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Detecting Orthologs Using Molecular Phenotypes a case study: human and mouse Alice S Weston What is a “molecular phenotype”? mRNA expression patterns detected using microarray techniques can reveal the co-expression of two genes in the same tissue or sample Hypothesis It is speculated that orthologous genes between Human and Mouse will be coexpressed with a similar set of partners compared to a pair of non-orthologous genes that are similar at the sequence level. Why do we care? categorize the biological function of mammalian core proteins learn about the similarity of genes with little sequence homology see how orthologous genes have changed since their divergence evolutionary sequence changes can mask orthologs BLAST hit #2 true ortholog! BLAST hit #1 paralog active site coding region = mutation Methods calculated Spearman correlations used z-Fisher transform because of missing data—consider dimension built co-expression neighborhood for each human gene (center), 100 each found related genes in neighborhoods of top two BLAST hits in mouse for the central human gene Example 6814 7375 8888 10270h 51763 9092 9646 20912 20912 22258 22258 54387 54387 54194m 56399m 19062 19062 20227 22083 BLAST hit #1 20227 22083 BLAST hit #2 Methods (cont.) determined the ranks of the neighbors in relation to their central mouse gene used a sign system to tell which mouse gene was more co-expressed with the human gene asked: Are there any instances where BLAST hit #2 is the true ortholog? Results Comparison of Neighbor Gene Ranks for Top Two Mouse Genes 600 400 300 200 100 Rank Mouse Gene 1 Mouse Gene 2 496 481 466 451 436 421 406 391 376 361 346 331 316 301 286 271 256 241 226 211 196 181 166 151 136 121 106 91 76 61 46 31 16 0 1 Number of Genes 500 Results Percentage of Neighbor Genes that Ranked Better in Top Mouse Gene 120 100 80 60 40 20 Percentage of Neighbor Genes 100 96 92 88 84 80 76 72 68 64 60 56 52 48 44 40 36 32 28 24 20 16 12 8 4 0 0 Number of Top Mouse Genes 140 Results cases where the second best mouse gene in BLAST has the best co-expression with the human gene the best mouse gene in BLAST has the best co-expression with the human gene ~62.9% of the time results look promising if sample size is increased problems along the way…. not enough microarray co-expression data to rank most of the neighbors some human genes have no predicted orthologs in mouse—for building mouse neighborhoods limited sample size: some human genes do not have two orthologs in mouse—to test hypothesis ….solutions do more microarray experiments, increase amount of data compare human genes to another species with more known orthologs Acknowledgments Josh Stuart Reading: Barak A Cohen, Yitzhak Pilpel, Robi D. Mitra, and George M. Church. (2002) Discrimination between Paralogs using Microarray Analysis: Application to the Yap1p and Yap2p Transcriptional Networks. Molecular Biology of the Cell. 13, 1608 – 1614. Happy Spring Break!!!