1. DNA Microarrays M. Ahmad Chaudhry, Ph. D. Director Microarray Facility University of Vermont

2. Outline of the lecture Overview of Micoarray Technology Types of Microarrays Manufacturing Instrumentation and Softwares Data analysis Applications

3. Mainly used in gene discovery Microarray Development Widely adopted Relatively young technology

4. Evolution & Industrialization 1994- First cDNAs arrays were developed at Stanford University. 1996- Commercialization of arrays 1997-Genome-wide Expression Monitoring in S. cerevisiae

5. Microarrays are simply small glass or silicon slides upon the surface of which are arrayed thousands of genes (usually between 500-20,000) Via a conventional DNA hybridization process, the level of expression/activity of genes is measured Data are read using laser-activated fluorescence readers The process is “ultra-high throughput” What are Microarrays?

6. Why use Microarrays? What genes are Present/Absent in a cell? What genes are Present/Absent in the experiment vs. control? Which genes have increased/decreased expression in experiment vs. control? Which genes have biological significance?

7. Why analyze so many genes? Just because we sequenced a genome doesn’t mean we know anything about the genes. Thousands of genes remain without an assigned function. Patterns/clusters of expression are more predictive than looking at one or two prognostic markers – can figure out new pathways

8. The 6 steps of a DNA microarray experiment (1-3) 1.Manufacturing of the microarray 2. Experimental design and choice of reference: what to compare to what? 3. Target preparation (labeling) and hybridization

9. The 6 steps of a microarray experiment (4-6) 4. Image acquisition (scanning) and quantification (signal intensity to numbers) 5. Database building, filtering and normalization 6. Statistical analysis and data mining

10. GENE EXPRESSION ANALYSIS WITH MICROARRAYS DNA Chips Miniaturized, high density arrays of oligos (Affymetrix Inc.) Printed cDNA or Oligonucleotide Arrays  Robotically spotted cDNAs or Oligonucleotides Printed on Nylon, Plastic or Glass surface

11. Affymetrix Microarrays Involves Fluorescently tagged cRNA One chip per sample One for control One for each experiment Glass Slide Microarrays Involves two dyes/one chip Red dye Green dye Control and experiment on same chip

12. Gene Chip Technology Affymetrix Inc Miniaturized, high density arrays of oligos 1.28-cm by 1.28-cm (409,000 oligos) Manufacturing Process Solid-phase chemical synthesis and Photolithographic fabrication techniques employed in semiconductor industry

13. Selection of Expression Probes Set of oligos to be synthesized is defined, based on its ability to hybridize to the target genes of interest Probes Sequence Perfect Match Mismatch Chip 5’ 3’ Computer algorithms are used to design photolithographic masks for use in manufacturing

14. Each gene is represented on the probe array by multiple probe pairs Each probe pair consists of a perfect match and a mismatch oligonucleotide

15. Photolithographic Synthesis Manufacturing Process Probe arrays are manufactured by light-directed chemical synthesis process which enables the synthesis of hundreds of thousands of discrete compounds in precise locations Lamp MaskChip

17. Affymetrix Wafer and Chip Format 1.28cm 20 - 50 µm Millions of identical oligonucleotide probes per feature 49 - 400 chips/wafer up to ~ 400,000 features/chip

19. Creating Targets Reverse Transcriptase in vitro transcription mRNA cDNA Target cRNA

20. RNA-DNA Hybridization probe sets DNA (25 base oligonucleotides of known sequence) Targets RNA

21. Non-Hybridized Targets are Washed Away “probe sets” (oligo’s) Targets (fluorescently tagged) Non-bound ones are washed away

22. Target Preparation cDNA Wash & Stain Scan Hybridize (16 hours) mRNA AAAA BBBB Biotin-labeled transcripts Fragment (heat, Mg 2+ ) Fragmented cRNA B B B B IVT (Biotin-UTP Biotin-CTP)

23. GeneChip ® Expression Analysis Hybridization and Staining Array cRNA Target Hybridized Array Streptravidin- phycoerythrin conjugate

25. Instrumentation Affymetrix GeneChip System 3000-7G Scanner 450 Fluidic Station 640 Hybridization Oven

26. Currently Available GeneChips B. subtilis Barley Genome Array Bovine Genome Array C. elegans Genome Array Canine Genome Array Chicken Genome Array Drosophila Genome Arrays E. coli Genome Arrays Human Genome Arrays Maize Genome Array Mouse Genome Arrays P. aeruginosa Genome Array Plasmodium/Anopheles Genome Array Porcine Genome Array Rat Genome Arrays Rice Genome Array Soybean Genome Array Sugar Cane Genome Array Vitis vinifera (Grape) Array Wheat Genome Array Xenopus laevis Genome Array Yeast Genome Arrays Zebrafish Genome Array Arabidopsis Genome Arrays

27. Custom GeneChips Affymetrix offers over 120 prokaryotic arrays that are manufactured by Nimblegen Inc. Custom GeneChips are also available for both Eukaryotic and Prokaryotic systems.

28. Quality Control Issues RNA purity and integrity cDNA synthesis efficiency Efficient cRNA synthesis, labeling and fragmentation Target evaluation with Test Chips

29. GENE EXPRESSION ANALYSIS WITH MICROARRAYS DNA Chips Miniaturized, high density arrays of oligos (Affymetrix Inc.) Printed cDNA or Oligonucleotide Arrays  Robotically spotted cDNAs or Oligonucleotides Printed on Nylon, Plastic or Glass surface

30. Microarray of thousands of genes on a glass slide

31. Spotted arrays 1 nanolitre spots 90-120 um diameter steel spotting pin

32. The process Building the chip: MASSIVE PCR PCR PURIFICATION and PREPARATION PREPARING SLIDESPRINTING RNA preparation: CELL CULTURE AND HARVEST RNA ISOLATION cDNA PRODUCTION Hybing the chip: POST PROCESSING ARRAY HYBRIDIZATION PROBE LABELING DATA ANALYSIS

33. Building the chip Arrayed Library (96 or 384-well plates of bacterial glycerol stocks) PCR amplification Directly from colonies with SP6-T7 primers in 96-well plates Consolidate into 384-well plates Spot as microarray on glass slides

34. Sample preparation

35. Hybridization Binding of cDNA target samples to cDNA probes on the slide cover slip Hybridize for 5-12 hours

36. LABEL 3XSSC HYB CHAMBER ARRAY SLIDE LIFTERSLIP SLIDE LABEL Humidity Temperature Formamide (Lowers the Tm) Hybridization chamber

37. Expression profiling with DNA microarrays cDNA “A” Cy5 labeled cDNA “B” Cy3 labeled Hybridization Scanning Laser 1 Laser 2 + AnalysisImage Capture

39. Image analysis The raw data from a cDNA microarray experiment consist of pairs of image files, 16-bit TIFFs, one for each of the dyes. Image analysis is required to extract measures of the red and green fluorescence intensities for each spot on the array.

40. Image analysis GenePix

41. Image analysis 1. Addressing. Estimate location of spot centers. 2. Segmentation. Classify pixels as foreground (signal) or background. 3. Information extraction. For each spot on the array and each dye signal intensities; background intensities; quality measures. R and G for each spot on the array.

42. Biological Question Sample Preparation Microarray Life Cycle Data Analysis & Modelling Microarray Reaction Microarray Detection

43. Spotted cDNA microarrays Advantages Lower price and flexibility Simultaneous comparison of two related biological samples (tumor versus normal, treated versus untreated cells) ESTs allow discovery of new genes Disadvantages Needs sequence verification Measures the relative level of expression between 2 samples

44. Data Pre-processing Filtering –Background subtraction –Low intensity spots –Saturated spots –Low quality spots (ghost spots, dust spots etc) Normalization –Housekeeping genes/ control genes

45. Affymetrix Software for Microarray Data Analysis Microarray Suite 5 Micro DB Data Mining Tool (DMT) NetAffx

46. Affymetrix Microarray Suite - Data Analysis Absolute Analysis – whether transcripts are Present or not (uses data from one probe array experiment). Comparison Analysis – determine the relative change in transcripts (uses data from two probe array experiments). Intensities for each experiment are compared to a baseline/control.

47. Microarray data analysis Scatter plots Intensities of experimental samples versus normal samples Quick look at the changes and overall quality of microarray

48. Normal vs. Normal Normal vs. Tumor

49. Lung Tumor: Up-Regulated Lung Tumor: Down-Regulated

50. Microarray data analysis Supervised versus unsupervised analysis –Clustering: organization of genes that are similar to each other –Statistical analysis: how significant are the results?

51. Hierarchical clustering Unsupervised: no assumption on samples The algorithm successively joins gene expression profiles to form a dendrogram based on their pair-wise similarities.

52. Cluster analysis of genes in G1 and G2 Chaudhry et. al., 2002

53. Publicly Available Softwares GenMAPP Visualize gene expression data on maps representing biological pathways and groupings of genes.

55. Microarray Applications Identify new genes implicated in disease progression and treatment response (90% of our genes have yet to be ascribed a function) Assess side-effects or drug reaction profiles Extract prognostic information, e.g. classify tumors based on hundreds of parameters rather than 2 or 3. Identify new drug targets and accelerate drug discovery and testing ???

56. Microarray Technology - Applications Gene Discovery- –Assigning function to sequence –Discovery of disease genes and drug targets –Target validation Genotyping –Patient stratification (pharmacogenomics) –Adverse drug effects (ADE) Microbial ID The List Continues To Grow….

57. Microarray Future Must go beyond describing differentially expressed genes Inexpensive, high-throughput, genome- wide scan is the end game for research applications Protein microarrays (Proteomics)

58. Microarray Future Publications are now being focused on biology rather than technology SNP analysis –Faster, cheaper, as accurate as sequencing –Disease association studies –Population surveys Chemicogenomics –Dissection of pathways by compound application –Fundamental change to lead validation

59. Microarray Future Diagnostics –Tumor classification –Patient stratification –Intervention therapeutics

60. Conclusion Technology is evolving rapidly. Blending of biology, automation, and informatics. New applications are being pursued –Beyond gene discovery into screening, validation, clinical genotyping, etc. Microarrays are becoming more broadly available and accepted. –Protein Arrays –Diagnostic Applications

61. W.W.W resources Complete guide to “microarraying” http://cmgm.stanford.edu/pbrown/mguide/ http://www.microarrays.org –Parts and assembly instructions for printer and scanner; –Protocols for sample prep; –Software; –Forum, etc. Animation: http://www.bio.davidson.edu/courses/genomics/chip/chip.html