Computer Technology in the Biomechanical Analysis of Bar-Bell Lifting Motion Structures

An improper selection of muscle-building exercises or a technically poor execution of an exercise frequently leads to an inadvertent loading of the motion system of man, to injuries, to a poorer resulting achievement, or to a deceleration of the expected performance growth, to a disturbed dynamic stereotype and -last but not least-to motivation losses. In order to be able to cope with the problems outlined above, it was necessary to create a data collection and processing system for speedpower and technical parameters realized on a bar-bell. The information thus obtained allows for assessing a weight-lifter's performance in qualitative and quantitative terms, using a set of pre-defined criteria. Consequently, prerequisites for describing and correcting potential mistakes in an executed exercise, as well as for its optimization and economization, are provided

MachiBase: a Drosophila melanogaster 5′-end mRNA transcription database

MachiBase (http://machibase.gi.k.u-tokyo.ac.jp/) provides a comprehensive and freely accessible resource regarding Drosophila melanogaster 5′-end mRNA transcription at different developmental states, supporting studies on the variabilities of promoter transcriptional activities and gene-expression profiles in the fruitfly. The data were generated in conjunction with the recently developed high-throughput genome sequencer Illumina/Solexa using a newly developed 5′-end mRNA collection method

Functional conservation of the Drosophila hybrid incompatibility gene Lhr

<p>Abstract</p> <p>Background</p> <p>Hybrid incompatibilities such as sterility and lethality are commonly modeled as being caused by interactions between two genes, each of which has diverged separately in one of the hybridizing lineages. The gene <it>Lethal hybrid rescue </it>(<it>Lhr</it>) encodes a rapidly evolving heterochromatin protein that causes lethality of hybrid males in crosses between <it>Drosophila melanogaster </it>females and <it>D. simulans </it>males. Previous genetic analyses showed that hybrid lethality is caused by <it>D. simulans Lhr </it>but not by <it>D. melanogaster Lhr</it>, confirming a critical prediction of asymmetry in the evolution of a hybrid incompatibility gene.</p> <p>Results</p> <p>Here we have examined the functional properties of <it>Lhr </it>orthologs from multiple Drosophila species, including interactions with other heterochromatin proteins, localization to heterochromatin, and ability to complement hybrid rescue in <it>D. melanogaster</it>/<it>D. simulans </it>hybrids. We find that these properties are conserved among most <it>Lhr </it>orthologs, including <it>Lhr </it>from <it>D. melanogaster</it>, <it>D. simulans </it>and the outgroup species <it>D. yakuba</it>.</p> <p>Conclusions</p> <p>We conclude that evolution of the hybrid lethality properties of <it>Lhr </it>between <it>D. melanogaster </it>and <it>D. simulans </it>did not involve extensive loss or gain of functions associated with protein interactions or localization to heterochromatin.</p

Global Identification and Characterization of Transcriptionally Active Regions in the Rice Genome

Genome tiling microarray studies have consistently documented rich transcriptional activity beyond the annotated genes. However, systematic characterization and transcriptional profiling of the putative novel transcripts on the genome scale are still lacking. We report here the identification of 25,352 and 27,744 transcriptionally active regions (TARs) not encoded by annotated exons in the rice (Oryza. sativa) subspecies japonica and indica, respectively. The non-exonic TARs account for approximately two thirds of the total TARs detected by tiling arrays and represent transcripts likely conserved between japonica and indica. Transcription of 21,018 (83%) japonica non-exonic TARs was verified through expression profiling in 10 tissue types using a re-array in which annotated genes and TARs were each represented by five independent probes. Subsequent analyses indicate that about 80% of the japonica TARs that were not assigned to annotated exons can be assigned to various putatively functional or structural elements of the rice genome, including splice variants, uncharacterized portions of incompletely annotated genes, antisense transcripts, duplicated gene fragments, and potential non-coding RNAs. These results provide a systematic characterization of non-exonic transcripts in rice and thus expand the current view of the complexity and dynamics of the rice transcriptome

Non-Coding RNA Prediction and Verification in Saccharomyces cerevisiae

Non-coding RNA (ncRNA) play an important and varied role in cellular function. A significant amount of research has been devoted to computational prediction of these genes from genomic sequence, but the ability to do so has remained elusive due to a lack of apparent genomic features. In this work, thermodynamic stability of ncRNA structural elements, as summarized in a Z-score, is used to predict ncRNA in the yeast Saccharomyces cerevisiae. This analysis was coupled with comparative genomics to search for ncRNA genes on chromosome six of S. cerevisiae and S. bayanus. Sets of positive and negative control genes were evaluated to determine the efficacy of thermodynamic stability for discriminating ncRNA from background sequence. The effect of window sizes and step sizes on the sensitivity of ncRNA identification was also explored. Non-coding RNA gene candidates, common to both S. cerevisiae and S. bayanus, were verified using northern blot analysis, rapid amplification of cDNA ends (RACE), and publicly available cDNA library data. Four ncRNA transcripts are well supported by experimental data (RUF10, RUF11, RUF12, RUF13), while one additional putative ncRNA transcript is well supported but the data are not entirely conclusive. Six candidates appear to be structural elements in 5′ or 3′ untranslated regions of annotated protein-coding genes. This work shows that thermodynamic stability, coupled with comparative genomics, can be used to predict ncRNA with significant structural elements

Automatic Annotation of Spatial Expression Patterns via Sparse Bayesian Factor Models

Advances in reporters for gene expression have made it possible to document and quantify expression patterns in 2D–4D. In contrast to microarrays, which provide data for many genes but averaged and/or at low resolution, images reveal the high spatial dynamics of gene expression. Developing computational methods to compare, annotate, and model gene expression based on images is imperative, considering that available data are rapidly increasing. We have developed a sparse Bayesian factor analysis model in which the observed expression diversity of among a large set of high-dimensional images is modeled by a small number of hidden common factors. We apply this approach on embryonic expression patterns from a Drosophila RNA in situ image database, and show that the automatically inferred factors provide for a meaningful decomposition and represent common co-regulation or biological functions. The low-dimensional set of factor mixing weights is further used as features by a classifier to annotate expression patterns with functional categories. On human-curated annotations, our sparse approach reaches similar or better classification of expression patterns at different developmental stages, when compared to other automatic image annotation methods using thousands of hard-to-interpret features. Our study therefore outlines a general framework for large microscopy data sets, in which both the generative model itself, as well as its application for analysis tasks such as automated annotation, can provide insight into biological questions

GAMETOPHYTE DEFECTIVE 1, a Putative Subunit of RNases P/MRP, Is Essential for Female Gametogenesis and Male Competence in Arabidopsis

RNA biogenesis, including biosynthesis and maturation of rRNA, tRNA and mRNA, is a fundamental process that is critical for cell growth, division and differentiation. Previous studies showed that mutations in components involved in RNA biogenesis resulted in abnormalities in gametophyte and leaf development in Arabidopsis. In eukaryotes, RNases P/MRP (RNase mitochondrial RNA processing) are important ribonucleases that are responsible for processing of tRNA, and transcription of small non-coding RNAs. Here we report that Gametophyte Defective 1 (GAF1), a gene encoding a predicted protein subunit of RNases P/MRP, AtRPP30, plays a role in female gametophyte development and male competence. Embryo sacs were arrested at stages ranging from FG1 to FG7 in gaf1 mutant, suggesting that the progression of the gametophytic division during female gametogenesis was impaired in gaf1 mutant. In contrast, pollen development was not affected in gaf1. However, the fitness of the mutant pollen tube was weaker than that of the wild-type, leading to reduced transmission through the male gametes. GAF1 is featured as a typical RPP30 domain protein and interacts physically with AtPOP5, a homologue of RNases P/MRP subunit POP5 of yeast. Together, our data suggest that components of the RNases P/MRP family, such as RPP30, play important roles in gametophyte development and function in plants

Semi-supervised learning for the identification of syn-expressed genes from fused microarray and in situ image data

Background: Gene expression measurements during the development of the fly Drosophila melanogaster are routinely used to find functional modules of temporally co-expressed genes. Complimentary large data sets of in situ RNA hybridization images for different stages of the fly embryo elucidate the spatial expression patterns. Results: Using a semi-supervised approach, constrained clustering with mixture models, we can find clusters of genes exhibiting spatio-temporal similarities in expression, or syn-expression. The temporal gene expression measurements are taken as primary data for which pairwise constraints are computed in an automated fashion from raw in situ images without the need for manual annotation. We investigate the influence of these pairwise constraints in the clustering and discuss the biological relevance of our results. Conclusion: Spatial information contributes to a detailed, biological meaningful analysis of temporal gene expression data. Semi-supervised learning provides a flexible, robust and efficient framework for integrating data sources of differing quality and abundance

MNS1 Is Essential for Spermiogenesis and Motile Ciliary Functions in Mice

During spermiogenesis, haploid round spermatids undergo dramatic cell differentiation and morphogenesis to give rise to mature spermatozoa for fertilization, including nuclear elongation, chromatin remodeling, acrosome formation, and development of flagella. The molecular mechanisms underlining these fundamental processes remain poorly understood. Here, we report that MNS1, a coiled-coil protein of unknown function, is essential for spermiogenesis. We find that MNS1 is expressed in the germ cells in the testes and localizes to sperm flagella in a detergent-resistant manner, indicating that it is an integral component of flagella. MNS1–deficient males are sterile, as they exhibit a sharp reduction in sperm production and the remnant sperm are immotile with abnormal short tails. In MNS1–deficient sperm flagella, the characteristic arrangement of “9+2” microtubules and outer dense fibers are completely disrupted. In addition, MNS1–deficient mice display situs inversus and hydrocephalus. MNS1–deficient tracheal motile cilia lack some outer dynein arms in the axoneme. Moreover, MNS1 monomers interact with each other and are able to form polymers in cultured somatic cells. These results demonstrate that MNS1 is essential for spermiogenesis, the assembly of sperm flagella, and motile ciliary functions

Identification of unannotated exons of low abundance transcripts in Drosophila melanogaster and cloning of a new serine protease gene upregulated upon injury

<p>Abstract</p> <p>Background</p> <p>The sequencing of the <it>D.melanogaster </it>genome revealed an unexpected small number of genes (~ 14,000) indicating that mechanisms acting on generation of transcript diversity must have played a major role in the evolution of complex metazoans. Among the most extensively used mechanisms that accounts for this diversity is alternative splicing. It is estimated that over 40% of <it>Drosophila </it>protein-coding genes contain one or more alternative exons. A recent transcription map of the <it>Drosophila </it>embryogenesis indicates that 30% of the transcribed regions are unannotated, and that 1/3 of this is estimated as missed or alternative exons of previously characterized protein-coding genes. Therefore, the identification of the variety of expressed transcripts depends on experimental data for its final validation and is continuously being performed using different approaches. We applied the Open Reading Frame Expressed Sequence Tags (ORESTES) methodology, which is capable of generating cDNA data from the central portion of rare transcripts, in order to investigate the presence of hitherto unnanotated regions of <it>Drosophila </it>transcriptome.</p> <p>Results</p> <p>Bioinformatic analysis of 1,303 <it>Drosophila </it>ORESTES clusters identified 68 sequences derived from unannotated regions in the current <it>Drosophila </it>genome version (4.3). Of these, a set of 38 was analysed by polyA⁺northern blot hybridization, validating 17 (50%) new exons of low abundance transcripts. For one of these ESTs, we obtained the cDNA encompassing the complete coding sequence of a new serine protease, named SP212. The <it>SP212 </it>gene is part of a serine protease gene cluster located in the chromosome region 88A12-B1. This cluster includes the predicted genes CG9631, CG9649 and CG31326, which were previously identified as up-regulated after immune challenges in genomic-scale microarray analysis. In agreement with the proposal that this <it>locus </it>is co-regulated in response to microorganisms infection, we show here that SP212 is also up-regulated upon injury.</p> <p>Conclusion</p> <p>Using the ORESTES methodology we identified 17 novel exons from low abundance <it>Drosophila </it>transcripts, and through a PCR approach the complete CDS of one of these transcripts was defined. Our results show that the computational identification and manual inspection are not sufficient to annotate a genome in the absence of experimentally derived data.</p