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Research Proposal On Genome Organization Of A Rhizobacteria

857 words - 4 pages

Heavy metal pollution of soil is a significant environmental problem and has its adverse effect on human health and agriculture. Rhizosphere, as an important interface of soil and plant, plays a significant role in phytoremediation , in which, microbial populations are known to affect heavy metal mobility and availability to the plant [1] [2] through improve trace element solubility in the rhizosphere, release of organic acids, production of co2 by respiration process, chelating agents, acidification, organic matter decomposition, phosphate solubilization and redox changes, and therefore, have potential to enhance phytoremediation processes [3]. In order to understand the mechanisms involved in the transfer and mobilization of heavy metals by rhizobacteria and to conduct research of microbial genomic sequence from rhizosphere of plants growing on heavy metal contaminated soils. However, genome of an organism is a complete genetic sequence on one set of chromosomes. The genome sequence in an organism requires the DNA sequences for each of the chromosomes. Homologous recombination between reiterated DNA sequences generates different types of genomic rearrangements [4] [5]. As the number of available genome sequences increases, genomic analysis is difficult to carry out without a suitable platform gathering not only curated annotation results using standardized computational methods. However, the genomic design hypothesis suggests that the shorter introns of highly expressed genes [6]. The ‘‘mutational bias’’ model suggests that it reflects regional mutation biases in rates of insertion and deletion [7], while the ‘‘genomic design’’ model postulates that it reflects selection for genomic organization to enable control of gene expression [8]. Moreover, prodigal version 2.60 [9] was performed to predict open reading frames (ORFs) and resulting ORFs were further annotated by comparison with NCBI-NR and Blast2GO [10]. The metabolic pathways were examined through KAAS (KEGG Automatic Annotation Server). SAGA (Sequence features generating application) can generate features from raw sequences by apply existing annotated genome information like ORF regions, promoter regions, calculate physical structures of DNA sequence such as DNA curvature or bend ability, compute genome features like GC Skew [11], AT Content [12] or any other quantifiable sequence features. Finally we conclude the study of genome sequence will provide the basis for a better understanding of its genetic background, which in turn will aid future studies.

Aim and objective of the proposed research:
1. The main goal of the genomic design is to obtain Rhizobacteria strain containing all the genetic information in a single replicon.
2. To develop a web-based computational system to collect, analyze, centralize, and integrate genomic and related...

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