Igor Ulitsky. “the branch of genetics that studies organisms in terms of their genomes (their...
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![Page 1: Igor Ulitsky. “the branch of genetics that studies organisms in terms of their genomes (their full DNA sequences)” Computational genomics in TAU ◦](https://reader030.fdocuments.in/reader030/viewer/2022020417/56649e8b5503460f94b90802/html5/thumbnails/1.jpg)
Challenges in Computational & Functional GenomicsIgor Ulitsky
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“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
Genomics
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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
“Solved” problems
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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
“Worked on” problems
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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
“Future” problems
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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
Using sequencing to find new antibiotics
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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
Using sequencing to uncover structural variation
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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.
Mutational landscape of human cancer
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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
Mutational landscape of human cancer
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Predicting ncRNAs Using histone
modifications and sequence conservation to uncover long non-coding RNAs (lincRNA)
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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
Using conservation to uncover regulatory elements
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