Modern Biology in Two Lectures
(Part II)
Gil Alterovitz
Harvard-MIT
Division of Health
Science & Technology
Course Administration
Handouts
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Background
Student Department Affiliation
Student Subject Area Strengths
50
45
45
R elative Strength- N ormalized to 100
40
40
35
Percent
30
25
20
15
10
5
35
30
25
20
15
10
5
0
6
HST
2
Department
7
0
Bio
Comp Sci
Engineering
Harvard-MIT
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Today
Introduction, Part II- Gil Alterovitz
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Review Part I
Splicing
Alternative Splicing
Post-Translational Modifications
Sequence Analysis- Manolis Kellis
Harvard-MIT
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Genes to Proteins
Transcription
Translation
DNA: “Lifetime Plan”
mRNA: “Task List”
5’ATCTACAGATCAGCTACGACGCGACGAT
TTAGCAGCAGCGACGCGACAGCAGCTAGTG
ACGATAGCACATAGTTAGCACAGAGCAGAC
ACAGACAGCACAGCGACAGCGACGACG-3’
5’AUCUACAGAUCAGCUACGACGCGACGAU
UUAGCAGCAGCGACGCGACAGCAGCUAGUG
ACGAUAGCACAUAGUUAGCACAGAGCAGAC
ACAGACAGCACAGCGACAGCGACGACG-3’
Protein: Machines
MWTRFDSALPRSTPSTAKLVMPOILLLLEE
EDTYESAQYKTWLMVCSDETTTE
Protein
mRNA
Ribosome
Figure by MIT OCW
DNA Sequencing
Source: HPCGG
Relative Expression
Levels
Figure by MIT OCW
Identification
Post translation modification
Splicing variants
Relative expression levels
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Genes
Gene 2
Gene 1
Intergenic Sequence
Communication analogy: start, message, stop.
Source: Ehsan Afkhami
Harvard-MIT
Division of Health
Science & Technology
Stereo Rack Analogy
Amplifier
Harvard-MIT
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Alternative Splicing
5' UTR
Protein coding sequence
Enhancer regulatory
element
3' UTR
Stabilizing domain
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AAAAAA A
Altered translation
Change in protein expression levels
AAAAAA A
AAAAAA A
mRNA instability
Altered protein structure and function
Change in protein expression levels
Change in protein isoform ratios
Figure by MIT OCW
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Sequence Ordering
Coding Strand
(Codons)
5' > > > - - - - - - T T C - - - - - - > > > 3'
Template Strand
(Anti-codons)
3' < < < - - - - - - A A G - - - - - - < < < 5'
RNA
Message (Codons)
5' > > > - - - - - - U U C - - - - - - > > > 3'
Protein
Amino Acid
DNA
Amino > > > Phenylalanine > > > Carboxy
Epigenetic factors
Feedback loops
DNA
Transcription
RNA
Processing
mRNA
Translation
Protein
>200 known post-translational modifications
(eg, phosphorylation, glycosylation
lipid attachment, peptide cleavage)
Effects
Transcriptional
Post-transcriptional
Translational and degradation
Activity controls
control
control (eg, alternative splicing,
controls
(eg, post-translational modifications,
alternative polyadenylation,
Translational frameshifting
degradation, compartmentalisation)
RNA editing)
Catalytic activity,
association, stability, half-life,
localisation, activity, etc)
Figure by MIT OCW
Harvard-MIT
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Post-translational Modifications
RESID ID
AA0039
Name
O4'-phospho-Ltyrosine
SequenceSpec
L-tyrosine
Weight
Keyword
Fc=243.1
5,
Fp=243.0
296,
Cc=79.98
Cp=79.96
63,
Feature
Enzyme
PIR:Binding site:
phosphate (Tyr)
(covalent)
PIR:Binding site:
phosphate (Tyr)
(covalent) (by ...)
Phosphoprotein
SP:MOD_RES
PHOSPHORYL
ATION
SP:MOD_RES
PHOSPHORYL
ATION (AUTO-)
proteintyrosine
kinase
(EC 2.7.1.112)
Phosphate
H
339 modifications in RESID Database
H
Amino group
H
H
H
OH
N
O
Carboxyl group
O
OH
H
O
P
H
H
Tyrosine side chain
Figure by MIT OCW
Harvard-MIT
Division of Health
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Bioinformatics: Trends,
Tools, and Databases
What kind of problems need to be solved?
How have previous problems in the field been
approached?
Databases Needed to Store
Growing List of Sequence Data
Entrez Human Protein Sequences
Entrez Human
Protein Sequences
Entrez Hum
an Nucleotide Sequences
Entrez Human
Nucleotide
Sequences
250000
8000000
7000000
200000
Number of Sequences
Number of Sequences
6000000
5000000
4000000
3000000
150000
100000
2000000
50000
1000000
0
1993
1995
1997
1999
Year
2001
2003
0
1993
1995
1997
1999
2001
2003
Year
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Alterovitz, G., Afkhami, E. & Ramoni, M. in Focus on Robotics and Intelligent Systems
Research, ed. Columbus, F. Nova Science Publishers, Inc., New York, 2005 (In press).
Harvard-MIT
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Paradigm Shifts in Bioinformatics
Sequencing (1980’s to early 1990’s)
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DNA/RNA/Protein Sequence Analysis/sequence storage
3-D Protein Structure Prediction (Mid-1980’s-late
1990’s)
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Databases of Protein structures
DNA/RNA Microarray Expression Experiments (Mid1990’s to 2000’s)
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Databases of expression data
Protein interaction experiments (Early 2000’s to
Present)
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Databases with pairwise interactions
Mass Spec proteomic pattern experiments (Early
2000’s to Present)
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Databases with mass spec, protein identifications, proteomic
patterns
Integration of multiple modalities (Ongoing)
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Human Genome Project
~ 99% of human genome has been sequenced (2004).
Nature 431: 931-945.
Error rate: ~1 event per 100,000 bases
Number of protein-coding genes: 20,000-25,000
Number of protein-coding genes in worm: ~18,000
Genes comprise only about 2% of the human genome.
„ The rest consists of non-coding regions: functions
may include providing chromosomal structural
integrity and gene regulation.
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