Transcript lecture2_456_2015.pptx

Biol 456/656
Molecular Epigenetics
Lecture #2
Wed August 26, 2015
5 BIG IDEAS
1. Instead of measuring your favorite gene’s
expression levels, measure everything!
Bisulfite Sequencing
RNA-seq
CHIP-seq
Gro-seq
3’-seq
Ribosome profiling
5 BIG IDEAS
2. RNA: more than a messenger!
lncRNA
siRNA
microRNA
piRNA
circRNA
snoRNA
5 BIG IDEAS
3. Gene Regulation: From bench to bedside
@Bench2Bedside
5 BIG IDEAS
(covered in 456/656)
4. Lineage Reprogramming
5 BIG IDEAS
5. Breaking the Genome with CRISPR/Cas
REVIEW OF THE BASICS
Gene expression.
• Transcription basics
• https://www.youtube.com/watch?v=tMr9XH64rtM
Eric Lander, MIT
REVIEW OF THE BASICS
Biomedical science is undergoing a rapid change
Gene-centric view
Genome-wide view
Technology changes everything
Motorola DynaTAC 8000X
$4000
1984
Motorola Moto G
$179
2015
Sanger Sequencing
-400 bases
1977
Illumina Hiseq 2500
-4 billion reads
2014
$10,000,000
$1000
human genome
2008
human genome
2015
http://www.illumina.com/systems/hiseq-xsequencing-system/system.html
--$100 million
2002
Computing power per $
~doubles every year
2012
--$1 million
Cost of sequencing
a human genome
--$10,000
Hayden, Nature 2014
• Methods to measure 1 RNA at a time
– Northern Blot
– RNAse protection assay
– Quantitative RT-PCR
REVIEW OF THE BASICS
Reverse Transcription
-create cDNA from RNA
PCR
http://www.lci-koeln.de/deutsch/veroeffentlichungen/lci-focus/die-polymerasekettenreaktion-pcr-
REVIEW OF THE BASICS
End Point PCR
Quantitative PCR
RNA-seq: quantify the transcriptome
mRNA from cells/tissues
Fragmentation
Convert to cDNA
Adapter ligation
Sequencing by synthesis
3’ 5’
cDNA/DNA
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Sample
preparation
Single
molecule
Cluster
growtharray
5’
Sequencing
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T G C T A C G A T …
Image acquisition
Base calling
Sequencing
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100’s Million Clusters
Per Flow Cell
100 Microns
RNA-seq
quantitative gene expression
novel transcript discovery
RNA-seq data from Fly tissues
Visualized using Integrated Genomics Viewer (IGV)
“Stranded”
OVARY
Mei-P26
1 read
• How do you deal with so much data?
• Different skill set required
– Non GUI (Graphical User Interface) software
– Unix
– Various programming languages (Perl, Python)
– Statistics/Visualization platform (R)
– Visualize sequencing data (IGV, UCSC genome
browser)
RNA-seq track of 6-8 hr embryos
http://genome.ucsc.edu/cgibin/hgTracks?hgS_doOtherUser=submit&hgS_otherUserName=pedstunite&
hgS_otherUserSessionName=brent
chr3R:18,842,756-18,864,455
Become a hybrid scientist!
-alternatively become a “genome-informed” health care worker