1. Work Process Using Enrich Load biological data Check enrichment of crossed data sets Extract statistically significant results Multiple hypothesis correction Cluster gene sets Save results  Continue to develop  More data available out there  Build a branched regulation network for the Yeast and other species Tali Goren, Ohad Manor, Tommy Kaplan and Nir Friedman School of Computer Science & Engineering, The Hebrew University, Israel Which Biological pathway involves a given TF? 3 STE12 RAP1 YAP5 MSN2 SFP1 FHL1 GAT1 Binary values Ribosomal Stress Cell cycle Metabolism HG test Significance threshold Ribosomal Stress Cell cycle Metabolism STE12 RAP1 YAP5 MSN2 SFP1 FHL1 GAT1 P-values Gene1 Gene2 Gene3 Gene4 Gene5 Gene6 Gene7 Gene8 Gene9 Gene10 Ribosomal Stress Cell cycle Metabolism GO Gene1 Gene2 Gene3 Gene4 Gene5 Gene6 Gene7 Gene8 Gene9 Gene10 ChIP STE12 RAP1 MSN2 FHL1 (a) (b) (c) (a) Data sets of the Yeast genes: ChIP analysis of TF binding genes promoters and GO annotations. (b) Performing a Hyper-Geometric test results in a matrix of p-values. (c) Conversion to a binary matrix using a threshold.The result shows which TFs are enriched along with certain GO annotation and one can infer that this TF may be involved in that Biological process (e.g. RAP1, SFP1, FHL1 in ribosomal processes) Metabolism Stress Cell cycle (a) Yeast Regulation Network 4 (a) A partial regulation network of Yeast cell was created using the method described at (3). (b) Zooming into the network, we see that ribosomal related transcription factors were predicted with no false positives. (c) In the process of Iron utilization, two TF are known to utilize iron, and the third is known to utilize Proline. (b) (c) Studying FHL1- Experimental Conditions 6 (a) Data sets of the Yeast genes: gene expression in various experiments and ChIP of gene binding to FHL1 TF. (b) Unpaired T-test results in a matrix of p-vals, where each cell represents the resulting p-value for the corresponding vectors, which is converted to a binary matrix by a threshold. (c) Same expression experiments, regarding various conditions such as temperature, starvation, stress etc. (d) Hyper-Geometric test results in a matrix of p-vals, connecting FHL1 to various experimental conditions. Enriched conditions may be extracted (e.g. heat shock, invasive growth). 1 FHL1-Summary 7 Enriched conditions Growth Stress response Enriched GO annotations Ribosome assembly RAP1 SFP1 GAT3 Enriched TFs (a)(b) (c) (a) Using the previously described methods, one can learn about enriched experimental conditions along with FHL1. Growth conditions and stress response show enrichment. (b) A GO annotation which shows enrichment for FHL1 is Ribosome assembly. (c) RAP1, SFP1 and GAT3 areTFs which are best correlated to FHL1 in the sense of genes regulated, all known to be highly involved in ribosome biogenesis. Summary and Future Directions 9 Studying FHL1-Using Related TF’s 5 (a) ChIP analysis of gene binding to the FHL1 transcription factor, and ChIP analysis of all the other TFs. (b) Hyper-Geometric test results in a matrix of p-values, connecting the FHL1 transcription factor to all the other TFs of Yeast. Enriched TFs resemble in genes regulated by them to FHL1 (e.g. RAP1, GAT3 are similar and FKH2 is not) What is known about FHL1?  Putative transcriptional regulator  Predicted to be involved in stress response  Required for rRNA processing  Null mutant shows reduced growth rate  Can we discover these properties using ? Gene1 Gene2 Gene3 Gene4 Gene5 Gene6 Gene7 Gene8 Gene9 Gene10 FHL1 Gene1 Gene2 Gene3 Gene4 Gene5 Gene6 Gene7 Gene8 Gene9 Gene10 ChIP HG test RAP1 FKH2 MBP1 GAT3 SOK2 P-values FHL1 (a) (b) (a) Studying Heat shock Effect 8 Unpaired T-test genes Gene1 Gene2 Gene3 Gene4 Gene5 Gene6 Gene7 Gene8 Gene9 Gene10 Exp. Gene1 Gene2 Gene3 Gene4 Gene5 Gene6 Gene7 Gene8 Gene9 Gene10 Localization HG test Exp.1 Exp.2 Exp.3 Exp.4 Exp.5 P-values Mitochondria Bud Neck Vacuole Cell periphery Nucleus Exp.1 Exp.2 Exp.3 Exp.4 Exp.5 Mitochondria Bud Neck Vacuole Cell periphery Nucleus Exp.1 Exp.2 Exp.3 Exp.4 Exp.5 Binary values Short HS Medium HS Long HS Severe HS Moderate HS P-values Short HS Medium HS Long HS Severe HS Moderate HS Cell periphery Mitochondria (a) (b) (c) (d) (e) (a) Gene expression in various experiments and Localization analysis of genes using GFP marking. (b) Unpaired T-test outputs a matrix of the resulting p-vals. A red cell represents a significant p-value, meaning that genes allocated to a certain cellular compartment show significant difference in expression than genes which do not have the same localization. (c) Conversion to a binary matrix using a threshold. (d) A binary values set for the same experiments, of various conditions involving a heat shock (e.g. temp., length, etc.) (e) Hyper-Geometric results in a matrix of p-vals, connecting the mitochondrial genes and the cell periphery genes to various heat shock conditions. The results suggest mit. genes they are more effected by heat shock than cell periphery genes. Is the effect of a heat shock on peripheral proteins different than the affect on mitochondrial proteins? References  Joseph T. et al. The transcription factor Ifh1 is a key regulator of yeast ribosomal protein genes. Nature. 2004. 432: 1054-1058.  Dietmar E. Martin et al. TOR Regulates Ribosomal Protein Gene Expression via PKA and the Forkhead Transcription Factor FHL1.  Cell. 2004. 119(7): 969-979.  Audry P. Gasch et al. Genomic Expression Programs in the Response of Yeast Cells to Environmental Changes. Mol. Biol. Cell. 2000. 11(12): 4241 – 4257. 1 Problems in Molecular Biology - A computational Aid Tool for Finding Enrichment in Various Data Sets Computational tool to check statistical enrichment Implemented in Perl Interactive command line May be scripted… Concatenate tests and matrix operations Data manipulation functions and queries What is ? 2 Spearman Correlation Pearson Correlation Quantify association between two variables Chi-Square testWilcoxon testPaired T test Compare two paired groups Kolmogorov- Smirnov Unpaired T test Compare two unpaired groups Binary Measurements Non- Parametric Tests Parametric Tests Do genes with a common expression pattern share the same sub-cellular localization? Which Transcription Factors regulate Amino Acid Biosynthesis? Mitochondrion Cell Periphery Does a heat shock affect peripheral proteins more than it affects mitochondrial proteins?