21 research outputs found

    Genome sequence of metarhizium rileyi, a microbial control agent for lepidoptera

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    Metarhizium rileyi (formerly known as Nomuraea rileyi) is a potential agent for microbial control of many insect pests from the order Lepidoptera, the damages of which can cause considerable loss of productivity in agriculture. We report the genome sequence and annotation of M. rileyi strain Cep018-CH2/ARSEF 7053.Fil: Binneck, Eliseu. Ministerio da Agricultura Pecuaria e Abastecimento de Brasil. Empresa Brasileira de Pesquisa Agropecuaria; BrasilFil: Lopez Lastra, Claudia Cristina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Centro de Estudios Parasitológicos y de Vectores. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. Centro de Estudios Parasitológicos y de Vectores; ArgentinaFil: Sosa Gómez, Daniel. Ministerio da Agricultura Pecuaria e Abastecimento de Brasil; Brasi

    A web-based bioinformatics interface applied to the GENOSOJA project: databases and pipelines

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    The Genosoja consortium is an initiative to integrate different omics research approaches carried out in Brazil. Basically, the aim of the project is to improve the plant by identifying genes involved in responses against stresses that affect domestic production, like drought stress and Asian Rust fungal disease. To do so, the project generated several types of sequence data using different methodologies, most of them sequenced by next generation sequencers. The initial stage of the project is highly dependent on bioinformatics analysis, providing suitable tools and integrated databases. In this work, we describe the main features of the Genosoja web database, including the pipelines to analyze some kinds of data (ESTs, SuperSAGE, microRNAs, subtractive cDNA libraries), as well as web interfaces to access information about soybean gene annotation and expression.203211Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq

    Size of AT(n) Insertions in Promoter Region Modulates Gmhsp17.6-L mRNA Transcript Levels

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    During earlier experiments, an SSR molecular marker (176 Soy HSP) showing high correlation (70%) with resistance/susceptibility to javanese root-knot nematode Meloidogyne javanica was identified in soybean. After being sequenced, results indicated that the SSR 176 Soy HSP marker was inserted in the promoter region of Gmhsp17.6-L gene. It was also detected in this region that resistant genotypes presented insertions between AT(31) and AT(33) in size and susceptible genotypes, AT(9). Gmhsp17.6-L gene coding region presented a perfect match in amino acid sequence in all soybean genotypes. A ribonuclease protection assay showed that Gmhsp17.6-L gene mRNA transcripts were present in all genotypes. A real-time relative quantification (qPCR) indicated in the resistant individuals higher mRNA transcripts levels, which presented in the sequencing more AT(n) insertions. These results suggest that the number of AT(n) insertions inside this promoter region could modulate up or down gene levels. Those findings can lead to the possibility of manipulating, between some limits, the mRNA transcripts levels using different sizes of AT(n) insertions

    A web-based bioinformatics interface applied to the GENOSOJA project: databases and pipelines

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    The Genosoja consortium is an initiative to integrate different omics research approaches carried out in Brazil. Basically, the aim of the project is to improve the plant by identifying genes involved in responses against stresses that affect domestic production, like drought stress and Asian Rust fungal disease. To do so, the project generated several types of sequence data using different methodologies, most of them sequenced by next generation sequencers. The initial stage of the project is highly dependent on bioinformatics analysis, providing suitable tools and integrated databases. In this work, we describe the main features of the Genosoja web database, including the pipelines to analyze some kinds of data (ESTs, SuperSAGE, microRNAs, subtractive cDNA libraries), as well as web interfaces to access information about soybean gene annotation and expression
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