Explore the vast range of titles available.

MicroRNAs are post-transcriptional regulators of gene expression, crucial for neuronal differentiation, survival, and activity. Age-related dysregulation of microRNA biogenesis increases neuronal vulnerability to cellular stress and may contribute to the development and progression of neurodegenerative diseases. All major neurodegenerative disorders are also associated with oxidative stress, which is widely recognized as a potential target for protective therapies. Albeit often considered separately, microRNA networks and oxidative stress are inextricably entwined in neurodegenerative processes. Oxidative stress affects expression levels of multiple microRNAs and, conversely, microRNAs regulate many genes involved in an oxidative stress response. Both oxidative stress and microRNA regulatory networks also influence other processes linked to neurodegeneration, such as mitochondrial dysfunction, deregulation of proteostasis, and increased neuroinflammation, which ultimately lead to neuronal death. Modulating the levels of a relatively small number of microRNAs may therefore alleviate pathological oxidative damage and have neuroprotective activity. Here, we review the role of individual microRNAs in oxidative stress and related pathways in four neurodegenerative conditions: Alzheimer’s (AD), Parkinson’s (PD), Huntington’s (HD) disease, and amyotrophic lateral sclerosis (ALS). We also discuss the problems associated with the use of oversimplified cellular models and highlight perspectives of studying microRNA regulation and oxidative stress in human stem cell-derived neurons.

In addition to regulating growth and development, the most important function of microRNAs (miRNAs) in plants is the regulation of a variety of cellular processes underlying plant adaptation to environmental stresses. To gain a deep understanding of the mechanism of drought tolerance in rice, genome-wide profiling and analysis of miRNAs was carried out in drought-challenged rice across a wide range of developmental stages, from tillering to inflorescence formation, using a microarray platform. Among the 30 miRNAs identified as significantly down- or up-regulated under the drought stress, 11 down-regulated miRNAs (miR170, miR172, miR397, miR408, miR529, miR896, miR1030, miR1035, miR1050, miR1088, and miR1126) and eight up-regulated miRNAs (miR395, miR474, miR845, miR851, miR854, miR901, miR903, and miR1125) were revealed for the first time to be induced by drought stress in plants, and nine (miR156, miR168, miR170, miR171, miR172, miR319, miR396, miR397, and miR408) showed opposite expression to that observed in drought-stressed Arabidopsis. The most conserved down-regulated miRNAs were ath-miR170, the miR171 family, and ath-miR396, and the most conserved up-regulated miRNAs were ptc-miR474 and ath-miR854a. The identification of differentially expressed novel plant miRNAs and their target genes, and the analysis of cis-elements provides molecular evidence for the possible involvement of miRNAs in the process of drought response and/or tolerance in rice.

Exosomes are small vesicles that are secreted from metazoan cells and may convey selected membrane proteins and small RNAs to target cells for the control of cell migration, development and metastasis. To study the mechanisms of RNA packaging into exosomes, we devised a purification scheme based on the membrane marker CD63 to isolate a single exosome species secreted from HEK293T cells. Using immunoisolated CD63-containing exosomes we identified a set of miRNAs that are highly enriched with respect to their cellular levels. To explore the biochemical requirements for exosome biogenesis and RNA packaging, we devised a cell-free reaction that recapitulates the species-selective enclosure of miR-223 in isolated membranes supplemented with cytosol. We found that the RNA-binding protein Y-box protein I (YBX1) binds to and is required for the sorting of miR-223 in the cell-free reaction. Furthermore, YBX1 serves an important role in the secretion of miRNAs in exosomes by HEK293T cells. Human cells release molecules into their surroundings via membrane-bound packets called exosomes. These molecules can then circulate throughout the body and are protected from degradation. Among the cargos carried by exosomes are small molecules of RNA known as microRNAs, which are involved in regulating gene activity. Only a select subset of the hundreds of microRNAs in a human cell end up packaged into exosomes. This suggests that there might be a specific mechanism that sorts those microRNAs that are destined for export. However, few proteins or other factors that might be involved in this sorting process had been identified to date. Shurtleff et al. set out to identify these factors and started by purifying exosomes from human cells grown in the laboratory and looking for microRNAs that were more abundant in the exosomes than the cells. One exosome-specific microRNA, called miR-223, was further studied via a test-tube based system that uses extracts from cells rather than cells themselves. These experiments confirmed that miR-223 is selectively packed into exosomes that formed in the test tube. Using this system, Shurtleff et al. then isolated a protein called Y-box Protein I (or YBX1 for short) that binds to RNA molecules and found that it was required for this selective packaging. YBX1 is known to be a constituent of exosomes released from intact cells and may therefore be required to sort other RNA molecules into exosomes. Future studies will explore how YBX1 recognizes those RNA molecules to be exported from cells via exosomes. Also, because exosomes have been implicated in some diseases such as cancer, it will be important to explore what role exosome-specific microRNAs play in both health and disease.

Victor Ambros and Gary Ruvkun identified a class of tiny molecules that have a crucial role in controlling gene expression. Victor Ambros and Gary Ruvkun identified a class of tiny molecules that have a crucial role in controlling gene expression. Credit: Steve Jennings/Getty for Breakthrough Prize Victor Ambros and Gary Ruvkun onstage during the Breakthrough Prize Awards Ceremony in 2014.

In recent years, accumulating evidences have shown that microRNA (miRNA) plays an important role in the exploration and treatment of diseases, so detection of the associations between miRNA and disease has been drawn more and more attentions. However, traditional experimental methods have the limitations of high cost and time- consuming, a computational method can help us more systematically and effectively predict the potential miRNA-disease associations. In this work, we proposed a novel network embedding-based heterogeneous information integration method to predict miRNA-disease associations. More specifically, a heterogeneous information network is constructed by combining the known associations among lncRNA, drug, protein, disease, and miRNA. After that, the network embedding method Learning Graph Representations with Global Structural Information (GraRep) is employed to learn embeddings of nodes in heterogeneous information network. In this way, the embedding representations of miRNA and disease are integrated with the attribute information of miRNA and disease (e.g. miRNA sequence information and disease semantic similarity) to represent miRNA-disease association pairs. Finally, the Random Forest (RF) classifier is used for predicting potential miRNA-disease associations. Under the 5-fold cross validation, our method obtained 85.11% prediction accuracy with 80.41% sensitivity at the AUC of 91.25%. In addition, in case studies of three major Human diseases, 45 (Colon Neoplasms), 42 (Breast Neoplasms) and 44 (Esophageal Neoplasms) of top-50 predicted miRNAs are respectively verified by other miRNA-disease association databases. In conclusion, the experimental results suggest that our method can be a powerful and useful tool for predicting potential miRNA-disease associations.

MicroRNA (miRNA) expression is dysregulated in many human malignancies, and a growing number of studies are focused on their potential use as tumor biomarkers. To identify a miRNA signature for papillary thyroid carcinomas (PTC), we investigated miRNA expression profiles in two independent cohorts of PTCs, which included major histological subtypes [classical-type (PTC-CT), follicular-variant (PTC-FV), and tall-cell variant (PTC-TCV)] and cases with low or intermediate risk of recurrence. Using TaqMan® Array Human MicroRNA A+B Cards v3.0, we first performed microRNA profiling of normal and neoplastic thyroid tissues from 29 PTC patients. Promising candidates were then investigated in a second, independent cohort of 76 PTCs using Custom TaqMan® Array MicroRNA Cards. We identified a molecular signature of 11 miRNAs that were significantly upregulated (miR-146b-5p, miR-146b-3p, miR-221-3p, miR-222-5p, miR-222-3p) or downregulated (miR-1179, miR-486-5p, miR-204-5p, miR-7-2-3p, miR-144-5p, miR-140-3p) in PTC tissues vs. normal thyroid tissue. Upregulation of miR-146b-5p and miR-222-3p was also significantly associated with an increased risk of recurrence. Higher than normal expression of miR-146b-5p and miR-146b-3p characterized PTC-CT and PTC-TCV but not PTC-FV, whereas miR-21-5p was significantly upregulated only in PTC-TCV. When PTC-FV were subclassified as encapsulated (PTC-EFV) or infiltrative (PTC-IFV), miR-204-5p was downregulated in all histological subtypes except PTC-EFV, which displayed expression levels similar to those of normal thyroid tissues. These findings provide new insights into the molecular classification of PTC, showing that different miRNA expression profiles are associated with different histological types of PTC and different risks of recurrence.

The past decades have witnessed the evolution of electronic and photonic integrated circuits, from application specific to programmable 1 , 2 . Although liquid-phase DNA circuitry holds the potential for massive parallelism in the encoding and execution of algorithms 3 , 4 , the development of general-purpose DNA integrated circuits (DICs) has yet to be explored. Here we demonstrate a DIC system by integration of multilayer DNA-based programmable gate arrays (DPGAs). We find that the use of generic single-stranded oligonucleotides as a uniform transmission signal can reliably integrate large-scale DICs with minimal leakage and high fidelity for general-purpose computing. Reconfiguration of a single DPGA with 24 addressable dual-rail gates can be programmed with wiring instructions to implement over 100 billion distinct circuits. Furthermore, to control the intrinsically random collision of molecules, we designed DNA origami registers to provide the directionality for asynchronous execution of cascaded DPGAs. We exemplify this by a quadratic equation-solving DIC assembled with three layers of cascade DPGAs comprising 30 logic gates with around 500 DNA strands. We further show that integration of a DPGA with an analog-to-digital converter can classify disease-related microRNAs. The ability to integrate large-scale DPGA networks without apparent signal attenuation marks a key step towards general-purpose DNA computing. Generic single-stranded oligonucleotides used as a uniform transmission signal can reliably integrate large-scale DNA integrated circuits with minimal leakage and high fidelity for general-purpose computing.

MicroRNAs are small noncoding RNAs that play an important role in the regulation of various biological processes through their interaction with cellular messenger RNAs. They are frequently dysregulated in cancer and have shown great potential as tissue-based markers for cancer classification and prognostication. microRNAs are also present in extracellular human body fluids such as serum, plasma, saliva, and urine. Most of circulating microRNAs are present in human plasma and serum cofractionate with the Argonaute2 (Ago2) protein. However, circulating microRNAs have been also found in membrane-bound vesicles such as exosomes. Since microRNAs circulate in the bloodstream in a highly stable, extracellular form, they may be used as blood-based biomarkers for cancer and other diseases. A knowledge base of extracellular circulating miRNAs is a fundamental tool for biomedical research. In this work, we present miRandola, a comprehensive manually curated classification of extracellular circulating miRNAs. miRandola is connected to miRò, the miRNA knowledge base, allowing users to infer the potential biological functions of circulating miRNAs and their connections with phenotypes. The miRandola database contains 2132 entries, with 581 unique mature miRNAs and 21 types of samples. miRNAs are classified into four categories, based on their extracellular form: miRNA-Ago2 (173 entries), miRNA-exosome (856 entries), miRNA-HDL (20 entries) and miRNA-circulating (1083 entries). miRandola is available online at: http://atlas.dmi.unict.it/mirandola/index.html.

Broomcorn millet ( Panicum miliaceum L.) is the most water-efficient cereal and one of the earliest domesticated plants. Here we report its high-quality, chromosome-scale genome assembly using a combination of short-read sequencing, single-molecule real-time sequencing, Hi-C, and a high-density genetic map. Phylogenetic analyses reveal two sets of homologous chromosomes that may have merged ~5.6 million years ago, both of which exhibit strong synteny with other grass species. Broomcorn millet contains 55,930 protein-coding genes and 339 microRNA genes. We find Paniceae-specific expansion in several subfamilies of the BTB (broad complex/tramtrack/bric-a-brac) subunit of ubiquitin E3 ligases, suggesting enhanced regulation of protein dynamics may have contributed to the evolution of broomcorn millet. In addition, we identify the coexistence of all three C 4 subtypes of carbon fixation candidate genes. The genome sequence is a valuable resource for breeders and will provide the foundation for studying the exceptional stress tolerance as well as C 4 biology. Broomcorn millet is one of the earliest domesticated plants and has the highest water use efficiency among cereals. Here, the authors report its genome assembly and annotation, which provides a valuable resource for breeders and paves the way for studying plant drought tolerance and C 4 photosynthesis.

MicroRNAs (miRNAs) are small, non-coding RNAs that play essential roles in plant growth, development, and stress response. Populus euphratica is a typical abiotic stress-resistant woody species. This study presents an efficient method for genome-wide discovery of new drought stress responsive miRNAs in P. euphratica. High-throughput sequencing of P. euphratica leaves found 197 conserved miRNAs between P. euphratica and Populus trichocarpa. Meanwhile, 58 new miRNAs belonging to 38 families were identified, an increase in the number of P. euphratica miRNAs. Twenty-six new and 21 conserved miRNA targets were verified by degradome sequencing, and target annotation showed that these targets were involved in multiple biological processes, including transcriptional regulation and response to stimulus. Furthermore, comparison of high-throughput sequencing with miRNA microarray profiling data indicated that 104 miRNA sequences were up-regulated, whereas 27 were down-regulated under drought stress. This preliminary characterization provides a framework for future analysis of miRNA genes and their roles in key poplar traits such as stress resistance, and could be useful for plant breeding and environmental protection