EGGSViz : Visualization and Exploration of Gene Clusters

1. EGGSViz : Visualization and Exploration of Gene Clusters Ankita Bhan Advisor : Prof. Sun Kim Co-advisor: Prof. Yves Brun Indiana University, Bloomington

2. Outline Background Motivation Problem Description Features Workflow 1 Workflow 2 Workflow 3 Exploration Feature 1 Exploration Feature 2 Future Work

3. Background Background Motivation Problem Description Features Workflow 1 Workflow 2 Workflow 3 Exploration1 Exploration2 Future Work Functionally related genes co-evolve, probably due to selection pressure during evolution. This leads to conservation of gene clusters across genomes (especially in microbial genomes).

4. Motivation Background Motivation Problem Description Features Workflow 1 Workflow 2 Workflow 3 Exploration1 Exploration2 Future Work Microbial genomes contain an abundance of genes with conserved proximity. Genes with conserved proximity are often co-transcribed as operons, or co-regulated as part of a larger biochemical network. Microbial Genomes contain an abundance of genes with conserved proximity forming clusters on the chromosome. Microbial Genomes contain an abundance of genes with conserved proximity forming clusters on the chromosome.

5. Motivation Background Motivation Problem Description Features Workflow 1 Workflow 2 Workflow 3 Exploration1 Exploration2 Future Work Gene clusters-Definition: Group of genes in microbial genomes with conserved proximity that are the possible candidates for being co-transcribed as operons, or co-regulated as part of a biochemical pathway. Microbial Genomes contain an abundance of genes with conserved proximity forming clusters on the chromosome. Microbial Genomes contain an abundance of genes with conserved proximity forming clusters on the chromosome.

8. Problem Description Background Motivation Problem Description Features Workflow 1 Workflow 2 Workflow 3 Exploration1 Exploration2 Future Work Predicting sets of families in genomes by interpreting a genome as a sequence of families & modeling as a gene cluster. Visualizing the clusters with the multiple genomes on a single display window is challenging as the clusters are scattered. Adding genes from a new unknown genome to a known cluster of genes is challenging. EggsViz is a tool for visualizing relationships among multiple genomes by combining all pair wise genome clusters. Exclusively developed to assist in finding corresponding genes amongst a group of genomes hence contributing to comparative genomics. Understanding the details of gene clusters is important as the conserved groups of genes in multiple genomes has a number of implications for comparative, evolutionary and functional genomics as well as synthetic biology. In case where family classification information of genes in the genome set is known, this problem can be thought as predicting sets of families in genomes by interpreting a genome as a sequence of families, and modeled as gene teamEggsViz is a tool for visualizing relationships among multiple genomes by combining all pair wise genome clusters. Exclusively developed to assist in finding corresponding genes amongst a group of genomes hence contributing to comparative genomics. Understanding the details of gene clusters is important as the conserved groups of genes in multiple genomes has a number of implications for comparative, evolutionary and functional genomics as well as synthetic biology. In case where family classification information of genes in the genome set is known, this problem can be thought as predicting sets of families in genomes by interpreting a genome as a sequence of families, and modeled as gene team

9. Features Background Motivation Problem Description Features Workflow 1 Workflow 2 Workflow 3 Exploration1 Exploration2 Future Work simultaneous visualization of all gene clusters on genome scale with zoom in/out features detailed view of individual cluster color coding scheme according to COG functional categories multiple sequence alignment of genes in a cluster selection of clusters by feeding in "genes-of-interest" by users adding a new genome and search for instances of clusters and saving the results of search

10. Features: Illustration of how EGGSVIZ works Background Motivation Problem Description Features Workflow 1 Workflow 2 Workflow 3 Exploration1 Exploration2 Future Work Workflow1 Main display of EGGSVIZ and broader view of cluster. Workflow2 Detailed view of an individual cluster Workflow 3 Further details of each gene in the Detail View window. Exploration feature 1 Visualizing our genes of interest. Exploration feature 2 Adding a new genome and saving the search.

11. Workflow 1 Background Motivation Problem Description Features Workflow 1 Workflow 2 Workflow 3 Exploration1 Exploration2 Future Work Display of all clusters on genome scale on a single display screen. Divided dynamic zoom (from low to high resolution) of genomic regions. Displays the cluster number and size(number of genes ) in a particular cluster in the main window. Highlights an individual cluster and shows the annotation information for each and every gene and cluster.

21. Workflow 2 Background Motivation Problem Description Features Workflow 1 Workflow 2 Workflow 3 Exploration1 Exploration2 Future Work How to choose a cluster? Detailed view of the individual cluster of our choice. Color Reverse and Disconnect genes options. Redirecting to a new window to show a detailed view of the individual cluster of your choice. Showing annotation information for each gene involved in the cluster. Disconnect genes and color reverse features available. On single clicking a gene the relationship with other genes in the synteny is highlighted. Color codes available for different functional catagories of COG. Features available to resize the genes. Redirecting to a new window to show a detailed view of the individual cluster of your choice. Showing annotation information for each gene involved in the cluster. Disconnect genes and color reverse features available. On single clicking a gene the relationship with other genes in the synteny is highlighted. Color codes available for different functional catagories of COG. Features available to resize the genes.

30. Workflow 3 Background Motivation Problem Description Features Workflow 1 Workflow 2 Workflow 3 Exploration 1 Exploration 2 Future Work On double clicking a gene redirection to sequence window. Sequence window retrieves sequences of genes related in the synteny. Clustalw button facilitates the multiple alignment of sequences. More features to be added to connect this information to web services.

36. Exploration Feature 1 Background Motivation Problem Description Features Workflow 1 Workflow 2 Workflow 3 Exploration 1 Exploration 2 Future Work A feature to explore the genes of interest is provided. �Input� button on the main window would prompt a window asking our genes of interest. On submitting the query we would get the complete detail of those genes and the genes would be highlighted in the detail view window.

45. Exploration Feature 2 Background Motivation Problem Description Features Workflow 1 Workflow 2 Workflow 3 Exploration 1 Exploration 2 Future Work Import an additional new Genome to the cluster on the detail view window. Connect that genome to the present cluster and predict clusters by connecting to a web server. A Hidden Markov Model is used to predict similar genes from the 4th genome.

51. Future Work Background Motivation Problem Description Features Workflow 1 Workflow 2 Workflow 3 Exploration 1 Exploration 2 Future Work Saving the results of the clusters generated after adding the 4th genome for faster and efficient lookup. Extending the cluster prediction and visualization beyond 3 genomes. Analyzing the gene clusters Phylogenetically and visualizing the results.

52. Acknowledgements