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Genomic adaptation of prokaryotic organisms at high temperature.

ABSTRACT: One of the central issues of evolutionary genomics is to find out the adaptive strategies of microorganisms to stabilize nucleic acid molecules under high temperature. Thermal adaptation hypothesis gives a link between G+C content and growth temperature if there is a considerable variation of guanine and cytosine content between species. However, there has been a long-standing debate regarding the correlations between genomic GC content and optimal growth temperature (Topt). We urged that adaptation to growth at high temperature requires a coordinated set of evolutionary changes affecting: (i) nucleic acid thermostability and (ii) stability of codon-anticodon interactions. Moreover, in Bacillaceae family we have demonstrated that a higher genomic GC level do not have any role in stabilizing mRNA secondary structure at high growth temperature. Comparative analysis between homologous sequences of thermophilic Thermus thermophilus and mesophilic Deinococcus radiodurans suggests that increased levels of GC contents in the coding sequence corresponding to strand structure of Thermus thermophilus genes have stabilizing effect on the mRNA secondary structure, whereas increased levels of GC contents in coding sequences corresponding to aperiodic structure have destabilizing effect on the mRNA secondary structure. In this perspective, a critical review of thermal adaptation hypothesis is further advocated.

SUBMITTER: Basak S

PROVIDER: S-EPMC2951671 | biostudies-literature | 2010 Feb

REPOSITORIES: biostudies-literature

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Genomic adaptation of prokaryotic organisms at high temperature.

Basak Surajit S Mukhopadhyay Pamela P Gupta Sanjib Kumar SK Ghosh Tapash Chandra TC

Bioinformation 20100228 8

One of the central issues of evolutionary genomics is to find out the adaptive strategies of microorganisms to stabilize nucleic acid molecules under high temperature. Thermal adaptation hypothesis gives a link between G+C content and growth temperature if there is a considerable variation of guanine and cytosine content between species. However, there has been a long-standing debate regarding the correlations between genomic GC content and optimal growth temperature (Topt). We urged that adapta ...[more]

PMID: 20975899

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Project description:BackgroundThe procedural aspects of genome sequencing and assembly have become relatively inexpensive, yet the full, accurate structural annotation of these genomes remains a challenge. Next-generation sequencing transcriptomics (RNA-Seq), global microarrays, and tandem mass spectrometry (MS/MS)-based proteomics have demonstrated immense value to genome curators as individual sources of information, however, integrating these data types to validate and improve structural annotation remains a major challenge. Current visual and statistical analytic tools are focused on a single data type, or existing software tools are retrofitted to analyze new data forms. We present Visual Exploration and Statistics to Promote Annotation (VESPA) is a new interactive visual analysis software tool focused on assisting scientists with the annotation of prokaryotic genomes though the integration of proteomics and transcriptomics data with current genome location coordinates.ResultsVESPA is a desktop Java™ application that integrates high-throughput proteomics data (peptide-centric) and transcriptomics (probe or RNA-Seq) data into a genomic context, all of which can be visualized at three levels of genomic resolution. Data is interrogated via searches linked to the genome visualizations to find regions with high likelihood of mis-annotation. Search results are linked to exports for further validation outside of VESPA or potential coding-regions can be analyzed concurrently with the software through interaction with BLAST. VESPA is demonstrated on two use cases (Yersinia pestis Pestoides F and Synechococcus sp. PCC 7002) to demonstrate the rapid manner in which mis-annotations can be found and explored in VESPA using either proteomics data alone, or in combination with transcriptomic data.ConclusionsVESPA is an interactive visual analytics tool that integrates high-throughput data into a genomic context to facilitate the discovery of structural mis-annotations in prokaryotic genomes. Data is evaluated via visual analysis across multiple levels of genomic resolution, linked searches and interaction with existing bioinformatics tools. We highlight the novel functionality of VESPA and core programming requirements for visualization of these large heterogeneous datasets for a client-side application. The software is freely available at https://www.biopilot.org/docs/Software/Vespa.php.

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Genomic adaptation of prokaryotic organisms at high temperature.

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Genomic adaptation of prokaryotic organisms at high temperature.

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