1. Next-generation sequencing and PBRC

2. Next Generation Sequencer Applications DeNovo Sequencing Resequencing, Comparative Genomics Global SNP Analysis Gene Expression Analysis Methylation Studies ChIP Sequencing-transcription factors, histones, polymerases Transcriptome Analysis-splicing, UTRs, cSNPs, nested transcripts MicroRNA Discovery and quantitation Metagenomics, Microbial diversity Copy number variation Chromosomal aberrations Gene regulation studies

3. AB SOLiD Ligation sequencing

4. How many sequence tags* do I need for my gene expression application? SAGE/CAGE – 2-5 million mappable miRNA – 10 million mappable ChIP Seq—10-20 million mappable Whole Transcriptome from polyA RNA – 40-50 million mappable Whole Transcriptome from rRNA depleted - >50 million mappable Whole Transcriptome for Allele Specific Expression - >>50 million mappable SOLiD™ 4 generates >1.4 billion mappable sequences/run (2 slides) Libraries can be multiplexed to decrease the cost/sample according to the application and number of sequences needed. * For human/mouse sized genomes; smaller organisms require fewer sequence tags.

5. SAGE Sequencing vs. Microarray SOLiD v4Microarray-Illumina Ref 8 Microarray-Illumina Ref 6 Data Points3.6 million25,60045,200 Known and novel transcripts Known transcripts Sensitivity6 logs3 logs Technical Reproducibility>.99-.9990.9 Correlation to Taqman0.90.7-0.8 Multiplexing/Barcoding Yes –up to 48 RNA or 96 DNA samples No No background –better for low abundance transcript detection Hybridization process creates background signal RNA quantity 5-10 ug750 ng 16 Sample Experiment Cost $7200-full service $6100-PI creates library $3600 $5200

6. Primary Data Analysis - Images to bases Tertiary Data Analysis – Experiment Specific Instrument-specific Sequences + Quality values Differential expression Methylation sites Binding sites Gene association Genomic structure Ref Seq + Alignment Assembly, De Novo Secondary Data Analysis – Bases to alignments/contigs Applications Tag Profiling Small RNA Analysis Transcriptome seq. ChIP-Seq Methylation Analysis Resequencing De novo assembly Algorithms Eland Maq SOAP Velvet Newbler Mapreads Others … Run Quality Sample/Library Quality Discovery Bioinformatics: Geospiza One or more Data sets

7. Next-gen sequencing: applications –Genome analysis: basic and translational research Genetics of disease – new frontiers Exome resequencing: confirmation of GWAS Genome sequence as diagnostic tool Genetic counseling –Epigenome analysis: basic research; biomarkers Analyses of DNA methylation, transcription factors, histone modifications, non-coding RNA Epigenomic biomarkers of disease –Gene expression analysis: basic research; diagnostics & biomarkers Whole transcriptome: all transcribed sequences in a cell SAGE analysis: expression of known genes Small RNA: microRNA as regulators of biology –Genotype to phenotype: a new frontier Pathology: systems biology Diagnosis: data filtering Personalized Genomic Medicine: Treatment recommendations

8. Next-gen sequencing: challenges –Rapid growth in methodology Technology and equipment changes & upgrades –High demands on informatics: Staff Software Computational resources –New ways of handling data needed: Interpretation Publication Storage