1. Genomics I: The Transcriptome RNA Expression Analysis Determining genomewide RNA expression levels

2. Genome-wide expression analysis methods Microarrays –Hybridization based RNA-seq –Direct sequencing of cDNAs

3. RNA- seq High throughput sequencing of cDNAs from biological samples Determine abundance of mRNA by representation in sequencing reads May detect variants (alternative splicing, specific alleles, etc.)

5. DNA Sequencing Cost per Genome

6. Comparison of NextGen Sequencing Platforms

7. A decade’s perspective on DNA sequencing technologyA decade’s perspective on DNA sequencing technology Elaine R. Mardis Nature 470, 198–203 (10 February 2011) doi:10.1038/nature09796 Elaine R. Mardis

8. Post-sequencing Analysis Align seq reads to each other or to reference genome Score number of reads per transcript (abundance) Compare abundance between experimental groups (statistical analysis of difference)

9. Analysis of transcriptome data Inherent variability: need for repetition –Biological and technical replicates Analysis algorithms –Based on statistical models Requires verification by independent methods –Quantitative PCR (Real Time RT-PCR) Means of generating hypotheses that need to be tested

10. Real-time PCR Sensitive means of measuring RNA abundance Not genomewide: used to verify microarray results SYBR Green method: Dye binds only to double- stranded nucleic acid and fluoresces when bound Fluorescence is proportional to amount of double-stranded DNA

11. Real-time PCR readout The readout of a real- time PCR reaction is a set of curves The curves indicate the PCR cycle at which fluorescence is detected Each cycle is twice the amount of the previous cycle

12. Meta-analysis of Microarray Data