Igor Ulitsky

 “the branch of genetics that studies organisms in terms of their genomes (their full DNA sequences)”  Computational genomics in TAU ◦ Ron Shamir’s lab – focus on gene expression and regulatory networks ◦ Eithan Ruppin’s lab – focus on metabolism ◦ Tal Pupko’s and Benny Chor’s labs – focus on phylogeny ◦ Roded Sharan’s lab – focus on networks ◦ Noam Shomron’s lab – focus on miRNA ◦ Eran Halperin’s lab – focus on genetics

 Alignment  Protein coding gene finding  Assembly of long reads  Basic microarray data analysis  Mapping of transcriptional regulation in simple organisms  Functional profiling in simple organisms

 Determining protein abundance  Assembly of short reads  Transcriptional regulation in higher eukaryotes  “Histone code”: Chromatin modifications, their function and regulation  Functional profiling of mammalian cells  Association studies for single-gene effects  Construction and modeling of synthetic circuits

 Digital gene expression from RNA-seq studies  Prediction of ncRNAs and their function  Global mapping of alternative splicing regulation  Integration of multi-level signaling (TFs, miRNA, chromatin)  Association studies for combinations of alleles

 All microbial genomes are sequenced in E. coli  Each sequencing efforts basically introduces genes (3-8Kb fragments) into E. coli  Sometimes sequencing fails  Idea: sequencing fails  barrier to horizontal gene transfer

 Even sequencing of reads with 100s of bp will no identify many indels  Idea: sequence pairs of sequences at some distance apart from each other

 High-throughput sequencing can identify all the mutations in different cancers  20,857 transcripts from 18,191 human genes sequenced in 11 breast and 11 colorectal cancers.

 Problems: few mutations are drivers most are passangers  Most studies did not identify high frequent risk allels  But: members of some pathways are affected in almost any tumour  Network biology needed

 Using histone modifications and sequence conservation to uncover long non- coding RNAs (lincRNA)

 12 fly species were sequenced to identify ◦ Evolution of genes and chromosome ◦ Evolutionary constrained sequence elements in promoters and 3’ UTRs  Starting point – genome-wide alignment of the genomes