- Technical Note
- Open Access
Rapid pair-wise synteny analysis of large bacterial genomes using web-based GeneOrder4.0
© Seto et al; licensee BioMed Central Ltd. 2010
- Received: 1 January 2010
- Accepted: 23 February 2010
- Published: 23 February 2010
The growing whole genome sequence databases necessitate the development of user-friendly software tools to mine these data. Web-based tools are particularly useful to wet-bench biologists as they enable platform-independent analysis of sequence data, without having to perform complex programming tasks and software compiling.
GeneOrder4.0 is a web-based "on-the-fly" synteny and gene order analysis tool for comparative bacterial genomics (ca. 8 Mb). It enables the visualization of synteny by plotting protein similarity scores between two genomes and it also provides visual annotation of "hypothetical" proteins from older archived genomes based on more recent annotations.
The web-based software tool GeneOrder4.0 is a user-friendly application that has been updated to allow the rapid analysis of synteny and gene order in large bacterial genomes. It is developed with the wet-bench researcher in mind.
- Gene Order
- Hypothetical Protein
- Protein Pair
- Synteny Analysis
- Synthetic Biology Approach
With the prospect now of very high-throughput and cost-effective DNA sequencing technology, and with its widespread applications routinely to many areas of biological interest, the number of available whole genome sequences grows at an astronomical rate. The Genomes Online Database (GOLD)  lists 957 complete and published bacterial genomes to date, with 3570 classified as "ongoing" (as of Dec. 2009). As a result of this tsunami of data, more genome analysis tools are needed in order to mine these data effectively, particularly for the bench scientist who may not be computer-savvy but is interested in using the genome data. Software tools have been developed for the analysis of gene order and synteny, which are important because they can be used to understand prokaryotic relationships and the evolution of their genomes , as well as to aid in gene function annotation , and to parse functional coupling prediction between genes in gene clusters . In addition, new metrics are necessary in comparative genomics and systems biology to describe newly available sequenced genomes ; gene order and synteny may be used as one of these metrics to describe genomes.
Unfortunately, some of these useful and needed software tools have become software "orphans" and are no longer available or supported, for one reason or another . In addition, some tools are not easily available to a wet-bench investigator as the tools must be downloaded, installed and compiled for use, i.e., problematic for non-computationally savvy users. In contrast, GeneOrder4.0 is a user-friendly, web-based tool that has been updated for the analysis of gene order and synteny between two large bacterial genomes. Previous versions of GeneOrder [7, 8] were limited to viral and smaller bacterial genomes analyses (up to ~2 Mb), and have been useful since its inception; that is, as noted there are many bacterial species of interest that contain smaller genomes. The GeneOrder algorithm also enables the finding of "core" sets of genes are being used in a comprehensive re-survey of the relationships and taxonomy of the bacteriophages [9, 10]. In response to requests, GeneOrder4.0 now performs rapid "on-the-fly" analysis of large bacterial genomes, up to at least 8 Mb size, with most analyses being completed between 5-10 minutes. This is achieved by implementing the "BLAST-like alignment tool" (BLAT) which performs more rapid "all-against-all" protein comparisons . The result is a plot of protein similarity scores between two genomes highlighting gene order and synteny information, and proteins that have high similarity scores, based on user preference and input. Analyzing the proteins in common between two genomes gives insight into the "pan-genome" of sets of bacterial strains, which consists of these shared proteins and contrasts the unique proteins . This will be useful, for example, in developing models for metabolic and expression regulatory pathways and for developing systems for bioremediation using a synthetic biology approach, one can re-annotate rapidly the genomes sequenced earlier using the more recently annotated ones. Thus, genomes such as the metal reducing bacteria, Shewanella, can be re-engineered and modelled based on newer genomes: S. oneidensis MR-1 (4657 genes), Shewanella sp. MR-4 (4099 genes), Shewanella sp.W3-18-1 (4238 genes) and S. denitrificans OS217 (3914 genes). Additionally, these four may be analyzed to map their metabolic pathways, allowing "gaps" to be either re-annotated or alternatives be examined.
GeneOrder4.0 is implemented using Java servlets and Tomcat. The tool requires entering two genomes as GenBank genome accession numbers. Files are retrieved from GenBank and the protein sequences are extracted. These sequences then serve as the input to BLAT algorithm. The speed of BLAT is due to the indexing of the database, whereas in the original BLAST, the query is indexed. Using BLAT allows the larger genomes, beyond 1-2 Mb, to be analyzed. Each protein pair is plotted on a graph according to user-specified BLAT threshold scores (default scores are "highest" (200+), "high" (100-200), and "low" (75-100)). These threshold scores are as follows: If the score is 200+, the proteins are very likely to be homologous; if the score is 100-200, they may not be homologous but are highly similar; and if the score is 75-100, they have limited similarity. In all cases, these results point to additional analyses, including wet-bench work, to verify homologies and similarities. Pairs of related proteins, as symbols on the graph, are "hot-linked", resulting in the opening of two browser windows comprising specific GenBank protein entries. The user can then examine the protein sequences in detail and determine directions for additional analyses.
In addition to the graphical representation of gene order and synteny, a table of protein similarity scores is generated and can be viewed by clicking the link on the bottom of the plot. This table has four columns comprising the two genomes, the score and whether either of the proteins are "hypothetical" proteins. These are noted with "*" in the last column with the heading "Hypo?". This is a useful function for annotating hypothetical proteins if the corresponding protein has a function that has already been annotated, especially in more recently sequenced and annotated genomes. Again, this is more convenient for the lab-bench researcher who is not inclined to use more detailed software.
Analysis of bacterial genomes using GeneOrder4.0
To illustrate a GeneOrder4.0 application in the analysis of a pair of ca. >4 Mb bacterial genomes, Methylobacterium extorquens DM4 (NC_012988) and Methylobacterium extorquens AM1 (NC_012808) were analyzed for gene order and synteny (5.9 Mb and 5.5 Mb, respectively). A two-dimensional plot (Figure 1) displays the results: red diagonal lines of similar protein pairs, indicated by red dots, indicate genome regions of synteny and high BLAST scores. Lower scores are indicated by crosses and open squares, all which may be default minimum values or user entered. The time it takes to generate this plot is approximately 4 minutes, a vast improvement over the earlier versions. As noted, an additional application of GeneOrder4.0 is for annotating hypothetical proteins. Many older genomes that were annotated in the past have coding sequences marked as hypothetical; these "holes" have been filled in for more recently sequenced and annotated genomes. However, in most cases, the GenBank file is not amended so the researcher retrieving the annotation often may have an annotation with many "hypotheticals", despite the fact that similar and more recent genomes, e.g., multiple and additional strains of the same organism, may have these particular "hypotheticals" annotated correctly. An experienced computational-savvy researcher may have other means to determine the updated annotations, but the 'casual' and often wet-bench researcher may not have the same experience. GeneOrder4.0 allows the alignment of these "hypotheticals" to the correct and presumable homologs or closest scoring equivalent, using specified BLAST/BLAT scores. As an example of this function, in M. extorquens DM4, the corresponding protein of a "hypothetical" based on BLAT score in M. extorquens AM1 is annotated as a putative protein-L-isoaspartate O-methyltransferase (GI:240141547). Additional and closer inspection of these two coding sequences show that these two proteins have the same length of 216 amino acids and share 97.6% identity, strongly suggesting that they have a conserved function. The GenBank entry for the hypothetical protein in M. extorquens DM4 (GI:254564064) does not mention that it may be a methyltransferase; hence, wet-bench verification is suggested from this putative annotation from GeneOrder4.0.
User-friendly and web-accessible tools allow wider access and application of the information-rich burgeoning data in genome databases. For many wet-bench biologists, again, this is very convenient because no downloading and installing of software are required; no compiling or tinkering with code is necessary. In addition to the enhancements for data visualization and graphing, the major advantage of GeneOrder4.0 is that it performs rapid analysis of two large bacterial genomes, while retaining its original validated "easy to use" functionality for the pair-wise gene order and synteny analysis of smaller genomes (mitochondrial, chloroplast, viral and bacterial).
Project name: GeneOrder4.0
Project home page: http://binf.gmu.edu:8080/GeneOrder4.0
Operating system(s): Platform independent
Programming language: Java
Any restrictions to use by non-academics: Contact authors
We are grateful to both the Apache Software Foundation (Tomcat) and the Regents of the University of California (Ptolemy Plot) for open access software. Chris Ryan, GMU, provides superb systems administration in support of maintaining this and other web-based genomics tools. PM received graduate student support from George Mason University, including travel funds to present progress at conferences.
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