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Genome Annotation and Assembly

Genome Annotation and Assembly

The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.

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Developing a biocuration workflow for AgBase, a non-model organism database.

Lakshmi Pillai¹, Philippe Chouvarine, Catalina O Tudor

¹Department of Basic Sciences, College of Veterinary Medicine, Mississippi State University, MS 39762, USA.

Database : the Journal of Biological Databases and Curation

|November 20, 2012

Summary

AgBase enhances agricultural gene product annotation using text mining and the Gene Ontology (GO). This improves biocuration efficiency by prioritizing genes and linking literature to GO terms for agricultural species.

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Area of Science:

Agricultural genomics
Bioinformatics
Gene Ontology annotation

Background:

Agricultural species lack the extensive functional annotation of model organisms.
Efficiently curating the literature for agricultural gene products is challenging due to non-standardized scientific publications.
AgBase aims to improve the annotation process for agricultural gene products.

Purpose of the Study:

To develop and implement an efficient biocuration system for agricultural gene products.
To leverage text mining for literature identification and gene product annotation.
To integrate Gene Ontology (GO) and Plant Ontology with agricultural gene data.

Main Methods:

Utilized a gene prioritization interface to rank gene products for annotation.
Developed Extracting Genic Information from Text (eGIFT), a text-mining tool to link literature to genes and GO terms.
Implemented a biocuration interface (BI) for data management and linked it to a Journal Database (JDB).
Employed text mining with disambiguation and filtering to handle ambiguous gene names and irrelevant literature.

Main Results:

AgBase successfully integrates GO and Plant Ontology for agricultural gene products.
The eGIFT tool facilitates rapid literature identification and curation by linking informative terms to GO terms.
The biocuration interface streamlines the annotation workflow, including bulk upload capabilities.
All annotations undergo GO Consortium quality checking.

Conclusions:

AgBase provides a robust platform for the annotation of agricultural gene products.
Text mining significantly enhances the efficiency and accuracy of biocuration for agricultural species.
The integrated system improves access to functional information for agricultural genes.