Host inhibits replication of European porcine reproductive and respiratory syndrome virus in macrophages by altering differential regulation of type-I interferon transcriptional response.

Porcine reproductive and respiratory syndrome (PRRS) is an infectious disease caused by a positive RNA strand arterivirus. PRRS virus (PRRSV) interacts primarily with lung macrophages. Little is known how the virus subverts the innate immune response to initiate its replication in alveolar macrophages. Large-scale transcriptional responses of macrophages with different levels of susceptibility to PRRSV infection were compared over 30 h of infection. This study demonstrates a rapid and intense host transcriptional remodelling during the early phase of the replication of the virus which correlates with transient repression of type-I interferon transcript as early as 8 h post-infection. These results support the suggestion from previous studies that host innate immune response inhibits replication of European porcine reproductive and respiratory syndrome virus in macrophages by altering differential regulation of type-I interferon transcriptional response.

Identification of melatonin-regulated genes in the ovine pituitary pars tuberalis, a target site for seasonal hormone control.

The pars tuberalis (PT) of the pituitary gland expresses a high density of melatonin (MEL) receptors and is believed to regulate seasonal physiology by decoding changes in nocturnal melatonin secretion. Circadian clock genes are known to be expressed in the PT in response to the decline (Per1) and onset (Cry1) of MEL secretion, but to date little is known of other molecular changes in this key MEL target site. To identify transcriptional pathways that may be involved in the diurnal and photoperiod-transduction mechanism, we performed a whole genome transcriptome analysis using PT RNA isolated from sheep culled at three time points over the 24-h cycle under either long or short photoperiods. Our results reveal 153 transcripts where expression differs between photoperiods at the light-dark transition and 54 transcripts where expression level was more globally altered by photoperiod (all time points combined). Cry1 induction at night was associated with up-regulation of genes coding for NeuroD1 (neurogenic differentiation factor 1), Pbef / Nampt (nicotinamide phosphoribosyltransferase), Hif1alpha (hypoxia-inducible factor-1alpha), and Kcnq5 (K+ channel) and down-regulation of Rorbeta, a key clock gene regulator. Using in situ hybridization, we confirmed day-night differences in expression for Pbef / Nampt, NeuroD1, and Rorbeta in the PT. Treatment of sheep with MEL increased PT expression for Cry1, Pbef / Nampt, NeuroD1, and Hif1alpha, but not Kcnq5. Our data thus reveal a cluster of Cry1-associated genes that are acutely responsive to MEL and novel transcriptional pathways involved in MEL action in the PT.

The EADGENE Microarray Data Analysis Workshop (open access publication).

Microarray analyses have become an important tool in animal genomics. While their use is becoming widespread, there is still a lot of ongoing research regarding the analysis of microarray data. In the context of a European Network of Excellence, 31 researchers representing 14 research groups from 10 countries performed and discussed the statistical analyses of real and simulated 2-colour microarray data that were distributed among participants. The real data consisted of 48 microarrays from a disease challenge experiment in dairy cattle, while the simulated data consisted of 10 microarrays from a direct comparison of two treatments (dye-balanced). While there was broader agreement with regards to methods of microarray normalisation and significance testing, there were major differences with regards to quality control. The quality control approaches varied from none, through using statistical weights, to omitting a large number of spots or omitting entire slides. Surprisingly, these very different approaches gave quite similar results when applied to the simulated data, although not all participating groups analysed both real and simulated data. The workshop was very successful in facilitating interaction between scientists with a diverse background but a common interest in microarray analyses.

Analysis of a simulated microarray dataset: comparison of methods for data normalisation and detection of differential expression (open access publication).

Microarrays allow researchers to measure the expression of thousands of genes in a single experiment. Before statistical comparisons can be made, the data must be assessed for quality and normalisation procedures must be applied, of which many have been proposed. Methods of comparing the normalised data are also abundant, and no clear consensus has yet been reached. The purpose of this paper was to compare those methods used by the EADGENE network on a very noisy simulated data set. With the a priori knowledge of which genes are differentially expressed, it is possible to compare the success of each approach quantitatively. Use of an intensity-dependent normalisation procedure was common, as was correction for multiple testing. Most variety in performance resulted from differing approaches to data quality and the use of different statistical tests. Very few of the methods used any kind of background correction. A number of approaches achieved a success rate of 95% or above, with relatively small numbers of false positives and negatives. Applying stringent spot selection criteria and elimination of data did not improve the false positive rate and greatly increased the false negative rate. However, most approaches performed well, and it is encouraging that widely available techniques can achieve such good results on a very noisy data set.