8 resultados para microRNA gene clusters

em University of Queensland eSpace - Australia


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Metallosphaera sedula is a thermoacidophilic Crenarchaeon which is capable of leaching metals from sulfidic ores. The authors have investigated the presence and expression of genes encoding respiratory complexes in this organism when grown heterotrophically or chemolithotrophically on either sulfur or pyrite. The presence of three gene clusters, encoding two terminal oxidase complexes, the quinol oxidase SoxABCD and the SoxM oxidase supercomplex, and a gene cluster encoding a high-potential cytochrome b and components of a bc(1) complex analogue (cbsBA-soxL2N gene cluster) was established. Expression studies showed that the soxM gene was expressed to high levels during heterotrophic growth of M. sedula on yeast extract, while the soxABCD mRNA was most abundant in cells grown on sulfur. Reduced-minus-oxidized difference spectra of cell membranes showed cytochrome-related peaks that correspond to published spectra of Sulfolobus-type terminal oxidase complexes. In pyrite-grown cells, expression levels of the two monitored oxidase gene clusters were reduced by a factor of 10-12 relative to maximal expression levels, although spectra of membranes clearly contained oxidase-associated haems, suggesting the presence of additional gene clusters encoding terminal oxidases in M. sedula. Pyrite- and sulfur-grown cells contained high levels of the cbsA transcript, which encodes a membrane-bound cytochrome b with a possible role in iron oxidation or chemolithotrophy. The cbsA gene is not co-transcribed with the soxL2N genes, and therefore does not appear to be an integral part of this bc(1) complex analogue. The data show for the first time the differential expression of the Sulfolobus-type terminal oxidase gene clusters in a Crenarchaeon in response to changing growth modes.

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The tropical abalone. Haliotis asinina. is,in ideal species to investigate the molecular mechanisms that control development. growth, reproduction and shell formation in all cultured haliotids. Here we describe the analysis of 232 expressed sequence tags (EST) obtained front a developmental H. asinina cDNA library intended for future microarray studies. From this data set we identified 183 unique gene Clusters. Of these, 90 clusters showed significant homology with sequences lodged in GenBank, ranging in function from general housekeeping to signal transduction, gene regulation and cell-cell communication. Seventy-one clusters possessed completely novel ORFs greater than 50 codons in length, highlighting the paucity of sequence data from molluscs and other lophotrochozoans. This study of developmental gene expression in H. asinina provides the foundation for further detailed analyses of abalone growth, development and reproduction.

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We consider the problem of assessing the number of clusters in a limited number of tissue samples containing gene expressions for possibly several thousands of genes. It is proposed to use a normal mixture model-based approach to the clustering of the tissue samples. One advantage of this approach is that the question on the number of clusters in the data can be formulated in terms of a test on the smallest number of components in the mixture model compatible with the data. This test can be carried out on the basis of the likelihood ratio test statistic, using resampling to assess its null distribution. The effectiveness of this approach is demonstrated on simulated data and on some microarray datasets, as considered previously in the bioinformatics literature. (C) 2004 Elsevier Inc. All rights reserved.

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Fifty-four different sugarcane resistance gene analogue (RGA) sequences were isolated, characterized, and used to identify molecular markers linked to major disease-resistance loci in sugarcane. Ten RGAs were identified from a sugarcane stem expressed sequence tag (EST) library; the remaining 44 were isolated from sugarcane stem, leaf, and root tissue using primers designed to conserved RGA motifs. The map location of 31 of the RGAs was determined in sugarcane and compared with the location of quantitative trait loci (QTL) for brown rust resistance. After 2 years of phenotyping, 3 RGAs were shown to generate markers that were significantly associated with resistance to this disease. To assist in the understanding of the complex genetic structure of sugarcane, 17 of the 31 RGAs were also mapped in sorghum. Comparative mapping between sugarcane and sorghum revealed syntenic localization of several RGA clusters. The 3 brown rust associated RGAs were shown to map to the same linkage group (LG) in sorghum with 2 mapping to one region and the third to a region previously shown to contain a major rust-resistance QTL in sorghum. These results illustrate the value of using RGAs for the identification of markers linked to disease resistance loci and the value of simultaneous mapping in sugarcane and sorghum.

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Motivation: The clustering of gene profiles across some experimental conditions of interest contributes significantly to the elucidation of unknown gene function, the validation of gene discoveries and the interpretation of biological processes. However, this clustering problem is not straightforward as the profiles of the genes are not all independently distributed and the expression levels may have been obtained from an experimental design involving replicated arrays. Ignoring the dependence between the gene profiles and the structure of the replicated data can result in important sources of variability in the experiments being overlooked in the analysis, with the consequent possibility of misleading inferences being made. We propose a random-effects model that provides a unified approach to the clustering of genes with correlated expression levels measured in a wide variety of experimental situations. Our model is an extension of the normal mixture model to account for the correlations between the gene profiles and to enable covariate information to be incorporated into the clustering process. Hence the model is applicable to longitudinal studies with or without replication, for example, time-course experiments by using time as a covariate, and to cross-sectional experiments by using categorical covariates to represent the different experimental classes. Results: We show that our random-effects model can be fitted by maximum likelihood via the EM algorithm for which the E(expectation) and M(maximization) steps can be implemented in closed form. Hence our model can be fitted deterministically without the need for time-consuming Monte Carlo approximations. The effectiveness of our model-based procedure for the clustering of correlated gene profiles is demonstrated on three real datasets, representing typical microarray experimental designs, covering time-course, repeated-measurement and cross-sectional data. In these examples, relevant clusters of the genes are obtained, which are supported by existing gene-function annotation. A synthetic dataset is considered too.

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Non- protein- coding RNAs ( ncRNAs) are increasingly being recognized as having important regulatory roles. Although much recent attention has focused on tiny 22- to 25- nucleotide microRNAs, several functional ncRNAs are orders of magnitude larger in size. Examples of such macro ncRNAs include Xist and Air, which in mouse are 18 and 108 kilobases ( Kb), respectively. We surveyed the 102,801 FANTOM3 mouse cDNA clones and found that Air and Xist were present not as single, full- length transcripts but as a cluster of multiple, shorter cDNAs, which were unspliced, had little coding potential, and were most likely primed from internal adenine- rich regions within longer parental transcripts. We therefore conducted a genome- wide search for regional clusters of such cDNAs to find novel macro ncRNA candidates. Sixty- six regions were identified, each of which mapped outside known protein- coding loci and which had a mean length of 92 Kb. We detected several known long ncRNAs within these regions, supporting the basic rationale of our approach. In silico analysis showed that many regions had evidence of imprinting and/ or antisense transcription. These regions were significantly associated with microRNAs and transcripts from the central nervous system. We selected eight novel regions for experimental validation by northern blot and RT- PCR and found that the majority represent previously unrecognized noncoding transcripts that are at least 10 Kb in size and predominantly localized in the nucleus. Taken together, the data not only identify multiple new ncRNAs but also suggest the existence of many more macro ncRNAs like Xist and Air.

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Little is known about the extent of allelic diversity of genes in the complex polyploid, sugarcane. Using sucrose phosphate synthase (SPS) Gene (SPS) Family III as an example, we have amplified and sequenced a 400 nt region from this gene from two sugarcane lines that are parents of a mapping population. Ten single nucleotide polymorphisms (SNPs) were identified within the 400 nt region of which seven were present in both lines. In the elite commercial cultivar Q165(A), 10 sequence haplotypes were identified, with four haplotypes recovered at 9% or greater frequency. Based on SNP presence, two clusters of haplotypes were observed. In IJ76-514, a Saccharum officinarum accession, 8 haplotypes were identified with 4 haplotypes recovered at 13% or greater frequency. Again, two clusters of haplotypes were observed. The results suggest that there may be two SPS Gene Family III genes per genome in sugarcane, each with different numbers of different alleles. This suggestion is supported by sequencing results in an elite parental sorghum line, 403463-2-1, in which 4 haplotypes, corresponding to two broad types, were also identified. Primers were designed to the sugarcane SNPs and screened over bulked DNA from high and low Sucrose-containing progeny from a cross between Q165(A) and IJ76-514. The SNP frequency did not vary in the two bulked DNA samples, suggesting that these SNPs from this SPS gene family are not associated with variation in sucrose content. Using an ecotilling approach, two of the SPS Gene Family III haplotypes were mapped to two different linkage groups in homology group 1 in Q165(A). Both haplotypes mapped near QTLs for increased sucrose content but were not themselves associated with any sugar-related trait.