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

peer-reviewedMotivation. 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/

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/

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

Putative novel bovine miRNAs discovered through miRDeep2 analysis of miRNAseq data from 24 bovine primary mammary epithelial cell samples.

*<p>Bovine miRNA names for the novel miRNAs have been assigned according to miRBase nomenclature rules.</p>**<p>The number of reads aligning the mature miRNA.</p

A network of miRNAs (arrow shapes) that were identified as being differentially expressed in BMEs at 4 hours post-infection with <i>S. uberis</i> and their predicted target genes (circles).

<p>Red arrow shapes represent up-regulated miRNAs at 4 hpi; green down-regulated. Red circles represent target genes that are annotated by <a href="http://www.innatedb.com" target="_blank">www.innatedb.com</a> as having a role in innate immunity. The network was constructed and visualised in Cytoscape v2.8.2. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0057543#pone.0057543-Shannon1" target="_blank">[69]</a>.</p

The proportion of reads aligning uniquely to bovine ncRNAs (averaged across 24 samples).

<p>The vast majority of reads aligned to known miRNAs.</p

Analysis of isomiR heterogeneity across 24 miRNAseq samples.

*<p>Only isomiRs present at >100 reads are shown.</p

Differentially expressed miRNAs at 2 hours post-infection (hpi).

<p>Differentially expressed miRNAs at 2 hours post-infection (hpi).</p

miRNA target predictions by miRanda and TargetScan and their intersect.

<p>miRNA target predictions by miRanda and TargetScan and their intersect.</p

Heatmap of miRNA expression (tpm) across infected and control replicates for each 4 hpi differentially expressed miRNA.

<p>The more red the color the more highly expressed that miRNA is. The heatmap was generated using the R v2.14.1 heatmap package.</p