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Abstract Background Macrophages are immune cells involved in various biological processes including host defence, homeostasis, differentiation, and organogenesis. Disruption of macrophage biology has been linked to increased pathogen infection, inflammation and malignant diseases. Differential gene expression observed in monocytic differentiation is primarily regulated by interacting transcription factors (TFs). Current research suggests that microRNAs (miRNAs) degrade and repress translation of mRNA, but also may target genes involved in differentiation. We focus on getting insights into the transcriptional circuitry regulating miRNA genes expressed during monocytic differentiation. Results We computationally analysed the transcriptional circuitry of miRNA genes during monocytic differentiation using in vitro time-course expression data for TFs and miRNAs. A set of TF→miRNA associations was derived from predicted TF binding sites in promoter regions of miRNA genes. Time-lagged expression correlation analysis was utilised to evaluate the TF→miRNA associations. Our analysis identified 12 TFs that potentially play a central role in regulating miRNAs throughout the differentiation process. Six of these 12 TFs (ATF2, E2F3, HOXA4, NFE2L1, SP3, and YY1) have not previously been described to be important for monocytic differentiation. The remaining six TFs are CEBPB, CREB1, ELK1, NFE2L2, RUNX1, and USF2. For several miRNAs (miR-21, miR-155, miR-424, and miR-17-92), we show how their inferred transcriptional regulation impacts monocytic differentiation. Conclusions The study demonstrates that miRNAs and their transcriptional regulatory control are integral molecular mechanisms during differentiation. Furthermore, it is the first study to decipher on a large-scale, how miRNAs are controlled by TFs during human monocytic differentiation. Subsequently, we have identified 12 candidate key controllers of miRNAs during this differentiation process.

Abstract Background About 5% of western populations are afflicted by autoimmune diseases many of which are affected by sex hormones. Autoimmune diseases are complex and involve many genes. Identifying these disease-associated genes contributes to development of more effective therapies. Also, association studies frequently imply genomic regions that contain disease-associated genes but fall short of pinpointing these genes. The identification of disease-associated genes has always been challenging and to date there is no universal and effective method developed. Results We have developed a method to prioritize disease-associated genes for diseases affected strongly by sex hormones. Our method uses various types of information available for the genes, but no information that directly links genes with the disease. It generates a score for each of the considered genes and ranks genes based on that score. We illustrate our method on early-onset myasthenia gravis (MG) using genes potentially controlled by estrogen and localized in a genomic segment (which contains the MHC and surrounding region) strongly associated with MG. Based on the considered genomic segment 283 genes are ranked for their relevance to MG and responsiveness to estrogen. The top three ranked genes, HLA-G, TAP2 and HLA-DRB1, are implicated in autoimmune diseases, while TAP2 is associated with SNPs characteristic for MG. Within the top 35 prioritized genes our method identifies 90% of the 10 already known MG-associated genes from the considered region without using any information that directly links genes to MG. Among the top eight genes we identified HLA-G and TUBB as new candidates. We show that our ab-initio approach outperforms the other methods for prioritizing disease-associated genes. Conclusion We have developed a method to prioritize disease-associated genes under the potential control of sex hormones. We demonstrate the success of this method by prioritizing the genes localized in the MHC and surrounding region and evaluating the role of these genes as potential candidates for estrogen control as well as MG. We show that our method outperforms the other methods. The method has a potential to be adapted to prioritize genes relevant to other diseases.

The contribution of host genetic and nongenetic factors to immunological differences in humans remains largely undefined. Here, we generated bacterial-, fungal-, and viral-induced immune transcriptional profiles in an age- and sex-balanced cohort of 1,000 healthy individuals and searched for the determinants of immune response variation. We found that age and sex affected the transcriptional response of most immune-related genes, with age effects being more stimulus-specific relative to sex effects, which were largely shared across conditions. Although specific cell populations mediated the effects of age and sex on gene expression, including CD8+ T cells for age and CD4+ T cells and monocytes for sex, we detected a direct effect of these intrinsic factors for the majority of immune genes. The mapping of expression quantitative trait loci (eQTLs) revealed that genetic factors had a stronger effect on immune gene regulation than age and sex, yet they affected a smaller number of genes. Importantly, we identified numerous genetic variants that manifested their regulatory effects exclusively on immune stimulation, including a Candida albicans-specific master regulator at the CR1 locus. These response eQTLs were enriched in disease-associated variants, particularly for autoimmune and inflammatory disorders, indicating that differences in disease risk may result from regulatory variants exerting their effects only in the presence of immune stress. Together, this study quantifies the respective effects of age, sex, genetics, and cellular heterogeneity on the interindividual variability of immune responses and constitutes a valuable resource for further exploration in the context of different infection risks or disease outcomes. [ABSTRACT FROM AUTHOR]

Background: Macrophages are immune cells involved in various biological processes including host defence, homeostasis, differentiation, and organogenesis. Disruption of macrophage biology has been linked to increased pathogen infection, inflammation and malignant diseases. Differential gene expression observed in monocytic differentiation is primarily regulated by interacting transcription factors (TFs). Current research suggests that microRNAs (miRNAs) degrade and repress translation of mRNA, but also may target genes involved in differentiation. We focus on getting insights into the transcriptional circuitry regulating miRNA genes expressed during monocytic differentiation. Results: We computationally analysed the transcriptional circuitry of miRNA genes during monocytic differentiation using in vitro time-course expression data for TFs and miRNAs. A set of TF→miRNA associations was derived from predicted TF binding sites in promoter regions of miRNA genes. Time-lagged expression correlation analysis was utilised to evaluate the TF→miRNA associations. Our analysis identified 12 TFs that potentially play a central role in regulating miRNAs throughout the differentiation process. Six of these 12 TFs (ATF2, E2F3, HOXA4, NFE2L1, SP3, and YY1) have not previously been described to be important for monocytic differentiation. The remaining six TFs are CEBPB, CREB1, ELK1, NFE2L2, RUNX1, and USF2. For several miRNAs (miR-21, miR-155, miR-424, and miR-17-92), we show how their inferred transcriptional regulation impacts monocytic differentiation. Conclusions: The study demonstrates that miRNAs and their transcriptional regulatory control are integral molecular mechanisms during differentiation. Furthermore, it is the first study to decipher on a large-scale, how miRNAs are controlled by TFs during human monocytic differentiation. Subsequently, we have identified 12 candidate key controllers of miRNAs during this differentiation process. [ABSTRACT FROM AUTHOR]