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International Journal of Plant Genomics
Volume 2011 (2011), Article ID 373875, 4 pages
Chromosome Visualization Tool: A Whole Genome Viewer
1Department of Genetics, Development, and Cell Biology, Iowa State University, Ames, IA 50011, USA
2United States Department of Agriculture-Agricultural Research Service, Corn Insects and Crop Genetics Research Unit, Ames, IA 50011, USA
Received 14 September 2011; Accepted 4 November 2011
Academic Editor: Pierre Sourdille
Copyright © 2011 Ethalinda K. S. Cannon and Steven B. Cannon. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
CViT (chromosome visualization tool) is a Perl utility for quickly generating images of features on a whole genome at once. It reads GFF3-formated data representing chromosomes (linkage groups or pseudomolecules) and sets of features on those chromosomes. It can display features on any chromosomal unit system, including genetic (centimorgan), cytological (centiMcClintock), and DNA unit (base-pair) coordinates. CViT has been used to track sequencing progress (status of genome sequencing, location and number of gaps), to visualize BLAST hits on a whole genome view, to associate maps with one another, to locate regions of repeat densities to display syntenic regions, and to visualize centromeres and knobs on chromosomes.
Visualizing features on a whole genome (all chromosomes together) can be informative for many reasons: for identifying genome-wide patterns such as gene or repeat densities, for viewing internal duplications or synteny, for assessing clustering of genes or repeats or other features, for comparing chromosomal structures such as centromeres and pericentromeric regions, or for looking for associations between different types of genomic features. Several very capable genome browsers enable visualization of single chromosomes or regions, but few visualization tools have been developed for whole-genome-at-a-time views. We present CViT (chromosome visualization tool), for viewing a wide range of genomic features on an arbitrary set of linear regions—typically, all of the chromosomes or linkage groups for a genome.
CViT is a set of Perl scripts that generate a PNG (portable network graphics) image of features on chromosomes. It can be executed as a standalone Unix command line utility or wrapped in a web page for either static display or as part of an interactive online tool. The characteristics of the output images are highly configurable. A package containing the CViT code itself along with documentation, examples, supporting scripts, and sample web implementations can be freely downloaded from SourceForge at http://sourceforge.net/projects/cvit/.
CViT was initially developed to support the Medicago truncatula sequencing project  where it was used to display the assembled bacterial artificial chromosomes (BACs) and the status of the sequencing for each BAC. CViT was also wrapped in web pages to create interactive tools: to display BLAST  hits on the whole genome (see http://www.medicagohapmap.org/advanced_search_page.php?seq) and to search where BACs of interest are anchored on the pseudomolecules. For other projects, it has also been used to display genetic maps and contig assemblies from related species  and to correlate genetic and cytogenetic maps (http://planthub.gdcb.iastate.edu/lawrencelab/Morgan2McClintock/Version3.0/) . It has been integrated into model organism databases at the Medicago genome sequencing and HapMap projects (http://medicago.org/ and http://medicagohapmap.org/) , at MaizeGDB (http://maizegdb.org/) , at the PrOject Portal for corn (POPcorn: http://popcorn.maizegdb.org/) , and at the legume-family clade database, the Legume Information System (LIS: http://comparative-legumes.org/) . It has also been used to generate analyses and images for publication on genome structure and evolution [9–11].
Several other whole genome viewers exist, but each has a different set of capabilities than CViT. One example of a whole genome viewer is Flash GViewer (http://gmod.org/wiki/Flash_GViewer), which was developed by the GMOD project (including the GBrowse browser). GViewer is entirely web based (being implemented in Flash), whereas CViT can be used either as a standalone command line utility or embedded in a web page. GViewer also uses an XML format for its data, while CViT uses GFF-formated data to make it compatible with GBrowse and other browsers. Being implemented in Flash, GViewer slows down when many (100 s) of features are displayed. CViT can usually display several thousand features, as the features are placed on a raster image and then handed off to the web client. GViewer is an interactive tool, while CViT requires additional web programming to be made interactive in a web page; on the other hand, GViewer does not produce images for publication, which is a key use for CViT. CViT also shares some of the capabilities of another whole genome viewer, the CIRCOS genome data visualizer , with the primary exception being the linear chromosome layout in CViT and circular layout in CIRCOS. The circular layout in CIRCOS facilitates display of relationships between chromosomes, through arcs that travel within the circle that is circumscribed by the ring of chromosomes. CViT is also capable of displaying within- or between-genome synteny relationships, as shown in Figure 1, but may have a greater strength in displaying other kinds of features, where the linear chromosome layout allows separation of features across whatever linear scale has been selected. In this respect, CViT bears some resemblance to genome browsers such as GBrowse , the Ensembl Genome Browser , IGB (the Integrated Genome Browser), Artemis , and the UCSC genome browser —although those browsers are designed primarily for close, interactive examination of single chromosomes at various scales rather than large scale patterns. CViT may therefore often be useful for providing a genome-wide overview, with the task of close, interactive examination of single chromosomal regions left to one of the genome browsers above. This has been done, for example, in the implementation at LIS, where BLAST hits displayed in CViT link to 100 kb GBrowse windows around the hit in the browser for the corresponding genome.
The GFF3 data format (http://www.sequenceontology.org/gff3.shtml), referred to from here on as just “GFF,” was selected because of its ease of use and effective representation of genetic and genomic information and also because it enables sharing data with GBrowse  and other GFF-capable browsers. As much as possible, we used GBrowse data and configuration conventions to enable display of the same data in both CViT and GBrowse.
Add-on scripts are provided in the download package to aid in preparation of GFF files—for example, for conversion from BLAST output to GFF. In addition, some web implementations are provided which can be used as is or modified to fit specific needs or to serve as examples of how CViT could be used as part of a larger online resource.
CViT consists of a package of Perl scripts along with a set of add-on scripts and some basic web implementations written in PHP. It requires libgd (http://bitbucket.org/pierrejoye/gd-libgd) and the GD Perl packages GD and GD::Arrow (http://search.cpan.org/dist/GD/). It has been tested on several Linux, Unix, and Apple OS X platforms and is expected to be operational on any Unix variant that can run Perl and libgd.
The input data, in GFF format, must at a minimum contain information about at least one chromosome. All features are related to the chromosome(s) by the value in the first (seqid) column. The coordinates of each feature must lie within the start and end coordinates of its chromosome. Features can be named with the “name” attribute in the last (attribute) column, with the name optionally displayed on the image, and grouped together with the “class” attribute, with each class of features displayed in a different color.
The term “chromosome” here refers to the backbone used to display features. It could in fact be a linkage group, pseudomolecule, BAC, contig, gene, or any stretch of DNA or genetic sequence upon which features can be placed. Similarly, the coordinate system can be based on any unit of measure, such as base pairs, centimorgans, centiMcClintocks , or microns.
A “feature” can be just about anything that can be associated with “chromosome” coordinates—for example, centromeres, markers, BACs, BLAST hits, repetitive elements, or gene loci. Feature densities (such as for genes or repetitive elements) can also be displayed using the histogram glyph.
CViT output includes three files: a PNG image displaying the chromosomes and features, a legend image describing the feature glyphs, and a file of feature names and coordinates where they are located on the image. The coordinate file can be used to create interactive web pages—for example, to create an HTML image map to enable clicking on features to get more information about them or to link out to other online resources.
Manipulation of the output image is enabled by a simple but extensive configuration file. This file enables control of almost all aspects of the output image without touching the code, including selecting fonts for labels. Two freely available True Type fonts are included in the download package and any True Type Font can be added. Colors, transparency, sizes of the glyph, location of glyphs relative to the chromosome, location of their text labels, and the appearance of the chromosomes themselves and their spacing are all under configuration control.
Add-on scripts include blastp_to_gff.pl, which generates a GFF file for CViT if provided a GFF file of peptides and either a tabular BLAST output file or a two-column hash of query IDs and peptide IDs, and clusterHSP.pl, which collapses adjacent BLAST HSPs that occur within a sliding window (often appropriate for a peptide or cDNA query against pseudomolecule sequences). The web implementations provided with the package include a simple “CViT-BLAST” implementation which can be used as is or modified to fit specific needs. There is also a web utility named “CViT-web” which provides a web interface for generating CViT images. For some users this may be easier than modifying the configuration file.
3. Biological Examples
Examples of two online instances of CViT are the soybean, Medicago truncatula, and Lotus japonicus genomes at LIS (http://comparative-legumes.org/) and the maize genome at MaizeGDB (http://maizegdb.org/).
The display of the soybean genome (Figure 1) illustrates the use of CViT for showing internal synteny (chromosomal correspondences) from a whole genome duplication that is estimated to have occurred in the Glycine genus between ~5 and 13 Mya [19, 20]. The implementation at LIS also shows correspondences between the three sequenced genomes (in addition to the correspondences within the duplicated soybean genome). The LIS implementation also allows a sequence search with a multi-FASTA file. Sequence matches (BLAST hits) are color coded and link out to the genome browser for the target genome, with browser views centered around each hit.
The display of the maize genome (Figure 2) illustrates the use of CViT for showing gene density, based on gene models generated as part of the Zea mays inbred B73 genome sequencing project . The MaizeGDB use of CViT also includes a BLAST utility that displays color-coded hits on the reference genome with links to GBrowse for closer investigation.
This work was supported in part by Grants from the National Science Foundation Plant Genome Research Program DBI-0321460 to Nevin Young (for initial development by S.B.Cannon and E.K.S.Cannon), DBI-0743804 to Carolyn Lawrence and DBI-1027527 to Patrick Schnable. The authors thank Carolyn Lawrence for critical reading of the paper, Shelley Wang and Atif Ahmed for contributions to earlier versions of the software, Reka Keleman for integrating CViT in the Morgan2McClintock translator, and Benjamin Mulaosmanovic for contributions to accessory scripts and to the LIS implementation of CViT.
- N. D. Young, S. B. Cannon, S. Sato et al., “Sequencing the genespaces of Medicago truncatula and Lotus japonicus,” Plant Physiology, vol. 137, no. 4, pp. 1174–1181, 2005.
- S. F. Altschul, T. L. Madden, A. A. Schaffer et al., “Gapped BLAST and PSI-BLAST: a new generation of protein database search programs,” Nucleic Acids Research, vol. 25, no. 17, pp. 3389–3402, 1997.
- R. W. Innes, C. Ameline-Torregrosa, T. Ashfield et al., “Differential accumulation of retroelements and diversification of NB-LRR disease resistance genes in duplicated regions following polyploidy in the ancestor of soybean,” Plant Physiology, vol. 148, no. 4, pp. 1740–1759, 2008.
- C. J. Lawrence, T. E. Seigfried, H. W. Bass, and L. K. Anderson, “Predicting chromosomal locations of genetically mapped loci in maize using the Morgan2McClintock Translator,” Genetics, vol. 172, no. 3, pp. 2007–2009, 2006.
- S. B. Cannon, L. Sterck, S. Rombauts et al., “Legume genome evolution viewed through the Medicago truncatula and Lotus japonicus genomes,” Proceedings of the National Academy of Sciences of the United States of America, vol. 103, no. 40, pp. 14959–14964, 2006.
- C. J. Lawrence, L. C. Harper, M. L. Schaeffer, et al., “MaizeGDB: the maize model organism database for basic, translational, and applied research,” International Journal of Plant Genomics, vol. 2008, Article ID 496957, 2008.
- E. K. S. Cannon, S. M. Birkett, B. M. Braun, et al., “POPcorn: an online resource providing access to distributed and diverse maize project data,” submitted to. International Journal of Plant Genomics.
- S. B. Cannon, G. D. May, and S. A. Jackson, “Three sequenced legume genomes and many crop species: rich opportunities for translational genomics,” Plant Physiology, vol. 151, no. 3, pp. 970–977, 2009.
- C. Ameline-Torregrosa, B. B. Wang, M. S. O'Bleness et al., “Identification and characterization of nucleotide-binding site-leucine-rich repeat genes in the model plant Medicago truncatula,” Plant Physiology, vol. 146, no. 1, pp. 5–21, 2008.
- D. J. Bertioli, M. C. Moretzsohn, L. H. Madsen et al., “An analysis of synteny of Arachis with Lotus and Medicago sheds new light on the structure, stability and evolution of legume genomes,” BMC Genomics, vol. 10, article 45, 2009.
- S. B. Cannon and R. C. Shoemaker, “Evolutionary and comparative analyses of the soybean genome,” Breeding Science. In press.
- M. Krzywinski, J. Schein, I. Birol et al., “Circos: an information aesthetic for comparative genomics,” Genome Research, vol. 19, no. 9, pp. 1639–1645, 2009.
- L. D. Stein, C. Mungall, S. Shu et al., “The generic genome browser: a building block for a model organism system database,” Genome Research, vol. 12, no. 10, pp. 1599–1610, 2002.
- P. Flicek, B. L. Aken, B. Ballester et al., “Ensembl's 10th year,” Nucleic Acids Research, vol. 38, supplement 1, pp. D557–D562, 2010.
- J. W. Nicol, G. A. Helt, S. G. Blanchard Jr., A. Raja, and A. E. Loraine, “The integrated genome browser: free software for distribution and exploration of genome-scale datasets,” Bioinformatics, vol. 25, no. 20, pp. 2730–2731, 2009.
- J. Zhu, J. Z. Sanborn, S. Benz et al., “The UCSC cancer genomics browser,” Nature Methods, vol. 6, no. 4, pp. 239–240, 2009.
- P. S. Schnable, D. Ware, R. S. Fulton et al., “The B73 maize genome: complexity, diversity, and dynamics,” Science, vol. 326, no. 5956, pp. 1112–1115, 2009.
- T. K. Wolfgruber, A. Sharma, K. L. Schneider et al., “Maize centromere structure and evolution: sequence analysis of centromeres 2 and 5 reveals dynamic loci shaped primarily by retrotransposons,” PLoS Genetics, vol. 5, no. 11, Article ID e1000743, 2009.
- J. J. Doyle and A. N. Egan, “Dating the origins of polyploidy events,” New Phytologist, vol. 186, no. 1, pp. 73–85, 2010.
- J. Schmutz, S. B. Cannon, J. Schlueter et al., “Genome sequence of the palaeopolyploid soybean,” Nature, vol. 463, no. 7278, pp. 178–183, 2010.