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

When Size Really Matters: The Eccentricities of Dystrophin Transcription and the Hazards of Quantifying mRNA from Very Long Genes

At 2.3 megabases in length, the dystrophin gene is enormous: transcription of a single mRNA requires approximately 16 h. Principally expressed in skeletal muscle, the dystrophin protein product protects the muscle sarcolemma against contraction-induced injury, and dystrophin deficiency results in the fatal muscle-wasting disease, Duchenne muscular dystrophy. This gene is thus of key clinical interest, and therapeutic strategies aimed at eliciting dystrophin restoration require quantitative analysis of its expression. Approaches for quantifying dystrophin at the protein level are well-established, however study at the mRNA level warrants closer scrutiny: measured expression values differ in a sequence-dependent fashion, with significant consequences for data interpretation. In this manuscript, we discuss these nuances of expression and present evidence to support a transcriptional model whereby the long transcription time is coupled to a short mature mRNA half-life, with dystrophin transcripts being predominantly nascent as a consequence. We explore the effects of such a model on cellular transcriptional dynamics and then discuss key implications for the study of dystrophin gene expression, focusing on both conventional (qPCR) and next-gen (RNAseq) approaches.

The skeletal muscle phenotype of the DE50-MD dog model of Duchenne muscular dystrophy

Background: Animal models of Duchenne muscular dystrophy (DMD) are essential to study disease progression and assess efficacy of therapeutic intervention, however dystrophic mice fail to display a clinically relevant phenotype, limiting translational utility. Dystrophin-deficient dogs exhibit disease similar to humans, making them increasingly important for late-stage preclinical evaluation of candidate therapeutics. The DE50-MD canine model of DMD carries a mutation within a human 'hotspot' region of the dystrophin gene, amenable to exon-skipping and gene editing strategies. As part of a large natural history study of disease progression, we have characterised the DE50-MD skeletal muscle phenotype to identify parameters that could serve as efficacy biomarkers in future preclinical trials. Methods: Vastus lateralis muscles were biopsied from a large cohort of DE50-MD dogs and healthy male littermates at 3-monthly intervals (3-18 months) for longitudinal analysis, with multiple muscles collected post-mortem to evaluate body-wide changes. Pathology was characterised quantitatively using histology and measurement of gene expression to determine statistical power and sample sizes appropriate for future work. Results: DE50-MD skeletal muscle exhibits widespread degeneration/regeneration, fibrosis, atrophy and inflammation. Degenerative/inflammatory changes peak during the first year of life, while fibrotic remodelling appears more gradual. Pathology is similar in most skeletal muscles, but in the diaphragm, fibrosis is more prominent, associated with fibre splitting and pathological hypertrophy. Picrosirius red and acid phosphatase staining represent useful quantitative histological biomarkers for fibrosis and inflammation respectively, while qPCR can be used to measure regeneration ( MYH3, MYH8), fibrosis ( COL1A1), inflammation ( SPP1), and stability of DE50-MD dp427 transcripts. Conclusion: The DE50-MD dog is a valuable model of DMD, with pathological features similar to young, ambulant human patients. Sample size and power calculations show that our panel of muscle biomarkers are of strong pre-clinical value, able to detect therapeutic improvements of even 25%, using trials with only six animals per group.

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

Background: Progression through mammalian embryogenesis involves many interacting cell types and multiple differentiating cell lineages. Quantitative polymerase chain reaction (qPCR) analysis of gene expression in the developing embryo is a valuable tool for deciphering these processes, but normalisation to stably-expressed reference genes is essential for such analyses. Gene expression patterns change globally and dramatically as embryonic development proceeds, rendering identification of consistently appropriate reference genes challenging. Methods: We have investigated expression stability in mouse embryos from mid to late gestation (E11.5-E18.5), both at the whole-embryo level, and within the head and forelimb specifically, using 15 candidate reference genes ( ACTB, 18S, SDHA, GAPDH, HTATSF1, CDC40, RPL13A, CSNK2A2, AP3D1, HPRT1, CYC1, EIF4A, UBC, B2M and PAK1IP1), and four complementary algorithms (geNorm, Normfinder, Bestkeeper and deltaCt). Results: Unexpectedly, all methods suggest that many genes within our candidate panel are acceptable references, though AP3D1, RPL13A and PAK1IP1 are the strongest performing genes overall (scoring highly in whole embryos, heads or forelimbs alone, and in all samples collectively). HPRT1 and B2M are conversely poor choices, and show strong developmental regulation. We further show that normalisation using our three highest-scoring references can reveal subtle patterns of developmental expression even in genes ostensibly ranked as acceptably stable ( CDC40, HTATSF1). Conclusion: AP3D1, RPL13A and PAK1IP1 represent universally suitable reference genes for expression studies in the E11.5-E18.5 mouse embryo.

Identification and validation of stable reference genes for quantitative real time PCR in different minipig tissues at developmental stages

Background

Quantitative real time PCR (qPCR) is a powerful tool to evaluate mRNA expression level. However, reliable qPCR results require normalization with validated reference gene(s). In this study, we investigated stable reference genes in seven tissues according to four developmental stages in minipigs. Six candidate reference genes and one target gene (ACE2) were selected and qPCR was performed. BestKeeper, geNorm, NormFinder, and delta Ct method through the RefFinder web-based tool were used to evaluate the stability of candidate reference genes. To verify the selected stable genes, relative expression of ACE2 was calculated and compared with each other.

Results

As a result, HPRT1 and 18S genes had lower SD value, while HMBS and GAPDH genes had higher SD value in all samples. Using statistical algorithms, HPRT1 was the most stable gene, followed by 18S, β-actin, B2M, GAPDH, and HMBS. In intestine, all candidate reference genes exhibited similar patterns of ACE2 gene expression over time, whereas in liver, lung, and kidney, gene expression pattern normalized with stable reference genes differed from those normalized with less stable genes. When normalized with the most stable genes, the expression levels of ACE2 in minipigs highly increased in intestine and kidney at PND28, which is consistent with the ACE2 expression pattern in humans.

Conclusions

We suggest that HPRT1 and 18S are good choices for analyzing all these samples across the seven tissues and four developmental stages. However, this study can be a reference literature for gene expression experiments using minipig because reference gene should be validated and chosen according to experimental conditions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08830-z.