Deep Sequencing Identification of Novel Glucocorticoid-Responsive miRNAs in Apoptotic Primary Lymphocytes

<div><p>Apoptosis of lymphocytes governs the response of the immune system to environmental stress and toxic insult. Signaling through the ubiquitously expressed glucocorticoid receptor, stress-induced glucocorticoid hormones induce apoptosis via mechanisms requiring altered gene expression. Several reports have detailed the changes in gene expression mediating glucocorticoid-induced apoptosis of lymphocytes. However, few studies have examined the role of non-coding miRNAs in this essential physiological process. Previously, using hybridization-based gene expression analysis and deep sequencing of small RNAs, we described the prevalent post-transcriptional repression of annotated miRNAs during glucocorticoid-induced apoptosis of lymphocytes. Here, we describe the development of a customized bioinformatics pipeline that facilitates the deep sequencing-mediated discovery of novel glucocorticoid-responsive miRNAs in apoptotic primary lymphocytes. This analysis identifies the potential presence of over 200 novel glucocorticoid-responsive miRNAs. We have validated the expression of two novel glucocorticoid-responsive miRNAs using small RNA-specific qPCR. Furthermore, through the use of Ingenuity Pathways Analysis (IPA) we determined that the putative targets of these novel validated miRNAs are predicted to regulate cell death processes. These findings identify two and predict the presence of additional novel glucocorticoid-responsive miRNAs in the rat transcriptome, suggesting a potential role for both annotated and novel miRNAs in glucocorticoid-induced apoptosis of lymphocytes.</p> </div

Pathways analysis predicts novel miRNA targets may contribute to glucocorticoid-induced apoptosis.

<div><p>(A) miRNA target predictions for novel miRNA candidates 44 and 166 were performed using the miRanda miRNA target prediction algorithm. The number of target mRNAs differentially expressed during glucocorticoid-induced apoptosis (p < 0.01; fold change > 1.2) is indicated for each candidate. </p> <p>(B) IPA-generated ranking of the top five molecular and cellular functions of genes differentially expressed during glucocorticoid-induced apoptosis (p < 0.01; fold change > 1.2), as well as the predicted targets of both candidates 44 and 166 (p-values for top functions are indicated beneath each ranking). Genes differentially expressed during glucocorticoid-induced apoptosis were identified by whole genome microarray analysis of untreated and 100nM dexamethasone-treated thymocytes (6 hours, 3 biological replicates). </p> <p>(C) Venn diagram analysis identified specific novel candidate predicted targets differentially expressed during glucocorticoid-induced apoptosis (p<.01) and the application IPA to this combined gene list (40 genes) generated a top 5 ranking of molecular and cellular functions regulated by these predicted targets (p-values for top functions are indicated beneath each ranking). </p></div

Development of a customized bioinformatics pipeline for the discovery of novel miRNAs from deep sequencing data.

<div><p>(A) This bioinformatics analysis workflow describes the novel miRNA discovery process adapted from miRanalyzer. The analysis pipeline uses next generation sequencing (miRNA-seq) data from untreated (control) or dexamethasone-treated rat primary thymocytes as input. This pipeline divides reads into three files: reads that align to an annotated mature miRNA (“Positive” training set), reads that align to other RNA subtypes (“Negative” training set), or reads that align at unannotated regions (“Test” set). Reads from each of these files are then aligned and alignment results are methodically processed to generate clusters, precursors and predicted secondary structures. Random forest machine learning is then employed to train the models for the prediction of novel miRNAs in the “Test” dataset. The output provides the genomic coordinates of predicted putative novel miRNAs.</p> <p>(B) Table describes total number of reads generated by miRNA-seq of control and dexamethasone treated primary thymocytes analyzed using the novel bioinformatics workflow described above. As expected, the majority of these reads align to known miRNAs when compared to other RNA subtypes. </p> <p>(C) Table summarizes the total number of known and predicted novel miRNAs identified by the bioinformatics workflow as induced or repressed in control and dexamethasone treated rat primary thymocytes. Both known and predicted novel miRNAs exhibit a trend of repressed expression during glucocorticoid-induced apoptosis.</p></div