16 resultados para Repetitive DNA sequences

em University of Queensland eSpace - Australia


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Phylogenetic relationships within the Capsalidae (Monogenea) were examined Using large subunit ribosomal DNA sequences from 17 capsalid species (representing 7 genera, 5 subfamilies), 2 outgroup taxa (Monocotylidae) plus Udonella caligorum (Udonellidae). Trees were constructed using maximum likelihood, minimum evolution and maximum parsimony algorithms. An initial tree, generated from sequences 315 bases long, Suggests that Capsalinae, Encotyllabinae, Entobdellinae and Trochopodinae are monophyletic, but that Benedeniinae is paraphyletic. Analyses indicate that Neobenedenia, currently in the Benedeniinae, should perhaps be placed in 2 separate subfamily. An additional analysis was made which omitted 3 capsalid taxa (for which only short sequences were available) and all outgroup taxa because of alignment difficulties. Sequence length increased to 693 bases and good branch support was achieved. The Benedeniinae was again paraphyletic. Higher-level classification of the Capsalidae, evolution of the Entobdellinae and issues of species identity in Neobenedenia are discussed.

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Immune cells respond to bacterial DNA containing unmethylated CpG motifs via Toll-like receptor 9 (TLR9). Given the apparent role of TLR9 in development of systemic lupus erythernatosus (SLE), there is interest in the development of TLR9 inhibitors. TLR9-mediated responses are reported to be inhibited by a confusing variety of different DNA sequences and structures. To aid characterization, we have provisionally categorized TLR9-inhibitory oligodeoxynucleoti des (ODN) into 4 classes, on the basis of sequence and probable mode of action. Class I are short G-rich ODN, which show sequence-specific inhibition of all TLR9 responses, and may be direct competitive inhibitors for DNA binding to TLR9. Class II are telomeric repeat motifs that inhibit STAT signaling, and thus are not specific to TLR9 responses. Because Class II ODN are generally made as 24-base phosphorothioate-modified ODN (PS-ODN), they also fall into Class IV, defined as long PS-ODN, which inhibit TLR9 responses in a sequence-nonspecific manner. Class III includes oligo (dG) that forms a 4-stranded structure and inhibits DNA uptake. The Class I G-rich motifs show the most promise as selective and potent TLR9 inhibitors for therapeutic applications.

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In simultaneous analyses of multiple data partitions, the trees relevant when measuring support for a clade are the optimal tree, and the best tree lacking the clade (i.e., the most reasonable alternative). The parsimony-based method of partitioned branch support (PBS) forces each data set to arbitrate between the two relevant trees. This value is the amount each data set contributes to clade support in the combined analysis, and can be very different to support apparent in separate analyses. The approach used in PBS can also be employed in likelihood: a simultaneous analysis of all data retrieves the maximum likelihood tree, and the best tree without the clade of interest is also found. Each data set is fitted to the two trees and the log-likelihood difference calculated, giving partitioned likelihood support (PLS) for each data set. These calculations can be performed regardless of the complexity of the ML model adopted. The significance of PLS can be evaluated using a variety of resampling methods, such as the Kishino-Hasegawa test, the Shimodiara-Hasegawa test, or likelihood weights, although the appropriateness and assumptions of these tests remains debated.

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Stx2d is a recently described Shiga toxin whose cytotoxicity is activated 10- to 1,000-fold by the elastase present in mouse or human intestinal mucus. We examined Shiga toxigenic Escherichia coli (STEC) strains isolated from food and livestock sources for the presence of activatable stx(2d). The stx(2) operons of STEC were first analyzed by PCR-restriction fragment length polymorphism (RFLP) analysis and categorized as stx(2), stx(2c) (vha), stx(2c) (vhb), or stx(2d) (EH250). Subsequently, the stx(2c) (vha) and stx(2c) (vhb) operons were screened for the absence of a PstI site in the stx(2a) subunit gene, a restriction site polymorphism which is a predictive indicator for the stx(2d) (activatable) genotype. Twelve STEC isolates carrying putative stx(2d) operons were identified, and nucleotide sequencing was used to confirm the identification of these operons as stx(2d). The complete nucleotide sequences of seven representative stx(2d) operons were determined. Shiga toxin expression in stx(2d) isolates was confirmed by immunoblotting. stx(2d) isolates were induced for the production of bacteriophages carrying stx. Two isolates were able to produce bacteriophages phi1662a and phi1720a carrying the stx(2d) operons. RFLP analysis of bacteriophage genomic DNA revealed that phi1662a and phi1720a were highly related to each other; however, the DNA sequences of these two stx(2d) operons were distinct. The STEC strains carrying these operons were isolated from retail ground beef. Surveillance for STEC strains expressing activatable stx(2d) Shiga toxin among clinical cases may indicate the significance of this toxin subtype to human health.

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DNA Microarray is a powerful tool to measure the level of a mixed population of nucleic acids at one time, which has great impact in many aspects of life sciences research. In order to distinguish nucleic acids with very similar composition by hybridization, it is necessary to design microarray probes with high specificities and sensitivities. Highly specific probes correspond to probes having unique DNA sequences; whereas highly sensitive probes correspond to those with melting temperature within a desired range and having no secondary structure. The selection of these probes from a set of functional DNA sequences (exons) constitutes a computationally expensive discrete non-linear search problem. We delegate the search task to a simple yet effective Evolution Strategy algorithm. The computational efficiency is also greatly improved by making use of an available bioinformatics tool.

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In recent years there has been much progress in our understanding of the phylogeny and evolution of ticks, in particular the hard ticks (Ixodidae). Indeed, a consensus about the phylogeny of the hard ticks has emerged which is quite different to the working hypothesis of 10 years ago. So that the classification reflects our knowledge of ticks, several changes to the nomenclature of ticks are imminent or have been made. One subfamily, the Hyalomminae, should be sunk, while another, the Bothriocrotoninae, has been created (Klompen, Dobson & Barker, 2002). Bothriocrotoninae, and its sole genus Bothriocroton, have been created to house an early-diverging ('basal') lineage of endemic Australian ticks that used to be in the genus Aponomma. The remaining species of the genus Aponomma have been moved to the genus Amblyomma. Thus, the name Aponomma is no longer a valid genus name. The genus Rhipicephalus is paraphyletic with respect to the genus Boophilus. Thus, the genus Boophilus has become a subgenus of the genus Rhipicephalus (Murrell & Barker, 2003). Knowledge of the phylogenetic relationships of ticks has also provided new insights into the evolution of ornateness and of their life cycles, and has allowed the historical zoogeography of ticks to be studied. Finally, we present a list of the 899 valid genus and species names of ticks as of February 2004.

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The molecular clock does not tick at a uniform rate in all taxa but maybe influenced by species characteristics. Eusocial species (those with reproductive division of labor) have been predicted to have faster rates of molecular evolution than their nonsocial relatives because of greatly reduced effective population size; if most individuals in a population are nonreproductive and only one or few queens produce all the offspring, then eusocial animals could have much lower effective population sizes than their solitary relatives, which should increase the rate of substitution of nearly neutral mutations. An earlier study reported faster rates in eusocial honeybees and vespid wasps but failed to correct for phylogenetic nonindependence or to distinguish between potential causes of rate variation. Because sociality has evolved independently in many different lineages, it is possible to conduct a more wide-ranging study to test the generality of the relationship. We have conducted a comparative analysis of 25 phylogenetically independent pairs of social lineages and their nonsocial relatives, including bees, wasps, ants, termites, shrimps, and mole rats, using a range of available DNA sequences (mitochondrial and nuclear DNA coding for proteins and RNAs, and nontranslated sequences). By including a wide range of social taxa, we were able to test whether there is a general influence of sociality on rates of molecular evolution and to test specific predictions of the hypothesis: (1) that social species have faster rates because they have reduced effective population sizes; (2) that mitochondrial genes would show a greater effect of sociality than nuclear genes; and (3) that rates of molecular evolution should be correlated with the degree of sociality. We find no consistent pattern in rates of molecular evolution between social and nonsocial lineages and no evidence that mitochondrial genes show faster rates in social taxa. However, we show that the most highly eusocial Hymenoptera do have faster rates than their nonsocial relatives. We also find that social parasites (that utilize the workers from related species to produce their own offspring) have faster rates than their social relatives, which is consistent with an effect of lower effective population size on rate of molecular evolution. Our results illustrate the importance of allowing for phylogenetic nonindependence when conducting investigations of determinants of variation in rate of molecular evolution.

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Table beet production in the Lockyer Valley of south-eastern Queensland is known to be adversely affected by soilborne root disease from infection by Pythium spp. However, little is known regarding the species or genotypes that are the causal agents of both pre- and post-emergence damping off. Based on RFLP analysis with HhaI, HinfI and MboI of the PCR amplified ITS region DNA from soil and diseased plant samples, the majority of 130 Pythium isolates could be grouped into three genotypes, designated LVP A, LVP B and LVP C. These groups comprised 43, 41 and 7% of all isolates, respectively. Deoxyribonucleic acid sequence analysis of the ITS region indicated that LVP A was a strain of Pythium aphanidermatum, with greater than 99% similarity to the corresponding P. aphanidermatum sequences from the publicly accessible databases. The DNA sequences from LVP B and LVP C were most closely related to P. ultimum and P. dissotocum, respectively. Lower frequencies of other distinct isolates with unique RFLP patterns were also obtained with high levels of similarity (> 97%) to P. heterothallicum, P. periplocum and genotypes of P. ultimum other than LVP B. Inoculation trials of 1- and 4-week-old beet seedlings indicated that compared with isolates of the LVP B genotype, a higher frequency of LVP A isolates caused disease. Isolates with the LVP A, LVP B and LVP C genotypes were highly sensitive to the fungicide Ridomil MZ, which suppressed radial growth on V8 agar between approximately four and thirty fold at 5 mu g/mL metalaxyl and 40 mu g/mL mancozeb, a concentration far lower than the recommended field application rate.

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Markov chain Monte Carlo (MCMC) is a methodology that is gaining widespread use in the phylogenetics community and is central to phylogenetic software packages such as MrBayes. An important issue for users of MCMC methods is how to select appropriate values for adjustable parameters such as the length of the Markov chain or chains, the sampling density, the proposal mechanism, and, if Metropolis-coupled MCMC is being used, the number of heated chains and their temperatures. Although some parameter settings have been examined in detail in the literature, others are frequently chosen with more regard to computational time or personal experience with other data sets. Such choices may lead to inadequate sampling of tree space or an inefficient use of computational resources. We performed a detailed study of convergence and mixing for 70 randomly selected, putatively orthologous protein sets with different sizes and taxonomic compositions. Replicated runs from multiple random starting points permit a more rigorous assessment of convergence, and we developed two novel statistics, delta and epsilon, for this purpose. Although likelihood values invariably stabilized quickly, adequate sampling of the posterior distribution of tree topologies took considerably longer. Our results suggest that multimodality is common for data sets with 30 or more taxa and that this results in slow convergence and mixing. However, we also found that the pragmatic approach of combining data from several short, replicated runs into a metachain to estimate bipartition posterior probabilities provided good approximations, and that such estimates were no worse in approximating a reference posterior distribution than those obtained using a single long run of the same length as the metachain. Precision appears to be best when heated Markov chains have low temperatures, whereas chains with high temperatures appear to sample trees with high posterior probabilities only rarely. [Bayesian phylogenetic inference; heating parameter; Markov chain Monte Carlo; replicated chains.]

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Eukaryotic genomes display segmental patterns of variation in various properties, including GC content and degree of evolutionary conservation. DNA segmentation algorithms are aimed at identifying statistically significant boundaries between such segments. Such algorithms may provide a means of discovering new classes of functional elements in eukaryotic genomes. This paper presents a model and an algorithm for Bayesian DNA segmentation and considers the feasibility of using it to segment whole eukaryotic genomes. The algorithm is tested on a range of simulated and real DNA sequences, and the following conclusions are drawn. Firstly, the algorithm correctly identifies non-segmented sequence, and can thus be used to reject the null hypothesis of uniformity in the property of interest. Secondly, estimates of the number and locations of change-points produced by the algorithm are robust to variations in algorithm parameters and initial starting conditions and correspond to real features in the data. Thirdly, the algorithm is successfully used to segment human chromosome 1 according to GC content, thus demonstrating the feasibility of Bayesian segmentation of eukaryotic genomes. The software described in this paper is available from the author's website (www.uq.edu.au/similar to uqjkeith/) or upon request to the author.

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In Late summer 1999, an outbreak of human encephalitis occurred in the northeastern United States that was concurrent with extensive mortality in crows (Corvus species) as well as the deaths of several exotic birds at a zoological park in the same area. Complete genome sequencing of a flavivirus isolated from the brain of a dead Chilean flamingo (Phoenicopterus chilensis), together with partial sequence analysis of envelope glycoprotein (E-glycoprotein) genes amplified from several other species including mosquitoes and two fatal human cases, revealed that West Nile (WN) virus circulated in natural transmission cycles and was responsible for the human disease. Antigenic mapping with E-glycoprotein-specific monoclonal antibodies and E-glycoprotein phylogenetic analysis confirmed these viruses as WN. This North American WN virus was most closely related to a WN virus isolated from a dead goose in Israel in 1998.