Introduction:

The following is a write-up for the RNA-Seq training Mini-Project. The RNA-Seq data used in this project is from the SRA study ‘ERP010786’. In this study, the transcriptome analyzed is between human epithelial cells following infection from Listeria monocytogenes. RNA-sequencing was performed on three replicates of uninfected ‘control’ samples and three replicates of treated samples.
The dataset can be found here: (https://www.ncbi.nlm.nih.gov/Traces/study/?acc=ERP010786&o=acc_s%3Aa).

Data Processing:

The dataset was loaded from the recount2 repository. Differential gene expression was calculated using the DESeq2 R package. To visually assess the differences in samples, a PCA plot was generated along with a hierarchical heatmap(below).

The segregation of the control and treated samples is evident not only in the PCA plot, but also in the hierarchical heatmap. The clear separation of the red and blue colors in the heatmap show how the control and treated samples cluster in their correlation. There appears to be biological differences between the two sample conditions.

MA Plot:

An MA plot was generated from the differential gene analysis and indicates there are many significant differentially expressed genes.

Volcano plot:

The volcano plot below shows a significant number of over and under differentially expressed genes. The Log^10P threshold was set at 1e-75, and the Log^2foldchange threshold was set at +/- 2.

Heatmap of Top 20 Differentially Expressed Genes:

In the heatmap displaying the top 20 DEGs, it is again clear the divergence of expression levels between the two sample conditions

GSEA:

Next a gene set enrichment analysis (GSEA) was carried out using the ranking metric of -log10(padj) * sign(log2FoldChange (-log10(FDR)*sign(log2FoldChange), and the gene sets were annotated using the ontology gene set from the molecular signatures database (MsigDB). The top 6 pathways that were up-regulated and down-regulated are plotted below.

Top Over-Expressed Pathways:

Top Under-Expressed Pathways:

Interestingly, the pathways that were up-regulated involved interferon-gamma (IFN-y) which is a macrophage-stimulating cytokine that is released in response to viral or bacterial infections. Pathways involved in viral defense are also activated further assisting in the cell’s response to the infection. The pathways that are under-expressed were those involved with protein trafficking, cell cycle and translation.

Conclusion:

Taking this analysis altogether, there is evidence of a strong divergence in differential expression of the genes between the control and treated cohorts of the study. The cells activate immune response pathways when infected with Listeria monocytogenes. Future experiments could examine how the cells respond over the course of time. The samples could undergo RNA Sequencing at progressing time points to provide insight into which pathways are up- or down-regulated over time.