Abstract

BackgroundProgress in genome sequencing is proceeding at an exponential pace, and several new algal genomes are becoming available every year. One of the challenges facing the community is the association of protein sequences encoded in the genomes with biological function. While most genome assembly projects generate annotations for predicted protein sequences, they are usually limited and integrate functional terms from a limited number of databases. Another challenge is the use of annotations to interpret large lists of 'interesting' genes generated by genome-scale datasets. Previously, these gene lists had to be analyzed across several independent biological databases, often on a gene-by-gene basis. In contrast, several annotation databases, such as DAVID, integrate data from multiple functional databases and reveal underlying biological themes of large gene lists. While several such databases have been constructed for animals, none is currently available for the study of algae. Due to renewed interest in algae as potential sources of biofuels and the emergence of multiple algal genome sequences, a significant need has arisen for such a database to process the growing compendiums of algal genomic data.DescriptionThe Algal Functional Annotation Tool is a web-based comprehensive analysis suite integrating annotation data from several pathway, ontology, and protein family databases. The current version provides annotation for the model alga Chlamydomonas reinhardtii, and in the future will include additional genomes. The site allows users to interpret large gene lists by identifying associated functional terms, and their enrichment. Additionally, expression data for several experimental conditions were compiled and analyzed to provide an expression-based enrichment search. A tool to search for functionally-related genes based on gene expression across these conditions is also provided. Other features include dynamic visualization of genes on KEGG pathway maps and batch gene identifier conversion.ConclusionsThe Algal Functional Annotation Tool aims to provide an integrated data-mining environment for algal genomics by combining data from multiple annotation databases into a centralized tool. This site is designed to expedite the process of functional annotation and the interpretation of gene lists, such as those derived from high-throughput RNA-seq experiments. The tool is publicly available at http://pathways.mcdb.ucla.edu.

Highlights

  • Progress in genome sequencing is proceeding at an exponential pace, and several new algal genomes are becoming available every year

  • To facilitate the analysis of Chlamydomonas genome-scale data, we developed the Algal Functional Annotation Tool, which provides a comprehensive analysis suite for functionally interpreting C. reinhardtii genes across all available protein identifiers

  • Numerous other enrichment analyses - including enrichment using pathway, ontology, protein family, or differential expression data - are available within the Algal Functional Annotation Tool

Read more

Summary

Conclusions

The Algal Functional Annotation Tool is intended as a comprehensive analysis tool to elucidate biological meaning from gene lists derived from high-throughput experimental techniques. Annotation sets from a number of biological databases have been pre-processed and assigned to gene identifiers of the green alga Chlamydomonas reinhardtii, and this annotation data may be explored in multiple ways, including the use of enrichment tests designed for large gene lists. The site enables the visualization of proteins within pathway maps Using several methods, such as inferring annotations from orthologous proteins of other organisms, the initially sparse annotation coverage of C. reinhardtii is alleviated, allowing for a more effective functional term enrichment analysis. List of Abbreviations Used API: Application Programming Interface; BLAST: Basic Local Alignment Search Tool; CGI: Common Gateway Interface; DAVID: Database for Annotation, Visualization, and Integrated Discovery; GO: Gene Ontology; KEGG: Kyoto Encyclopedia of Genes and Genomes; JGI: Joint Genome Institute; SOAP: Simple Object Access Protocol. Author details 1Department of Molecular, Cell, and Developmental Biology, University of California, Los Angeles, CA, USA.

Background
Utility and Discussion
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call