1. CS 6293 Advanced Topics: Translational Bioinformatics
Lectures 1 & 2: Introduction to Bioinformatics and Molecular Biology

2. Outline
Course overview
Short introduction to molecular biology

3. Course Info Time: TR 4:00-5:15pm Location: MB 1.01.03
Instructor: Dr. Jianhua Ruan
Office: S.B
Phone:
Office hours: W 2-3pm or by appointment
Web: follow link to teaching, then to cs6293

4. Survey Help me better design lectures and assignments
Form available on course webpage
Your name
Academic preparation
Interests

5. 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

6. Reading materials No textbooks Reading materials Slides Book chapters
Journal / conference papers
Posted on course website usually a week before discussion

7. Covered topics Biology (Next-generation) sequence analysis algs
Gene expression data mining
Translational bioinformatics
Use the PLoS Computational Biology collection:
TBD
You are expected to read a lot of papers and doing multiple presentations

8. Grading Attendance: 10% Homeworks and presentations: 40%
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%

9. 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

10. Growth of GenBank vs Moore’s law

11. Genome annotations
Meyer, Trends and Tools in Bioinfo and Compt Bio, 2006

12. 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.

13. 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.

15. Computer Scientists vs Biologists (courtesy Serafim Batzoglou, Stanford)

16. Biologists vs computer scientists
(almost) Everything is true or false in computer science
(almost) Nothing is ever true or false in Biology

17. 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

18. 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

19. Some examples of central role of CS in bioinformatics

20. 1. Genome sequencing 3x109 nucleotides ~500 nucleotides
AGTAGCACAGACTACGACGAGACGATCGTGCGAGCGACGGCGTAGTGTGCTGTACTGTCGTGTGTGTGTACTCTCCT
3x109 nucleotides
~500 nucleotides

21. 1. Genome sequencing 3x109 nucleotides A big puzzle ~60 million pieces
AGTAGCACAGACTACGACGAGACGATCGTGCGAGCGACGGCGTAGTGTGCTGTACTGTCGTGTGTGTGTACTCTCCT
3x109 nucleotides
A big puzzle
~60 million pieces
Computational Fragment Assembly
Introduced ~1980
1995: assemble up to 1,000,000 long DNA pieces
2000: assemble whole human genome

22. 2. Gene Finding Where are the genes? In humans: ~22,000 genes
~1.5% of human DNA

23. 2. Gene Finding Hidden Markov Models
Start codon
ATG 5’ 3’
Exon 1
Exon 2
Exon 3
Intron 1
Intron 2
Stop codon
TAG/TGA/TAA
Splice sites
The problem of predicting genes means to give coordinates for the exon boundaries.
The first kind of information that prediction algorithms use, is the regular structure of a gene. Every gene starts with an ATG codon, and then exons alternate with introns; at the exon-intron boundaries, the splice sites, there are short words that are approximately preserved.
Hidden Markov Models
(Well studied for many years in speech recognition)

24. 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

25. 4. Sequence Comparison—Alignment
AGGCTATCACCTGACCTCCAGGCCGATGCCC
TAGCTATCACGACCGCGGTCGATTTGCCCGAC
-AGGCTATCACCTGACCTCCAGGCCGA--TGCCC---
| | | | | | | | | | | | | x | | | | | | | | | | |
TAG-CTATCAC--GACCGC--GGTCGATTTGCCCGAC
Sequence Alignment
Introduced ~1970
BLAST: 1990, one of the most cited papers in history
Still very active area of research
query DB
BLAST
Efficient string matching algorithms
Fast database index techniques

26. Lipman & Pearson, 1985
…, 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).
…, 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).
Database size today: 1012
(increased by 2 million folds).
BLAST search: 1.5 minutes

27. 5. Microarray data analysis Example: 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

28. 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

29. A short introduction to molecular biology

30. Life Two categories: Prokaryotes (e.g. bacteria)
Unicellular
No nucleus
Eukaryotes (e.g. fungi, plant, animal)
Unicellular or multicellular
Has nucleus

31. Prokaryote vs Eukaryote
Eukaryote has many membrane-bounded compartment inside the cell
Different biological processes occur at different cellular location

32. Organism, Organ, Cell
Organism
Organ

33. 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

34. 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

35. 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

36. 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

37. 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

38. 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

39. Units of RNA: ribo-nucleotide
A ribonucleotide has 3 components
Sugar - Ribose
Phosphate group
Nitrogen base
Adenine (A)
Guanine (G)
Cytosine (C)
Uracil (U)

40. 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)

41. Polymerization: Nucleotides => nucleic acids
Phosphate
Sugar
Nitrogen Base
Phosphate
Sugar
Nitrogen Base
Phosphate
Sugar
Nitrogen Base

42. DNA 5’-AGCGACTG-3’ AGCGACTG Base Phosphate Sugar
Free phosphate 5’ G A T C
5 prime
3 prime
5’-AGCGACTG-3’
AGCGACTG
DNA
Often recorded from 5’ to 3’, which is the direction of many biological processes.
e.g. DNA replication, transcription, etc.
Base 5
Phosphate
Sugar 4 1 2 3 3’

43. RNA 5’-AGUGACUG-3’ AGUGACUG e.g. translation. 5’ Free phosphate A
5 prime
3 prime
5’-AGUGACUG-3’
AGUGACUG
RNA
Often recorded from 5’ to 3’, which is the direction of many biological processes.
e.g. translation. 3’

44. 5’-AGCGACTG-3’ 3’-TCGCTGAC-5’ AGCGACTG TCGCTGAC
Base-pair:
A = T
G = C G A T C
Forward (+) strand
5’-AGCGACTG-3’
3’-TCGCTGAC-5’
AGCGACTG
TCGCTGAC
Backward (-) strand
One strand is said to be reverse- complementary to the other 3’ 5’
DNA usually exists in pairs.

45. DNA double helix
G-C pair is stronger than A-T pair

46. Reverse-complementary sequences
5’-ACGTTACAGTA-3’
The reverse complement is:
3’-TGCAATGTCAT-5’
=>
5’-TACTGTAACGT-3’
Or simply written as
TACTGTAACGT

47. 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’

48. 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

49. Protein zoom-in
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
Side chain
Amino group
Carboxyl group
Generic chemical form of amino acid

50. Units of Protein: Amino acid
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

51. Amino acids => peptide
R R
| |
H2N--C--COOH H2N--C--COOH
H H
R R
| |
H2N--C--CO--NH--C--COOH
H H
Peptide bond

52. Protein … Has orientations
H2N
COOH
N-terminal
C-terminal …
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

53. 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.

54. 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!

55. Formation of chromosome

56. 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

57. Gene Gene: unit of heredity in living organisms
A segment of DNA with information to make a protein or a functional RNA

58. Some statistics Chromosomes Bases Genes Human 46 3 billion 20k-25k Dog78
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

60. Human genome 46 chromosomes: 22 pairs + X + Y Female: X + X
1 from mother, 1 from father
Female: X + X
Male: X + Y

61. 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 chromosomes …

62. Cell division: mitosis
A cell duplicates its genome and divides into two identical cells
These cells build up different parts of your body

63. 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

64. Central dogma of molecular biology
DNA replication is critical in both mitosis and meiosis

65. 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’

66. Mutation: changes in DNA base-pairs
Nucleotide triphosphate
(dNTP) p
Mutation: changes in DNA base-pairs
Proofreading and error-correcting mechanisms exist to ensure extremely high fidelity (one mistake per 109 – 1011 nucleotides)

67. Central dogma of molecular biology

68. 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

69. Transcription DNA-RNA pair: A=U, C=G T=A, G=C
(where genetic information is stored)
DNA-RNA pair:
A=U, C=G
T=A, G=C
(for making mRNA)
Coding strand: 5’-ACGTAGACGTATAGAGCCTAG-3’
Template strand: 3’-TGCATCTGCATATCTCGGATC-5’
mRNA: ’-ACGUAGACGUAUAGAGCCUAG-3’
Coding strand and mRNA have the same sequence, except that T’s in DNA are replaced by U’s in mRNA.

70. 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

71. The Genetic Code
Third
letter

72. 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

73. 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.
tRNA-Pro
Anti-codon
Nascent peptide
tRNA-Leu
mRNA

74. Transcriptional regulation
Transcription factor
RNA Polymerase
Transcription starting site
promoter
gene
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

75. Splicing Pre-mRNA needs to be “edited” to form mature mRNA
Transcription starting site
promoter
gene
transcription
Pre-mRNA
Pre-mRNA needs to be “edited” to form mature mRNA
intron
intron
Pre-mRNA
5’ UTR
exon
exon
exon
3’ UTR
Splicing
Mature mRNA
(mRNA)
Open reading frame (ORF)
Start codon
Stop codon

76. 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.
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

77. Experimental techniques to manipulate DNA

78. DNA synthesis Creating DNA synthetically in a laboratory
Chemical synthesis
Chemical reactions
Arbitrary sequences
Typically around bases, single stranded
Maximum length
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

79. in vitro DNA Cloning Polymerase chain reaction (PCR) 5’ 5’ denature 5’
Primer (< 30 bases) 5’ 5’ 5’ 5’
DNA Polymerase
dNTP 5’ 5’ 5’ 5’

80. in vivo DNA Cloning
Connect a piece of DNA to bacterial DNA, which can then be replicated together with the host DNA
bacterial DNA

81. DNA sequencing technology
Read out the letters from a DNA sequence
Chain-termination method (Sanger method)
1974, Frederick Sanger
GTGAGGCGCTGC

82. 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

83. DNA sequencing, cont

84. DNA sequencing, cont

85. Base
calling

86. 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

87. 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

88. 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 ( )
$300 million

89. Prior to year 2007 Over 300 genomes have been sequenced
~ nt

90. 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 : “Illumina Drops Personal Genome Sequencing Price to Below $20,000”

92. What’s next? 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?

93. Continue to sequence more species? More individuals?
Genome 10K project
More individuals?
1000 Genome project
What to do with those sequences?

94. Coming next: biological sequence analysis