Reference genes for reverse transcription quantitative PCR in canine brain tissue. (December 2015)

• Record Type: Journal Article
• Authors: Stassen, Quirine; Riemers, Frank; Reijmerink, Hannah; Leegwater, Peter; Penning, Louis
• Is Part Of: BMC research notes. Volume 8:Number 1(2015)
• Page Start: 1
• Page End: 8
• Publication Date: 2015-12
• Subjects: Reference genes -- Dog -- Brain -- RT-qPCR; Medicine -- Periodicals; Biology -- Periodicals; 610.5
• DOI: 10.1186/s13104-015-1628-4
• Languages: English
• ISSNs: 1756-0500

Abstract

Abstract Background In the last decade canine models have been used extensively to study genetic causes of neurological disorders such as epilepsy and Alzheimer's disease and unravel their pathophysiological pathways. Reverse transcription quantitative polymerase chain reaction is a sensitive and inexpensive method to study expression levels of genes involved in disease processes. Accurate normalisation with stably expressed so-called reference genes is crucial for reliable expression analysis. Results Following the minimum information for publication of quantitative real-time PCR experiments precise guidelines, the expression of ten frequently used reference genes, namelyYWHAZ, HMBS, B2M, SDHA, GAPDH, HPRT, RPL13A, RPS5, RPS19 andGUSB was evaluated in seven brain regions (frontal lobe, parietal lobe, occipital lobe, temporal lobe, thalamus, hippocampus and cerebellum) and whole brain of healthy dogs. The stability of expression varied between different brain areas. Using the GeNorm and Normfinder softwareHMBS, GAPDH andHPRT were the most reliable reference genes for whole brain. Furthermore based on GeNorm calculations it was concluded that as little as two to three reference genes are sufficient to obtain reliable normalisation, irrespective the brain area. Conclusions Our results amend/extend the limited previously published data on canine brain reference genes. Despite the excellent expression stability ofHMBS, GAPDH andHRPT, the evaluation of expression stability of reference genes must be a standard and integral part of experimental design and subsequent data analysis.