Lack of Conserved miRNA Deregulation in HPV-Induced Squamous Cell Carcinomas

Squamous cell carcinomas (SCCs) in the anogenital and head and neck regions are associated with high-risk types of human papillomaviruses (HR-HPV). Deregulation of miRNA expression is an important contributor to carcinogenesis. This study aimed to pinpoint commonly and uniquely deregulated miRNAs in cervical, anal, vulvar, and tonsillar tumors of viral or non-viral etiology, searching for a common set of deregulated miRNAs linked to HPV-induced carcinogenesis. RNA was extracted from tumors and nonmalignant tissues from the same locations. The miRNA expression level was determined by next-generation sequencing. Differential expression of miRNAs was calculated, and the patterns of miRNA deregulation were compared between tumors. The total of deregulated miRNAs varied between tumors of different locations by two orders of magnitude, ranging from 1 to 282. The deregulated miRNA pool was largely tumor-specific. In tumors of the same location, a low proportion of miRNAs were exclusively deregulated and no deregulated miRNA was shared by all four types of HPV-positive tumors. The most significant overlap of deregulated miRNAs was found between tumors which differed in location and HPV status (HPV-positive cervical tumors vs. HPV-negative vulvar tumors). Our results imply that HPV infection does not elicit a conserved miRNA deregulation in SCCs.

Deciphering the miRNA transcriptome of breast muscle from the embryonic to post-hatching periods in chickens

Background miRNAs play critical roles in growth and development. Various studies of chicken muscle development have focused on identifying miRNAs that are important for embryo or adult muscle development. However, little is known about the role of miRNAs in the whole muscle development process from embryonic to post-hatching periods. Here, we present a comprehensive investigation of miRNA transcriptomes at 12-day embryo (E12), E17, and day 1 (D1), D14, D56 and D98 post-hatching stages. Results We identified 337 differentially expressed miRNAs (DE-miRNAs) during muscle development. A Short Time-Series Expression Miner analysis identified two significantly different expression profiles. Profile 4 with downregulated pattern contained 106 DE-miRNAs, while profile 21 with upregulated pattern contained 44 DE-miRNAs. The DE-miRNAs with the upregulated pattern mainly played regulatory roles in cellular turnover, such as pyrimidine metabolism, DNA replication, and cell cycle, whereas DE-miRNAs with the downregulated pattern directly or indirectly contributed to protein turnover metabolism such as glycolysis/gluconeogenesis, pyruvate metabolism and biosynthesis of amino acids. Conclusions The main functional miRNAs during chicken muscle development differ between embryonic and post-hatching stages. miRNAs with an upregulated pattern were mainly involved in cellular turnover, while miRNAs with a downregulated pattern mainly played a regulatory role in protein turnover metabolism. These findings enrich information about the regulatory mechanisms involved in muscle development at the miRNA expression level, and provide several candidates for future studies concerning miRNA-target function in regulation of chicken muscle development.

Identification of miRNA-eQTLs in maize mature leaf by GWAS

Background MiRNAs play essential roles in plant development and response to biotic and abiotic stresses through interaction with their target genes. The expression level of miRNAs shows great variations among different plant accessions, developmental stages, and tissues. Little is known about the content within the plant genome contributing to the variations in plants. This study aims to identify miRNA expression-related quantitative trait loci (miR-QTLs) in the maize genome. Results The miRNA expression level from next generation sequencing (NGS) small RNA libraries derived from mature leaf samples of the maize panel (200 maize lines) was estimated as phenotypes, and maize Hapmap v3.2.1 was chosen as the genotype for the genome-wide association study (GWAS). A total of four significant miR-eQTLs were identified contributing to miR156k-5p, miR159a-3p, miR390a-5p and miR396e-5p, and all of them are trans-eQTLs. In addition, a strong positive coexpression of miRNA was found among five miRNA families. Investigation of the effects of these miRNAs on the expression levels and target genes provided evidence that miRNAs control the expression of their targets by suppression and enhancement. Conclusions These identified significant miR-eQTLs contribute to the diversity of miRNA expression in the maize penal at the developmental stages of mature leaves in maize, and the positive and negative regulation between miRNA and its target genes has also been uncovered.

The Serum Cell-Free microRNA Expression Profile in MCTD, SLE, SSc, and RA Patients

Mixed connective tissue disease (MCTD) is a rare disorder characterized by symptoms that overlap two or more Autoimmune Connective Tissue Diseases (ACTDs). The aim of this study was to determine whether miRNAs participating in the TLRs signaling pathway could serve as biomarkers differentiating MCTD or other ACTD entities from a healthy control group and between groups of patients. Although the selected miRNA expression level was not significantly different between MCTD and control, we observed that miR-126 distinguishes MCTD patients from all other ACTD groups. The expression level of miRNAs was significantly higher in the serum of systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA) patients compared to controls. The miR-145 and -181a levels distinguished RA from other ACDT patients. miR-155 was specific for SLE patients. MiR-132, miR-143, and miR-29a distinguished RA and SLE patients from the systemic sclerosis (SSc) group. Additionally, some clinical parameters were significantly related to the miRNA expression profile in the SLE group. SLE and RA are characterized by a specific serum expression profile of the microRNAs associated with the Toll-like receptors (TLRs) signaling pathway. The analysis showed that their level distinguishes these groups from the control and from other ACTD patients. The present study did not reveal a good biomarker for MCTD patients.

Effects of Fe3O4 Nanoparticle Stress on the Growth and Development of Rocket Eruca sativa

Plants exposed to stress use the variety of gene regulatory mechanisms to achieve cellular homeostasis, including posttranscriptional regulation of gene expression where microRNAs (miRNAs) play a pivotal role. Since various environmental stress factors such as nanoparticles affect crop productivity and quality, the aim of the present study was to evaluate the genotoxicity level and to estimate miRNA expression level and chlorophyll a level in the magnetite (Fe3O4) nanoparticle-stressed rocket (Eruca sativa Mill.) seedlings grown in hydroponics. Rocket seedlings were exposed to 1 mg/L, 2 mg/L, and 4 mg/L Fe3O4 nanoparticles, and after 5 weeks, seed germination rate, root-shoot elongation, genotoxicity, chlorophyll a, and miRNA expression levels were evaluated. The obtained results indicated that 1 mg/L, 2 mg/L, and 4 mg/L concentrations of Fe3O4 nanoparticles induce low genotoxicity and have a positive effect on the growth and development of rocket seedlings and that nanoparticles may improve the ability of plants to stand against environmental stresses.

Genome-Wide Analysis of Human MicroRNA Stability

Increasing studies have shown that microRNA (miRNA) stability plays important roles in physiology. However, the global picture of miRNA stability remains largely unknown. Here, we had analyzed genome-wide miRNA stability across 10 diverse cell types using miRNA arrays. We found that miRNA stability shows high dynamics and diversity both within individual cells and across cell types. Strikingly, we observed a negative correlation between miRNA stability and miRNA expression level, which is different from current findings on other biological molecules such as proteins and mRNAs that show positive and not negative correlations between stability and expression level. This finding indicates that miRNA has a distinct action mode, which we called “rapid production, rapid turnover; slow production, slow turnover.” This mode further suggests that high expression miRNAs normally degrade fast and may endow the cell with special properties that facilitate cellular status-transition. Moreover, we revealed that the stability of miRNAs is affected by cohorts of factors that include miRNA targets, transcription factors, nucleotide content, evolution, associated disease, and environmental factors. Together, our results provided an extensive description of the global landscape, dynamics, and distinct mode of human miRNA stability, which provide help in investigating their functions in physiology and pathophysiology.

Highly Ordered Architecture of MicroRNA Cluster

Although it is known that the placement of genes in a cluster may be critical for proper expression patterns, it remains largely unclear whether the orders of members in an miRNA cluster have biological insights. By investigating the relationship between expression and orders for miRNAs from the oncogenic miR-17-92 cluster, we observed a highly ordered architecture in this cluster. A significant correlation between miRNA expression level and its placement was revealed. More importantly, the placement of these miRNAs is associated with their dysregulation in cancer. Here, we presented the opinion that miRNA clusters are not arranged randomly but show highly ordered architectures, which may have critical roles in physiology and pathology.

A PROBABILISTIC FRAMEWORK TO IMPROVE MICRORNA TARGET PREDICTION BY INCORPORATING PROTEOMICS DATA

Due to the difficulties in identifying microRNA (miRNA) targets experimentally in a high-throughput manner, several computational approaches have been proposed. To this date, most leading algorithms are based on sequence information alone. However, there has been limited overlap between these predictions, implying high false-positive rates, which underlines the limitation of sequence-based approaches. Considering the repressive nature of miRNAs at the mRNA translational level, here we describe a probabilistic model to make predictions by combining sequence complementarity, miRNA expression level, and protein abundance. Our underlying assumption is that, given sequence complementarity between a miRNA and its putative mRNA targets, the miRNA expression level should be high and the protein abundance of the mRNA should be low. Having identified a set of confident predictions, we then built a second probabilistic model to trace back to the mRNA expression of the confident targets to investigate the mechanisms of the miRNA-mediated post-transcriptional regulation. Our results suggest that translational repression (which has no effect on mRNA level), instead of mRNA degradation, is the dominant mechanism in miRNA regulation. This observation explained the previously observed discordant correlation between mRNA expression and protein abundance.