SNP analysis reveals an evolutionary acceleration of the human-specific microRNAs

MicroRNAs are one class of important gene regulators at the post-transcriptional level by binding to the 3’UTRs of target mRNAs. It has been reported that human microRNAs are evolutionary conserved and show lower single nucleotide polymorphisms (SNPs) than their flanking regions. However, in this study, we report that the human-specific microRNAs show a higher SNP density than both the conserved microRNAs and other control regions, suggesting rapid evolution and positive selection has occurred in these regions. Furthermore, we observe that the human-specific microRNAs show greater SNPs minor allele frequency and the SNPs in the human-specific microRNAs show fewer effects on the stability of the microRNA secondary structure, indicating that the SNPs in the human-specific microRNAs tend to be less deleterious. Finally, two microRNAs hsa-mir-423 (SNP: rs6505162), hsa-mir-608 (SNP: rs4919510) and 288 target genes that have apparently been under recent positive selection are identified. These findings will improve our understanding of the functions, evolution, and population disease susceptibility of human microRNAs

A Network of Cancer Genes with Co-Occurring and Anti-Co-Occurring Mutations

Certain cancer genes contribute to tumorigenesis in a manner of either co-occurring or mutually exclusive (anti-co-occurring) mutations; however, the global picture of when, where and how these functional interactions occur remains unclear. This study presents a systems biology approach for this purpose. After applying this method to cancer gene mutation data generated from large-scale and whole genome sequencing of cancer samples, a network of cancer genes with co-occurring and anti-co-occurring mutations was constructed. Analysis of this network revealed that genes with co-occurring mutations prefer direct signaling transductions and that the interaction relations among cancer genes in the network are related with their functional similarity. It was also revealed that genes with co-occurring mutations tend to have similar mutation frequencies, whereas genes with anti-co-occurring mutations tend to have different mutation frequencies. Moreover, genes with more exons tend to have more co-occurring mutations with other genes, and genes having lower local coherent network structures tend to have higher mutation frequency. The network showed two complementary modules that have distinct functions and have different roles in tumorigenesis. This study presented a framework for the analysis of cancer genome sequencing outputs. The presented data and uncovered patterns are helpful for understanding the contribution of gene mutations to tumorigenesis and valuable in the identification of key biomarkers and drug targets for cancer

Principles of microRNA regulation of a human cellular signaling network

MicroRNAs (miRNAs) are endogenous 22-nucleotide RNAs, which suppress gene expression by selectively binding to the 3-noncoding region of specific message RNAs through base-pairing. Given the diversity and abundance of miRNA targets, miRNAs appear to functionally interact with various components of many cellular networks. By analyzing the interactions between miRNAs and a human cellular signaling network, we found that miRNAs predominantly target positive regulatory motifs, highly connected scaffolds and most downstream network components such as signaling transcription factors, but less frequently target negative regulatory motifs, common components of basic cellular machines and most upstream network components such as ligands. In addition, when an adaptor has potential to recruit more downstream components, these components are more frequently targeted by miRNAs. This work uncovers the principles of miRNA regulation of signal transduction networks and implies a potential function of miRNAs for facilitating robust transitions of cellular response to extracellular signals and maintaining cellular homeostasis

miR2Gene: pattern discovery of single gene, multiple genes, and pathways by enrichment analysis of their microRNA regulators

<p>Abstract</p> <p>Background</p> <p>In recent years, a number of tools have been developed to explore microRNAs (miRNAs) by analyzing their target genes. However, a reverse problem, that is, inferring patterns of protein-coding genes through their miRNA regulators, has not been explored. As various miRNA annotation data become available, exploring gene patterns by analyzing the prior knowledge of their miRNA regulators is becoming more feasible.</p> <p>Results</p> <p>In this study, we developed a tool, miR2Gene, for this purpose. Various sets of miRNAs, according to prior rules such as function, associated disease, tissue specificity, family, and cluster, were integrated with miR2Gene. For given genes, miR2Gene evaluates the enrichment of the predicted miRNAs that regulate them in each miRNA set. This tool can be used for single genes, multiple genes, and KEGG pathways. For the KEGG pathway, genes with enriched miRNA sets are highlighted according to various rules. We confirmed the usefulness of miR2Gene through case studies.</p> <p>Conclusions</p> <p>miR2Gene represents a novel and useful tool that integrates miRNA knowledge for protein-coding gene analysis. miR2Gene is freely available at <url>http://cmbi.hsc.pku.edu.cn/mir2gene</url>.</p

Esub8: A novel tool to predict protein subcellular localizations in eukaryotic organisms

BACKGROUND: Subcellular localization of a new protein sequence is very important and fruitful for understanding its function. As the number of new genomes has dramatically increased over recent years, a reliable and efficient system to predict protein subcellular location is urgently needed. RESULTS: Esub8 was developed to predict protein subcellular localizations for eukaryotic proteins based on amino acid composition. In this research, the proteins are classified into the following eight groups: chloroplast, cytoplasm, extracellular, Golgi apparatus, lysosome, mitochondria, nucleus and peroxisome. We know subcellular localization is a typical classification problem; consequently, a one-against-one (1-v-1) multi-class support vector machine was introduced to construct the classifier. Unlike previous methods, ours considers the order information of protein sequences by a different method. Our method is tested in three subcellular localization predictions for prokaryotic proteins and four subcellular localization predictions for eukaryotic proteins on Reinhardt's dataset. The results are then compared to several other methods. The total prediction accuracies of two tests are both 100% by a self-consistency test, and are 92.9% and 84.14% by the jackknife test, respectively. Esub8 also provides excellent results: the total prediction accuracies are 100% by a self-consistency test and 87% by the jackknife test. CONCLUSIONS: Our method represents a different approach for predicting protein subcellular localization and achieved a satisfactory result; furthermore, we believe Esub8 will be a useful tool for predicting protein subcellular localizations in eukaryotic organisms

microRNA evolution in a human transcription factor and microRNA regulatory network

<p>Abstract</p> <p>Background</p> <p>microRNAs (miRNAs) are important cellular components. The understanding of their evolution is of critical importance for the understanding of their function. Although some specific evolutionary rules of miRNAs have been revealed, the rules of miRNA evolution in cellular networks remain largely unexplored. According to knowledge from protein-coding genes, the investigations of gene evolution in the context of biological networks often generate valuable observations that cannot be obtained by traditional approaches.</p> <p>Results</p> <p>Here, we conducted the first systems-level analysis of miRNA evolution in a human transcription factor (TF)-miRNA regulatory network that describes the regulatory relations among TFs, miRNAs, and target genes. We found that the architectural structure of the network provides constraints and functional innovations for miRNA evolution and that miRNAs showed different and even opposite evolutionary patterns from TFs and other protein-coding genes. For example, miRNAs preferentially coevolved with their activators but not with their inhibitors. During transcription, rapidly evolving TFs frequently activated but rarely repressed miRNAs. In addition, conserved miRNAs tended to regulate rapidly evolving targets, and upstream miRNAs evolved more rapidly than downstream miRNAs.</p> <p>Conclusions</p> <p>In this study, we performed the first systems level analysis of miRNA evolution. The findings suggest that miRNAs have a unique evolution process and thus may have unique functions and roles in various biological processes and diseases. Additionally, the network presented here is the first TF-miRNA regulatory network, which will be a valuable platform of systems biology.</p

TAM: A method for enrichment and depletion analysis of a microRNA category in a list of microRNAs

<p>Abstract</p> <p>Background</p> <p>MicroRNAs (miRNAs) are a class of important gene regulators. The number of identified miRNAs has been increasing dramatically in recent years. An emerging major challenge is the interpretation of the genome-scale miRNA datasets, including those derived from microarray and deep-sequencing. It is interesting and important to know the common rules or patterns behind a list of miRNAs, (i.e. the deregulated miRNAs resulted from an experiment of miRNA microarray or deep-sequencing).</p> <p>Results</p> <p>For the above purpose, this study presents a method and develops a tool (TAM) for annotations of meaningful human miRNAs categories. We first integrated miRNAs into various meaningful categories according to prior knowledge, such as miRNA family, miRNA cluster, miRNA function, miRNA associated diseases, and tissue specificity. Using TAM, given lists of miRNAs can be rapidly annotated and summarized according to the integrated miRNA categorical data. Moreover, given a list of miRNAs, TAM can be used to predict novel related miRNAs. Finally, we confirmed the usefulness and reliability of TAM by applying it to deregulated miRNAs in acute myocardial infarction (AMI) from two independent experiments.</p> <p>Conclusion</p> <p>TAM can efficiently identify meaningful categories for given miRNAs. In addition, TAM can be used to identify novel miRNA biomarkers. TAM tool, source codes, and miRNA category data are freely available at <url>http://cmbi.bjmu.edu.cn/tam</url>.</p

Heat transfer and pressure drop experimental correlations for air-water bubbly flow

In this paper, a novel air–water bubbly flow heat transfer experiment is performed to investigate the characteristics of pressure drop of airflow and heat transfer between water and tubes for its potential application in evaporative cooling. The attempts to reduce the pressure drop while maintaining higher heat transfer coefficient have been achieved by decreasing the bubble layer thickness through the water pump circulation. Pressure drops of air passing through the sieve plate and the bubbling layer are measured for different height of bubble layer, hole–plate area ratio of the sieve plate and the superficial air velocity. Experimental data show that the increase of bubble layer height and air velocity both increase the pressure drop while the effect of the hole–plate area ratio of the sieve plate on the heat transfer coefficient is relatively sophisticated. A pressure drop correlation including the effects of all the tested parameters is proposed, which has a mean absolute deviation of 14.5% to that of the experimental data. Heat transfer coefficients of the water and the outside tube wall are measured and the effects of superficial air velocity, heat flux and bubble layer height are also examined. Through a dimensional analysis, a heat transfer correlation with a mean absolute deviation of 9.7% is obtained based on experimental data

The acceleration of micro- and nano-particles in supersonic De-Laval-Type nozzle

The particle velocity in cold gas dynamic spraying (CGDS) is one of the most important factors that can determine the properties of the bonding to the substrate. The acceleration of gas to particles is strongly dependent on the densities of particles and the particle size. In this paper, the acceleration process of micro-scale and nano-scale copper (Cu) and platinum (Pt) particles in De-Laval-Type nozzle is investigated. A numerical simulation is performed for the gas-particle two phase flow with particle diameter ranging from 100nm to 50µm, which are accelerated by carrier gas Nitrogen in a supersonic DeLaval-type nozzle. The results show that cone-shape weak shocks (compression waves) occur at the exit of divergent section and the particle density has significant effect on the accele ration of micro-scale particles. At same inlet condition, the velocity of the smaller particles is larger than the larger particles at the exit of the divergent section of the nozzle

Numerical investigations on cold gas dynamic spray process with nano- and microsize particles

The particle velocity in cold gas dynamic spraying (CGDS) is one of the most important factors that can determine the properties of the bonding to the substrate. In this paper, the acceleration process of microscale and sub-microscale copper (Cu) and platinum (Pt) particles inside and outside De-Laval-Type nozzle is investigated. A numerical simulation is performed for the gas-particle two phase flow with particle diameter ranging from 100 nm to 50 lm, which are accelerated by carrier gas nitrogen and helium in a supersonic De-Laval-type nozzle. The carrier gas velocity and pressure distributions in the nozzle and outside the nozzle are illustrated. The centerline velocity for two types of particles, Pt and Cu, are demonstrated. It is observed that the existence of the bow shocks near the substrate prevents the smaller size particles (less than 0.5 lm) from penetrating, thus leads to poor coating in the actual practices. Furthermore, the extended straight section may have different optimal length for different size particles, and even may be unnecessary for sub-microsize particles