994 resultados para Independent Sequence
Resumo:
Japanese isolates of Candidatus Liberibacter asiaticus have been shown to be clearly differentiated by simple sequence repeat (SSR) profiles at four loci. In this study, 25 SSR loci, including these four loci, were selected from the whole-genome sequence and were used to differentiate non-Japanese samples of Ca. Liberibacter asiaticus (13 Indian, 3 East Timorese, 1 Papuan and 8 Floridian samples). Out of the 25 SSR loci, 13 were polymorphic. Dendrogram analysis using SSR loci showed that the clusters were mostly consistent with the geographical origins of the isolates. When single nucleotide polymorphisms (SNPs) were searched around these 25 loci, only the upstream region of locus 091 exhibited polymorphism. Phylogenetic tree analysis of the SNPs in the upstream region of locus 091 showed that Floridian samples were clustered into one group as shown by dendrogram analysis using SSR loci. The differences in nucleotide sequences were not associated with differences in the citrus hosts (lime, mandarin, lemon and sour orange) from which the isolates were originally derived.
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Phosphine is the only economically viable fumigant for routine control of insect pests of stored food products, but its continued use is now threatened by the world-wide emergence of high-level resistance in key pest species. Phosphine has a unique mode of action relative to well-characterised contact pesticides. Similarly, the selective pressures that lead to resistance against field sprays differ dramatically from those encountered during fumigation. The consequences of these differences have not been investigated adequately. We determine the genetic basis of phosphine resistance in Rhyzopertha dominica strains collected from New South Wales and South Australia and compare this with resistance in a previously characterised strain from Queensland. The resistance levels range from 225 and 100 times the baseline response of a sensitive reference strain. Moreover, molecular and phenotypic data indicate that high-level resistance was derived independently in each of the three widely separated geographical regions. Despite the independent origins, resistance was due to two interacting genes in each instance. Furthermore, complementation analysis reveals that all three strains contain an incompletely recessive resistance allele of the autosomal rph1 resistance gene. This is particularly noteworthy as a resistance allele at rph1 was previously proposed to be a necessary first step in the evolution of high-level resistance. Despite the capacity of phosphine to disrupt a wide range of enzymes and biological processes, it is remarkable that the initial step in the selection of resistance is so similar in isolated outbreaks.
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Fusarium oxysporum f. sp. cubense (Foc), causal agent of fusarium wilt of banana, is among the most destructive pathogens of banana and plantain. The development of a molecular diagnostic capable of reliably distinguishing between the various races of the pathogen is of key importance to disease management. However, attempts to distinguish isolates using the standard molecular loci typically used for fungal phylogenetics have been complicated by a poor correlation between phylogeny and pathogenicity. Among the available alternative loci are several putative effector genes, known as SIX genes, which have been successfully used to differentiate the three races of F. oxysporum f. sp. lycopersici. In this study, an international collection of Foc isolates was screened for the presence of the putative effector SIX8. Using a PCR and sequencing approach, variation in Foc-SIX8 was identified which allowed race 4 to be differentiated from race 1 and 2 isolates, and tropical and subtropical race 4 isolates to be distinguished from one another.
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The application of variable-number tandem repeats (VNTR) genotyping of Mycobacterium avium subsp. paratuberculosis isolates to assist in investigating incidents of bovine Johne’s disease in a low-prevalence region of Australia is described in the current study. Isolates from a response to detection of bovine Johne’s disease in Queensland were compared with strains from national and international sources. The tandem application of mycobacterial interspersed repetitive unit (MIRU) and multilocus short sequence repeats (MLSSR) genotyping identified 2 strains, 1 that infected cattle on multiple properties with trace-forward histories from a common infected property, and 1 genotypically different strain recovered from a single property. The former strain showed an identical genotype to an isolate from India. Neither strain showed a genotypic link to regions of Australia with a higher prevalence of the disease. Genotyping has indicated incursions from 2 independent sources. This intelligence has informed investigations into potential routes of entry and the soundness of ongoing control measures, and supported strategy and policy decisions regarding management of Mycobacterium avium subsp. paratuberculosis incursions for Queensland.
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NMR spectroscopy enables the study of biomolecules from peptides and carbohydrates to proteins at atomic resolution. The technique uniquely allows for structure determination of molecules in solution-state. It also gives insights into dynamics and intermolecular interactions important for determining biological function. Detailed molecular information is entangled in the nuclear spin states. The information can be extracted by pulse sequences designed to measure the desired molecular parameters. Advancement of pulse sequence methodology therefore plays a key role in the development of biomolecular NMR spectroscopy. A range of novel pulse sequences for solution-state NMR spectroscopy are presented in this thesis. The pulse sequences are described in relation to the molecular information they provide. The pulse sequence experiments represent several advances in NMR spectroscopy with particular emphasis on applications for proteins. Some of the novel methods are focusing on methyl-containing amino acids which are pivotal for structure determination. Methyl-specific assignment schemes are introduced for increasing the size range of 13C,15N labeled proteins amenable to structure determination without resolving to more elaborate labeling schemes. Furthermore, cost-effective means are presented for monitoring amide and methyl correlations simultaneously. Residual dipolar couplings can be applied for structure refinement as well as for studying dynamics. Accurate methods for measuring residual dipolar couplings in small proteins are devised along with special techniques applicable when proteins require high pH or high temperature solvent conditions. Finally, a new technique is demonstrated to diminish strong-coupling induced artifacts in HMBC, a routine experiment for establishing long-range correlations in unlabeled molecules. The presented experiments facilitate structural studies of biomolecules by NMR spectroscopy.
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Abstract is not available.
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The first complete genome sequence of capsicum chlorosis virus (CaCV) from Australia was determined using a combination of Illumina HiSeq RNA and Sanger sequencing technologies. Australian CaCV had a tripartite genome structure like other CaCV isolates. The large (L) RNA was 8913 nucleotides (nt) in length and contained a single open reading frame (ORF) of 8634 nt encoding a predicted RNA-dependent RNA polymerase (RdRp) in the viral-complementary (vc) sense. The medium (M) and small (S) RNA segments were 4846 and 3944 nt in length, respectively, each containing two non-overlapping ORFs in ambisense orientation, separated by intergenic regions (IGR). The M segment contained ORFs encoding the predicted non-structural movement protein (NSm; 927 nt) and precursor of glycoproteins (GP; 3366 nt) in the viral sense (v) and vc strand, respectively, separated by a 449-nt IGR. The S segment coded for the predicted nucleocapsid (N) protein (828 nt) and non-structural suppressor of silencing protein (NSs; 1320 nt) in the vc and v strand, respectively. The S RNA contained an IGR of 1663 nt, being the largest IGR of all CaCV isolates sequenced so far. Comparison of the Australian CaCV genome with complete CaCV genome sequences from other geographic regions showed highest sequence identity with a Taiwanese isolate. Genome sequence comparisons and phylogeny of all available CaCV isolates provided evidence for at least two highly diverged groups of CaCV isolates that may warrant re-classification of AIT-Thailand and CP-China isolates as unique tospoviruses, separate from CaCV.
Resumo:
Summary We have determined the full-length 14,491-nucleotide genome sequence of a new plant rhabdovirus, alfalfa dwarf virus (ADV). Seven open reading frames (ORFs) were identified in the antigenomic orientation of the negative-sense, single-stranded viral RNA, in the order 3′-N-P-P3-M-G-P6-L-5′. The ORFs are separated by conserved intergenic regions and the genome coding region is flanked by complementary 3′ leader and 5′ trailer sequences. Phylogenetic analysis of the nucleoprotein amino acid sequence indicated that this alfalfa-infecting rhabdovirus is related to viruses in the genus Cytorhabdovirus. When transiently expressed as GFP fusions in Nicotiana benthamiana leaves, most ADV proteins accumulated in the cell periphery, but unexpectedly P protein was localized exclusively in the nucleus. ADV P protein was shown to have a homotypic, and heterotypic nuclear interactions with N, P3 and M proteins by bimolecular fluorescence complementation. ADV appears unique in that it combines properties of both cytoplasmic and nuclear plant rhabdoviruses.
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Bacteria play an important role in many ecological systems. The molecular characterization of bacteria using either cultivation-dependent or cultivation-independent methods reveals the large scale of bacterial diversity in natural communities, and the vastness of subpopulations within a species or genus. Understanding how bacterial diversity varies across different environments and also within populations should provide insights into many important questions of bacterial evolution and population dynamics. This thesis presents novel statistical methods for analyzing bacterial diversity using widely employed molecular fingerprinting techniques. The first objective of this thesis was to develop Bayesian clustering models to identify bacterial population structures. Bacterial isolates were identified using multilous sequence typing (MLST), and Bayesian clustering models were used to explore the evolutionary relationships among isolates. Our method involves the inference of genetic population structures via an unsupervised clustering framework where the dependence between loci is represented using graphical models. The population dynamics that generate such a population stratification were investigated using a stochastic model, in which homologous recombination between subpopulations can be quantified within a gene flow network. The second part of the thesis focuses on cluster analysis of community compositional data produced by two different cultivation-independent analyses: terminal restriction fragment length polymorphism (T-RFLP) analysis, and fatty acid methyl ester (FAME) analysis. The cluster analysis aims to group bacterial communities that are similar in composition, which is an important step for understanding the overall influences of environmental and ecological perturbations on bacterial diversity. A common feature of T-RFLP and FAME data is zero-inflation, which indicates that the observation of a zero value is much more frequent than would be expected, for example, from a Poisson distribution in the discrete case, or a Gaussian distribution in the continuous case. We provided two strategies for modeling zero-inflation in the clustering framework, which were validated by both synthetic and empirical complex data sets. We show in the thesis that our model that takes into account dependencies between loci in MLST data can produce better clustering results than those methods which assume independent loci. Furthermore, computer algorithms that are efficient in analyzing large scale data were adopted for meeting the increasing computational need. Our method that detects homologous recombination in subpopulations may provide a theoretical criterion for defining bacterial species. The clustering of bacterial community data include T-RFLP and FAME provides an initial effort for discovering the evolutionary dynamics that structure and maintain bacterial diversity in the natural environment.
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A limited number of plant rhabdovirus genomes have been fully sequenced, making taxonomic classification, evolutionary analysis and molecular characterization of this virus group difficult. We have for the first time determined the complete genome sequence of 13,188 nucleotides of Datura yellow vein nucleorhabdovirus (DYVV). DYVV genome organization resembles that of its closest relative, Sonchus yellow net virus (SYNV), with six ORFs in antigenomic orientation, separated by highly conserved intergenic regions and flanked by complementary 3′ leader and 5′ trailer sequences. As is typical for nucleorhabdoviruses, all viral proteins, except the glycoprotein, which is targeted to the endoplasmic reticulum, are localized to the nucleus. Nucleocapsid (N) protein, matrix (M) protein and polymerase, as components of nuclear viroplasms during replication, have predicted strong canonical nuclear localization signals, and N and M proteins exclusively localize to the nucleus when transiently expressed as GFP fusions. As in all nucleorhabdoviruses studied so far, N and phosphoprotein P interact when co-expressed, significantly increasing P nuclear localization in the presence of N protein. This research adds to the list of complete genomes of plant-infecting rhabdoviruses, provides molecular tools for further characterization and supports classification of DYVV as a nucleorhabdovirus closely related to but with some distinct differences from SYNV.
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Background: Mango fruits contain a broad spectrum of phenolic compounds which impart potential health benefits; their biosynthesis is catalysed by enzymes in the phenylpropanoid-flavonoid (PF) pathway. The aim of this study was to reveal the variability in genes involved in the PF pathway in three different mango varieties Mangifera indica L., a member of the family Anacardiaceae: Kensington Pride (KP), Irwin (IW) and Nam Doc Mai (NDM) and to determine associations with gene expression and mango flavonoid profiles. Results: A close evolutionary relationship between mango genes and those from the woody species poplar of the Salicaceae family (Populus trichocarpa) and grape of the Vitaceae family (Vitis vinifera), was revealed through phylogenetic analysis of PF pathway genes. We discovered 145 SNPs in total within coding sequences with an average frequency of one SNP every 316bp. Variety IW had the highest SNP frequency (one SNP every 258bp) while KP and NDM had similar frequencies (one SNP every 369bp and 360bp, respectively). The position in the PF pathway appeared to influence the extent of genetic diversity of the encoded enzymes. The entry point enzymes phenylalanine lyase (PAL), cinnamate 4-mono-oxygenase (C4H) and chalcone synthase (CHS) had low levels of SNP diversity in their coding sequences, whereas anthocyanidin reductase (ANR) showed the highest SNP frequency followed by flavonoid 3'-hydroxylase (F3'H). Quantitative PCR revealed characteristic patterns of gene expression that differed between mango peel and flesh, and between varieties. Conclusions: The combination of mango expressed sequence tags and availability of well-established reference PF biosynthetic genes from other plant species allowed the identification of coding sequences of genes that may lead to the formation of important flavonoid compounds in mango fruits and facilitated characterisation of single nucleotide polymorphisms between varieties. We discovered an association between the extent of sequence variation and position in the pathway for up-stream genes. The high expression of PAL, C4H and CHS genes in mango peel compared to flesh is associated with high amounts of total phenolic contents in peels, which suggest that these genes have an influence on total flavonoid levels in mango fruit peel and flesh. In addition, the particularly high expression levels of ANR in KP and NDM peels compared to IW peel and the significant accumulation of its product epicatechin gallate (ECG) in those extracts reflects the rate-limiting role of ANR on ECG biosynthesis in mango. © 2015 Hoang et al.
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Expressed sequence tag (EST) databases provide a primary source of nuclear DNA sequences for genetic marker development in non-model organisms. To date, the process has been relatively inefficient for several reasons: - 1) priming site polymorphism in the template leads to inferior or erratic amplification; - 2) introns in the target amplicon are too large and/or numerous to allow effective amplification under standard screening conditions, and; - 3) at least occasionally, a PCR primer straddles an exon–intron junction and is unable to bind to genomic DNA template. The first is only a minor issue for species or strains with low heterozygosity but becomes a significant problem for species with high genomic variation, such as marine organisms with extremely large effective population sizes. Problems arising from unanticipated introns are unavoidable but are most pronounced in intron-rich species, such as vertebrates and lophotrochozoans. We present an approach to marker development in the Pacific oyster Crassostrea gigas, a highly polymorphic and intron-rich species, which minimizes these problems, and should be applicable to other non-model species for which EST databases are available. Placement of PCR primers in the 3′ end of coding sequence and 3′ UTR improved PCR success rate from 51% to 97%. Almost all (37 of 39) markers developed for the Pacific oyster were polymorphic in a small test panel of wild and domesticated oysters.
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The analysis of sequential data is required in many diverse areas such as telecommunications, stock market analysis, and bioinformatics. A basic problem related to the analysis of sequential data is the sequence segmentation problem. A sequence segmentation is a partition of the sequence into a number of non-overlapping segments that cover all data points, such that each segment is as homogeneous as possible. This problem can be solved optimally using a standard dynamic programming algorithm. In the first part of the thesis, we present a new approximation algorithm for the sequence segmentation problem. This algorithm has smaller running time than the optimal dynamic programming algorithm, while it has bounded approximation ratio. The basic idea is to divide the input sequence into subsequences, solve the problem optimally in each subsequence, and then appropriately combine the solutions to the subproblems into one final solution. In the second part of the thesis, we study alternative segmentation models that are devised to better fit the data. More specifically, we focus on clustered segmentations and segmentations with rearrangements. While in the standard segmentation of a multidimensional sequence all dimensions share the same segment boundaries, in a clustered segmentation the multidimensional sequence is segmented in such a way that dimensions are allowed to form clusters. Each cluster of dimensions is then segmented separately. We formally define the problem of clustered segmentations and we experimentally show that segmenting sequences using this segmentation model, leads to solutions with smaller error for the same model cost. Segmentation with rearrangements is a novel variation to the segmentation problem: in addition to partitioning the sequence we also seek to apply a limited amount of reordering, so that the overall representation error is minimized. We formulate the problem of segmentation with rearrangements and we show that it is an NP-hard problem to solve or even to approximate. We devise effective algorithms for the proposed problem, combining ideas from dynamic programming and outlier detection algorithms in sequences. In the final part of the thesis, we discuss the problem of aggregating results of segmentation algorithms on the same set of data points. In this case, we are interested in producing a partitioning of the data that agrees as much as possible with the input partitions. We show that this problem can be solved optimally in polynomial time using dynamic programming. Furthermore, we show that not all data points are candidates for segment boundaries in the optimal solution.