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      An oligo-based microarray offers novel transcriptomic approaches for the analysis of pathogen resistance and fruit quality traits in melon ( Cucumis melo L.)

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          Abstract

          Background

          Melon ( Cucumis melo) is a horticultural specie of significant nutritional value, which belongs to the Cucurbitaceae family, whose economic importance is second only to the Solanaceae. Its small genome of approx. 450 Mb coupled to the high genetic diversity has prompted the development of genetic tools in the last decade. However, the unprecedented existence of a transcriptomic approaches in melon, highlight the importance of designing new tools for high-throughput analysis of gene expression.

          Results

          We report the construction of an oligo-based microarray using a total of 17,510 unigenes derived from 33,418 high-quality melon ESTs. This chip is particularly enriched with genes that are expressed in fruit and during interaction with pathogens. Hybridizations for three independent experiments allowed the characterization of global gene expression profiles during fruit ripening, as well as in response to viral and fungal infections in plant cotyledons and roots, respectively. Microarray construction, statistical analyses and validation together with functional-enrichment analysis are presented in this study.

          Conclusion

          The platform validation and enrichment analyses shown in our study indicate that this oligo-based microarray is amenable for future genetic and functional genomic studies of a wide range of experimental conditions in melon.

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          Most cited references 65

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          In silico prediction of protein-protein interactions in human macrophages

          Background: Protein-protein interaction (PPI) network analyses are highly valuable in deciphering and understanding the intricate organisation of cellular functions. Nevertheless, the majority of available protein-protein interaction networks are context-less, i.e. without any reference to the spatial, temporal or physiological conditions in which the interactions may occur. In this work, we are proposing a protocol to infer the most likely protein-protein interaction (PPI) network in human macrophages. Results: We integrated the PPI dataset from the Agile Protein Interaction DataAnalyzer (APID) with different meta-data to infer a contextualized macrophage-specific interactome using a combination of statistical methods. The obtained interactome is enriched in experimentally verified interactions and in proteins involved in macrophage-related biological processes (i.e. immune response activation, regulation of apoptosis). As a case study, we used the contextualized interactome to highlight the cellular processes induced upon Mycobacterium tuberculosis infection. Conclusion: Our work confirms that contextualizing interactomes improves the biological significance of bioinformatic analyses. More specifically, studying such inferred network rather than focusing at the gene expression level only, is informative on the processes involved in the host response. Indeed, important immune features such as apoptosis are solely highlighted when the spotlight is on the protein interaction level.
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            A draft sequence of the rice genome (Oryza sativa L. ssp. indica).

             J. Yu (2002)
            We have produced a draft sequence of the rice genome for the most widely cultivated subspecies in China, Oryza sativa L. ssp. indica, by whole-genome shotgun sequencing. The genome was 466 megabases in size, with an estimated 46,022 to 55,615 genes. Functional coverage in the assembled sequences was 92.0%. About 42.2% of the genome was in exact 20-nucleotide oligomer repeats, and most of the transposons were in the intergenic regions between genes. Although 80.6% of predicted Arabidopsis thaliana genes had a homolog in rice, only 49.4% of predicted rice genes had a homolog in A. thaliana. The large proportion of rice genes with no recognizable homologs is due to a gradient in the GC content of rice coding sequences.
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              Microsatellites are preferentially associated with nonrepetitive DNA in plant genomes.

              Microsatellites are a ubiquitous class of simple repetitive DNA sequence. An excess of such repetitive tracts has been described in all eukaryotes analyzed and is thought to result from the mutational effects of replication slippage. Large-scale genomic and EST sequencing provides the opportunity to evaluate the abundance and relative distribution of microsatellites between transcribed and nontranscribed regions and the relationship of these features to haploid genome size. Although this has been studied in microbial and animal genomes, information in plants is limited. We assessed microsatellite frequency in plant species with a 50-fold range in genome size that is mostly attributable to the recent amplification of repetitive DNA. Among species, the overall frequency of microsatellites was inversely related to genome size and to the proportion of repetitive DNA but remained constant in the transcribed portion of the genome. This indicates that most microsatellites reside in regions pre-dating the recent genome expansion in many plants. The microsatellite frequency was higher in transcribed regions, especially in the untranslated portions, than in genomic DNA. Contrary to previous reports suggesting a preferential mechanism for the origin of microsatellites from repetitive DNA in both animals and plants, our findings show a significant association with the low-copy fraction of plant genomes.
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                Author and article information

                Journal
                BMC Genomics
                BMC Genomics
                BioMed Central
                1471-2164
                2009
                12 October 2009
                : 10
                : 467
                Affiliations
                [1 ]Molecular Genetics Department, Centre for Research in Agricultural Genomics CRAG (CSIC-IRTA-UAB), Barcelona (08034), Spain
                [2 ]IRTA, Plant Genetics Department Centre for Research in Agricultural Genomics CRAG (CSIC-IRTA-UAB), Cabrils (08348), Spain
                [3 ]Departamento de Biología del Estrés y Patología Vegetal, Centro de Edafología y Biología Aplicada del Segura (CEBAS)-CSIC, Apdo. correos 164, 30100 Espinardo (Murcia), Spain
                [4 ]Instituto de Conservación y Mejora de la Agrodiversidad Valenciana (COMAV-UPV), CPI, Ed.8E, Camino de Vera s/n, 46022 Valencia, Spain
                [5 ]Research Unit on Biomedical Informatics (GRIB), Experimental and Health Science Department (Universitat Pompeu Fabra) Barcelona (08080), Spain
                Article
                1471-2164-10-467
                10.1186/1471-2164-10-467
                2767371
                19821986
                Copyright © 2009 Mascarell-Creus et al; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                Categories
                Research Article

                Genetics

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