Transcript Wrap up Genes and Expression

Genes and Expression
51:123
Terry Braun
1
Today's Outline
• Gene structure
–
–
–
–
–
–
–
genomic structure vs mRNA structure
ESTs
coding and noncoding exons
introns
primary transcript processing
memory pneumonic
alternative splicing and differential polyadenylation
2
Genome (3 Bb) – zoom in
Adenine
Thymine
Guanine
Cytosine
ATGC
purines AG
pyrimidines
CT
3
www.ensembl.org
Central Dogma
• gene – portions of a genome that affect the
transcription, translation, and expression of
functionally active molecules (proteins, DNA
[promoters] rRNA, mRNA, tRNA, etc)
• gene – often used to describe the “coding”
regions of genomes – the portions of DNA that
are “made” into a protein (via transcription, and
translation)
• DNA -> pre-mRNA -> mRNA -> protein
4
Central Dogma
• DNA -> pre-mRNA -> mRNA -> protein
– DNA is “transcribed” into pre-mRNA
– “introns” are removed
• lariat structure
– “exons” remain (“spliced together”), also
called the “coding regions” – called mRNA
• splice site junctions
– mRNA is “translated” into protein
5
Schellenberg MJ, Ritchie DB, MacMillan AM.
Pre-mRNA splicing: a complex picture in higher definition.
Trends Biochem Sci. 2008 Jun;33(6):243-6. Epub 2008 May 9. Review.
6
Gene Structure: gene to protein
7
Example of Gene in Genomic
Context
Context of gene – BBS4 – in the human genome.
Scale = 72.28 Kb
Exons and introns
Note possible upstream gene, on other strand
Less than 3% of the genome is transcribed and translated into a protein.
8
Human Genome Project
• Problem
– How do you find all of the genes in a sea of
DNA?
9
Where’s the gene?
>BBS4 exon2
TAAAGTAACTCTATCACAATATGGATTTAATGGATTAATTGCATAATTGGTGAGCTACTG
ATTATTCTTGTTATTTGGATGCTTCTTTAAGTTAGCAAGTTTATATTGTGGTGCTTCAAT
ATAGACTACTTATTTCATTTCAGAGAACTCAATTTCCTGTATCTACTGAGTCTCAAAAAC
CCCGGCAGAAAAAAGGTCTGTATGCAGTTTCATGGTATGTGTATGTTTGCACAGACAGAT
TTCTCTTTTATTTATTTATTTATTTTTTTTTTTGGAGGCAGAGTCTCACTGTCACCCAGG
CTGGAGTGCAGTAGCACAATCTTGGCTCACTGCAACCTTTGCCTCTGGGGCTCAAGCAAT
TCTCCTGCCTCAGCCTCCCGAGTAGCTGGGATTACAGGTGCACGCCACCACACCTGGCTA
10
Where’s the gene?
>BBS4 exon2
TAAAGTAACTCTATCACAATATGGATTTAATGGATTAATTGCATAATTGGTGAGCTACTG
ATTATTCTTGTTATTTGGATGCTTCTTTAAGTTAGCAAGTTTATATTGTGGTGCTTCAAT
ATAGACTACTTATTTCATTTCAGAGAACTCAATTTCCTGTATCTACTGAGTCTCAAAAAC
CCCGGCAGAAAAAAGGTCTGTATGCAGTTTCATGGTATGTGTATGTTTGCACAGACAGAT
TTCTCTTTTATTTATTTATTTATTTTTTTTTTTGGAGGCAGAGTCTCACTGTCACCCAGG
CTGGAGTGCAGTAGCACAATCTTGGCTCACTGCAACCTTTGCCTCTGGGGCTCAAGCAAT
TCTCCTGCCTCAGCCTCCCGAGTAGCTGGGATTACAGGTGCACGCCACCACACCTGGCTA
11
ESTs
• Expressed Sequence Tags
• If we could read the sequence at only the front
(5') or end(3') of mRNAs (transcripts), or even in
the middle, that would be conclusive evidence of
a gene
– Uniquely (?) identify all of the genes
– Do not have full expense of sequencing the whole
gene sequence (100's of nucleotides VS 1000's)
– Can observe differences of expression in tissues
– Many questioned whether the complete genome
should even be sequenced
12
ESTs at Iowa
• Approach
– Harvest mRNAs and sequence them
– Subtract out what you have already seen
(serial subtraction)
• Rat gene discovery at Iowa (2003)
– 233,890 3-prime ESTs, 50,075 5-prime
ESTs
– 57,822 clusters (8/26/2003)
– novelty = 57,822/(233,890 + 50,075) = 0.20
13
14
C-Value Paradox
Hartl, “Molecular melodies in high and low C,” Nat. Rev. Genetics, Nov 2001
• refers to the massive, counterintuitive and
seemingly arbitrary differences in genome size
observed in eukaryotic organisms
– Drosophila melanogaster 180 Mb
– Podisma pedestris 18,000 Mb
– difference is difficult to explain in view of apparently
similar levels of evolutionary, developmental, and
behavioral complexity
• more to a genome than coding sequences
– example – Alu repeats ~ 250 nucleotides
– humans, chimps, gorillas
– Not in rat/mouse
15
Repetitive Elements
number elements
LINEs
SINEs
alus
transposons
20.4%
13.4
10.6
2.8
868,000
1,558,000
1,090,000
294,000
Sudbery 2002 Human Mol Genetics
16
Alternative Splicing
Every conceivable pattern of alternative
splicing is found in nature. Exons have
multiple 5’ or 3’ splice sites alternatively
used (a, b). Single cassette exons can
reside between 2 constitutive exons
such that alternative exon is either
included or skipped ( c ). Multiple
cassette exons can reside between 2
constitutive exons such that the splicing
machinery must choose between them
(d). Finally, introns can be retained in
the mRNA and become translated.
Graveley, “Alternative splicing:
increasing diversity in the proteomic
world.” Trends in Genetics, Feb., 2001.
17
Relevance to disease: changes
L to I?
Cysteine and disulfide bonds
Each amino acid contains an
"amine" group (NH3) and a
"carboxy" group (COOH)
(shown in black in the
diagram).
The amino acids vary in their
side chains (indicated in blue
in the diagram).
The eight amino acids in the
orange area are nonpolar/
hydrophobic.
The other amino acids are
polar/ hydrophilic ("water
loving").
The two amino acids in the
purple box are acidic
("carboxy" group in the side
chain).
The three amino acids in the
blue box are basic ("amine"
group in the side chain).
Know relationship between
DNA, mRNA, and aa’s
nonpolar: internal, polar: external (interacts with H20)
18
•
•
•
•
•
•
•
•
•
•
A ala alanine
M met methionine
C cys cysteine
N asn aspargine
D asp aspartic acid P pro proline
E glu glutamic acid
Q gln glutamine
F phe phenylalanine
R arg arginine
G gly glycine
S ser serine
H his histidine
T thr
threonine
I ile isoleucine
V val
valine
K lys lysine
W trp tryptophane
L leu leucine
Y tyr
tyrosine
19
The Genetic Code (mRNA)
Review
1st position
(5' end)
C
A
G
U
Phe F
Phe F
Leu L
Leu L
Ser S
Ser S
Ser S
Ser S
Tyr Y
Tyr Y
STOP
STOP
Cys C
Cys C
STOP
Trp W
U
C
A
G
C
Leu L
Leu L
Leu L
Leu L
Pro P
Pro P
Pro P
Pro P
His H
His H
Gln Q
Gln Q
Arg R
Arg R
Arg R
Arg R
U
C
A
G
A
Ile I
Ile I
Ile I
Met M
Thr T
Thr T
Thr T
Thr T
Asn N
Asn N
Lys K
Lys K
Ser S
Ser S
Arg R
Arg R
U
C
A
G
G
Val V
Val V
Val V
Val V
Ala A
Ala A
Ala A
Ala A
Asp D
Asp D
Glu E
Glu E
Gly G
Gly G
Gly G
Gly G
U
C
A
G
gene prediction
One codon: Met, Trp.
Two codons: Asn, Asp,
Cys, Gln, Glu, His, Lys,
Phe, Tyr,
Three codons: Ile, STOP
("nonsense").
Four codons: Ala, Gly, Pro,
Thr, Val.
Five codons: none.
Six codons: Arg, Leu, Ser.
3rd position
(3' end)
U
Codon Table
degenerate code
2nd position (middle)
20
Mutations
• Mis-sense
• Non-sense
• www.hgvs.org
• http://www.hgvs.org/mutnomen/
21
From Slide 6…
ATG CCC TTC TCC AAC AGC
M
P
F
S
N
GT -- splice donor
S
CCT GCC CCC CAT GCC TGA
P
A
P
H
A
STOP
Delete CC
ATG CCC TTC TAA CAG CCC
M
P
F
Stop Q
P
TGC CCC CCA TGC CTG AGG GGC
C
P
P
C
L
R
G
…?
22
Codon Bias
• PAM1 (Point Accepted Mutations) Dayhoff
1978
– global alignment of closely related proteins (85%
identical)
– <= 1% divergence between proteins
• Blosum62 (Blocks Substitution Matrix) Henikoff
1992
– proteins across species containing “blocks” of
homology with at least 62 percent were compared
– a residue change measurement was computed based
on observed residue changes
• rare change = -4
• common change = 11
23
#
#
#
#
#
#
A
R
N
D
C
Q
E
G
H
I
L
K
M
F
P
S
T
W
Y
V
B
Z
X
*
Matrix made by matblas from blosum62.iij
* column uses minimum score
BLOSUM Clustered Scoring Matrix in 1/2 Bit Units
Blocks Database = /data/blocks_5.0/blocks.dat
Cluster Percentage: >= 62
Entropy =
0.6979, Expected = -0.5209
A R N D C Q E G H I L K M F P S T
4 -1 -2 -2 0 -1 -1 0 -2 -1 -1 -1 -1 -2 -1 1 0
-1 5 0 -2 -3 1 0 -2 0 -3 -2 2 -1 -3 -2 -1 -1
-2 0 6 1 -3 0 0 0 1 -3 -3 0 -2 -3 -2 1 0
-2 -2 1 6 -3 0 2 -1 -1 -3 -4 -1 -3 -3 -1 0 -1
0 -3 -3 -3 9 -3 -4 -3 -3 -1 -1 -3 -1 -2 -3 -1 -1
-1 1 0 0 -3 5 2 -2 0 -3 -2 1 0 -3 -1 0 -1
-1 0 0 2 -4 2 5 -2 0 -3 -3 1 -2 -3 -1 0 -1
0 -2 0 -1 -3 -2 -2 6 -2 -4 -4 -2 -3 -3 -2 0 -2
-2 0 1 -1 -3 0 0 -2 8 -3 -3 -1 -2 -1 -2 -1 -2
-1 -3 -3 -3 -1 -3 -3 -4 -3 4 2 -3 1 0 -3 -2 -1
-1 -2 -3 -4 -1 -2 -3 -4 -3 2 4 -2 2 0 -3 -2 -1
-1 2 0 -1 -3 1 1 -2 -1 -3 -2 5 -1 -3 -1 0 -1
-1 -1 -2 -3 -1 0 -2 -3 -2 1 2 -1 5 0 -2 -1 -1
-2 -3 -3 -3 -2 -3 -3 -3 -1 0 0 -3 0 6 -4 -2 -2
-1 -2 -2 -1 -3 -1 -1 -2 -2 -3 -3 -1 -2 -4 7 -1 -1
1 -1 1 0 -1 0 0 0 -1 -2 -2 0 -1 -2 -1 4 1
0 -1 0 -1 -1 -1 -1 -2 -2 -1 -1 -1 -1 -2 -1 1 5
-3 -3 -4 -4 -2 -2 -3 -2 -2 -3 -2 -3 -1 1 -4 -3 -2
-2 -2 -2 -3 -2 -1 -2 -3 2 -1 -1 -2 -1 3 -3 -2 -2
0 -3 -3 -3 -1 -2 -2 -3 -3 3 1 -2 1 -1 -2 -2 0
-2 -1 3 4 -3 0 1 -1 0 -3 -4 0 -3 -3 -2 0 -1
-1 0 0 1 -3 3 4 -2 0 -3 -3 1 -1 -3 -1 0 -1
0 -1 -1 -1 -2 -1 -1 -1 -1 -1 -1 -1 -1 -1 -2 0 0
-4 -4 -4 -4 -4 -4 -4 -4 -4 -4 -4 -4 -4 -4 -4 -4 -4
W
-3
-3
-4
-4
-2
-2
-3
-2
-2
-3
-2
-3
-1
1
-4
-3
-2
11
2
-3
-4
-3
-2
-4
Y
-2
-2
-2
-3
-2
-1
-2
-3
2
-1
-1
-2
-1
3
-3
-2
-2
2
7
-1
-3
-2
-1
-4
V
0
-3
-3
-3
-1
-2
-2
-3
-3
3
1
-2
1
-1
-2
-2
0
-3
-1
4
-3
-2
-1
-4
B
-2
-1
3
4
-3
0
1
-1
0
-3
-4
0
-3
-3
-2
0
-1
-4
-3
-3
4
1
-1
-4
Z
-1
0
0
1
-3
3
4
-2
0
-3
-3
1
-1
-3
-1
0
-1
-3
-2
-2
1
4
-1
-4
X
0
-1
-1
-1
-2
-1
-1
-1
-1
-1
-1
-1
-1
-1
-2
0
0
-2
-1
-1
-1
-1
-1
-4
*
-4
-4
-4
-4
-4
-4
-4
-4
-4
-4
-4
-4
-4
-4
-4
-4
-4
-4
-4
-4
-4
-4
-4 24
1
Expression
• A gene is expressed when the DNA sequence in
the genome is transcribed into an mRNA
molecule, and that mRNA molecule is correctly
made into a protein (aka. string of amino acids
for polypeptide).
• Note that evaluation of expression is often done
by examining/counting the amount/number of
mRNA molecules made by the cells of a
particular tissue.
25
DNA/RNA/Protein and Strands
• promoters
–
–
–
–
anywhere from 1 to 10 KB to ??? upstream of a gene
many proteins and other molecules (RNAs) involved
largely unknown
“promoter bashing”
• replace or delete regions of DNA in promoter
• measure level of expression
• trans- and cis- regulatory elements
– trans – not co-localized to the gene
– cis – generally localized to the gene
26
Example -- LCR
An example of the functional potential for non-coding regions is the locus control
region of the opsin gene cluster (Nathans, et. al. 1989) shown to cause 50% of
the cases of blue cone monochromacy. The locus control region is approximately
4 kilobases upstream of the red opsin gene, and 43 kilobases upstream of the
green opsin gene. The 579 base region was mapped to the X-chromosome using
observed deletions upstream of the red-green opsin gene cluster in individuals
with blue cone monochromacy. Blue cone monochromatism is characterized by
poor central vision and color discrimination and nearly normal retinal appearance.
27
DNA/RNA/protein figure
28
End
29
Microarray Technology
• No genomics discussion would be complete
without describing microarray technology.
• A powerful tool for genetic research which
utilizes nucleic acid hybridization techniques and
recent advancements in computing technology
to evaluate the mRNA expression profile of
thousands of gene in one single experiment.
• It has proven to be an extremely valuable
method to better utilize the enormous amount of
information provided by the completion of the
human Genome Project.
30
Gene Expression: Motivation
Pattern of gene expression in a cell is
characteristic of its current state
Virtually all differences in cell state or type
can be correlated with differences in
mRNA expression levels
Expression patterns can provide clues to
gene function and metabolic pathway
architecture
31
Potential Impact
Preventative medicine
Subtype diseases in order to design better
drugs for a specific genotype
More targeted drug treatment -- treat
disease rather than symptoms
32
Steps involved in Designing
Microarray Experiment
• Preparation of fluorescently labeled target
from RNA isolated from the biological
sample (aka biological sample).
• Hybridization of the labeled target to the
microarray.
• Washing, staining, and scanning of the
array.
• Analysis of the scanned image.
• Generation of gene expression profiles.
33
Physical Spotting
34
DNA Array Technology
cDNA libraries and/or gene
sequence data
Cell Lines
RNA
Hybridization
Target
Surface
Probe
Data Acquisition
Expression Levels
Analysis
35
Probe Example
36
37
Microarrays: What are they?
38
Microarray Experiment
326 Rat Heart Genes, 2x spotting
39
Affymetrix Technology
40
Affymetrix Chip
41
Hybridization/Microarray Tech.
• Very large scale
• multiples of 1K density for glass slides
– cheap
– custom
– considered not as reliable
• Affy – U133
–
–
–
–
2 chips
45,000 probe sets
39,000 transcripts
33,000 genes
• SNP chip
– 11,500 SNPs (single nucleotide polymorphisms, or genotypes)
– 100,000 SNPs (another year?)
• Research and funding dilemma
– NIH sponsored funding
– only distilled data (if that) made available
– confidentiality issues
42
Examples of Analysis
• simple filter
– all up, all down
• clustering
– Eisen diagrams
– volcano plots
– Mootha approach
43
End Expression
44
Polyadenylation (Poly-A)
• The addition of multiple adenines to a premRNA and is part of the end of the
transcription process
• Three steps
– 1) the RNA strand is cleaved at a particular
site
– 2) the addition of poly-A's to the 3' end
– 3) the degradation of the remainder of the
RNA transcript
45
Polyadenylation
Cut
polyadenylated
degraded
AAAn
46
Poly-A Signal
AAUAAA – specifies where the mRNA is cleaved, and the
Poly-A is added
Typically 23 or 24 bases downstream of this signal
10-200 A's added
Increases translatability by about 20-fold (mechanism
unknown).
Also thought to improve stability – protecting the end of the
mRNA molecule from exonucleases.
47
Alternative Polyadenylation
• common in human RNA (Edwards-Gilbert
1997)
• in many genes, 2 or more poly-A signals in
3’ UTR
– alternative transcripts can show tissue
specificity
• alternative poly-A signals may be brought
into play following alternative splicing
48
Edwards-Gilbert. Nucleic Acids Res, 13, 1997
49
End
50