Michael Snyder, Stanford, "Tech. for Analyzing Transcriptomes and Genomes"

Cost of DNA Sequencing: dropped at 10-fold per year!

Prediction: $1000 genome by end of 2011.

From DNA sequence: how do we understand the genome?

1. RNA Seq for gene expression
2. Mapping structural variation using paired sequencing and sequencing depth.
3. Transcription factor binding sites (ChIP Seq)

RNA Seq

• Start with mRNA
• fragment into bits, or copy to cDNA (and then fragment)
• EST library with adaptation
• generate short sequence reads
• map back to genome
• Get a signal read
• exon regions
• poly-A tail
• reads which span introns (ends map to two exons)
• Advantages
• define exons and introns
• follow espression of genes, exons, and splicing isoforms
• discover new exons and genes
• Types
• Single end (short or long reads)
• long reads are expensive (454, Sanger)
• Paired end reads
• Allow detection of novel transcripts
• RNA Seq is quantitative information
• High correlation with QPCR
• 8000 fold dynamic range (vs 100 fold for microarray)
• Microarray: low expression levels are not able to be measured
• Lot of splice junctions being discovered through RNA-Seq
• some (much?) background, not used
• Single Cell Analysis with RNA-Seq
• Not very detailed yet

Mapping variation among people

• SNPs (Single nucleotide polymorphisms)
• Structural variation
• deletion, insertions (copy number variation (CNV)), inversions
• 3-4% difference per person
• likely involved in phenotype variation and disease
• most detection methods are low resolution (> 50kb)
• can be detected to a certain extent using sequencing
• 17% of variations affect genes

 All of these technologies can and are being used to characterize cancer.