Abstract
Determining which reference genes have the highest stability, and are therefore appropriate for normalising data, is a crucial step in the design of real-time quantitative PCR (qPCR) gene expression studies. This is particularly warranted in non-model and ecologically important species for which appropriate reference genes are lacking, such as the mallard—a key reservoir of many diseases with relevance for human and livestock health. Previous studies assessing gene expression changes as a consequence of infection in mallards have nearly universally used β-actin and/or GAPDH as reference genes without confirming their suitability as normalisers. The use of reference genes at random, without regard for stability of expression across treatment groups, can result in erroneous interpretation of data. Here, eleven putative reference genes for use in gene expression studies of the mallard were evaluated, across six different tissues, using a low pathogenic avian influenza A virus infection model. Tissue type influenced the selection of reference genes, whereby different genes were stable in blood, spleen, lung, gastrointestinal tract and colon. β-actin and GAPDH generally displayed low stability and are therefore inappropriate reference genes in many cases. The use of different algorithms (GeNorm and NormFinder) affected stability rankings, but for both algorithms it was possible to find a combination of two stable reference genes with which to normalise qPCR data in mallards. These results highlight the importance of validating the choice of normalising reference genes before conducting gene expression studies in ducks. The fact that nearly all previous studies of the influence of pathogen infection on mallard gene expression have used a single, non-validated reference gene is problematic. The toolkit of putative reference genes provided here offers a solid foundation for future studies of gene expression in mallards and other waterfowl.
Highlights
Measuring host cellular responses to pathogens is a key requirement to understand pathogenesis and disease progression [1,2,3]
The quantitative PCR (qPCR) approach to measure gene expression can be useful for species where large-scale multiplex methods such as microarrays, Serial Analysis of Gene Expression (SAGE) and RNA seq are not viable
We show that different putative reference genes (RGs) are stable in different tissues, but that for each tissue analysed it is possible to find a combination of two RGs that provide adequate normalisation when investigating low pathogenic avian influenza virus (AIV) infected versus control ducks
Summary
Measuring host cellular responses to pathogens is a key requirement to understand pathogenesis and disease progression [1,2,3]. One approach is to measure changes in mRNA transcription of genes of interests in infected versus uninfected individuals via real-time quantitative PCR (hereafter qPCR). Such studies allow elucidation of the contribution of individual genes and, in some cases, genetic pathways involved in host immune responses to pathogens By measuring gene expression over a time-course of infection, it is possible to determine the speed, magnitude and longevity of the immune response The qPCR approach to measure gene expression can be useful for species where large-scale multiplex methods such as microarrays, Serial Analysis of Gene Expression (SAGE) and RNA seq are not viable
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