Algal Functional Annotation Tool: a web-based analysis suite to functionally interpret large gene lists using integrated annotation and expression data

Abstract

Background: Progress 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.

Description: The 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.

Conclusions: The 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.

Figure 1

Algal Functional Annotation Tool. The front page of the Algal Functional Annotation Tool. A 'Quick Start' analysis is available to test for enrichment using the richest annotation databases included in the tool. Other features accessible from the sidebar include more specific enrichment tests (based on biological pathways, ontology terms, or protein families), a gene identifier conversion tool, a manual annotation search tool, and an expression similarity search tool.

Figure 2

Annotation Enrichment Results. Annotation enrichment results, sorted by ascending hypergeometric p-values, are shown in expandible/collapsible HTML tables such as the one shown. When expanded, the genes within the user-submitted list containing the expanded annotation are shown alongside additional statistical information. All results are downloadable as tab-delimited text files.

Figure 3

Dynamic Visualization of Gene Lists onto KEGG Pathway Maps. Dynamic KEGG pathway maps may be visualized to show the different proteins within a user-submitted gene list. Shown is the 'Sulfur Metabolism' dynamic pathway with the matching proteins submitted highlighted in red. In this example, the submitted gene list is drawn from literature characterizing Chlamydomonas under sulfur-deprived conditions [26].

Figure 4

Expression Similarity Search Tool Results. An example of the results from the Gene Similarity Search Tool. Pairwise distances between resulting genes and the submitted gene are shown in the lower right corner when the mouse hovers over a gene of interest. Whenever applicable, a short description of the resulting gene is also shown when hovering over a gene. Expression data is shown when hovering over a point of the colormap.