Similarity in targets with REST points to neural and glioblastoma related miRNAs

Detection of features predictive of microRNA targets by integration of network data

Gene activity is controlled by multiple molecular mechanisms, for instance through transcription factors or by microRNAs (miRNAs), among others. Established bioinformatics tools for the prediction of miRNA target genes face the challenge of ensuring accuracy, due to high false positive rates. Further, these tools present poor overlap. However, we demonstrated that it is possible to filter good predictions of miRNA targets from the bulk of all predictions by using information from the gene regulatory network. Here, we take advantage of this strategy that selects a large subset of predicted microRNA binding sites as more likely to possess less false-positives because of their over-representation in RE1 silencing transcription factor (REST)-regulated genes from the background of TargetScanHuman 7.2 predictions to identify useful features for the prediction of microRNA targets. These enriched miRNA families would have silencing activity for neural transcripts overlapping the repressive activity on neural genes of REST. We analyze properties of associated microRNA binding sites and contrast the outcome to the background. We found that the selected subset presents significant differences respect to the background: (i) lower GC-content in the vicinity of the predicted miRNA binding site, (ii) more target genes with multiple identical microRNA binding sites and (iii) a higher density of predicted microRNA binding sites close to the 3’ terminal end of the 3’-UTR. These results suggest that network selection of miRNA-mRNA pairs could provide useful features to improve microRNA target prediction.

MicroRNA-129-5p is regulated by choline availability and controls EGF receptor synthesis and neurogenesis in the cerebral cortex

Choline availability modulates neurogenesis and cerebral cortex development through the regulation of neural progenitor cell (NPC) proliferative and differentiation capacity. In this study, we demonstrated that cortical NPC self-renewal is controlled by choline via the expression of a microRNA (miR-129-5p), whose role in the developing brain has not been examined, and which, in turn, inhibits synthesis of the epidermal growth factor receptor (EGFR) protein. Specifically, we found that low choline (LC) availability led to the upregulation of miR-129-5p expression in cortical NPCs in vitro and in vivo, causing the downregulation of EGFR and thereby disrupting NPC self-renewal and cortical neurogenesis. Furthermore, in response to LC availability, methylation potential (the S-adenosylmethionine: S-adenosylhomocysteine ratio) in the developing brain was reduced. Restoring methylation potential in LC cortical NPCs led to the re-establishment of normal miR-129-5p expression. We concluded that inhibiting miR-129-5p function and restoring EGFR protein levels in vivo is sufficient to reverse LC-induced defects in cortical NPC self-renewal. For the first time, to our knowledge, we have identified the molecular links that explain how a change in the availability of the diet metabolite choline impacts the essential cellular processes underlying brain development.-Trujillo-Gonzalez, I., Wang, Y., Friday, W. B., Vickers, K. C., Toth, C. L., Molina-Torres, L., Surzenko, N., Zeisel, S. H. MicroRNA-129-5p is regulated by choline availability and controls EGF receptor synthesis and neurogenesis in the cerebral cortex.

Modeling Gene Regulation in Liver Hepatocellular Carcinoma with Random Forests

Liver hepatocellular carcinoma (HCC) remains a leading cause of cancer-related death. Poor understanding of the mechanisms underlying HCC prevents early detection and leads to high mortality. We developed a random forest model that incorporates copy-number variation, DNA methylation, transcription factor, and microRNA binding information as features to predict gene expression in HCC. Our model achieved a highly significant correlation between predicted and measured expression of held-out genes. Furthermore, we identified potential regulators of gene expression in HCC. Many of these regulators have been previously found to be associated with cancer and are differentially expressed in HCC. We also evaluated our predicted target sets for these regulators by making comparison with experimental results. Lastly, we found that the transcription factor E2F6, one of the candidate regulators inferred by our model, is predictive of survival rate in HCC. Results of this study will provide directions for future prospective studies in HCC.

Maternal dietary intake of choline in mice regulates development of the cerebral cortex in the offspring

Maternal diets low in choline, an essential nutrient, increase the risk of neural tube defects and lead to low performance on cognitive tests in children. However, the consequences of maternal dietary choline deficiency for the development and structural organization of the cerebral cortex remain unknown. In this study, we fed mouse dams either control (CT) or low-choline (LC) diets and investigated the effects of choline on cortical development in the offspring. As a result of a low choline supply between embryonic day (E)11 and E17 of gestation, the number of 2 types of cortical neural progenitor cells (NPCs)-radial glial cells and intermediate progenitor cells-was reduced in fetal brains (P< 0.01). Furthermore, the number of upper layer cortical neurons was decreased in the offspring of dams fed an LC diet at both E17 (P< 0.001) and 4 mo of age (P< 0.001). These effects of LC maternal diet were mediated by a decrease in epidermal growth factor receptor (EGFR) signaling in NPCs related to the disruption of EGFR posttranscriptional regulation. Our findings describe a novel mechanism whereby low maternal dietary intake of choline alters brain development.-Wang, Y., Surzenko, N., Friday, W. B., Zeisel, S. H. Maternal dietary intake of choline in mice regulates development of the cerebral cortex in the offspring.

mBISON: Finding miRNA target over-representation in gene lists from ChIP-sequencing data

Background

Over-representation of predicted miRNA targets in sets of genes regulated by a given transcription factor (e.g. as defined by ChIP-sequencing experiments) helps to identify biologically relevant miRNA targets and is useful to get insight into post-transcriptional regulation.

Findings

To facilitate the application of this approach we have created the mBISON web-application. mBISON calculates the significance of over-representation of miRNA targets in a given non-ranked gene set. The gene set can be specified either by a list of genes or by one or more ChIP-seq datasets followed by a user-defined peak-gene association procedure. mBISON is based on predictions from TargetScan and uses a randomization step to calculate False-Discovery-Rates for each miRNA, including a correction for gene set specific properties such as 3’UTR length. The tool can be accessed from the following web-resource: http://cbdm.mdc-berlin.de/~mgebhardt/cgi-bin/mbison/home.

Conclusion

mBISON is a web-application that helps to extract functional information about miRNAs from gene lists, which is in contrast to comparable applications easy to use by everyone and can be applied on ChIP-seq data directly.