1 / 83

Gene Expression Analysis

Gene Expression Analysis. Benny Shomer January 2005. Whole in situ hybridization with the myeloid-specific marker, lysozyme C. NOTE!!! Studying a static RNA expression level is far from providing the ultimate answer!.

inez-harmon
Download Presentation

Gene Expression Analysis

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Gene Expression Analysis Benny Shomer January 2005

  2. Whole in situ hybridization with the myeloid-specific marker, lysozyme C NOTE!!!Studying a static RNA expression level is far from providing the ultimate answer! The study of cellular processes and biological phenomena requires analysis of changes in levels of gene expression between various states of the cell.

  3. Expression studies rely on various hybridization protocols with labeled nucleic acid probes. • Common Labeling Agent: • Radioactive labeling. • Chemiluminescence • Fluorochromes • Horseradish Peroxidase • Biotin/Avidin systems

  4. A A A A A A A A A A A A A A A A T T T T T T T T T T T T T T T T A A A Probe Labeling Extract Total RNA Polyadenylated RNA Reverse Transcriptase+ oligo dT + dNTP mix with labeled dNTP RNAse to clean probe

  5. Detection Methods • Northern Blot: • Highly sensitive method for detection of faint signals. • Slow, consumes resources • limited in number of studied genes. • Requires a large amount of RNA and of labeled probes.

  6. Detection Methods • In-Situ Hybridization: • Detects Signals in target tissues without an extraction phase. • Difficult to quantitate and inaccurate. • limited in number of studied genes. • Low sensitivity

  7. A A A A A A A A A A A A A A A A T T T T T T T T T T T T T T T T T T T T T T T T T T T T T T T T A A A Detection Methods RT-PCR 1. 2. 3. Real-Time

  8. Higher capacities All the previously described methods, share a major common disadvantage: Limited Number of Studied Genes per Experiment Traditional Molecular Biology Concept - One Gene per One Experiment

  9. Higher capacities • Nylon membrane arrays can be “Home made” (with effort). • May be cheap to make (depends). • Can be highly sensitive. • Nylon membrane arrays consume a large quantity of labeled probe RNA. • Are time consuming. • Medium/Small size array. • Single-color analysis

  10. Higher capacities

  11. The Need for Precise Spotting • Varying quantities of DNA between spots • Different diameters of spots • Different shapes of spots • Smears and cracks • Dispersion of material within spot is not uniform Artifacts

  12. Precise Spotting Pin-and-Ring System

  13. Precise Spotting Pin-and-Ring System

  14. Capillary Force Precise Spotting Quill System

  15. Precise Spotting Quill System

  16. Higher capacities

  17. Higher capacities • Glass slide arrays are still limited in number of spots and require a relatively high volume of labeled RNA. • For every spot on the slide, target DNA needs to be specifically synthesized.

  18. RFLP Based Differential Expression BamH I Bgl III BsoB I Fok I Nae I

  19. RFLP Based Differential Expression BamH I Bgl III BsoB I Fok I Nae I Store Virtual RFLP in Specialized Database

  20. RFLP Based Differential Expression BsoB I + Nae I Nae I + Fok I BamH I + Bgl III • Cut cDNA (from RNA) with R. enzymes • Run on High Definition Gels +/- 1bp. • Compare Real life with Virtual RFLP

  21. RFLP Based Differential Expression • Differential • No need to label probes • No need to synthesize bound DNA in advance • Full Genome coverage • Requires large quantities of RNA • Specialized methodology (patent protected) • Provided only as a service (unsuitable for local administration)

  22. 12 mm

  23. Potential Applications • Identification of complex genetic diseases • Mutation/polymorphism (SNP) detection • Pathogen analysis • Differential expression of genes over time, between tissues, between states

  24. Joseph L. DeRisi, Vishwanath R. Iyer, Patrick O. Brown (1997) Exploring the Metabolic and Genetic Control of Gene Expression on a Genomic Scale. Science, Vol 278, Issue 5338, 680-686 Classics… Diauxic Shift On Glucose rich medium, the preferred metabolic method of budding yeast, is converting Glucose into Ethanol. When Glucose is exhausted, the cell turns to other energy sources, mainly ethanol. The shift from anaerobic fermentation of glucose to aerobic respiration of ethanol is called the "diauxic shift"

  25. DeRisi et al. • Characterize gene differential expression during thediauxic shift over the entire yeast genome. • Investigate the genetic circuitry that regulates this temporal program of gene expression accompanying the metabolic shift from fermentation to respiration. We expect a shift correlated with fundamental processes, like Carbon Metabolism, Protein Synthesis and Carbohydrate Storage.

  26. DeRisi et al. Yeast Genome Microarray (18x18mm)

  27. Cy3 Cy5 Cy5 Cy5 DeRisi et al. – The experiment 2 hours  Exponential Growth Harvesting (x7)

  28. DeRisi et al. – Findings

  29. DeRisi et al. – Findings The global pattern of gene expression was remarkably stable during exponential growth of yeast colony in glucose-rich medium. Over the first 2 hours interval only 0.3% of the genes presented a significant difference in expression.

  30. DeRisi et al. – Findings The global pattern of gene expression changed significantly as glucose was progressively depleted from the growth media during the course of the experiment. • mRNA levels for approximately 710 genes were induced by a factor of at least 2 • mRNA levels for 1030 genes declined by a factor of at least 2 • mRNA levels for 183 genes increased by a factor of at least 4 • mRNA levels for 203 genes declined by a factor of at least 4 • half of these differentially expressed genes have no currently recognized function and are not yet named.

  31. DeRisi et al. – Findings Decreased Expression Fold Change Increased Expression

  32. Microarray Design • Generic Vs. Process Oriented. • Oligo synthesis in-situ Vs. cDNA spotting. • Source of information to generate the targets (e.g. complete CDS Vs. EST) • Duplicates or Replicates of same gene. • How many controls. Placement of controls. Type of controls (“house keeping”, Spike-in, blanks).

  33. Control “Spike-in” for normalization. Microarray Design Van de Peppel et al, EMBO Reports, 4:387 (2003)

  34. Experimental Design Preparing mRNA samples: Mouse model Dissection of tissue RNA Isolation Amplification Probe labelling Hybridization

  35. Experimental Design Pooling: looking at very small amount of tissues Mouse model Dissection of tissue RNA Isolation Pooling Probe labelling Hybridization

  36. Bias Rocket Science There is a plentitude of causes for bias • Difference in binding ability of the fluorochromes • Variation in tipping – spot form and size • Variant RNA quantities • Different labs, technicians and reagents. • Technical differences between scanners • Batch variance between the chips

  37. Steps in analysis Manual Validation Image Analysis Normalization Differential Analysis Clustering and Biological Data Mining

  38. Pseudo-colour overlay Cy3 Cy5 Image Analysis Laser Scan

  39. Image Analysis “gridding” • Predetermined positions • Predetermined sub-positions • Grid-Placement controls

  40. Image Analysis Background Intensity Extraction Target Detection Target Intensity Extraction

  41. Normalization • Normalization can be based on: • All spots in the array (for low heterogeneity situations where <20% of the genes are differential. • House keeping genes (between 70 – 100 genes) • Spiked-in foreign genes (usually from a foreign species). • Invariant-Set: Try to statistically locate genes in a set with similar level of expression without prior knowledge.

  42. Normalization BEFORE AFTER

  43. R vs. G R = Log2(Red channel) G = Log2(Green channel)

More Related