In disease dynamics, high immune gene diversity can confer a selective advantage to hosts in the face of a rapidly evolving and diverse pathogen fauna. This is supported empirically for genes involved in pathogen recognition and signalling. In contrast, effector genes involved in pathogen clearance may be more constrained. b-Defensins are innate immune effector genes; their main mode of action is via disruption of microbial membranes. Here, five b-defensin genes were characterized in mallards (Anas platyrhynchos) and other waterfowl; key reservoir species for many zoonotic diseases. All five genes showed remarkably low diversity at the individual-, population-, and species-level. Furthermore, there was widespread sharing of identical alleles across species divides. Thus, specific b-defensin alleles were maintained not only spatially but also over long temporal scales, with many amino acid residues being fixed across all species investigated. Purifying selection to maintain individual, highly efficacious alleles was the primary evolutionary driver of these genes in waterfowl. However, we also found evidence for balancing selection acting on the most recently duplicated b-defensin gene (AvBD3b). For this gene, we found that amino acid replacements were more likely to be radical changes, suggesting that duplication of b-defensin genes allows exploration of wider functional space. Structural conservation to maintain function appears to be crucial for avian b-defensin effector molecules, resulting in low tolerance for new allelic variants. This contrasts with other types of innate immune genes, such as receptor and signalling molecules, where balancing selection to maintain allelic diversity has been shown to be a strong evolutionary force.
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.
This article provides data on primer sequences used to amplify the innate immune genes RIG-I and Mx and a set of normalizing reference genes in mallards (Anas platyrhynchos), and shows which reference genes are stable, per tissue, for our experimental settings. Data on the expressional changes of these two genes over a time-course of infection with low pathogenic avian influenza virus (LPAI) are provided. Individual-level data are also presented, including LPAI infection load, and per tissue gene expression of RIG-I and Mx. Gene expression in two outlier individuals is explored in more depth.
While thousands of in vitro-produced (IVP) bovine embryos have been transferred commercially with no reports of disease transmission, such risks must be considered. Due to differences in their zonae pellucidae, the disease risks with IVP embryos are known to be higher than with in vivo-derived embryos. Possible sources of infection include the oocytes, spermatozoa, serum, and co-culture cells. The Terrestrial Animal Health Code of the Office International des Epizooties (OIE, 2003) stipulates that disease risk management should meet standards set by the World Trade Organization. These standards include subjecting the IVP procedures to quantitative risk assessment to evaluate disease transmission risk. The purpose of the present work was to measure the risks of transmitting disease with IVP embryos obtained from abattoir-derived tissues. A simulation model was developed using Microsoft Excel spreadsheets with the Palisade @RISK (London, UK) software program. The model incorporates probability distributions, the shapes of which reflect the random nature of some of the data (e.g. fluid volumes in cultures and washes) and the conjectural nature of some of the scientific information (e.g. on disease agents). The model is adaptable so that, when accurate data or information become available, variability estimates and degrees of uncertainty can be replaced with fixed values. The model assumes: (1) the IVP method is as described in the IETS Manual (1998); (2) there are five possible sources of infection; donor cow, donor bull, fetal calf serum, bovine serum albumin, and co-culture cells; (3) the disease agents can survive and/or proliferate during in vitro maturation, fertilization and culture; (4) fluid volumes in cultures and washes follow "known" normal distributions; (5) uncertainties in current knowledge of IVP embryos and disease agents can be taken into account by use of appropriate probability distributions; (6) different methods of in vitro fertilization do not affect the level of risk; and (7) different methods of in vitro culture can affect the level of risk. The model as constructed fits comfortably into a single workbook with one worksheet allocated for the model itself and another serving to store data on diseases of interest. Data on oocytes, blastocyst numbers, etc., and on media and wash fluid volumes are held within the model while information relating to particular diseases can be selected from a drop-down list at the top of the first worksheet. The relevant data stored in the database are then retrieved and used for modelling, using Monte Carlo simulation. The model estimates the final titer of the disease agent in IVP embryos and the probability of at least one infective transmission to a recipient, expressed as distributions. The seasonal demand for farmed venison in New Zealand has necessitated the concentration of red deer breeding into the first month of the four-month breeding season. Because of this constraint it is difficult to obtain enough in vitro-produced blastocysts for transfer. Succes...
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