High-resolution genome-wide scan of genes, gene-networks and cellular systems impacting the yeast ionome
- Equal contributors
1 Department of Statistics, Purdue University, West Lafayette, IN, USA
2 Institute of Biological and Environmental Science, University of Aberdeen, Scotland, UK
3 USDA-ARS Plant Genetics Research Unit, Donald Danforth Plant Science Center, St. Louis, MO, USA
4 Department of Crop and Soil Sciences, Cornell University, Ithaca, NY, USA
5 Department of Computer Science, Purdue University, West Lafayette, IN, USA
6 Cyber Center, Purdue University, West Lafayette, IN, USA
7 Current address: Qatar Computing Research Institute, Qatar Foundation, Doha, Qatar
BMC Genomics 2012, 13:623 doi:10.1186/1471-2164-13-623Published: 14 November 2012
Additional file 1: Table S1:
Moderated Z-scores for all significant genes in the KO dataset that pass the annealing process. Elements highlighted in yellow with red text passed the significance difference cut of (−3.328, 3.473). Table S2 Moderated Z-scores for all significant genes in the KOd dataset that pass the annealing process. Elements highlighted in yellow with red text passed the significance difference cut of (−3.527, 3.572). Table S3 Moderated Z-scores for all significant genes in the OE dataset that pass the annealing process. Elements highlighted in yellow with red text passed the significance difference cut of (−3.801, 3.735). Table S4 The overlap of significant genes in the KO, KOd and OE data sets. Table S5 Genes known to be involved in regulating the ionome from the literature.
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Additional file 2: Figure S1:
Growth of yeast wild-type and zrt3 deletion mutant in the presence of Cd in the growth media. Yeast were grown in YNB at 30°C with shaking (200 rpm) in the presence of various concentrations of Cd2+ and optical density measured after 48hr. Data represents means (n = 9) ± standard deviations.
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Additional file 3: Figure S2:
Directed Acyclic Graph (DAG) and pie charts for Gene Ontology (GO) data for KO (A & B), KOd (C & D) and OE (D & F) gene datasets. The R packages GOstats, Rgraphviz and graphics were utilized to perform GO enrichment, generate the DAG plots and the pie plots.
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Additional file 4: Figure S3:
Clusters of ionomic profiles using the exhaustive significance clustering (ESC) method for the KO (A), KOd (B) and OE (C) data sets of genes that have a significant impact on the ionome. The X-axis represents the elements used in the clustering and the Y-axis represents the moderated Z values used for each element. Only the genes that significantly affect at least one element and pass the annealing process are included, and only the clusters that include at least 3 genes are shown.
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Additional file 5: Figure S4:
Median elemental abundances (quantified as moderated Z-scores) of clusters generated using exhaustive significance clustering (ESC) on the ionome of yeast mutants from the KOd (A) or OE (B) data sets are visualized using a heat map. The clusters including less than three genes are not shown. Clusters are represented in rows and elements are represented in columns. The dendrogram represents relationships between cluster (left) and elements (top) using hierarchical clustering. The grey-scale shading on the left of the heat map visually represents the number of genes in a cluster (darker represents more genes). Numbers on the heat map are moderated Z-scores for each element within each cluster. The highlight color of the numbers represents the magnitude of the abundance - green if the median elemental is less than −3.527 (A) or −3.801 (B) , yellow if it is greater than 3.572 (A) or 3.735 (B), a gradient of blue if between the lower significance cut of and 0, and a gradient of magenta if between 0 and the upper significance cut off. The yellow and green colors emphasize the elements that are significantly positively changed or significantly negatively changed in each of the clusters.
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Additional file 6: Figure S5:
Visualization of ionomic gene interaction networks for all elements quantified in the ionome of yeast in the knockout collection (KO). For each element quantified in the KO data genes that significantly affect the abundance of that element were selected and an interaction network built based on known protein protein and genetic interactions. Protein protein and genetic interaction information were obtained from BioGRID . Nodes represent genes, node color represents the direction of changes in elemental abundance (magenta increase in abundance, blue decrease in abundance), and node size represents the magnitude of the change in the ionome based on moderated Z-score. Lines joining the nodes (edges) in the graph represent the interactions. The type of line used for the edge represents the type of known interaction between the pairs of genes, with a dotted line representing a genetic interaction, and solid line represents a physical interaction. Numbers on the edges represent the correlation between connected nodes (genes) based on the ionomic profiles of the loss of function mutants in genes represented by the nodes. Only networks are shown with at least 2 nodes and 1 edge.
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