, F 2011. Reference gene selection for quantitative real-time PCR normalization: application in the caprine mammary gland. Small Ruminant Research 95, 2026.CrossRefGoogle Scholar
Frohnert, BI, Bernlohr, DA 2000. Regulation of fatty acid transporters in mammalian cells. Progress in Lipid Research 39, 83107.CrossRefGoogle ScholarPubMed
Gabrielsson, BG, Olofsson, LE, Sjogren, A, Jernas, M, Elander, A, Lonn, M, Rudemo, M, Carlsson, LM 2005. Evaluation of reference genes for studies of gene expression in human adipose tissue. Obesity Research 13, 649652.Google Scholar
Goossens, K, Van Poucke, M, Van Soom, A, Vandesompele, J, Van Zeveren, A, Peelman, LJ 2005. Selection of reference genes for quantitative real-time PCR in bovine preimplantation embryos. BMC Developmental Biology 5, 27.CrossRefGoogle ScholarPubMed
Graugnard, DE, Piantoni, P, Bionaz, M, Berger, LL, Faulkner, DB, Loor, JJ 2009. Adipogenic and energy metabolism gene networks in longissimus lumborum during rapid post-weaning growth in Angus and Angus × Simmental cattle fed high-starch or low-starch diets. BMC Genomics 10, 142.CrossRefGoogle ScholarPubMed
Gutgesell, A, Ringseis, R, Eder, K 2009. Short communication: dietary conjugated linoleic acid down-regulates fatty acid transporters in the mammary glands of lactating rats. Journal of Dairy Science 92, 11691173.Google Scholar
Hosseini, A, Sauerwein, H, Mielenz, M 2010. Putative reference genes for gene expression studies in propionate and β-hydroxybutyrate treated bovine adipose tissue explants. Journal of Animal Physiology and Animal Nutrition 94, e178e184.Google Scholar
Jump, DB 2008. N-3 polyunsaturated fatty acid regulation of hepatic gene transcription. Current Opinion in Lipidology 19, 242247.Google Scholar
Kadegowda, AK, Bionaz, M, Thering, B, Piperova, LS, Erdman, RA, Loor, JJ 2009. Identification of internal control genes for quantitative polymerase chain reaction in mammary tissue of lactating cows receiving lipid supplements. Journal of Dairy Science 92, 20072019.Google Scholar
Lisowski, P, Pierzchala, M, Goscik, J, Pareek, CS, Zwierzchowski, L 2008. Evaluation of reference genes for studies of gene expression in the bovine liver, kidney, pituitary, and thyroid. Journal of Applied Genetics 49, 367372.Google Scholar
Niemann, H, Kuhla, B, Flachowsky, G 2011. Perspectives for feed-efficient animal production. Journal of Animal Science 89, 43444363.Google Scholar
Saremi, B, Sauerwein, H, Dänicke, S, Mielenz, M 2012. Technical note: identification of reference genes for gene expression studies in different bovine tissues focusing on different fat depots. Journal of Dairy Science 95, 31313138.Google Scholar
Thering, BJ, Graugnard, DE, Piantoni, P, Loor, JJ 2009. Adipose tissue lipogenic gene networks due to lipid feeding and milk fat depression in lactating cows. Journal of Dairy Science 92, 42904300.CrossRefGoogle ScholarPubMed
Toral, PG, Bernard, L, Delavaud, C, Gruffat, D, Leroux, C, Chilliard, Y 2013. Effects of fish oil and additional starch on tissue fatty acid profile and lipogenic gene mRNA abundance in lactating goats fed a diet containing sunflower-seed oil. Published online Animal doi:10.1017/S1751731113000049.Google Scholar
Tramontana, S, Bionaz, M, Sharma, A, Graugnard, DE, Cutler, EA, Ajmone-Marsan, P, Hurley, WL, Loor, JJ 2008. Internal controls for quantitative polymerase chain reaction of swine mammary glands during pregnancy and lactation. Journal of Dairy Science 91, 30573066.Google Scholar
Vandesompele, J, De Preter, K, Pattyn, F, Poppe, B, Van Roy, N, De Paepe, A, Speleman, F 2002. Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biology 3, RESEARCH0034.CrossRefGoogle ScholarPubMed
Varshney, N, Mohanty, AK, Kumar, S, Kaushik, JK, Dang, AK, Mukesh, M, Mishra, BP, Kataria, R, Kimothi, SP, Mukhopadhyay, TK, Malakar, D, Prakash, BS, Grover, S, Batish, VK 2012. Selection of suitable reference genes for quantitative gene expression studies in milk somatic cells of lactating cows (Bos indicus). Journal of Dairy Science 95, 29352945.Google Scholar
Wang, YH, Byrne, KA, Reverter, A, Harper, GS, Taniguchi, M, McWilliam, SM, Mannen, H, Oyama, K, Lehnert, SA 2005. Transcriptional profiling of skeletal muscle tissue from two breeds of cattle. Mammalian Genome 16, 201210.Google Scholar
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