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Lecture 5 Post-genomics

Lecture 5 Post-genomics. Post-genomics. Post-genomics. Functional genomics (A) Identifying genes from the sequence (B) Gene expression profiling (transcriptome) (C) Model systems Proteomics Systems biology. (A) Hunting genes from the sequence. 2 broad approaches

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Lecture 5 Post-genomics

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  1. Lecture 5 Post-genomics

  2. Post-genomics

  3. Post-genomics Functional genomics (A) Identifying genes from the sequence (B) Gene expression profiling (transcriptome) (C) Model systems Proteomics Systems biology

  4. (A) Hunting genes from the sequence 2 broad approaches 1) Ab initio method (computational) 2) Experimental method

  5. 1) Ab initio method (computational) Scanning ORFs (open reading frames)

  6. Ab initio method (computational) • initiation or termination codons • Codon bias found in specific species Not all codons used at same frequency e.g.human leucine mainly coded by CTG and rarely by TTA or CTA • Exon-intron boundaries (splice sites) 5’-AG GTAAGT-3’ hit and miss affair • Upstream control sequences – e.g conserved motifs in transcription factor binding regions • CpG islands

  7. 2) experimental method Experimental evaluation based on the use of transcribed RNA to locate exons and entire genes from DNA fragment.

  8. experimental method Some strategies • Hybridisation approaches – Northern Blots, cDNA capture / cDNA select, Zoo blots • Transcript mapping: RT-PCR, exon trapping etc In this method, known DNA databases are searched to find out whether the test sequence is similar to any other known genes, suggesting an evolutionary relationship.

  9. Zoo Blot Northern Blot

  10. (B) Gene expression profiling Transcriptome complete collection of transcribed elements of the genome (global mRNA profiling) transcriptome maps will provide clues on • Regions of transcription • Transcription factor binding sites • Sites of chromatin modification • Sites of DNA methylation • Chromosomal origins of replication

  11. COMPUTATIONAL APPROACH Homology searches(BLAST searches) - Orthologous genes (homologues in different organisms with common ancestor) – comparative genomics - Paralogous genes (genes in the same organism, e.g. multigene families) - orphan genes / families

  12. The transcriptome Analysis can be done by either Microarray technology SAGE (serial analysis of gene expression) technology

  13. (a) Schematic drawing of a DNA chip. Microarray (chip)

  14. (a) Schematic drawing of a DNA chip. Microarray (chip)

  15. (a) Schematic drawing of a DNA chip. Microarray (chip) Segment of a chip

  16. (a) Schematic drawing of a DNA chip. Microarray (chip) Segment of a chip Spot containing copies of a single DNA molecule

  17. A G G DNA bases A C G T (a) Schematic drawing of a DNA chip. Microarray (chip) Segment of a chip Spot containing copies of a single DNA molecule Part of one DNA strand

  18. (b) The analysis of the hybridization process identifies genes that respond in specific ways. Cell samples are stabilized and fluorescent labels are added.

  19. A chip DNA G G G G A A A G C A A A G T T C T T T T C C A G G C C Examples of reactions

  20. Pair of complementary bases cDNA from treated cells A chip DNA G C G G C G A A T A C G C A T A G A G T A T G C T T A T A T C G C T A G C G C G C Examples of reactions

  21. Pair of complementary bases cDNA from treated cells T A cCNA from untreated cells chip DNA C G C G C G C G T A T A T A C G G C T A T A G A C G A T A T G C A T A T A T A T G C G C T A C G C G G C G C Examples of reactions

  22. (c) Computer analysis of the binding of complementary sequences can identify genes that respond to drug treatment.

  23. (c) Computer analysis of the binding of complementary sequences can identify genes that respond to drug treatment. Gene that strongly increased activity in treated cells

  24. (c) Computer analysis of the binding of complementary sequences can identify genes that respond to drug treatment. Gene that strongly increased activity in treated cells Gene that strongly decreased activity in treated cells

  25. (c) Computer analysis of the binding of complementary sequences can identify genes that respond to drug treatment. Gene that strongly increased activity in treated cells Gene that strongly decreased activity in treated cells Gene that was equally active in treated and untreated cells

  26. (c) Computer analysis of the binding of complementary sequences can identify genes that respond to drug treatment. Gene that strongly increased activity in treated cells Gene that strongly decreased activity in treated cells Gene that was equally active in treated and untreated cells Gene that was inactive in both groups

  27. High-throughput microarrays

  28. MODEL SYSTEMS gene inactivation methods (knockouts, RNAi, site-directed mutagenesis, transposon tagging, genetic footprinting etc) Gene overexpression methods (knock-ins, transgenics, reporter genes)

  29. RNAi RNAi mimics loss-of-function mutations Non-inheritable Lack of reproducibility

  30. How does RNAi work? http://www.nature.com/focus/rnai/animations/index.html

  31. MODEL SYSTEMS Gene overexpression methods (knock-ins, transgenics, reporter genes etc)

  32. Proteomics Analysis of protein expression Protein structure and function Protein-protein interactions Nature (2003) March 13: Insight articles from pg 194

  33. Proteomics Proteome projects - co-ordinated by the HUPO (Human Protein Organisation) Involve protein biochemistry on a high-throughput scale Problems • limited and variable sample material, • sample degradation, • abundance, • post-translational modifications, • huge tissue, developmental and temporal specificity as well as disease and drug influences. Nature (2003) March 13: Insight articles from pgs 191-197.

  34. Approaches in proteomics High throughput approach • Mass- spectrometry • Array based proteomics • Structural proteomics Nature (2003) March 13: Insight articles from pgs 191-197.

  35. High throughput approaches in proteomics 1) Mass spectrometry-based proteomics: relies on the discovery of protein ionisation techniques. used for • protein identification and quantification, • profiling, • protein interactions and • modifications. Nature (2003) March 13: Insight articles from pgs 191-197

  36. Identification of proteins in complex mixtures two dimensional gels and mass spectrometry

  37. two dimensional gels 19_09.jpg

  38. Mass spectrometry (MS) Nature (2003) March 13: Insight articles from pgs 191-197

  39. Principle of MS ionizer source: converts analyte to gaseous ions mass analyser: measures mass-to-charge ratio (m/z)detector: registers the number of ions at each m/z

  40. Types of ionizer sources • Electrospray ionisation (ESI) • matrix-assisted laser desortion/ionisation (MALDI) • MALDI-MS - simple peptide mixtures whereas • ESI-MS - for complex samples. Nature (2003) March 13: Insight articles from pgs 191-197.

  41. 2) Array-based proteomics Based on thecloning and amplification of identified ORFs into homologous (ideally used for bacterial and yeast proteins) or sometimes heterologous systems (insect cells which result in post-translational modifications similar to mammalian cells). A fusion tag (short peptide or protein domain that is linked to each protein member e.g. GST) is incorporated into the plasmid construct. Nature (2003) March 13: Insight articles from pgs 191-197.

  42. Array based proteomics…. a.  Protein expression and purification b.  Protein activity: Analysis can be done using biochemical genomics or functional protein microarrays. c.  Protein interaction analysis two-hybrid analysis (yeast 2-hybrid), FRET (Fluorescence resonance energy transfer), phage display etc d. Protein localisation: immunolocalisation of epitope-tagged products. E.g the use of GFP or luciferase tags Nature (2003) March 13: Insight articles from pgs 191-197.

  43. Array based proteomics…. Protein chips Antibody chips – arrayed antibodies Antigen chips – arrayed antigens Functional arrays – arrayed proteins Protein capture chips – arrayed capture agents that interact with proteins e.g. BIAcore Solution arrays – nanoparticles Nature (2003) March 13: Insight articles from pgs 191-197.

  44. 3) Structural proteomics 19_14.jpg

  45. 3) Structural proteomics 19_14.jpg

  46. Identification of protein-protein interactionsaffinity capture/mass spectrometry Fig. 10. 31

  47. Identification of protein-protein interactionsPhage display Fig. 10.32

  48. Systems Biology – the global study of multiple components of biological systems and their interactions • New approach to studying biological systems has made possible • Sequencing genomes • High-throughput platform development • Development of powerful computational tools • The use of model organisms • Comparative genomics

  49. Six steps in systems approach • Formulate computer based model for the system • Discovery science to define as many of the system’s elements as possible • Perturb the system genetically or environmentally • Integrating levels of information form perturbations • Formulate hypothesis to explain disparities between model and experimental data • Refine the model after integrating data

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