MCB 317 Genetics and Genomics Topic 11 Genomics

Readings Genomics: Hartwell Chapter 10 of full textbook; chapter 6 of the abbreviated textbook

Concept “Genomics” and Genomic techniques” are Often “High-throughput” versions of Standard Techniques in Genetics, Molecular Biology, Biochemistry or Cell Biology Single gene/protein Most/all genes/proteins in an Organism

Ab Protein Txn Profile Gene Orthologs and Paralogs Mutant Gene Biochemistry Genetics Mutant Organism A C F Subunits of Protein Complex B, G D E Protein Profile/ Localization Genomics: High-throughput genetics Genomics B, G H

Genomics Summary A.Microarrays: expression profiling and other uses B.Global Gene Knockouts C.Global protein localization in yeast D.Global complex identification in yeast E.Global two-hybrid analysis in yeast and other organisms F.RNAi G.Transgenics, gene “knock-outs” (genetics not genomics) H.Human Genome Project, Next Generation Sequencing, and Comparative Genomics

Northern Blots Qualitative Change in Transcription Analysis of Tissue Specific Transcription Isolate RNA (mRNA) from 2 tissues e.g. liver and muscle Probe = DNA from one gene Lane 1 = liver mRNA Lane 2 = muscle mRNA 1 2

Northern Blots -> Quantitative Change in Transcription Same Approach: this time mix two probes (two genes); look at relative change Probe = DNA from two genes A and B Lane 1 = liver mRNA Lane 2 = muscle mRNA 1 2 A B

DNA Microarrays =DNA from gene 1, 2 = DNA from Gene 2, etc… Where get DNA??? PCR!

DNA Microarray Outline 1. Isolate mRNA from two samples (two tissues, or two conditions- e.g. +/- hormone, glucose vs. galactose, mutant vs. wild-type organism) 2. Label one mRNA population RED Label the other mRNA population GREEN (or convert to labeled DNA) 3. Mix both sets of labeled mRNA (or DNA) and hybridize both to the DNA Microarray

Lodish 9-36

DNA Microarrays Liver mRNA = REDMuscle mRNA = GREEN 1.On in Liver, Off in Muscle = RED 2.On in Muscle off in Liver = GREEN 3.On in both = YELLOW (RED + GREEN) 4.Off in both = BLACK (no flourescence)

Intensity of color is a quantitative measure of the amount of mRNA present [extent of txn] DNA on the array is in excess, signal is proportional to the amount of RNA produced in the cell.

Hartl Fig 13.30

DNA Micro-arrays and Expression Profiling Array DNA from ORFs “Read” and quantitated by fluorescence scanner

Examples of Microarray Color Schemes

Another way to view the data: computer conversion to fold effect Red = condition 1, Green = condition 2 Fold change from condition 1 to condition

Another way to view the data: computer conversion to fold effect Red = condition 1, Green = condition 2 Fold change from condition 1 to condition > -4 fold change -2 to -4 fold change +2 to -2 fold change +2 to +4 fold change > +4 fold change

Another way to view the data: Important Note: Color scheme = fold change in condition 2 relative to condition 1 0 change = white -> both yellow and black in previous color scheme = white here

Four Yeast Experiments A. Wild-type vs. hypomorphic allele of an RNAPII subunit B. Wild-type vs. nonessential subunit of mediator C. Wild-type vs. gene X  D. Wild-type vs snf2 

Color scheme = fold change in mutant relative to wild-type Coupling Microarrays and Yeast Genetics: Mutant v. Wild-type Cell type 1 = WT Cell type 2 = Mutant

Gene Discovery via Expression Profiling 1. Micro-array 2. Rearrange data from array into a list so that genes with with similar expression patters are adjacent to each other in the list. 3. This arrangement = cluster analysis 4. Genes that display similar patterns of expression (txn) often code for proteins that are functionally related (that are involved in the same biological process)

Series of Experiments Yeast cells can be “synchronized” so that they are all in the same stage of the cell cycle 1. Asynchronous vs. early M-phase 2. Asynchronous vs. mid M-phase 3. Asynchronous vs. late M-phase 4. Asynchronous vs. early G1 5. Asynchronous vs. mid G1 etc… throughout all stages of the cell cycle

Cluster Analysis

Yeast cell cycle clusters

Yeast cell cycle clusters part 2

A = DNA Replication cluster Expression Profile Identifies Genes that may play a role in DNA replication in this example

Candidate gene discovery by expression pattern

DNA Arrays and Cancer Diagnostics Gene discovery and mechanism Many types of cancer Many subtypes of cancer 3-7 genes mutated depending on type of cancer

Cancer Diagnostics and Gene Discovery

Cancer 3-7 genes mutated Histology parallels genetic progression

Primary Tumor Metastasized Tumor

Candidate Genes for Involvement in Metastasis

Concept “Genomics” and Genomic techniques” are Often “High-throughput” versions of Standard Techniques in Genetics, Molecular Biology, Biochemistry or Cell Biology Single Gene/Protein Most/All Genes/Proteins in an Organism

Genomics Summary A.Microarrays: expression profiling and other uses B.Global Gene Knockouts C.Global protein localization in yeast D.Global complex identification in yeast E.Global two-hybrid analysis in yeast and other organisms F.RNAi G.Transgenics, gene “knock-outs” (genetics not genomics) H.Human Genome Project, Next Generation Sequencing, and Comparative Genomics

YFG encodes a DNA binding protein ChIP against epitope tagged YFG Label ChIP’d DNA Red Label total genomic DNA green Hybridize both sets of DNA to microarray that has intergenic regions and ORFs Scan array and analyze data

ChIP on a chip ChIP Seq

Rap1 binding sites in the yeast genome

Other Uses of DNA Micro-arrays 1.SNP genotyping 2. Recombination 3. Replication timing 4. Other…..