Anti-UXT (internal region) polyclonal antibody

Gene expression analysis unravels the complex changes or relations at transcriptomic level. To nullify all type of errors that can be incorporated during any stage of RNA extraction into cDNA synthesis and for reliable results, the data obtained from qPCR have to be normalized using the appropriate/suitable housekeeping genes (HKGs). Unfortunately, till date, no such HKG has been reported for bubaline mammary gland. The objective of the present study was thus to identify and validate the potential HKGs for the gene expression studies in buffalo mammary gland. Mammary tissues from twelve buffaloes during different physiological stages: pre-pubertal (heifer), lactation and involution were obtained for the present study. A total of 16 potential HKGs (GAPDH, -actin, UXT, 2M, A2M, RPl4, RPS9, RPS15A, RPS18, RPS23, HMBS, HPRT1, GTP, EEF1A1, UB1 and RPL22) from different functional classes were evaluated. The analysis revealed that the expression of EEF1A1, RPl4, 2M and RPS15A was most consistent across different physiological stages of buffalo mammary gland. On the other hand, -actin, A2M, RPL22 and GAPDH were the least stable genes making them unsuitable as HKGs. Based on our analysis, we recommend the use of EEF1A1, RPl4, 2M and RPS15A genes as suitable HKGs for accurate normalization of gene expression data in bubaline mammary gland.

Real-time quantitative PCR (RT-qPCR) is widely used to measure and evaluate gene expression. The precision and reliability of RT-qPCR are critically dependent on the selection of suitable reference genes (RGs). In this study, an effort was made to identify the optimal RGs for RT-qPCR analysis of adipose and the longissimus dorsi muscle (LM) in buffaloes. RNA sequencing data were firstly analyzed to obtain 10 candidate genes (FKBP1A,C25H16orf72,PNRC2,IQGAP1,ATP5PD,RPL6,NDUFB4,TRA2A,CAPRIN1, andMETAP2) that with high and stable expression across adipose tissues. Four other identified RGs (GAPDH,ACTB,TOP2B, andUXT) were selected as well. The expression stability of the candidate RGs was evaluated by three algorithms (geNorm, NormFinder, and BestKeeper) and then further validated by adipocyte and myocyte markers. Our results showed thatUXTandTOP2Bwere the optimal RGs for RT-qPCR analysis across adipose tissues in buffaloes; three RGs,RPL6,UXT, andTOP2B, were the optimal RGs for RT-qPCR analysis across adipose and the LM tissues in buffaloes. This study provides significant information for improving the accuracy of gene expression in research on intramuscular fat deposition in buffaloes.