A human 3'UTR clone collection to study post-transcriptional gene regulation

MicroRNA Expression Profiling, Target Identification, and Validation in Chondrocytes

MicroRNAs (miRNAs) are a class of noncoding small RNAs, which play a critical role in various biological processes including musculoskeletal formation and arthritis pathogenesis via regulating target gene expressions, raising the potentially substantial effects on gene expression networks. Over 2000 miRNAs are encoded in the human genome and a single miRNA potentially targets hundreds of genes. To examine the expression and function of miRNAs in chondrocytes and arthritis pathogenesis, we describe the protocols for the current miRNA related experiments including miRNA expression profiling by (1) Next Generation Sequencing and by TaqMan Array system, (2) miRNA target prediction by TargetScan, (3) miRNA target screening by cell-based reporter library assay, and (4) miRNA and its target interaction by HITS-CLIP (high-throughput sequencing of RNAs isolated by cross-linking immunoprecipitation) in cartilage and chondrocyte research.

Regulation of ribosomal protein genes: An ordered anarchy

Ribosomal protein genes are among the most highly expressed genes in most cell types. Their products are generally essential for ribosome synthesis, which is the cornerstone for cell growth and proliferation. Many cellular resources are dedicated to producing ribosomal proteins and thus this process needs to be regulated in ways that carefully balance the supply of nascent ribosomal proteins with the demand for new ribosomes. Ribosomal protein genes have classically been viewed as a uniform interconnected regulon regulated in eukaryotic cells by target of rapamycin and protein kinase A pathway in response to changes in growth conditions and/or cellular status. However, recent literature depicts a more complex picture in which the amount of ribosomal proteins produced varies between genes in response to two overlapping regulatory circuits. The first includes the classical general ribosome‐producing program and the second is a gene‐specific feature responsible for fine‐tuning the amount of ribosomal proteins produced from each individual ribosomal gene. Unlike the general pathway that is mainly controlled at the level of transcription and translation, this specific regulation of ribosomal protein genes is largely achieved through changes in pre‐mRNA splicing efficiency and mRNA stability. By combining general and specific regulation, the cell can coordinate ribosome production, while allowing functional specialization and diversity. Here we review the many ways ribosomal protein genes are regulated, with special focus on the emerging role of posttranscriptional regulatory events in fine‐tuning the expression of ribosomal protein genes and its role in controlling the potential variation in ribosome functions.

This article is categorized under:

Translation > Ribosome Biogenesis

Translation > Ribosome Structure/Function

Translation > Translation Regulation

Combining Results from Distinct MicroRNA Target Prediction Tools Enhances the Performance of Analyses

Target prediction is generally the first step toward recognition of bona fide microRNA (miRNA)-target interactions in living cells. Several target prediction tools are now available, which use distinct criteria and stringency to provide the best set of candidate targets for a single miRNA or a subset of miRNAs. However, there are many false-negative predictions, and consensus about the optimum strategy to select and use the output information provided by the target prediction tools is lacking. We compared the performance of four tools cited in literature—TargetScan (TS), miRanda-mirSVR (MR), Pita, and RNA22 (R22), and we determined the most effective approach for analyzing target prediction data (individual, union, or intersection). For this purpose, we calculated the sensitivity, specificity, precision, and correlation of these approaches using 10 miRNAs (miR-1-3p, miR-17-5p, miR-21-5p, miR-24-3p, miR-29a-3p, miR-34a-5p, miR-124-3p, miR-125b-5p, miR-145-5p, and miR-155-5p) and 1,400 genes (700 validated and 700 non-validated) as targets of these miRNAs. The four tools provided a subset of high-quality predictions and returned few false-positive predictions; however, they could not identify several known true targets. We demonstrate that union of TS/MR and TS/MR/R22 enhanced the quality of in silico prediction analysis of miRNA targets. We conclude that the union rather than the intersection of the aforementioned tools is the best strategy for maximizing performance while minimizing the loss of time and resources in subsequent in vivo and in vitro experiments for functional validation of miRNA-target interactions.

Identification of targets of tumor suppressor microRNA-34a using a reporter library system

miRNAs play critical roles in various biological processes by targeting specific mRNAs. Current approaches to identifying miRNA targets are insufficient for elucidation of a miRNA regulatory network. Here, we created a cell-based screening system using a luciferase reporter library composed of 4,891 full-length cDNAs, each of which was integrated into the 3' UTR of a luciferase gene. Using this reporter library system, we conducted a screening for targets of miR-34a, a tumor-suppressor miRNA. We identified both previously characterized and previously uncharacterized targets. miR-34a overexpression in MDA-MB-231 breast cancer cells repressed the expression of these previously unrecognized targets. Among these targets, GFRA3 is crucial for MDA-MB-231 cell growth, and its expression correlated with the overall survival of patients with breast cancer. Furthermore, GFRA3 was found to be directly regulated by miR-34a via its coding region. These data show that this system is useful for elucidating miRNA functions and networks.

Evolutionary patterns of metazoan microRNAs reveal targeting principles in the let-7 and miR-10 families

MicroRNAs (miRNAs) regulate gene output by targeting degenerate elements in mRNAs and have undergone drastic expansions in higher metazoan genomes. The evolutionary advantage of maintaining copies of highly similar miRNAs is not well understood, nor is it clear what unique functions, if any, miRNA family members possess. Here, we study evolutionary patterns of metazoan miRNAs, focusing on the targeting preferences of the let-7 and miR-10 families. These studies reveal hotspots for sequence evolution with implications for targeting and secondary structure. High-throughput screening for functional targets reveals that each miRNA represses sites with distinct features and regulates a large number of genes with cooperative function in regulatory networks. Unexpectedly, given the high degree of similarity, single-nucleotide changes grant miRNA family members with distinct targeting preferences. Together, our data suggest complex functional relationships among miRNA duplications, novel expression patterns, sequence change, and the acquisition of new targets.