Selection of stably expressed internal control genes in circulating polymorphoneutrophils of periparturient Sahiwal (Bos indicus) cows

MANISHI MUKESH; AMIT KISHORE; ANKITA SHARMA; M S TANTIA; R S KATARIA; A K MOHANTY; MONIKA SODHI

doi:10.56093/ijans.v88i1.79507

Authors

MANISHI MUKESH ICAR National Fellow and Principal Scientist, ICAR-National Bureau of Animal Genetic Resources, Karnal, Haryana 132 001 India
AMIT KISHORE Ex Research Associate, ICAR-National Bureau of Animal Genetic Resources, Karnal, Haryana 132 001 India
ANKITA SHARMA Research Associate, ICAR-National Bureau of Animal Genetic Resources, Karnal, Haryana 132 001 India
M S TANTIA Principal Scientist-I/c Network, Division of Animal Biotechnology, ICAR-National Bureau of Animal Genetic Resources, Karnal, Haryana 132 001 India
R S KATARIA Principal Scientist, ICAR-National Bureau of Animal Genetic Resources, Karnal, Haryana 132 001 India
A K MOHANTY Principal Scientist, ICAR- National Dairy Research Institute, Karnal, Haryana
MONIKA SODHI Principal Scientist, ICAR-National Bureau of Animal Genetic Resources, Karnal, Haryana 132 001 India

https://doi.org/10.56093/ijans.v88i1.79507

Keywords:

Bos indicus, PMN, Periparturient stage, Internal control genes, Normalization, q-PCR

Abstract

Around parturition, animal undergoes a state of immune-suppression and become more susceptible to pathogens. This study was aimed to identify appropriate internal control genes (ICG) for transcriptional studies in polymorphoneutrophils (PMN)of Sahiwal (Bos indicus) cows during the periparturient period. The study involved 4 periparturient Sahiwal cows (–21 days to 0 day to +21 days relative to parturition) and 10 known internal control genes (ICG)from different functional classes. ForqPCR reaction following conditions were employed: 2 min at 50°C, 10 min at 95 °C, 40 cycles of 15 s at 95 °C (denaturation) and 1 min at 60°C (annealing + extension).To measure the transcript stability of 10 ICG genes, threesoftwareprogrammes;geNorm, Normfinder and BestKeeper were used. All the genes showed acceptable expression stability as per the recommended threshold values. The geNorm analysis showed RPS9, RPS15A and RPS23 genes to be most stably expressed while HMBS and HPRT1 showed least stability.The expression stability for all the 10 ICG were within the acceptable range (M value <1.5).The pair wise variation analysis recommended the use of RPS9, RPS15Agenes for normalization. The geNorm and Normfinder identified same set of most and least stable genes. BestKeeper analysis identified ACTB, RPS9/ B2M,RPS23, RPS15A genes showing consistent expression while HMBS and HPRT1 showed relatively much higher variability. Our analysis identified RPS9, RPS15Aand ACTBgenesassuitable ICG to provide accurate normalization totranscriptional dataof PMN during the periparturient stages of Indian cows.

Downloads

Download data is not yet available.

References

Aggarwal J, Sharma A, Kishore A, Mishra BP, Yadav A, Mohanty A, Sodhi M, Kataria RS, Malakar D and Mukesh M. 2013. Identification of suitable housekeeping genes for normalization of quantitative real-time PCR data during different physiological stages of mammary gland in riverine buffaloes (Bubalus bubalis). Journal of Animal Production and Nutrition 97(6): 1132–41. DOI: https://doi.org/10.1111/jpn.12027

Bionaz M and Loor JJ. 2007. Identification of reference genes for quantitative real-time PCR in the bovine mammary gland during the lactation cycle. Physiological Genomics 29: 312–19. DOI: https://doi.org/10.1152/physiolgenomics.00223.2006

Brunner AM, Yakovlev I A and Strauss SH. 2004. Validating internal controls for quantitative plant gene expression studies. BMC Plant Biology 4: 14. DOI: https://doi.org/10.1186/1471-2229-4-14

Bustin SA. 2000. Absolute quantification of mRNA using realtime reverse transcription polymerase chain reaction assays. Journal of Molecular Endocrinology 25: 169-93. DOI: https://doi.org/10.1677/jme.0.0250169

Cai TQ, Weston PG, Lund LA, Brodie B, McKenna DJ andWagnerW. 1994. Association between neutrophil functions and periparturient disorders in cows. American Journal of Veterinary Research 55(7): 934–43.

Deindl E, Boengler K, van Royen N and Schaper W.2002. Differential expression of GAPDH and beta3-actin in growing collateral arteries. Molecular and Cellular Biochemistry 236: 139–46. DOI: https://doi.org/10.1023/A:1016166127465

De Ketelaere A, Goossens K, Peelman L and Burvenich C. 2006. Validation of internal control genes for gene expression analysis in bovine polymorphonuclear leukocytes. Journal of Dairy Science 89(10): 4066–69. DOI: https://doi.org/10.3168/jds.S0022-0302(06)72450-X

Dheda K, Huggett JF, Bustin SA, Johnson MA, Rook G and Zumla A. 2004. Validation of housekeeping genes for normalizing RNA expression in real-time PCR. Biotechniques 37: 112–19. DOI: https://doi.org/10.2144/04371RR03

Garcia-Crespo D, Juste RA, Garcia-Crespo D H A, Juste RA and Hurtado A. 2005. Selection of ovine housekeeping genes for normalisation by real time RT-PCR; analysis of PrP gene expression and genetic susceptibility to scrapie. BMC Veterinary Research 1: 3. DOI: https://doi.org/10.1186/1746-6148-1-3

Huggett J, Dheda K, Bustin S and Zumla A. 2005. Real-time RTPCR normalisation strategies and considerations. Genes and Immunity 6: 279–84. DOI: https://doi.org/10.1038/sj.gene.6364190

Janovick GNA, Dan HM, Carlson DB, Murphy MR, Loor JJ and Drackley JK. 2007.Housekeeping gene expression in bovine liver is affected by physiological state, feed intake, and dietary treatment. Journal of Dairy Science 90(5): 2246–52. DOI: https://doi.org/10.3168/jds.2006-640

Kadegowda AK, Bionaz M, Thering B, Piperova LS, Erdman RA and 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(5): 2007–19. DOI: https://doi.org/10.3168/jds.2008-1655

Kehrli ME Jr, Nonnecke BJ and Roth JA. 1989. Alterations in bovine neutrophil function during the periparturient period. American Journal of Veterinary Research 50(2): 207–14.

Musters S, Coughlan K, McFadden T, Maple R, Mulvey T and Plaut K. 2004. Exogenous TGF-beta1 promotes stromal development in the heifer mammary gland. Journal of Dairy Science 87: 896–904. DOI: https://doi.org/10.3168/jds.S0022-0302(04)73234-8

Oh H, Siano B and Diamond S. 2008. Neutrophil isolation protocol. Journal of Visualized Experiments 17: 745. DOI: https://doi.org/10.3791/745

Pfaffl MW, Tichopad A, Prgomet C andNeuvians TP. 2004. Determination of stable housekeeping genes, differentially regulated target genes and sample integrity: Best Keeper – Excel-based tool using pair-wise correlations. Biotechnology Letters 26: 509–15. DOI: https://doi.org/10.1023/B:BILE.0000019559.84305.47

Radonic A, Thulke S, Mackay IM, Landt O, Siegert W and Nitsche A. 2004. Guideline to reference gene selection for quantitative real-time PCR. Biochemical and Biophysical Research Communications 313: 856–62. DOI: https://doi.org/10.1016/j.bbrc.2003.11.177

Rasmussen R, Meuer S, WittwerC and Nakagawara K.2001. Quantification on the Light Cycler instrument. Rapid Cycle Real time PCR.Methods and Applications, Springer, Heidelberg, pp 21–34.

Stamova BS, Michelle A, WynnLW, Yingfang T, Huichun X, Peter A, Xinhua Z, Liu D, Bradley PA, Isaac HL, Jeffrey PG, Renee JT, Glen J, Lisa L and Sharp FR. 2009. Identification and validation of suitable endogenous reference genes for gene expression studies in human peripheral blood. BMC Medical Genomics 2(49): 1755–8794. DOI: https://doi.org/10.1186/1755-8794-2-49

Suzuki T, Higgins PJ andCrawford DR. 2000. Control selection for RNA quantitation. Biotechniques 29: 332–37. DOI: https://doi.org/10.2144/00292rv02

Thorn SR, Meyer MJ,Van Amburgh ME and Boisclair YR. 2007. Effect of estrogen on leptin and expression of leptin receptor transcripts in prepubertal dairy heifers. Journal of Dairy Science 90: 3742–50. DOI: https://doi.org/10.3168/jds.2007-0009

Thorn SR, Purup S, Cohick WS, Vestergaard M, Sejrsen K and Boisclair YR.2006. Leptin does not act directly on mammary epithelial cells in prepubertal dairy heifers. Journal of Dairy Science 89: 1467–77. DOI: https://doi.org/10.3168/jds.S0022-0302(06)72214-7

Tong Z, Gao Z, Wang F, Zhou J and Zhang Z. 2009. Selection of reliable reference genes for gene expression studies in peach using real-time PCR. BMC Molecular Biology 10: 71. DOI: https://doi.org/10.1186/1471-2199-10-71

Tramontana S, Bionaz M, Sharma A, Graugnard DE, Cutler EA, Ajmone-Marsan P, Hurley WL and Loor J J. 2008. Internal controls for quantitative polymerase chain reaction of swine mammary glands during pregnancy and lactation. Journal of Dairy Science 91: 3057–66. DOI: https://doi.org/10.3168/jds.2008-1164

Valasek M A and Repa J J.2005. The power of real-time PCR.Advances in Physiology Education 29: 151–59. DOI: https://doi.org/10.1152/advan.00019.2005

Vandesompele J, Preter KD, Pattyn F, Poppe B, Roy NV, Paepe A D and Speleman F. 2002. Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biology 3: 7. DOI: https://doi.org/10.1186/gb-2002-3-7-research0034

Zhang X, Ding L, Sandford AJ, Zhang X, Ding L and Sandford AJ.2005. Selection of reference genes for gene expression studies in human neutrophils by real-time PCR. BMC Molecular Biology 6: 4. DOI: https://doi.org/10.1186/1471-2199-6-4