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Genomic DNA in Prokaryotes

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The genome of most prokaryotic organisms consists of double-stranded DNA organized into one circular chromosome in a region of cytoplasm called the nucleoid. The chromosome is tightly wound, or supercoiled, for efficient storage. Prokaryotes also contain other circular pieces of DNA called plasmids. These plasmids are smaller than the chromosome and often carry genes that confer adaptive functions, such as antibiotic resistance.
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Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

A computational genomics pipeline for prokaryotic sequencing projects.

Andrey O Kislyuk¹, Lee S Katz, Sonia Agrawal

¹School of Biology, Georgia Institute of Technology, Atlanta, GA 30332, USA.

Bioinformatics (Oxford, England)

|June 4, 2010

Summary

A new open-source pipeline automates prokaryotic genome sequencing, assembly, gene prediction, and annotation. This bioinformatics tool enhances data interpretation and is suitable for sensitive genomic projects.

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Area of Science:

Computational genomics
Bioinformatics
Prokaryotic genetics

Background:

High-throughput sequencing technologies have advanced prokaryotic genome research.
A lack of integrated, off-the-shelf bioinformatics solutions hinders the interpretation of sequencing data.
The need for custom informatics support impedes accessibility to high-throughput sequence data.

Purpose of the Study:

To present a self-contained, automated, open-source computational pipeline for prokaryotic genome sequencing projects.
To provide a solution for combined genome assembly, gene prediction, annotation, and data presentation.
To address the need for accessible bioinformatics tools in high-throughput sequencing.

Main Methods:

Developed an automated pipeline integrating multiple assemblers and gene predictors.
Implemented functional annotation of genes and gene products, including virulence factors.
Ensured all computational components run locally for data security and sensitive projects.

Main Results:

The pipeline successfully analyzed *Neisseria meningitidis* and *Bordetella bronchiseptica* genomes.
It supports enhanced or manually assisted reference-based assembly.
Functional annotation includes virulence-related features, beneficial for pathogenic prokaryote research.

Conclusions:

The presented open-source pipeline offers a comprehensive solution for prokaryotic genome analysis.
Its local execution capability makes it ideal for sensitive genomic data.
This tool democratizes high-throughput sequence data interpretation for researchers worldwide.