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MCB 317 Genetics and Genomics

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,

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MCB 317 Genetics and Genomics

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  1. MCB 317Genetics and Genomics Topic 11 Genomics

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

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

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

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

  6. Northern Blots 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 Qualitative Change in Transcription Analysis of Tissue Specific Transcription

  7. Northern Blots 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 A B 1 2 -> Quantitative Change in Transcription

  8. 1 5 2 6 3 7 4 8 DNA Microarrays 1=DNA from gene 1, 2 = DNA from Gene 2, etc… Where get DNA??? PCR!

  9. 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

  10. Lodish 9-36

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

  12. 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.

  13. Hartl Fig 13.30

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

  15. Examples of Microarray Color Schemes

  16. Another way to view the data: computer conversion to fold effect Red = condition 1, Green = condition 2 Fold change from condition 1 to condition 2 +2 +1.5 +2 0 0 -1.5 -2 -4 0 +3 -3 +1.2 0 +3 +4 -2

  17. Another way to view the data: computer conversion to fold effect Red = condition 1, Green = condition 2 Fold change from condition 1 to condition 2 +2 +1.5 +2 > -4 fold change 0 0 -2 to -4 fold change -1.5 +2 to -2 fold change -2 +2 to +4 fold change -4 0 > +4 fold change +3 -3 +1.2 0 +3 +4 -2

  18. 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

  19. 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

  20. 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

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

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

  23. Cluster Analysis

  24. Yeast cell cycle clusters

  25. Yeast cell cycle clusters part 2

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

  27. Candidate gene discovery by expression pattern

  28. 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

  29. Cancer Diagnostics and Gene Discovery

  30. Cancer • 3-7 genes mutated • Histology parallels genetic progression

  31. Primary Tumor Metastasized Tumor

  32. Candidate Genes for Involvement in Metastasis

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

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

  35. 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

  36. ChIP on a chip ChIPSeq

  37. Rap1 binding sites in the yeast genome

  38. Other Uses of DNA Micro-arrays SNP genotyping Recombination Replication timing Other…..

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