962 resultados para gene locus
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Sequencing of mba gene fragments of reference strains of Ureaplasma urealyticum serovars 1, 3, 6, 14, in addition to 33 clinical U. urealyticum isolates is reported. A phylogenetic tree deduced from an alignment of these sequences clearly demonstrates two major clusters (confidence limit 100%), which equate to the parvo and T960 biovars, and five types which we have designated mba 1, 3, 6, 8 and X. These relationships are supported by bootstrap analysis. Polymorphisms within the mba fragment of types mba 1, 3, and 6 were used to define nine subtypes (mba 1a, 1b, 3a, 3b, 3c, 3d, 3e, 6a, and 6b) thus facilitating high resolution typing of U. urealyticum. Inclusion of the reference strains for serovars 1, 3, 6, and 8 in the mba typing scheme showed that the results of this analysis are broadly consistent with currently accepted serotyping. In addition a ure gene fragment from nine of the clinical isolates was amplified and sequenced. Comparisons of the sequences clearly distinguished the two biovars of U. urealyticum; however this fragment was invariant within the parvo biovar. This study has shown that the sequence of the mba can reveal the fine details of the relationships between U. urealyticum isolates and also supports the significant evolutionary gap between the two biovars.
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Background Accumulated biological research outcomes show that biological functions do not depend on individual genes, but on complex gene networks. Microarray data are widely used to cluster genes according to their expression levels across experimental conditions. However, functionally related genes generally do not show coherent expression across all conditions since any given cellular process is active only under a subset of conditions. Biclustering finds gene clusters that have similar expression levels across a subset of conditions. This paper proposes a seed-based algorithm that identifies coherent genes in an exhaustive, but efficient manner. Methods In order to find the biclusters in a gene expression dataset, we exhaustively select combinations of genes and conditions as seeds to create candidate bicluster tables. The tables have two columns: (a) a gene set, and (b) the conditions on which the gene set have dissimilar expression levels to the seed. First, the genes with less than the maximum number of dissimilar conditions are identified and a table of these genes is created. Second, the rows that have the same dissimilar conditions are grouped together. Third, the table is sorted in ascending order based on the number of dissimilar conditions. Finally, beginning with the first row of the table, a test is run repeatedly to determine whether the cardinality of the gene set in the row is greater than the minimum threshold number of genes in a bicluster. If so, a bicluster is outputted and the corresponding row is removed from the table. Repeating this process, all biclusters in the table are systematically identified until the table becomes empty. Conclusions This paper presents a novel biclustering algorithm for the identification of additive biclusters. Since it involves exhaustively testing combinations of genes and conditions, the additive biclusters can be found more readily.
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The human kallikrein-related peptidases are a subgroup of trypsin and chymotrypsin-like serine peptidases that are characterized by their homology to tissue kallikrein or kallikrein 1 (KLK1) encoded by the KLK1 gene (reviewed in[1-4]). The human KLK locus spans an approximately 320 kb region on chromosome 19q13.3-13.4 and contains fifteen genes encoding KLK1 and fourteen other kallikrein-related peptidases, KLK2-KLK15, which have been named contiguously in the locus in the order of their discovery [5-8] (Figure 606.1). It is the largest contiguous cluster of serine protease encoding genes in the human genome which has evolved from gene duplication of KLK1 and then subsequent reduplication of the newly evolved KLK genes [2]. The high conservation noted for KLK1-KLK3 (62-77%) reflects the proposed duplication of the KLK1 gene that produced the KLK2 gene which further generated the KLK3 gene. In contrast, the newer KLK4-KLK15 proteases share much less similarity, from 24-66%, although strong homology between KLK4 and KLK5, KLK9 and KLK11, and KLK10 and KLK12 suggests these genes are duplications of each other [2]...
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Wing length is a key character for essential behaviours related to bird flight such as migration and foraging. In the present study, we initiate the search for the genes underlying wing length in birds by studying a long-distance migrant, the great reed warbler (Acrocephalus arundinaceus). In this species wing length is an evolutionary interesting trait with pronounced latitudinal gradient and sex-specific selection regimes in local populations. We performed a quantitative trait locus (QTL) scan for wing length in great reed warblers using phenotypic, genotypic, pedigree and linkage map data from our long-term study population in Sweden. We applied the linkage analysis mapping method implemented in GRIDQTL (a new web-based software) and detected a genome-wide significant QTL for wing length on chromosome 2, to our knowledge, the first detected QTL in wild birds. The QTL extended over 25 cM and accounted for a substantial part (37%) of the phenotypic variance of the trait. A genome scan for tarsus length (a bodysize-related trait) did not show any signal, implying that the wing-length QTL on chromosome 2 was not associated with body size. Our results provide a first important step into understanding the genetic architecture of avian wing length, and give opportunities to study the evolutionary dynamics of wing length at the locus level. This journal is© 2010 The Royal Society.
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Historical information can be used, in addition to pedigree, traits and genotypes, to map quantitative trait locus (QTL) in general populations via maximum likelihood estimation of variance components. This analysis is known as linkage disequilibrium (LD) and linkage mapping, because it exploits both linkage in families and LD at the population level. The search for QTL in the wild population of Soay sheep on St. Kilda is a proof of principle. We analysed the data from a previous study and confirmed some of the QTLs reported. The most striking result was the confirmation of a QTL affecting birth weight that had been reported using association tests but not when using linkage-based analyses. Copyright © Cambridge University Press 2010.
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Motivation: Unravelling the genetic architecture of complex traits requires large amounts of data, sophisticated models and large computational resources. The lack of user-friendly software incorporating all these requisites is delaying progress in the analysis of complex traits. Methods: Linkage disequilibrium and linkage analysis (LDLA) is a high-resolution gene mapping approach based on sophisticated mixed linear models, applicable to any population structure. LDLA can use population history information in addition to pedigree and molecular markers to decompose traits into genetic components. Analyses are distributed in parallel over a large public grid of computers in the UK. Results: We have proven the performance of LDLA with analyses of simulated data. There are real gains in statistical power to detect quantitative trait loci when using historical information compared with traditional linkage analysis. Moreover, the use of a grid of computers significantly increases computational speed, hence allowing analyses that would have been prohibitive on a single computer. © The Author 2009. Published by Oxford University Press. All rights reserved.
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The power of testing for a population-wide association between a biallelic quantitative trait locus and a linked biallelic marker locus is predicted both empirically and deterministically for several tests. The tests were based on the analysis of variance (ANOVA) and on a number of transmission disequilibrium tests (TDT). Deterministic power predictions made use of family information, and were functions of population parameters including linkage disequilibrium, allele frequencies, and recombination rate. Deterministic power predictions were very close to the empirical power from simulations in all scenarios considered in this study. The different TDTs had very similar power, intermediate between one-way and nested ANOVAs. One-way ANOVA was the only test that was not robust against spurious disequilibrium. Our general framework for predicting power deterministically can be used to predict power in other association tests. Deterministic power calculations are a powerful tool for researchers to plan and evaluate experiments and obviate the need for elaborate simulation studies.
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Research Question: What relationships exist between general self efficacy, locus of control and the nursing practice environment and caring efficacy and job satisfaction? Background: Important characteristics of current nursing practice include nurses having the ability to develop and continue therapeutic relationships with patients, nurses having autonomy and control over the practice environment and nurses having more involvement in decision making. In addition, employee satisfaction is enhanced when organisations offer access to authority. Despite this, nurses continue to complain of feeling powerless in their ability to make decisions. Sample: The study population and criteria for selection included Registered Nurses in Australia who were at the time members of an Australian professional and industrial organisation. Methods: A cross-sectional survey was undertaken. Data analysis was conducted using descriptive and bivariate statistics, and structural equation modeling. Results: The model fit the data well (χ² = 2.3594, χ²/df = 2.3594 and CFI = 0.9987). Twenty four percent of variation in caring efficacy (CE) can be accounted for by general self-efficacy (GSE); work locus of control (WLC) and practice environment (PE) and 62% of the variation in job satisfaction (JS) can be accounted for by GSE, WLC and PE. All pathways were found to be significant except PE to CE. GSE positively explained CE (β = 0.38). WLC was negatively related to CE i.e., as CE scores increased WLC scores decreased (β = -0.23). Further testing of the model found CE was positively related to GSE (βZ = 0.38, p < 0.001) and negatively related to WLC (βZ = - 0.23, p = 0.001). PE was not significantly associated with CE (βZ = - 0.01, p = 0.85). JS was explained by PE, which was positively related (βZ = 0.69, p = < 0.001); GSE which was negatively related (βZ - 0 .09, p < 0.001) and WLC, which was also negatively related (βZ = - 0.20, p < 0.001). Implications for Practice Nursing and organisational leaders should ensure the development of strategies for professional development and orientation programmes which may enhance nurses’ ability to develop caring relationships and express caring behaviours to their patients and as a result improve organisational and patient outcomes. Nursing shortages and turnover rates are associated with job satisfaction and the nursing practice environment. Improving the nursing environment can produce benefits to the health system such as better job satisfaction, improved workforce retention and better patient outcomes.
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The sheep (Ovis aries) is commonly used as a large animal model in skeletal research. Although the sheep genome has been sequenced there are still only a limited number of annotated mRNA sequences in public databases. A complementary DNA (cDNA) library was constructed to provide a generic resource for further exploration of genes that are actively expressed in bone cells in sheep. It was anticipated that the cDNA library would provide molecular tools for further research into the process of fracture repair and bone homeostasis, and add to the existing body of knowledge. One of the hallmarks of cDNA libraries has been the identification of novel genes and in this library the full open reading frame of the gene C12orf29 was cloned and characterised. This gene codes for a protein of unknown function with a molecular weight of 37 kDa. A literature search showed that no previous studies had been conducted into the biological role of C12orf29, except for some bioinformatics studies that suggested a possible link with cancer. Phylogenetic analyses revealed that C12orf29 had an ancient pedigree with a homologous gene found in some bacterial taxa. This implied that the gene was present in the last common eukaryotic ancestor, thought to have existed more than 2 billion years ago. This notion was further supported by the fact that the gene is found in taxa belonging to the two major eukaryotic branches, bikonts and unikonts. In the bikont supergroup a C12orf29-like gene was found in the single celled protist Naegleria gruberi, whereas in the unikont supergroup, encompassing the metazoa, the gene is universal to all chordate and, therefore, vertebrate species. It appears to have been lost to the majority of cnidaria and protostomes taxa; however, C12orf29-like genes have been found in the cnidarian freshwater hydra and the protostome Pacific oyster. The experimental data indicate that C12orf29 has a structural role in skeletal development and tissue homeostasis, whereas in silico analysis of the human C12orf29 promoter region suggests that its expression is potentially under the control of the NOTCH, WNT and TGF- developmental pathways, as well SOX9 and BAPX1; pathways that are all heavily involved in skeletogenesis. Taken together, this investigation provides strong evidence that C12orf29 has a very important role in the chordate body plan, in early skeletal development, cartilage homeostasis, and also a possible link with spina bifida in humans.
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Currently, mass spectrometry-based metabolomics studies extend beyond conventional chemical categorization and metabolic phenotype analysis to understanding gene function in various biological contexts (e.g., mammalian, plant, and microbial). These novel utilities have led to many innovative discoveries in the following areas: disease pathogenesis, therapeutic pathway or target identification, the biochemistry of animal and plant physiological and pathological activities in response to diverse stimuli, and molecular signatures of host-pathogen interactions during microbial infection. In this review, we critically evaluate the representative applications of mass spectrometry-based metabolomics to better understand gene function in diverse biological contexts, with special emphasis on working principles, study protocols, and possible future development of this technique. Collectively, this review raises awareness within the biomedical community of the scientific value and applicability of mass spectrometry-based metabolomics strategies to better understand gene function, thus advancing this application's utility in a broad range of biological fields
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Global aquaculture has expanded rapidly to address the increasing demand for aquatic protein needs and an uncertain future for wild fisheries. To date, however, most farmed aquatic stocks are essentially wild and little is known about their genomes or the genes that affect important economic traits in culture. Biologists have recognized that recent technological advances including next generation sequencing (NGS) have opened up the possibility of generating genome wide sequence data sets rapidly from non-model organisms at a reasonable cost. In an era when virtually any study organism can 'go genomic', understanding gene function and genetic effects on expressed quantitative trait locus phenotypes will be fundamental to future knowledge development. Many factors can influence the individual growth rate in target species but of particular importance in agriculture and aquaculture will be the identification and characterization of the specific gene loci that contribute important phenotypic variation to growth because the information can be applied to speed up genetic improvement programmes and to increase productivity via marker-assisted selection (MAS). While currently there is only limited genomic information available for any crustacean species, a number of putative candidate genes have been identified or implicated in growth and muscle development in some species. In an effort to stimulate increased research on the identification of growth-related genes in crustacean species, here we review the available information on: (i) associations between genes and growth reported in crustaceans, (ii) growth-related genes involved with moulting, (iii) muscle development and degradation genes involved in moulting, and; (iv) correlations between DNA sequences that have confirmed growth trait effects in farmed animal species used in terrestrial agriculture and related sequences in crustacean species. The information in concert can provide a foundation for increasing the rate at which knowledge about key genes affecting growth traits in crustacean species is gained.
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An influenza virus-inspired polymer mimic nanocarrier was used to deliver siRNA for specific and near complete gene knockdown of an osteoscarcom cell line (U-2SO). The polymer was synthesized by single-electron transfer living radical polymerization (SET-LRP) at room temperature to avoid complexities of transfer to monomer or polymer. It was the only LRP method that allowed good block copolymer formation with a narrow molecular weight distribution. At nitrogen to phosphorus (N/P) ratios of equal to or greater than 20 (greater than a polymer concentration of 13.8 μg/mL) with polo-like kinase 1 (PLK1) siRNA gave specific and near complete (>98%) cell death. The polymer further degrades to a benign polymer that showed no toxicity even at polymer concentrations of 200 μg/mL (or N/P ratio of 300), suggesting that our polymer nanocarrier can be used as a very effective siRNA delivery system and in a multiple dose administration. This work demonstrates that with a well-designed delivery device, siRNA can specifically kill cells without the inclusion of an additional clinically used highly toxic cochemotherapeutic agent. Our work also showed that this excellent delivery is sensitive for the study of off-target knockdown of siRNA.