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Chapter 22—Genomics II
• Functional Genomics—studying genes in groups, with respect to the cell, tissue, signaling pathway or organism
• Proteomics—to understand the interplay among many different proteins (cellular processes and organismal level [traits])
• Bioinformatics—using computers, math, and statistics to understand the genome and proteome information (record, store, analyze, predict)
Chapter 22—Genomics II
• Functional Genomics—studying genes in groups, with respect to the cell, tissue, signaling pathway or organism
• Proteomics—to understand the interplay among many different proteins (cellular processes and organismal level [traits])
• Bioinformatics—using computers, math, and statistics to understand the genome and proteome information (record, store, analyze, predict)
Add reverse transcriptase, poly-dTprimers that anneal to the mRNAs,and fluorescent nucleotides.Note: Only 1 complementarycDNA strand is made.
View with a laser scanner.
Hybridize cDNAsto the microarray.
A mixture of 3different types ofmRNA
A portion of a DNA microarray
Fluorescentlylabeled cDNA thatis complementaryto the mRNA
A
A
AA B
C D
E F
A B
C D
E F
D
FF
F
D
D
A
AA
D
FF
F
D
D
Figure 22.1 Copyright ©The McGraw-Hill Companies, Inc. Permission required for reproduction or display
Microarrays for studying gene
expression or re-sequencing
Modern day “Southerns” and “Northerns”—microarray analysis
Two distinct forms of large B-cell lymphoma are shown by the expression pattern: GC B-like DLBCL (orange) and Activated B-like DLBCL (blue)
ASH ALIZADEH et al. 2000Nature 403, 503-511 (3 February 2000)
significantly better overall survival
Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling
Observation/problem• Diffuse large B-cell lymphoma (DLBCL) = most common subtype of non-Hodgkin's
lymphoma is clinically heterogeneous: 40% of patients respond well to current therapy and have prolonged survival, whereas the remainder succumb to the disease
Hypothesis• variability in natural history reflects unrecognized molecular heterogeneity in the
tumours.
Experiment• DNA microarrays used for a systematic characterization of gene expression in B-cell
malignancies.
Results• Diversity in gene expression among the tumours of DLBCL patients (reflecting the
variation in tumour proliferation rate, host response and differentiation state of the tumour).
• Identified two molecularly distinct forms of DLBCL which had gene expression patterns indicative of different stages of B-cell differentiation.
– One type expressed genes characteristic of germinal centre B cells ('germinal centre B-like DLBCL'); – the second type expressed genes normally induced during in vitro activation of peripheral blood B
cells ('activated B-like DLBCL').
• Patients with germinal centre B-like DLBCL had a significantly better overall survival than those with activated B-like DLBCL.
Conclusion• Molecular classification of tumours on the basis of gene expression can thus identify
previously undetected and clinically significant subtypes of cancer.ASH ALIZADEH et al. 2000
Nature 403, 503-511 (3 February 2000)
Add formaldehyde to crosslinkprotein to DNA. Lyse the cells.Sonicate DNA into small pieces.
Add antibodies that recognize theprotein of interest. The antibodiesare bound to heavy beads. Afterthe antibodies bind to the proteinof interest, the sample issubjected to centrifugation.
Collect complexes in pellet.Add chemical that breaks thecrosslinks to remove the protein.
Unknown Candidates:Ligate DNA linkers to theends of the DNA.
Known Candidates: Conduct PCR using primersto a known DNA region.
If PCR amplifies the DNA,the protein was bound tothe DNA region recognizedby the primers.
Conduct PCR using primersthat are complementary tothe linkers. Incorporatefluorescently labelednucleotides during PCR.
Denature DNA andhybridize to a microarray.
Antibody againstprotein of interest
Protein of interest
Bead
Protein of interest
Linker
or
Pellet
See Figure 22.1
Figure 22.2
Which DNA sequences bind to my protein of
interest?
Chromatin Immunoprecipitation Assay (ChIP)
Chapter 22—Genomics II
• Functional Genomics—studying genes in groups, with respect to the cell, tissue, signaling pathway or organism
• Proteomics—to understand the interplay among many different proteins (cellular processes and organismal level [traits])
• Bioinformatics—using computers, math, and statistics to understand the genome and proteome information (record, store, analyze, predict)
Exon 1 Exon 2 Exon 3 Exon 4 Exon 5 Exon 6
Exon 1Exon 2
Exon 4Exon 5
Alternative splicingTranslation
Exon 6
Exon 1
(a) Alternative splicing
Exon 3Exon 4
or
or
Exon 5Exon 6
pre-mRNA
Exon 1Exon 2
Exon 4Exon 6
Why is the proteome so large? Alternative splicing
Proteolyticprocessing
Attachment ofprostheticgroups, sugars,or lipids
Sugar
Hemegroup
Phospholipid
Disulfide bondformation
S SSH SH
Irreversible modifications
(b) Posttranslational covalent modification
Phosphorylation
Methylation
Phosphategroup
Acetylgroup
Methylgroup
PO42-
C
CH3
CH3
O
Reversible modifications
Acetylation
Copyright © The McGraw-Hill Companies, Inc. Permission required for reproduction or display.
Why is the proteome so
large? Post translational
modification
SDS-polyacrylamide gel
Proteins migrate until theyreach the pH where theirnet charge is 0. At thispoint, a single band couldcontain 2 or moredifferent proteins.
Lyse a sample of cells andload the resulting mixtureof proteins onto an isoelectricfocusing gel.
pH 10.0pH 4.0
pH 10.0
pH 4.0
200 kDa
10 kDa
Lay the tube gel onto anSDS-polyacrylamide gel andseparate proteins accordingto their molecular mass.
Techniques to study the
proteome: 2D Gel analysis
Brooker, Fig 22.4
Copyright ©The McGraw-Hill Companies, Inc. Permission required for reproduction or display
Digest protein intosmall fragmentsusing a protease.
Determine the massof these fragments witha first spectrometer.
C
N
C
N
Purified protein
Mass/charge
Ab
un
dan
ce
0 4000
1652 daltons
Techniques to study the proteome:
Mass spectrometry
Brooker, Fig 22.5
Brooker, Fig 22.5, cont.
Copyright ©The McGraw-Hill Companies, Inc. Permission required for reproduction or display
Analyze this fragment witha second spectrometer.The peptide is fragmentedfrom one end.
Mass/charge
Ab
un
dan
ce
0 4000
1652 daltons
Mass/charge
Ab
un
dan
ce
900
–Asn–Ser–Asn–Leu–His–Ser–
10081114
12011315
1428
1565
1652
1800
Tandem mass spectrometry to
sequence peptides
Chapter 22—Genomics II
• Functional Genomics—studying genes in groups, with respect to the cell, tissue, signaling pathway or organism
• Proteomics—to understand the interplay among many different proteins (cellular processes and organismal level [traits])
• Bioinformatics—using computers, math, and statistics to understand the genome and proteome information (record, store, analyze, predict)
Copyright ©The McGraw-Hill Companies, Inc. Permission required for reproduction or displayNumbers represent the base number
in the sequence file
Example of DNA Sequence as stored in Genetic Database
A bioinformatics program may ask:• Does the sequence contain a gene?• Which nt’s are the functional sites (e.g. promoters,
exons, introns, termination sequence)?• Does the sequence encode a protein? (have an open
reading frame [ORF]• What is the secondary structure of its RNA or
associated amino acid sequence?• Is the sequence homologous to any other known
sequences?• What is the evolutionary relationship between two
or more sequences?
3′ end
5′ end
Copyright ©The McGraw-Hill Companies, Inc. Permission required for reproduction or display
Brooker, Fig 22.7
A secondary structural model forE. coli 16S rRNA
Copyright ©The McGraw-Hill Companies, Inc. Permission required for reproduction or display
• DNA sequences of the lacY gene– ~ 78% of the bases are a perfect match
• In this case, the two sequences are similar because the genes are homologous to each other– They have been derived from the same ancestral gene– Refer to Figure 22.6
Sequence matches between E. coli and K. pneumoniae
Human Pa Ca
Mouse Lu Ca
Human LHON, Human Thy Ca
Mouse Lu Ca
Example output from a computer alignment program (and
comparison to real world data)
Interesting cancer mutation pattern in mitochondrial ND6 protein
Sequence homology used to “hang” human cancer mutations on the bovine crystal structure of Cytochrome B
Chen and Uberto 2014
Federal Genetic Databases
National Center for Biotechnology Informationwww.ncbi.nlm.nih.gov/
U.S. government-funded national resource for molecular biology information.
BLAST programs identify sequences with homology or similarity
Table 22.5
Copyright ©The McGraw-Hill Companies, Inc. Permission required for reproduction or display
Figure 22.6
Accumulation ofrandom mutationsin the 2 genes
Mutation
Ancestral lacY gene
Ancestralorganism
Evolutionary separationof 2 (or more)distinct species
lacY gene
E. coli
lacY gene
lacY gene lacY gene
K. pneumoniae
Mutation
Origin of orthologous
genes
Myoglobin
a chains b chains
Hemoglobins
Mil
lio
ns
of
year
s ag
o
1,000
800
600
400
200
0
Mb ζ ψζ ψα2ψα1 α2 α1
f ε gG gA ψβ δ β
Copyright ©The McGraw-Hill Companies, Inc. Permission required for reproduction or display
Brooker, Fig 8.7
DuplicationBetter at binding and
storing oxygen in muscle cells
Better at binding and transporting oxygen via red
blood cellsAncestral globin
Orthologs, paralogs, homologs
From Thompson and Thompson,
Genetics in Medicine, 6th ed.
Like Brooker fig 8-7
• All the globin genes have homology to each other• a-like genes are paralogs of each other; • b-like genes are paralogs of each other; • a-1 in mice and a-1 in humans are orthologs