6 resultados para genomics

em Universidad Politécnica de Madrid


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Two scientific schools have been in coexistence from the beginning of genetics, one of them searching for factors of inheritance and the other one applying biometrical models to study the relationships between relatives. With the development of molecular genetics, the possibilities of detecting genes having a noticeable effect in traits augmented. Some genes with large or medium effects were localized in animals, although the most common result was to detect markers linked to these genes, allowing the possibility of assisting selection programs with markers. When a large amount of simple and inexpensive markers were available, the SNPs, new possibilities were opened since they did not need the presence of genes of large or medium effect controlling a trait, because the whole genome was scanned. Using a large amount of SNPs permits having a prediction of the breeding value at birth accurate enough to be used in some cases, like dairy cattle, to halve its generation interval. In other animal breeding programs, the implementation of genomic selection is less clear and the way in which it can be useful should be carefully studied. The need for large populations for associating phenotypic data and markers, plus the need for repeating the process continuously, complicates its application in some cases. The implementation of the information provided by the SNPs in current genetic programs has led to the development of complex statistical tools, joining the efforts of the two schools, factorial and biometrical, that nowadays work closely related.

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Background: One of the main challenges for biomedical research lies in the computer-assisted integrative study of large and increasingly complex combinations of data in order to understand molecular mechanisms. The preservation of the materials and methods of such computational experiments with clear annotations is essential for understanding an experiment, and this is increasingly recognized in the bioinformatics community. Our assumption is that offering means of digital, structured aggregation and annotation of the objects of an experiment will provide necessary meta-data for a scientist to understand and recreate the results of an experiment. To support this we explored a model for the semantic description of a workflow-centric Research Object (RO), where an RO is defined as a resource that aggregates other resources, e.g., datasets, software, spreadsheets, text, etc. We applied this model to a case study where we analysed human metabolite variation by workflows. Results: We present the application of the workflow-centric RO model for our bioinformatics case study. Three workflows were produced following recently defined Best Practices for workflow design. By modelling the experiment as an RO, we were able to automatically query the experiment and answer questions such as “which particular data was input to a particular workflow to test a particular hypothesis?”, and “which particular conclusions were drawn from a particular workflow?”. Conclusions: Applying a workflow-centric RO model to aggregate and annotate the resources used in a bioinformatics experiment, allowed us to retrieve the conclusions of the experiment in the context of the driving hypothesis, the executed workflows and their input data. The RO model is an extendable reference model that can be used by other systems as well.

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The analysis of the interaction between Arabidopsis thaliana and adapted (PcBMM) and nonadapted (Pc2127) isolates of the necrotrophic fungus Plectosphaerella cucumerina has contributed to the identification of molecular mechanisms controlling plant resistance to necrotrophs.To characterize the pathogenicity bases of the virulence of necrotrophic fungi in Arabidopsis, we developed P. cucumerina functional genomics tools using Agrobacterium tumefaciens-mediated transformation.We generated PcBMM-GFP and Pc2127-GFP transformants constitutively expressing the green fluorescence protein (GFP), and a collection of random T-DNA insertional PcBMM transformants. Confocal microscopy analyses of the initial stages of PcBMM-GFP infection revealed that this pathogen, like other necrotrophic fungi, does not form an appressorium or penetrate into plant cells, but causes successive degradation of leaf cell layers

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Rhizobium leguminosarum bv. viciae establishes root nodule symbioses with several legume genera. Although most isolates are equally effective in establishing symbioses with all host genera, previous evidence suggests that hosts select specific rhizobial genotypes among those present in the soil. We have used population genomics to further investigate this observation. P. sativum, L. culinaris, V. sativa, and V. faba plants were used to trap rhizobia from a well-characterized soil, and pooled genomic DNAs from one-hundred isolates from each plant were sequenced. Sequence reads were aligned to the R. leguminosarum bv. viciae 3841 reference genome. High overall conservation of sequences was observed in all subpopulations, although several multigenic regions were absent from the soil population. A large fraction (16-22%) of sequence reads could not be recruited to the reference genome, suggesting that they represent sequences specific to that particular soil population. Although highly conserved, the 16S-23S rRNA gene region presented single nucleotide polymorphisms (SNPs) regarding the reference genome, but no striking differences could be found among plant-selected subpopulations. Plant-specific SNP patterns were, however, clearly observed within the nod gene cluster, supporting the existence of a plant preference for specific rhizobial genotypes. This was also shown after genome-wide analysis of SNP patterns.

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Most Rhizobium leguminosarum bv. viciae isolates are able to specifically nodulate plants of any of four different legume genera: Pisum, Lens, Vicia, and Lathyrus. However, previous evidence suggests that some genotypes are more adapted to a given plant host than others, and that the plant host can select specific genotypes among those present in a given soil population. We have used a population genomics approach to confirm that this is indeed the case, and to analyze the specific genotypic characteristics that each plant host selects

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Legumes establish a root-nodule symbiosis with soil bacteria collectively known as rhizobia. This symbiosis allows legumes to benefit from the nitrogen fixation capabilities of rhizobia and thus to grow in the absence of any fixed nitrogen source. This is especially relevant for Agriculture, where intensive plant growth depletes soils of useable, fixed nitrogen sources. One of the main features of the root nodule symbiosis is its specificity. Different rhizobia are able to nodulate different legumes. Rhizobium leguminosarum bv. viciae is able to establish an effective symbiosis with four different plant genera (Pisum, Lens, Vicia, Lathyrus), and any given isolate will nodulate any of the four plant genera. A population genomics study with rhizobia isolated from P. sativum, L. culinaris, V. sativa or V. faba, all originating in the same soil, showed that plants select specific genotypes from those available in that soil. This was demonstrated at the genome-wide level, but also for specific genes. Accelerated mesocosm studies with successive plant cultures provided additional evidence on this plant selection and on the nature of the genotypes selected. Finally, representatives from the major rhizobial genotypes isolated from these plants allowed characterization of the size and nature of the respective pangenome and specific genome compartments. These were compared to the different genotypes ?symbiotic and non-symbiotic?present in rhizobial populations isolated directly from the soil without plant intervention.