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ProfileGrids as a new visual representation of large multiple sequence alignments: a case study of the RecA protein family.

Roca AI, Almada AE, Abajian AC - BMC Bioinformatics (2008)

Bottom Line: Figures suitable for publication can be generated from the saved spreadsheet output of the colored matrices as well as by the export of conservation information for use in the PyMOL molecular visualization program.We demonstrate the utility of ProfileGrids on 300 bacterial homologs of the RecA family - a universally conserved protein involved in DNA recombination and repair.ProfileGrids allow large protein families to be visualized more effectively than the traditional stacked sequence alignment form.This new graphical representation facilitates the determination of the sequence conservation at residue positions of interest, enables the examination of structural patterns by using residue physical properties, and permits the display of rare sequence features within the context of an entire alignment.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Molecular Biology and Biochemistry, 560 Steinhaus Hall, University of California, Irvine, California 92697-3900, USA. aroca@uci.edu

ABSTRACT

Background: Multiple sequence alignments are a fundamental tool for the comparative analysis of proteins and nucleic acids. However, large data sets are no longer manageable for visualization and investigation using the traditional stacked sequence alignment representation.

Results: We introduce ProfileGrids that represent a multiple sequence alignment as a matrix color-coded according to the residue frequency occurring at each column position. JProfileGrid is a Java application for computing and analyzing ProfileGrids. A dynamic interaction with the alignment information is achieved by changing the ProfileGrid color scheme, by extracting sequence subsets at selected residues of interest, and by relating alignment information to residue physical properties. Conserved family motifs can be identified by the overlay of similarity plot calculations on a ProfileGrid. Figures suitable for publication can be generated from the saved spreadsheet output of the colored matrices as well as by the export of conservation information for use in the PyMOL molecular visualization program.We demonstrate the utility of ProfileGrids on 300 bacterial homologs of the RecA family - a universally conserved protein involved in DNA recombination and repair. Careful attention was paid to curating the collected RecA sequences since ProfileGrids allow the easy identification of rare residues in an alignment. We relate the RecA alignment sequence conservation to the following three topics: the recently identified DNA binding residues, the unexplored MAW motif, and a unique Bacillus subtilis RecA homolog sequence feature.

Conclusion: ProfileGrids allow large protein families to be visualized more effectively than the traditional stacked sequence alignment form. This new graphical representation facilitates the determination of the sequence conservation at residue positions of interest, enables the examination of structural patterns by using residue physical properties, and permits the display of rare sequence features within the context of an entire alignment. JProfileGrid is free for non-commercial use and is available from http://www.profilegrid.org. Furthermore, we present a curated RecA protein collection that is more diverse than previous data sets; and, therefore, this RecA ProfileGrid is a rich source of information for nanoanatomy analysis.

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A screen shot of the JProfileGrid parameter settings window.
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Figure 1: A screen shot of the JProfileGrid parameter settings window.

Mentions: The program is controlled from the parameter settings window (Figure 1) which is arranged from top-to-bottom for loading an alignment, customizing the appearance of a ProfileGrid, calculating the similarity plot values, and exporting the results. The ProfileGrid viewer (Figure 2) shows the results of the JProfileGrid calculation after opening the alignment file (here of the RecA family of 300 sequences). The first 3 rows are a position ruler, a majority consensus, and a template sequence (here of the E. coli RecA homolog). The next 21 rows tabulate the frequency of the amino acid and gap characters at the corresponding MSA column position. ProfileGrid cells are color shaded according to the residue frequency value (Figure 3) with the legend in the lower-left corner of the ProfileGrid viewer read from left to right as low to high conservation, respectively. The top-left corner identifies the character and the frequency of the ProfileGrid cell currently selected by the cursor. Note that each column total equals the number of sequences in the alignment. Since the ProfileGrid matrix needs only 21 residue rows to represent protein sequences, there is practically no limit to the number of homologs that can be visualized.


ProfileGrids as a new visual representation of large multiple sequence alignments: a case study of the RecA protein family.

Roca AI, Almada AE, Abajian AC - BMC Bioinformatics (2008)

A screen shot of the JProfileGrid parameter settings window.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2663765&req=5

Figure 1: A screen shot of the JProfileGrid parameter settings window.
Mentions: The program is controlled from the parameter settings window (Figure 1) which is arranged from top-to-bottom for loading an alignment, customizing the appearance of a ProfileGrid, calculating the similarity plot values, and exporting the results. The ProfileGrid viewer (Figure 2) shows the results of the JProfileGrid calculation after opening the alignment file (here of the RecA family of 300 sequences). The first 3 rows are a position ruler, a majority consensus, and a template sequence (here of the E. coli RecA homolog). The next 21 rows tabulate the frequency of the amino acid and gap characters at the corresponding MSA column position. ProfileGrid cells are color shaded according to the residue frequency value (Figure 3) with the legend in the lower-left corner of the ProfileGrid viewer read from left to right as low to high conservation, respectively. The top-left corner identifies the character and the frequency of the ProfileGrid cell currently selected by the cursor. Note that each column total equals the number of sequences in the alignment. Since the ProfileGrid matrix needs only 21 residue rows to represent protein sequences, there is practically no limit to the number of homologs that can be visualized.

Bottom Line: Figures suitable for publication can be generated from the saved spreadsheet output of the colored matrices as well as by the export of conservation information for use in the PyMOL molecular visualization program.We demonstrate the utility of ProfileGrids on 300 bacterial homologs of the RecA family - a universally conserved protein involved in DNA recombination and repair.ProfileGrids allow large protein families to be visualized more effectively than the traditional stacked sequence alignment form.This new graphical representation facilitates the determination of the sequence conservation at residue positions of interest, enables the examination of structural patterns by using residue physical properties, and permits the display of rare sequence features within the context of an entire alignment.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Molecular Biology and Biochemistry, 560 Steinhaus Hall, University of California, Irvine, California 92697-3900, USA. aroca@uci.edu

ABSTRACT

Background: Multiple sequence alignments are a fundamental tool for the comparative analysis of proteins and nucleic acids. However, large data sets are no longer manageable for visualization and investigation using the traditional stacked sequence alignment representation.

Results: We introduce ProfileGrids that represent a multiple sequence alignment as a matrix color-coded according to the residue frequency occurring at each column position. JProfileGrid is a Java application for computing and analyzing ProfileGrids. A dynamic interaction with the alignment information is achieved by changing the ProfileGrid color scheme, by extracting sequence subsets at selected residues of interest, and by relating alignment information to residue physical properties. Conserved family motifs can be identified by the overlay of similarity plot calculations on a ProfileGrid. Figures suitable for publication can be generated from the saved spreadsheet output of the colored matrices as well as by the export of conservation information for use in the PyMOL molecular visualization program.We demonstrate the utility of ProfileGrids on 300 bacterial homologs of the RecA family - a universally conserved protein involved in DNA recombination and repair. Careful attention was paid to curating the collected RecA sequences since ProfileGrids allow the easy identification of rare residues in an alignment. We relate the RecA alignment sequence conservation to the following three topics: the recently identified DNA binding residues, the unexplored MAW motif, and a unique Bacillus subtilis RecA homolog sequence feature.

Conclusion: ProfileGrids allow large protein families to be visualized more effectively than the traditional stacked sequence alignment form. This new graphical representation facilitates the determination of the sequence conservation at residue positions of interest, enables the examination of structural patterns by using residue physical properties, and permits the display of rare sequence features within the context of an entire alignment. JProfileGrid is free for non-commercial use and is available from http://www.profilegrid.org. Furthermore, we present a curated RecA protein collection that is more diverse than previous data sets; and, therefore, this RecA ProfileGrid is a rich source of information for nanoanatomy analysis.

Show MeSH