Evaluating the Effect of 3′-UTR Variants in DICER1 and DROSHA on Their Tissue-Specific Expression by miRNA Target Prediction

Untranslated gene regions (UTRs) play an important role in controlling gene expression. 3′-UTRs are primarily targeted by microRNA (miRNA) molecules that form complex gene regulatory networks. Cancer genomes are replete with non-coding mutations, many of which are connected to changes in tumor gene expression that accompany the development of cancer and are associated with resistance to therapy. Therefore, variants that occurred in 3′-UTR under cancer progression should be analysed to predict their phenotypic effect on gene expression, e.g., by evaluating their impact on miRNA target sites. Here, we analyze 3′-UTR variants in DICER1 and DROSHA genes in the context of myelodysplastic syndrome (MDS) development. The key features of this analysis include an assessment of both “canonical” and “non-canonical” types of mRNA-miRNA binding and tissue-specific profiling of miRNA interactions with wild-type and mutated genes. As a result, we obtained a list of DICER1 and DROSHA variants likely altering the miRNA sites and, therefore, potentially leading to the observed tissue-specific gene downregulation. All identified variants have low population frequency consistent with their potential association with pathology progression.     

Schizophrenia-associated MicroRNA–Gene Interactions in the Dorsolateral Prefrontal Cortex

Schizophrenia-associated anomalies in gene expression in postmortem brain can be attributed to a combination of genetic and environmental influences. Given the small effect size of common variants, it is likely that we may only see the combined impact of some of these at the pathway level in small postmortem studies. At the gene level, however, there may be more impact from common environmental exposures mediated by influential epigenomic modifiers, such as microRNA (miRNA). We hypothesise that dysregulation of miRNAs and their alteration of gene expression have significant implications in the pathophysiology of schizophrenia. In this study, we integrate changes in cortical gene and miRNA expression to identify regulatory interactions and networks associated with the disorder. Gene expression analysis in post-mortem prefrontal dorsolateral cortex (BA 46) (n = 74 matched pairs of schizophrenia, schizoaffective, and control samples) was integrated with miRNA expression in the same cohort to identify gene–miRNA regulatory networks. A significant gene–miRNA interaction network was identified, including miR-92a, miR-495, and miR-134, which converged with differentially expressed genes in pathways involved in neurodevelopment and oligodendrocyte function. The capacity for miRNA to directly regulate gene expression through respective binding sites in BCL11A, PLP1, and SYT11 was also confirmed to support the biological relevance of this integrated network model. The observations in this study support the hypothesis that miRNA dysregulation is an important factor in the complex pathophysiology of schizophrenia.     

Inferring the perturbed microRNA regulatory networks from gene expression data using a network propagation based method

Background

MicroRNAs (miRNAs) are a class of endogenous small regulatory RNAs. Identifications of the dys-regulated or perturbed miRNAs and their key target genes are important for understanding the regulatory networks associated with the studied cellular processes. Several computational methods have been developed to infer the perturbed miRNA regulatory networks by integrating genome-wide gene expression data and sequence-based miRNA-target predictions. However, most of them only use the expression information of the miRNA direct targets, rarely considering the secondary effects of miRNA perturbation on the global gene regulatory networks.

Results

We proposed a network propagation based method to infer the perturbed miRNAs and their key target genes by integrating gene expressions and global gene regulatory network information. The method used random walk with restart in gene regulatory networks to model the network effects of the miRNA perturbation. Then, it evaluated the significance of the correlation between the network effects of the miRNA perturbation and the gene differential expression levels with a forward searching strategy. Results show that our method outperformed several compared methods in rediscovering the experimentally perturbed miRNAs in cancer cell lines. Then, we applied it on a gene expression dataset of colorectal cancer clinical patient samples and inferred the perturbed miRNA regulatory networks of colorectal cancer, including several known oncogenic or tumor-suppressive miRNAs, such as miR-17, miR-26 and miR-145.

Conclusions

Our network propagation based method takes advantage of the network effect of the miRNA perturbation on its target genes. It is a useful approach to infer the perturbed miRNAs and their key target genes associated with the studied biological processes using gene expression data.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-255) contains supplementary material, which is available to authorized users.     

Identification of the highly accumulated microRNA*s in Arabidopsis (Arabidopsis thaliana) and rice (Oryza sativa)

Plant microRNAs (miRNAs) are crucial for the regulation of gene expression, which is involved in almost all the important biological processes. In the cytoplasm, the miRNA strand is selectively incorporated into a specific Argonaute (AGO)-associated gene silencing complex, while the miRNA* is degraded rapidly. Thus, most miRNA*s were thought to be biologically meaningless. Interestingly, several recent reports in both plants and animals have shaken this notion. Many miRNA*s were demonstrated to possess regulatory roles in gene expression. However, the low accumulation levels of most miRNA*s raise the question whether the activities of this small RNA (sRNA) species are widespread in plants. Here, by using publicly available sRNA high-throughput sequencing data, we found that the accumulation levels of several miRNA*s could be much higher than those of their miRNA partners in certain organs, mutants and/or AGO-associated silencing complexes of both Arabidopsis (Arabidopsis thaliana) and rice (Oryza sativa). Based on target prediction and degradome sequencing data-based validation, some of these highly accumulated miRNA*s were indicated to possess cleavage-based potential regulatory role on certain targets. Besides, some interesting biological interpretations were obtained based on the accumulation patterns of the miRNA*s, the annotations of the target genes, and literature mining. Taken together, the expanded list of the highly accumulated miRNA*s along with their potential target genes discovered in this study further strengthened the current notion that certain members of the miRNA* species are biologically relevant, which needs further inspection.     

MicroRNA-target gene responses to root knot nematode (Meloidogyne incognita) infection in cotton (Gossypium hirsutum L.)

MicroRNAs (miRNAs) are a large class of small regulatory RNA molecules, however no study has been performed to elucidate the role of miRNAs in cotton (Gossypium hirsutum) response to the root knot nematode (RKN, Meloidogyne incognita) infection. We selected 28 miRNAs and 8 miRNA target genes to investigate the miRNA-target gene response to M. incognita infection. Our results show that RKN infection significantly affected the expression of several miRNAs and their targeted genes. After 10 days of RKN infection, expression fold changes on miRNA expressions ranged from down-regulated by 33% to upregulated by 406%; meanwhile the expression levels of miRNA target genes were 45.8% to 231%. Three miRNA-target pairs, miR159-MYB, miR319-TCP4 and miR167-ARF8, showed inverse expression patterns between gene targets and their corresponded miRNAs, suggesting miRNA-mediated gene regulation in cotton roots in response to RKN infection.     

Identification of microRNAs and their corresponding targets involved in the susceptibility interaction of wheat response to Puccinia striiformis f. sp. tritici

MicroRNAs (miRNAs) play very important roles in plant defense responses. However, little is known about their roles in the susceptibility interaction between wheat and Puccinia striiformis f. sp. tritici (Pst). In this study, two miRNA libraries were constructed from the leaves of the cultivar Xingzi 9104 inoculated with the virulent Pst race CYR32 and sterile water, respectively. A total of 1316 miRNA candidates, including 173 known miRNAs that were generated from 98 pre‐miRNAs, were obtained. The remaining 1143 miRNA candidates included 145 conserved and 998 wheat‐specific miRNAs that were generated from 87 and 1088 pre‐miRNAs, respectively. The 173 known and 145 conserved miRNAs were sub‐classified into 63 miRNA families. The target genes of wheat miRNAs were also confirmed using degradome sequencing technology. Most of the annotated target genes were related to signal transduction or energy metabolism. Additionally, we found that miRNAs and their target genes form complicated regulation networks. The expression profiles of miRNAs and their corresponding target genes were further analyzed by quantitative real‐time polymerase chain reaction (qRT‐PCR), and the results indicate that some miRNAs are involved in the compatible wheat‐Pst susceptibility interaction. Importantly, tae‐miR1432 was highly expressed when wheat was challenged with CYR32, and the corresponding target gene, predicted to be a calcium ion‐binding protein, also exhibited upregulated expression but a divergent expression trend. PC‐3P‐7484, a specific wheat miRNA, was highly expressed in the wheat response to Pst infection, while the expression of the corresponding target gene ubiquillin was dramatically downregulated. These data provide the foundation for evaluating the important regulatory roles of miRNAs in wheat‐Pst susceptibility interaction.