Profiling microRNA expression in bovine alveolar macrophages using RNA-seq.

MicroRNAs (miRNAs) are important regulators of gene expression and are known to play a key role in regulating both adaptive and innate immunity. Bovine alveolar macrophages (BAMs) help maintain lung homeostasis and constitute the front line of host defense against several infectious respiratory diseases, such as bovine tuberculosis. Little is known, however, about the role miRNAs play in these cells. In this study, we used a high-throughput sequencing approach, RNA-seq, to determine the expression levels of known and novel miRNAs in unchallenged BAMs isolated from lung lavages of eight different healthy Holstein-Friesian male calves. Approximately 80 million sequence reads were generated from eight BAM miRNA Illumina sequencing libraries, and 80 miRNAs were identified as being expressed in BAMs at a threshold of at least 100 reads per million (RPM). The expression levels of miRNAs varied over a large dynamic range, with a few miRNAs expressed at very high levels (up to 800,000RPM), and the majority lowly expressed. Notably, many of the most highly expressed miRNAs in BAMs have known roles in regulating immunity in other species (e.g. bta-let-7i, bta-miR-21, bta-miR-27, bta-miR-99b, bta-miR-146, bta-miR-147, bta-miR-155 and bta-miR-223). The most highly expressed miRNA in BAMs was miR-21, which has been shown to regulate the expression of antimicrobial peptides in Mycobacterium leprae-infected human monocytes. Furthermore, the predicted target genes of BAM-expressed miRNAs were found to be statistically enriched for roles in innate immunity. In addition to profiling the expression of known miRNAs, the RNA-seq data was also analysed to identify potentially novel bovine miRNAs. One putatively novel bovine miRNA was identified. To the best of our knowledge, this is the first RNA-seq study to profile miRNA expression in BAMs and provides an important reference dataset for investigating the regulatory roles miRNAs play in this important immune cell type.

Next generation sequencing reveals the expression of a unique miRNA profile in response to a gram-positive bacterial infection.

MicroRNAs (miRNAs) are short, non-coding RNAs, which post-transcriptionally regulate gene expression and are proposed to play a key role in the regulation of innate and adaptive immunity. Here, we report a next generation sequencing (NGS) approach profiling the expression of miRNAs in primary bovine mammary epithelial cells (BMEs) at 1, 2, 4 and 6 hours post-infection with Streptococcus uberis, a causative agent of bovine mastitis. Analysing over 450 million sequencing reads, we found that 20% of the approximately 1,300 currently known bovine miRNAs are expressed in unchallenged BMEs. We also identified the expression of more than 20 potentially novel bovine miRNAs. There is, however, a significant dynamic range in the expression of known miRNAs. The top 10 highly expressed miRNAs account for >80% of all aligned reads, with the remaining miRNAs showing much lower expression. Twenty-one miRNAs were identified as significantly differentially expressed post-infection with S. uberis. Several of these miRNAs have characterised roles in the immune systems of other species. This miRNA response to the Gram-positive S. uberis is markedly different, however, to lipopolysaccharide (LPS) induced miRNA expression. Of 145 miRNAs identified in the literature as being LPS responsive, only 9 were also differentially expressed in response to S. uberis. Computational analysis has also revealed that the predicted target genes of miRNAs, which are down-regulated in BMEs following S. uberis infection, are statistically enriched for roles in innate immunity. This suggests that miRNAs, which potentially act as central regulators of gene expression responses to a Gram-positive bacterial infection, may significantly regulate the sentinel capacity of mammary epithelial cells to mobilise the innate immune system.

Pathway-GPS and SIGORA: identifying relevant pathways based on the over-representation of their gene-pair signatures.

Motivation. Predominant pathway analysis approaches treat pathways as collections of individual genes and consider all pathway members as equally informative. As a result, at times spurious and misleading pathways are inappropriately identified as statistically significant, solely due to components that they share with the more relevant pathways. Results. We introduce the concept of Pathway Gene-Pair Signatures (Pathway-GPS) as pairs of genes that, as a combination, are specific to a single pathway. We devised and implemented a novel approach to pathway analysis, Signature Over-representation Analysis (SIGORA), which focuses on the statistically significant enrichment of Pathway-GPS in a user-specified gene list of interest. In a comparative evaluation of several published datasets, SIGORA outperformed traditional methods by delivering biologically more plausible and relevant results. Availability. An efficient implementation of SIGORA, as an R package with precompiled GPS data for several human and mouse pathway repositories is available for download from http://sigora.googlecode.com/svn/.