Transcript Lecture 21 Student Powerpoint

Lecture
189Functional
Genomics
Based on chapter 8
Functional and
Comparative Genomics
Copyright © 2010 Pearson Education Inc.
1 - RNA Expression Analysis – Determining
Genomewide RNA Expression Levels
•
Genomewide RNA expression analysis
• Types of microarrays
• Making microarrays
• Hybridization to microarrays
7 - Genomic Expression Analysis Methods
1. Microarrays
a. Hybridization based
2. SAGE – Serial analysis of gene expression
3. MPSS – Massively parallel signature
sequencing
8 - Nucleic Acid Hybridization
1.
Measurements of RNA abundance by microarrays
based on hybridization
a. Between complementary strands of RNA and DNA
b. Or two complementary DNA strands
2. Similar in principle to RNA blot (Northern blot)
9 - Hybridization Issues
1.
RNA integrity must be verified
a. If RNA degraded, hybridization not quantitative
2. DNA Probe must be in excess of bound RNA
3. Hybridization must be for a sufficient time to allow
probe to find target RNA
4. Comparison between samples requires loading
control
10 - Northern Blots vs. Microarrays
1. Global expression analysis:
microarrays
a. RNA levels of every
gene in the genome
analyzed in parallel
2. Northern blot
a. Only 1 gene at a time
target –
loading –
control
11 - Basics of Microarrays
1. DNA probe attached to
solid support
a. Glass, plastic, or
nylon
2. RNA or cDNA is labeled
a. Usually indirectly
3. Bound DNA is the
equivalent of the “probe”
a. Labeled RNA (cDNA)
is the “target”
4. Each “probe” is specific
for a different gene.
12 - Microarray Hybridization
1. Usually comparative
a. Ratio between two
samples
2. Examples
a. Tumor vs. normal
tissue
b. Drug treatment vs.
no treatment
c. Embryo vs. adult
samples
mRNA
cDNA
DNA
microarray
13 - How Microarrays are Made: Spotted
Microarrays
1.
2.
DNA mechanically placed on glass slide
Need to deliver nanoliter to picoliter volumes
a. Too small for normal pipetting devices
3. Robot “prints,” or “spots,” DNA in specific places
14 - DNA spotting I
1. DNA spotting usually
uses multiple pins
2. DNA in microtiter plate
3. DNA usually PCR
amplified
4. Oligonucleotides can
also be spotted
17 - How Microarrays are Made: Affymetrix
GeneChips
1.
Oligonucleotides synthesized on silicon chip
a. One base at a time
2. Uses process of photolithography
a. Developed for printing computer circuits
18 - Affymetrix GeneChips
1.
Oligonucleotides
a. Usually 20–25 bases in length
b. 10–20 different oligonucleotides for each gene
2. Oligonucleotides for each gene selected by
computer program to be the following:
a. Unique in genome
b. Nonoverlapping
3. Composition based on design rules
a. Empirically derived
19 - Photolithography
1. Light-activated
chemical reaction
a. For addition of
bases to growing
oligonucleotide
2. Custom masks
a. Prevent light from
reaching spots
where bases not
wanted
lamp
mask
chip
20 - Example: Building Oligonucleotides by
Photolithography
1. Want to add nucleotide
G
2. Mask all other spots on
chip
3. Light shines only where
addition of G is desired
4. G added and reacts
5. Now G is on subset of
oligonucleotides
light
21 - Example: Adding a Second Base
1. Want to add T
2. New mask covers
spots where T not
wanted
3. Light shines on mask
4. T added
5. Continue for all four
bases
6. Need 80 masks for
total
7.
20-mer
oligonucleotide
light
23 - Target labeling: Fluorescent cDNA
1. cDNA made using
reverse transcriptase
2. Fluorescently labeled
nucleotides added
3. Labeled nucleotides
incorporated into
cDNA
25 - Labels
1. Cy3 and Cy5
a. Fluoresce at different wavelengths
b. Used for competitive hybridization
2. Biotin
a. Binds to fluorescently labeled avidin
b. Used with Affymetrix GeneChips
27 - Scanning of Microarrays
1. Confocal laser
scanning microscopy
2. Laser beam excites
each spot of DNA
3. Amount of
fluorescence detected
4. Different lasers used
for different
wavelengths
a. Cy3
b. Cy5
laser
detection
28 - Analysis of Hybridization
1. Results given as
ratios
2. Images use colors:
Cy3 = Green
Cy5 = red
Yellow
3. Yellow is equal
intensity or no
change in expression
29 - Example of Spotted Microarray
1. RNA from irradiated
cells (red)
2. Compare with
untreated cells (green)
3. Most genes have little
change (yellow)
4. Gene CDKN1A: red =
increase in expression
5. Gene Myc: green =
decrease in
expression
CDKNIA
MYC
2 – Yeast Cell Cycle Experimental
3 - Analysis of cell-cycle regulation
1. Yeast cells stopped at
different stages of cell
cycle
 G1, S, G2, and M
2. RNA extracted from
each stage
3. Control RNA from
unsynchronized
culture
4 - Results of cell-cycle analysis
1.
800 genes identified whose expression changes
during cell cycle
2. Grouped by peak expression
a. M/G1, G1, S, G2, and M
3. Four different treatments used to synchronize cells
a. All gave similar results
4. Results from Spellman et al., 1998; Cho et al., 1998
5 - Cell-cycle regulated genes




Each gene is a line on
the longitudinal axis
Treatments in different
panels
Cell-cycle stages are
color coded at top
Vertical axis groups
genes by stage in
which expression
peaks
Alpha
cdc15
cdc28
Elu
M/G1
G1
S
G2
M
Brown and Botstein, 1999
6 - Affymetrix GeneChip experiment
1. RNA from different types of brain tumors
extracted
2. Extracted RNA hybridized to GeneChips
containing approximately 6,800 human
genes
3. Identified gene expression profiles
specific to each type of tumor
7 - Profiling tumors
1. Image portrays gene
expression profiles
showing differences
between different
tumors
2. Tumors:
a. MD
(medulloblastoma)
b. Mglio (malignant
glioma)
c. Rhab (rhabdoid)
d. PNET (primitive
neuroectodermal
tumor)
3. Ncer: normal cerebella
1. Gene expression
differences for
medulloblastoma
correlated with
response to
chemotherapy
2. Those who failed to
respond had a
different profile from
survivors
3. Can use this approach
to determine treatment
60 different samples
8 - Cancer Diagnosis by Microarray
9 - Analysis of microarray results
1. Inherent variability: need for repetition
a. Biological and technical replicates
2. Analysis algorithms
a. Based on statistical models
3. Means of generating hypotheses that
need to be tested
10 – Serial Analysis of Gene Expression
(SAGE)
1. Serial analysis of gene expression
2. Concept: sequence a small piece of each
cDNA in a library
a. Gives measure of abundance of each
RNA species
3. Method
a. Cut off “tag” from each cDNA
b. Ligate tags together into a concatemer
c. Sequence the concatemer
13 - SAGE IV
1. Sequence the concatemers
2. Identify tag borders
a. Size of tag and restriction-enzyme sites
3. Compare tag sequences to database
4. Abundance of tag is measure of abundance
of that RNA species
14 - MPSS I
1. Massively parallel
signature sequencing
2. Means of determining
abundance of RNA
species
3. Unique tags added
to cDNAs
4. Tags hybridized to
oligonucleotides on
microbeads
Slide 15 – MPSS I
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Sequencing performed
in glass chamber
Initiated by restriction
enzyme revealing fourbase overhang
Hybridization of fourbase adapters used to
read sequence
Number of times a
particular sequence is
found is measure of
RNA abundance