Identification of qPCR reference genes suitable for normalizing gene expression in the mdx mouse model of Duchenne muscular dystrophy

Abstract

The mdx mouse is the most widely-used animal model of the human disease Duchenne muscular dystrophy, and quantitative PCR analysis of gene expression in the muscles of this animal plays a key role in the study of pathogenesis and disease progression and in evaluation of potential therapeutic interventions. Normalization to appropriate stably-expressed reference genes is essential for accurate quantitative measurement, but determination of such genes is challenging: healthy and dystrophic muscles present very different transcriptional environments, further altering with disease progression and muscle use, raising the possibility that no single gene or combination of genes may be stable under all experimental comparative scenarios. Despite the pedigree of this animal model, this problem remains unaddressed. The aim of this work was therefore to comprehensively assess reference gene suitability in the muscles of healthy and dystrophic mice, identifying reference genes appropriate for specific experimental comparisons, and determining whether an essentially universally-applicable set of genes exists. Using a large sample collection comprising multiple muscles (including the tibialis anterior, diaphragm and heart muscles) taken from healthy and mdx mice at three disease-relevant ages, and a panel of sixteen candidate reference genes (FBXO38, FBXW2, MON2, ZFP91, HTATSF1, GAPDH, ACTB, 18S, CDC40, SDHA, RPL13a, CSNK2A2, AP3D1, PAK1IP1, B2M and HPRT1), we used the geNorm, BestKeeper and Normfinder algorithms to identify genes that were stable under multiple possible comparative scenarios. We reveal that no single gene is stable under all conditions, but a normalization factor derived from multiple genes (RPL13a, CSNK2A2, AP3D1 and the widely-used ACTB) appears suitable for normalizing gene expression in both healthy and dystrophic mouse muscle regardless of muscle type or animal age. We further show that other popular reference genes, including GAPDH, are markedly disease- or muscle-type correlated. This study demonstrates the importance of empirical reference gene identification, and should serve as a valuable resource for investigators wishing to study gene expression in mdx mice.

Multiplex in situ hybridization within a single transcript: RNAscope reveals dystrophin mRNA dynamics

“…Isolation and preparation methods were as described previously (33,34): RNA was isolated from muscle powder (homogenized under liquid nitrogen) using TRIzol reagent (Invitrogen) with inclusion of an additional chloroform extraction (1:1) after phase separation. RNA was assessed to determine yield and purity (nanodrop ND1000) and used to prepare cDNA via RTnanoscript2 (Primerdesign).…”

Identification of qPCR reference genes suitable for normalising gene expression in the developing mouse embryo

“…Identification of appropriate reference genes a priori is challenging, and various mathematical approaches exist: the geNorm [33], Normfinder [34], Bestkeeper [35] and deltaCt [36] methods all require a representative collection of cDNA samples, and a broad panel of candidate reference genes, but each assesses suitability via subtly different criteria (see supplementary data for an overview). Combining these complementary approaches increases the power of investigations: individual rankings might differ between methods, but truly strong candidates should consistently score highly regardless of assessment method (and discrepancies between methods can moreover highlight interesting biological information, as reported previously [26, 37]).…”

“…For validation, we employed an approach we have used previously [26, 37]: using our high scoring candidates ( AP3D1 , RPL13A , PAK1IP1 ) to normalise our lowest scoring candidates ( HPRT1 and B2M ). Raw data for these genes suggested modest expression with a dramatic increase at E18.5, however following normalisation both genes show a progressive increase in expression with increasing age, whether in whole embryos, heads, or limbs (Fig 9).…”

“…Tissues (whole embryos, heads or forelimbs) were pulverised via dry-ice-cooled cell-crusher (Cellcrusher Ltd), and ~100-200mg frozen tissue powder (well mixed to ensure representative sampling) was used to prepare RNA. RNA was isolated using TRIzol (Invitrogen) as described previously [26, 37], with inclusion of an additional chloroform extraction (1:1) after the phase separation step and inclusion of 10μg glycogen during precipitation to maximise RNA yield. RNA yield and purity were assessed via nanodrop (ND1000) and samples with 260/230 ratios below 1.7 were subjected to a second precipitation.…”

“…Our collection of samples is substantial (N=3-5 per time point) and we have used a broad panel of 15 candidate reference genes ( ACTB, 18S, SDHA, GAPDH, HTATSF1, CDC40, RPL13A, CSNK2A2, AP3D1, HPRT1, CYC1, EIF4A, UBC, B2M and PAK1IP1 - Table 1). This panel includes candidates widely used historically ( 18S , GAPDH , ACTB ), those that we have shown be strong references in mouse skeletal muscle ( CSNK2A2 , AP3D1 , RPL13A ) [25, 37], and also shown by others to be viable references in rodent brains ( UBC , HPRT1 , RPL13A, 18S ) [46, 47]. To maximise the power of our study, we have assessed reference gene suitability using all four algorithms described above (geNorm, deltaCt, BestKeeper and Normfinder).…”