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L1 retrotransposons can pose a threat to genome integrity. The host has evolved to restrict L1 replication. However, mechanisms underlying L1 propagation out of the host surveillance remains unclear. Here, we propose an evolutionary survival strategy of L1, which exploits RNA m6A modification. We discover that m6A ‘writer’ METTL3 facilitates L1 retrotransposition, whereas m6A ‘eraser’ ALKBH5 suppresses it. The essential m6A cluster that is located on L1 5′ UTR serves as a docking site for eukaryotic initiation factor 3 (eIF3), enhances translational efficiency and promotes the formation of L1 ribonucleoprotein. Furthermore, through the comparative analysis of human- and primate-specific L1 lineages, we find that the most functional m6A motif-containing L1s have been positively selected and became a distinctive feature of evolutionarily young L1s. Thus, our findings demonstrate that L1 retrotransposons hijack the RNA m6A modification system for their successful replication. [ABSTRACT FROM AUTHOR]

Hyper-redundant robots, robots with many degrees of freedom, are considered to be advantageous in many tasks, such as minimally invasive surgery, surveillance and inspection. However, due to their hyper degrees of freedom, the control of hyper-redundant robots is always challenging. Several fitting algorithms, which iteratively fit a hyper-redundant robot into a continuous curve, have been proposed to control the configuration of hyperredundant robots. However, these algorithms require heavy computation, preventing them from being used in practice. In this study, we propose a novel modular control scheme for a hyper-redundant robot to reduce the computational load by dividing the robot into smaller modules and fitting each module separately. A Jacobianbased position control algorithm is also used to utilize the redundancy of each module to ensure that the overall configuration of the robot resembles the given desired curve. Simulation results show that the proposed scheme can be used to control hyper-redundant robots effectively. [ABSTRACT FROM AUTHOR]

The Total Integrated Archive of short-Read and Array (TIARA; http://tiara.gmi.ac.kr) database stores and integrates human genome data generated from multiple technologies including next-generation sequencing and high-resolution comparative genomic hybridization array. The TIARA genome browser is a powerful tool for the analysis of personal genomic information by exploring genomic variants such as SNPs, indels and structural variants simultaneously. As of September 2012, the TIARA database provides raw data and variant information for 13 sequenced whole genomes, 16 sequenced transcriptomes and 33 high resolution array assays. Sequencing reads are available at a depth of ~30× for whole genomes and 50× for transcriptomes. Information on genomic variants includes a total of ~9.56 million SNPs, 23 025 of which are non-synonymous SNPs, and ~1.19 million indels. In this update, by adding high coverage sequencing of additional human individuals, the TIARA genome database now provides an extensive record of rare variants in humans. Following TIARA's fundamentally integrative approach, new transcriptome sequencing data are matched with whole-genome sequencing data in the genome browser. Users can here observe, for example, the expression levels of human genes with allele-specific quantification. Improvements to the TIARA genome browser include the intuitive display of new complex and large-scale data sets. [ABSTRACT FROM AUTHOR]

Background: Cross-platform analysis of gene express data requires multiple, intricate processes at different layers with various platforms. However, existing tools handle only a single platform and are not flexible enough to support custom changes, which arise from the new statistical methods, updated versions of reference data, and better platforms released every month or year. Current tools are so tightly coupled with reference information, such as reference genome, transcriptome database, and SNP, which are often erroneous or outdated, that the output results are incorrect and misleading. Results: We developed AnyExpress, a software package that combines cross-platform gene expression data using a fast interval-matching algorithm. Supported platforms include next-generation-sequencing technology, microarray, SAGE, MPSS, and more. Users can define custom target transcriptome database references for probe/read mapping in any species, as well as criteria to remove undesirable probes/reads. AnyExpress offers scalable processing features such as binding, normalization, and summarization that are not present in existing software tools. As a case study, we applied AnyExpress to published Affymetrix microarray and Illumina NGS RNA-Seq data from human kidney and liver. The mean of within-platform correlation coefficient was 0.98 for within-platform samples in kidney and liver, respectively. The mean of cross-platform correlation coefficients was 0.73. These results confirmed those of the original and secondary studies. Applying filtering produced higher agreement between microarray and NGS, according to an agreement index calculated from differentially expressed genes. Conclusion: AnyExpress can combine cross-platform gene expression data, process data from both open- and closed-platforms, select a custom target reference, filter out undesirable probes or reads based on custom-defined biological features, and perform quantile-normalization with a large number of microarray samples. AnyExpress is fast, comprehensive, flexible, and freely available at http://anyexpress.sourceforge.net. [ABSTRACT FROM AUTHOR]

Background: Identifying disease causing genes and understanding their molecular mechanisms are essential to developing effective therapeutics. Thus, several computational methods have been proposed to prioritize candidate disease genes by integrating different data types, including sequence information, biomedical literature, and pathway information. Recently, molecular interaction networks have been incorporated to predict disease genes, but most of those methods do not utilize invaluable disease-specific information available in mRNA expression profiles of patient samples. Results: Through the integration of protein-protein interaction networks and gene expression profiles of acute myeloid leukemia (AML) patients, we identified subnetworks of interacting proteins dysregulated in AML and characterized known mutation genes causally implicated to AML embedded in the subnetworks. The analysis shows that the set of extracted subnetworks is a reservoir rich in AML genes reflecting key leukemogenic processes such as myeloid differentiation. Conclusion: We showed that the integrative approach both utilizing gene expression profiles and molecular networks could identify AML causing genes most of which were not detectable with gene expression analysis alone due to the minor changes in mRNA level. [ABSTRACT FROM AUTHOR]

The article examines admission policy issues related to curriculum development and implementation for the gifted education in science at special high schools in Korea. High school admission policies provided a means to identify and select a population of the scientifically gifted with certain characteristics and gave major directions for curriculum development while university admission policies had significant influences on curriculum implementation in special high schools. The admission policies for science high schools in Korea selected a homogeneous group of high achievers in all subject areas while special high schools for the gifted tended to select a heterogeneous group of the scientifically gifted in various areas of science including physics, chemistry, biology, earth science or information technology. University admission policies seemed to function as a parameter to achieve successful curriculum implementation. [ABSTRACT FROM AUTHOR]

The Ni/AlGaN interfaces in AlGaN/GaN Schottky diodes were investigated to explore the physical origin of postannealing effects in AlGaN/GaN heterostructures using electron beam induced current (EBIC) and current-voltage characteristics. Black spot density in EBIC images of as-deposited Ni/AlGaN/GaN diodes is in the same order of 108 cm-2 as the dislocation density of AlGaN/GaN heterostructures characterized by atomic force microscopy, indicating that recombination sites near Ni/AlGaN interface are related to dislocations. The EBIC images of the annealed diodes showed that the postannealing reduced the electrically active states at the Schottky metal/AlGaN interfaces. The thermal reaction near Ni/AlGaN interface due to the postannealing induced passivation effect, leading to decrease in reverse leakage current density, ideality factor, and saturation current density of the diodes and increase in the Schottky barrier height. We suggest that the postannealing process is an effective way to passivate the AlGaN/GaN heterojunction field effect transistors. [ABSTRACT FROM AUTHOR]