cs 6293 advanced topics: translational bioinformatics
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CS 6293 Advanced Topics: Translational Bioinformatics
Lectures 1 & 2: Introduction to Bioinformatics and Molecular Biology
Outline
• Course overview
• Short introduction to molecular biology
Course Info
• Time: TR 4:00-5:15pm• Location: MB 1.01.03• Instructor: Dr. Jianhua Ruan
Office: S.B. 4.01.48Phone: 458-6819Email: jianhua.ruan@utsa.eduOffice hours: W 2-3pm or by appointment
• Web: http://www.cs.utsa.edu/~jruan, follow link to teaching, then to cs6293
Survey
• Help me better design lectures and assignments
• Form available on course webpage– Your name– Email– Academic preparation– Interests
Course description
• Review of the “most recent” developments & research problems in bioinformatics– Some overlap with CS5263: (Introduction to)
Bioinformatics and CS6293 Fall 2010
• Prerequisite:– CS5263– Strong background in algorithms and data structures – Solid knowledge of statistics and probability– Desire and ability to learn by yourself
Reading materials
• No textbooks
• Reading materials– Slides– Book chapters– Journal / conference papers– Posted on course website usually a
week before discussion
Covered topics
• Biology• (Next-generation) sequence analysis algs• Gene expression data mining• Translational bioinformatics
– Use the PLoS Computational Biology collection: http://www.ploscollections.org/article/browseIssue.action?issue=info:doi/10.1371/issue.pcol.v03.i11
• TBD• You are expected to read a lot of papers and
doing multiple presentations
Grading
• Attendance: 10%– At most 3 classes missed without affecting grade,
unless approved by the instructor• Homeworks and presentations: 40%
– 3-5 assignments• Combination of theoretical and programming exercises• Presenting and discussing papers• Scribing
– No late submission accepted– Read the collaboration policy!
• Midterm project / exam: 20%• Final project / exam: 30%
Why bioinformatics
• The advance of experimental technology has resulted in a huge amount of data– The human genome is “finished”– Even if it were, that’s only the beginning…
• The bottleneck is how to integrate and analyze the data– Noisy– Diverse
Growth of GenBank vs Moore’s law
Genome annotations
Meyer, Trends and Tools in Bioinfo and Compt Bio, 2006
What is bioinformatics
• National Institutes of Health (NIH):– Research, development, or application of
computational tools and approaches for expanding the use of biological, medical, behavioral or health data, including those to acquire, store, organize, archive, analyze, or visualize such data.
What is bioinformatics
• National Center for Biotechnology Information (NCBI):– the field of science in which biology, computer
science, and information technology merge to form a single discipline. The ultimate goal of the field is to enable the discovery of new biological insights as well as to create a global perspective from which unifying principles in biology can be discerned.
Chemistry
MathematicsStatistics
Computer ScienceInformatics
Physics
Medicine
BiologyMolecular Biology
Bioinformatics
Computer Scientists vs Biologists
(courtesy Serafim Batzoglou, Stanford)
Biologists vs computer scientists
• (almost) Everything is true or false in computer science
• (almost) Nothing is ever true or false in Biology
Biologists vs computer scientists
• Biologists seek to understand the complicated, messy natural world
• Computer scientists strive to build their own clean and organized virtual world
Biologists vs computer scientists
• Computer scientists are obsessed with being the first to invent or prove something
• Biologists are obsessed with being the first to discover something
Some examples of central role of CS in bioinformatics
1. Genome sequencing
AGTAGCACAGACTACGACGAGACGATCGTGCGAGCGACGGCGTAGTGTGCTGTACTGTCGTGTGTGTGTACTCTCCT
3x109 nucleotides
~500 nucleotides
AGTAGCACAGACTACGACGAGACGATCGTGCGAGCGACGGCGTAGTGTGCTGTACTGTCGTGTGTGTGTACTCTCCT
3x109 nucleotides
Computational Fragment AssemblyIntroduced ~19801995: assemble up to 1,000,000 long DNA pieces2000: assemble whole human genome
A big puzzle~60 million pieces
1. Genome sequencing
Where are the genes?Where are the genes?
2. Gene Finding
In humans:
~22,000 genes~1.5% of human DNA
Start codonATG
5’ 3’Exon 1 Exon 2 Exon 3Intron 1 Intron 2
Stop codonTAG/TGA/TAA
Splice sites
2. Gene Finding
Hidden Markov Models
(Well studied for many years in speech recognition)
3. Protein Folding• The amino-acid sequence of a protein determines the 3D fold
• The 3D fold of a protein determines its function
• Can we predict 3D fold of a protein given its amino-acid sequence?– Holy grail of computational biology —40 years old problem
– Molecular dynamics, computational geometry, machine learning
4. Sequence Comparison—Alignment
AGGCTATCACCTGACCTCCAGGCCGATGCCC
TAGCTATCACGACCGCGGTCGATTTGCCCGAC
-AGGCTATCACCTGACCTCCAGGCCGA--TGCCC--- | | | | | | | | | | | | | x | | | | | | | | | | |
TAG-CTATCAC--GACCGC--GGTCGATTTGCCCGAC
Sequence AlignmentIntroduced ~1970BLAST: 1990, one of the most cited papers
in historyStill very active area of research
query
DB
BLAST
Efficient string matching algorithms
Fast database index techniques
…, comparison of a 200-amino-acid sequence to the 500,000 residues in the National Biomedical Research Foundation library would take less than 2 minutes on a minicomputer, and less than 10 minutes on a microcomputer (IBM PC).
Lipman & Pearson, 1985
Database size today: 1012
(increased by 2 million folds).
BLAST search: 1.5 minutes
…, comparison of a 200-amino-acid sequence to the 500,000 residues in the National Biomedical Research Foundation library would take less than 2 minutes on a minicomputer, and less than 10 minutes on a microcomputer (IBM PC).
5. Microarray data analysisExample: Clinical prediction of Leukemia type
• 2 types of leukemia– Acute lymphoid (ALL)
– Acute myeloid (AML)
• Different treatments & outcomes• Predict type before treatment?
Bone marrow samples: ALL vs AML
Measure amount of each gene
Some goals of biology for the next 50 years
• List all molecular parts that build an organism– Genes, proteins, other functional parts
• Understand the function of each part• Understand how parts interact physically and functionally• Study how function has evolved across all species• Find genetic defects that cause diseases• Design drugs rationally• Sequence the genome of every human, use it for personalized
medicine
• Bioinformatics is an essential component for all the goals above
A short introduction to molecular biology
Life
• Two categories:– Prokaryotes (e.g. bacteria)
• Unicellular• No nucleus
– Eukaryotes (e.g. fungi, plant, animal)• Unicellular or multicellular• Has nucleus
Prokaryote vs Eukaryote
• Eukaryote has many membrane-bounded compartment inside the cell– Different biological processes occur at different
cellular location
Organism, Organ, CellOrganism
Organ
Chemical contents of cell
• Water• Macromolecules (polymers) - “strings” made by linking
monomers from a specified set (alphabet)–Protein–DNA–RNA–…
• Small molecules–Sugar–Ions (Na+, Ka+, Ca2+, Cl- ,…)–Hormone–…
DNA
• DNA: forms the genetic material of all living organisms– Can be replicated and passed to descendents– Contains information to produce proteins
• To computer scientists, DNA is a string made from alphabet {A, C, G, T}– e.g. ACAGAACGTAGTGCCGTGAGCG
• Each letter is a nucleotide• Length varies from hundreds to billions
RNA
• Historically thought to be information carrier only– DNA => RNA => Protein– New roles have been found for them
• To computer scientists, RNA is a string made from alphabet {A, C, G, U}– e.g. ACAGAACGUAGUGCCGUGAGCG
• Each letter is a nucleotide• Length varies from tens to thousands
Protein
• Protein: the actual “worker” for almost all processes in the cell– Enzymes: speed up reactions– Signaling: information transduction– Structural support– Production of other macromolecules– Transport
• To computer scientists, protein is a string made from 20 kinds of characters– E.g. MGDVEKGKKIFIMKCSQCHTVEKGGKHKTGP
• Each letter is called an amino acid• Length varies from tens to thousands
DNA/RNA zoom-in
• Commonly referred to as Nucleic Acid• DNA: Deoxyribonucleic acid• RNA: Ribonucleic acid• Found mainly in the nucleus of a cell (hence
“nucleic”)• Contain phosphoric acid as a component (hence
“acid”)• They are made up of a string of nucleotides
Nucleotides• A nucleotide has 3 components
– Sugar ring (ribose in RNA, deoxyribose in DNA)
– Phosphoric acid– Nitrogen base
• Adenine (A)• Guanine (G)• Cytosine (C)• Thymine (T) in DNA and Uracil (U) in RNA
Units of RNA: ribo-nucleotide
• A ribonucleotide has 3 components– Sugar - Ribose– Phosphate group– Nitrogen base
• Adenine (A)• Guanine (G)• Cytosine (C)• Uracil (U)
Units of DNA: deoxy-ribo-nucleotide
• A deoxyribonucleotide has 3 components– Sugar – Deoxy-ribose– Phosphate group– Nitrogen base
• Adenine (A)• Guanine (G)• Cytosine (C)• Thymine (T)
Polymerization: Nucleotides => nucleic acids
Phosphate
Sugar
Nitrogen Base
Phosphate
Sugar
Nitrogen Base
Phosphate
Sugar
Nitrogen Base
G
A
G
T
C
A
G
C
5’-AGCGACTG-3’
AGCGACTG
Phosphate
Sugar
Base
1
23
4
5
Often recorded from 5’ to 3’, which is the direction of many biological processes.e.g. DNA replication, transcription, etc.
5’
3’
DNA
Free phosphate 5 prime 3 prime
G
A
G
U
C
A
G
U
5’-AGUGACUG-3’
AGUGACUG
Often recorded from 5’ to 3’, which is the direction of many biological processes.e.g. translation.
5’
3’
RNA
Free phosphate 5 prime 3 prime
T
C
A
C
T
G
G
C
G
A
G
T
C
A
G
C
Base-pair:
A = T
G = C
5’
5’3’
3’
5’-AGCGACTG-3’3’-TCGCTGAC-5’
AGCGACTGTCGCTGAC
Forward (+) strand
Backward (-) strand
One strand is said to be reverse- complementary to the other
DNA usually exists in pairs.
DNA double helix
G-C pair is stronger than A-T pair
Reverse-complementary sequences
• 5’-ACGTTACAGTA-3’
• The reverse complement is:
3’-TGCAATGTCAT-5’
=>
5’-TACTGTAACGT-3’
• Or simply written as
TACTGTAACGT
Orientation of the double helix
• Double helix is anti-parallel–5’ end of one strand pairs with 3’ end of the other–5’ to 3’ motion in one strand is 3’ to 5’ in the other
• Double helix has no orientation–Biology has no “forward” and “reverse” strand–Relative to any single strand, there is a “reverse complement” or “reverse strand”–Information can be encoded by either strand or both strands
5’TTTTACAGGACCATG 3’3’AAAATGTCCTGGTAC 5’
RNA
• RNAs are normally single-stranded
• Form complex structure by self-base-pairing
• A=U, C=G
• Can also form RNA-DNA and RNA-RNA double strands.– A=T/U, C=G
Carboxyl groupAmino group
Protein zoom-in
Side chain
Generic chemical form of amino acid
• Protein is the actual “worker” for almost all processes in the cell
• A string built from 20 kinds of chars– E.g. MGDVEKGKKIFIMKCSQCHTVEKGGKH
• Each letter is called an amino acid
R | H2N--C--COOH | H
• 20 amino acids, only differ at side chains– Each can be expressed by three letters– Or a single letter: A-Y, except B, J, O, U, X, Z
– Alanine = Ala = A
– Histidine = His = H
Units of Protein: Amino acid
R R | | H2N--C--CO--NH--C--COOH | | H H
R R | | H2N--C--COOH H2N--C--COOH | | H H
Amino acids => peptide
Peptide bond
Protein
• Has orientations• Usually recorded from N-terminal to C-terminal• Peptide vs protein: basically the same thing• Conventions
– Peptide is shorter (< 50aa), while protein is longer– Peptide refers to the sequence, while protein has 2D/3D structure
R
H2N
R R R R R
COOH
N-terminal C-terminal
…
Protein structure• Linear sequence of amino acids folds to
form a complex 3-D structure.
• The structure of a protein is intimately connected to its function.
Genome and chromosome
• Genome: the complete DNA sequences in the cell of an organism – May contain one (in most prokaryotes) or
more (in eukaryotes) chromosomes
• Chromosome: a single large DNA molecule in the cell– May be circular or linear– Contain genes as well as “junk DNAs”– Highly packed!
Formation of chromosome
Formation of chromosome
50,000 times shorter than extended DNA
The total length of DNA present in one adult human is the equivalent of nearly 70 round trips from the earth to the sun
Gene
• Gene: unit of heredity in living organisms – A segment of DNA with information to make a
protein or a functional RNA
Some statistics
Chromosomes Bases Genes
Human 46 3 billion 20k-25k
Dog 78 2.4 billion ~20k
Corn 20 2.5 billion 50-60k
Yeast 16 20 million ~7k
E. coli 1 4 million ~4k
Marbled lungfish
? 130 billion ?
Human genome
• 46 chromosomes: 22 pairs + X + Y1 from mother, 1 from father
• Female: X + X
• Male: X + Y
Human genome
• Every cell contains the same genomic information– Except sperms and eggs, which only contain
half of the genome• Otherwise your children would have 46 + 46
chromosomes …
Cell division: mitosis• A cell duplicates its
genome and divides into two identical cells
• These cells build up different parts of your body
Cell division: meiosis• A reproductive cell
divides into four cells, each containing only half of the genomes– Diploid => haploid
• Two haploid cells (sperm + egg) forms a zygote– Which will then develop
into a multi-cellular organism by mitosis
Central dogma of molecular biology
DNA replication is critical in both mitosis and meiosis
DNA Replication
• The process of copying a double-stranded DNA molecule– Semi-conservative
5’-ACATGATAA-3’
3’-TGTACTATT-5’
5’-ACATGATAA-3’ 5’-ACATGATAA-3’
3’-TGTACTATT-5’ 3’-TGTACTATT-5’
• Mutation: changes in DNA base-pairs• Proofreading and error-correcting mechanisms
exist to ensure extremely high fidelity (one mistake per 109 – 1011 nucleotides)
p p p Nucleotide triphosphate(dNTP)
Central dogma of molecular biology
Transcription
• The process that a DNA sequence is copied to produce a complementary RNA– Called message RNA (mRNA) if the RNA carries
instruction on how to make a protein – Called non-coding RNA if the RNA does not carry
instruction on how to make a protein– Only consider mRNA for now
• Similar to replication, but– Only one strand is copied– No proof-reading so relatively higher error rate
Transcription(where genetic information is stored)
(for making mRNA)
Coding strand: 5’-ACGTAGACGTATAGAGCCTAG-3’
Template strand: 3’-TGCATCTGCATATCTCGGATC-5’
mRNA: 5’-ACGUAGACGUAUAGAGCCUAG-3’
Coding strand and mRNA have the same sequence, except that T’s in DNA are replaced by U’s in mRNA.
DNA-RNA pair:
A=U, C=G
T=A, G=C
Translation
• The process of making proteins from mRNA• A gene uniquely encodes a protein• There are four bases in DNA (A, C, G, T), and four in
RNA (A, C, G, U), but 20 amino acids in protein• How many nucleotides are required to encode an amino
acid in order to ensure correct translation?– 4^1 = 4– 4^2 = 16– 4^3 = 64
• The actual genetic code used by the cell is a triplet.– Each triplet is called a codon
The Genetic CodeThirdletter
Translation
• The sequence of codons is translated to a sequence of amino acids
• Gene: -GCT TGT TTA CGA ATT-• mRNA: -GCU UGU UUA CGA AUU -• Peptide: - Ala - Cys - Leu - Arg - Ile –
• Start codon: AUG– Also code Methionine– Stop codon: UGA, UAA, UAG
Translation• Transfer RNA (tRNA) – a different type of RNA.
– Freely float in the cell.– Every amino acid has its own type of tRNA that binds
to it alone.
• Anti-codon – codon binding crucial.
mRNA
tRNA-Leu
Nascent peptide
tRNA-Pro
Anti-codon
Transcriptional regulation
genepromoter
Transcription starting site
RNA PolymeraseTranscription factor
• RNA polymerase binds to certain location on promoter to initiate transcription
• Transcription factor binds to specific sequences on the promoter to regulate the transcription– Recruit RNA polymerase: induce– Block RNA polymerase: repress– Multiple transcription factors may coordinate
Splicing
genepromoter
Transcription starting site
Pre-mRNAtranscription
• Pre-mRNA needs to be “edited” to form mature mRNA
5’ UTR 3’ UTRexon exon exon
intron intron
Start codon Stop codon
Open reading frame (ORF)
Pre-mRNA
Mature mRNA(mRNA)
Splicing
Summary• DNA: a string made from {A, C, G, T}
– Forms the basis of genes– Has 5’ and 3’– Normally forms double-strand by reverse complement
• RNA: a string made from {A, C, G, U}– mRNA: messenger RNA– tRNA: transfer RNA– Other types of RNA: rRNA, miRNA, etc.– Has 5’ and 3’– Normally single-stranded. But can form secondary structure
• Protein: made from 20 kinds of amino acids– Actual worker in the cell– Has N-terminal and C-terminal– Sequence uniquely determined by its gene via the use of codons– Sequence determines structure, structure determines function
• Central dogma: DNA transcribes to RNA, RNA translates to Protein– Both steps are regulated
Experimental techniques to manipulate DNA
DNA synthesis
• Creating DNA synthetically in a laboratory• Chemical synthesis
– Chemical reactions– Arbitrary sequences– Typically around 15-25 bases, single stranded– Maximum length 160-200
• Cloning: make copies based on a DNA template– Biological reactions– Requires template– Utilizes same mechanisms as in DNA replication– Many copies of a long DNA in a short time
in vitro DNA Cloning
• Polymerase chain reaction (PCR)
denature
5’
5’5’
5’ 5’5’
5’
Primer (< 30 bases)
5’ 5’
dNTP
5’5’
5’
DNA Polymerase
in vivo DNA Cloning
• Connect a piece of DNA to bacterial DNA, which can then be replicated together with the host DNA
bacterial DNA
DNA sequencing technology
• Read out the letters from a DNA sequence• Chain-termination method (Sanger method)
1974, Frederick Sanger
GTGAGGCGCTGC
DNA sequencing: Basic idea
• PCR primer extension
5’-TTACAGGTCCATACTA 3’-AATGTCCAGGTATGATACATAGG-5’
• We need to supply A, C, G, T for the synthesis to continue
• Besides A, C, G, T, we add some A*, C*, G*, and T*– Very similar to ACGT in all aspects, except that– The extension will stop if used
DNA sequencing, cont
DNA sequencing, cont
Basecalling
Sequencing speed
• Current methods can directly sequence only relatively short (<1000bp long) DNA fragments in a single reaction
• Automated DNA-sequencing instruments (using gel-filled capillaries) can sequence up to 384 DNA samples in a single batch (run) in up to 24 runs a day: ~ 3,000,000 bases per day
Advances in DNA sequencing
• 1969: three years to sequence 115nt DNA• 1979: three years to sequence ~1650nt• 1989: one week to sequence ~1650nt• 1995: Haemophilus genome sequenced at
TIGR - 1,830,138nt• 2000: Human Genome - working draft
sequence, 3 billion bases• 2004: 454 Life Science invented the first
new-generation sequencer
The bioinformatics landmark
• Completion of human genome sequencing is a success embraced by – Advancement in sequencing technology– Speed of computation– Algorithm development in bioinformatics
• HGP (Human Genome Project) strategy – Hierarchical sequencing– Estimated 15 years (1990 – 2005), completed in 13 years– $3 billion
• Celera strategy– Whole-genome shotgun sequencing– Three years (1998-2001)– $300 million
Prior to year 2007
• Over 300 genomes have been sequenced
• ~1011 - 1012 nt
Year 2007• Genomes of three individual human were
sequenced– James Watson– Craig Venter– Yang Huanming
• Cost for sequencing Watson’s genome– $3 million, 2 months– Compared to $3 billion, 13 years for HGP
• These are achieved without the new-generation sequencing technology !
• June 3 2010: “Illumina Drops Personal Genome Sequencing Price to Below $20,000”
• Sequencing speed has been tremendously improved
• High efficiency and relatively low cost makes it possible to sequence the genome of any individual from any species
What’s next?
Continue to sequence more species? Genome 10K project
More individuals?1000 Genome project
What to do with those sequences?
Coming next: biological sequence analysis
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