Genomic Arrays – an overview

1. Genomic Arrays – an overview Dr. Colin Campbell

2. The Central Dogma Genome Regulation AAAAA Transcription Transcription Translation Protein DNA mRNA

3. Genomics in perspective

4. Post Genomic Challenges Sequences available for hundreds of genomesviruses/plasmids >> mammalian genomesGenome sequence only the startNeed to understand:genomic structure, replication, expression Problem of scale, complexity and diversityAdvent of HTS functional genomic technologies:microarray, Si RNA, mutagenesis, proteomics, imaging

5. Post genomic approaches Functional genomics toolbox ascribe function Monitor expression Sequence Classify Identify all genes used to assemble an organism

6. Microarrays – a post genomic technology Mammalian Genome Database Gene Expression/Genotyping Proteomics Fundamental and applied biomedical research Supporting Technologies Statistics/Bioinformatics HTS Technology Developments: Arraying/ Scanning/ Lab-on-a-chip Computing/ Databases

7. Evolution of array technology Traditional method: taking gene by gene approach Insufficientto meet magnitude of problem Array technology Developed to provide a systematic way of studying RNA expression, genotyping, DNA/ RNA interactions and numerous other applications Array = A regular or uniform arrangement e.g. of DNA probes or other elements such as proteins or tissue sections arranged on glass slides or nylon membranes

8. The Central Dogma Genome Regulation AAAAA Transcription Transcription Translation Protein DNA mRNA

9. RNA transcription analysis Expression of RNA assessed by Northern blotting, RNAase protection, RT-PCR methods Low to medium throughput approaches. Do not easily accommodate scale, complexity and diversity challenges e.g. Northern Blot Filters exposed to labelled DNA probe and subject to radiography Cell DNA Gel electrophoresis, RNA separated by Size and blotted on filter mRNA Denature proteins RNA transcripts anlysed singly. Definiton of transcriptome would take thousands of blots

10. The microarray solution cDNA(s) or oligonucleotide(s) representative of genes spotted on slide Intensity value 1 Relative Value = Intensity value 2 1 +ve = upreg Array 2 3 genes 3 4 4 DNA GENOME Hybridise to array Test cDNA control cDNA DNA Reverse transcribe RNA Using Cy3 (test RNA) orCy5 (control) dCTP Relative expression of RNA defined at whole genome level mRNA proteins

11. Microarray options First attempts at exploiting array approaches involved filter based screening of clone libraries Basic genomic and RNA expression studies Two key innovations have enhanced the utility of genomic microarrays 1. Use of glass substrates to construct miniaturised arrays DIRECT DEPOSITION: Using automated printers: ~30-40K DNA probe elements deposited on a glass slide IN SITU SYNTHESIS: several million individual DNA probe elements defined by photolithography on silicon wafers 2. The use of fluorescence for detection

12. Method 1. Array of 5,000 mouse genes - direct deposition method

13. The microarray solution cDNA(s) or oligonucleotide(s) representative of genes spotted on slide Intensity value 1 Relative Value = Intensity value 2 1 +ve = upreg Array 2 3 genes 3 4 4 DNA GENOME Hybridise to array Test cDNA control cDNA DNA Reverse transcribe RNA Using Cy3 (test RNA) orCy5 (control) dCTP Relative expression of RNA defined at whole genome level mRNA proteins

14. Direct deposition DNA microarray scanner image

15. Method 2. In situ synthesised oligo array - Affymetrix GeneChip® system G G G G G G G T T T T T T A A A A A A C C C C C Gene Sequence representative DNA sequences derived from 3’ end of gene 3’ 25 mer T L Many million fold bound in specific feature 20 features used to represent one gene 400,000 features per array representing ~ 12,000 genes

16. TTT TTT TTT TTT AAA AAA AAA AAA AAA AAA AAA Affymetrix target labelling Cell/ Tissue of interest 2nd strand cDNA synthesis 1st strand cDNA synthesis DNA TTT TTT Isolation of total RNA ds cDNA AAA TTT TTT T7 Promoter incorporated in first strand synthesis

17. b b b b b SA SA SA SA Affymetrix labelling and hybridisation In vitro transcription using Biotinylated dNTPs Hybridise to Array Biotinylated cRNA TTT L b TTT L b b TTT b L b TTT b L b

18. Affymetrix Gene Chip results Expression of 10K genes – but what is the result ? Statistics and Bioinformatics essential

19. Microarray technology - pros and cons Scale - true global analyses possible Semi-quantitative advantages High throughput Sensitivity Precision Scale demands stringent QC and analytical routines Emerging standards for analysis disadvantages Relative cost/logistics Context independent

20. Microarrays in cancer biology • RNA Expression profiling arrays: Targets > pathways • Genotyping arrays: HTS SNP analysis > gene association studies • Protein arrays: marker sets • Expression based classification to detect dominant patterns of expression in heterogeneous tumours • Can identify: • Tumour markers • Origin of tumour • Developmental stage • Metastatic potential • Therapeutic response profile • Fundamental insights >> definition of cancer pathways and control • Contribute to diagnosis, prognosis and therapy.

21. Clustered gene sets Interferon related Breast luminal cell profile Basal epithelial cell profile Lung adenocarcinoma enriched profile Proliferation gene set

22. DNA microarrays – a platform technology DNA microarrays now extensively employed for RNA expression profilingstudies in biomedical research. Crucial role for statistics, bioinfomatics and computational science to turn HTS data into useful information (gene targets and pathway definition) for the biologist to interpretProvides a critical approach to a thorough understanding of fundamental biological processes. Also contributing to applied areas such as disease diagnosis and definition.DNA microarrays providing a HTS and global platform technology for numerous biomedical and genomic research applications- splicing- sequencing and SNP analysis (v. high density oligo arrays under development)- CGH, BAC clones- epigenetic studies e.g. DNA methylation- Also, platforms developing for: proteins, cells and tissuesDNA microarray approaches will ultimately replace many of the standard methods genetic analysis.

23. Biological context Full definition of biological processes requires additional contextual inforrmation (e.g. spatial, temporal, modification) Methods for precise micro sampling of complex cell populations and tissues can be combined with microarray readouts. Initial step involves precise sampling via cell sorting/enrichment or micro-dissection techniques Combine with target sample (micro RNA sample) amplification methods to enable readout on standard DNA microarray platforms Increases power of analysis and biological interpretation

24. Future potential in biology and medicine Array technology will continue to develop for DNA, RNA, protein and various other physiological measurements. Developments will require increasing interface of biology with physical sciences and technology. Allow new questions to be asked at the whole genome/proteome level. Integration of HTS genomic, proteomic and cellular readouts will be required to define biological complexity and approach systems level understanding Key to this is input from bioinformatics and computational science to analyse, store and visualise data