Examinando por Materia "sequence"

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    Bacillus subtilis EA-CB0575 genome reveals clues for plant growth promotion and potential for sustainable agriculture
    (Springer, 2020-01-01) Franco-Sierra, N.D.; Posada, L.F.; Santa-María, G.; Romero-Tabarez, M.; Villegas-Escobar, V.; Álvarez, J.C.; Universidad EAFIT. Departamento de Ciencias; Biodiversidad, Evolución y Conservación
    Bacillus subtilis is a remarkably diverse bacterial species that displays many ecological functions. Given its genomic diversity, the strain Bacillus subtilis EA-CB0575, isolated from the rhizosphere of a banana plant, was sequenced and assembled to determine the genomic potential associated with its plant growth promotion potential. The genome was sequenced by Illumina technology and assembled using Velvet 1.2.10, resulting in a whole genome of 4.09 Mb with 4332 genes. Genes involved in the production of indoles, siderophores, lipopeptides, volatile compounds, phytase, bacilibactin, and nitrogenase were predicted by gene annotation or by metabolic pathway prediction by RAST. These potential traits were determined using in vitro biochemical tests, finding that B. subtilis EA-CB0575 produces two families of lipopeptides (surfactin and fengycin), solubilizes phosphate, fixes nitrogen, and produces indole and siderophores compounds. Finally, strain EA-CB0575 increased 34.60% the total dry weight (TDW) of tomato plants with respect to non-inoculated plants at greenhouse level. These results suggest that the identification of strain-specific genes and predicted metabolic pathways might explain the strain potential to promote plant growth by several mechanisms of action, accelerating the development of plant biostimulants for sustainable agricultural. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.
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    Unsupervised fuzzy binning of metagenomic sequence fragments on three-dimensional Barnes-Hut t-Stochastic Neighbor Embeddings
    (Institute of Electrical and Electronics Engineers Inc., 2018-01-01) Ariza-Jimenez L.; Quintero O.L.; Pinel N.; Universidad EAFIT. Departamento de Ciencias; Biodiversidad, Evolución y Conservación
    Shotgun metagenomic studies attempt to reconstruct population genome sequences from complex microbial communities. In some traditional genome demarcation approaches, high-dimensional sequence data are embedded into two-dimensional spaces and subsequently binned into candidate genomic populations. One such approach uses a combination of the Barnes-Hut approximation and the t -Stochastic Neighbor Embedding (BH-SNE) algorithm for dimensionality reduction of DNA sequence data pentamer profiles; and demarcation of groups based on Gaussian mixture models within humanimposed boundaries. We found that genome demarcation from three-dimensional BH-SNE embeddings consistently results in more accurate binnings than 2-D embeddings. We further addressed the lack of a priori population number information by developing an unsupervised binning approach based on the Subtractive and Fuzzy c-means (FCM) clustering algorithms combined with internal clustering validity indices. Lastly, we addressed the subject of shared membership of individual data objects in a mixed community by assigning a degree of membership to individual objects using the FCM algorithm, and discriminated between confidently binned and uncertain sequence data objects from the community for subsequent biological interpretation. The binning of metagenome sequence fragments according to thresholds in the degree of membership opens the door for the identification of horizontally transferred elements and other genomic regions of uncertain assignment in which biologically meaningful information resides. The reported approach improves the unsupervised genome demarcation of populations within complex communities, increases the confidence in the coherence of the binned elements, and enables the identification of evolutionary processes ignored in hard-binning approaches in shotgun metagenomic studies. © 2018 IEEE.