1. BCB 444/544 F07 ISU Dobbs #4 - Sequence Alignment
8/27/07
Finish: Lecture 2- Biological Databases
Lecture 4
Sequence Alignment
#4_Aug27
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2. Required Reading (before lecture)
#4 - Sequence Alignment
Required Reading (before lecture)
8/27/07
Mon Aug 27 - for Lecture #4
Pairwise Sequence Alignment
Chp 3 - pp Xiong Textbook
Wed Aug 29 - for Lecture #5
Dynamic Programming
Eddy: What is Dynamic Programming?
Thurs Aug 30 - Lab #2:
Databases, ISU Resources,& Pairwise Sequence Alignment
Fri Aug 31 - for Lecture #6
Scoring Matrices and Alignment Statistics
Chp 3 - pp 41-49
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3. BCB 444/544 F07 ISU Dobbs #4 - Sequence Alignment
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HW#2:
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4. Back to: Chp 2- Biological Databases
#4 - Sequence Alignment
8/27/07
Back to: Chp 2- Biological Databases
Xiong: Chp 2
Introduction to Biological Databases
What is a Database?
Types of Databases
Biological Databases
Pitfalls of Biological Databases
Information Retrieval from Biological Databases
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5. BCB 444/544 F07 ISU Dobbs #4 - Sequence Alignment
What is a Database?
8/27/07
Duh!!
OK: skip we'll skip that!
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6. BCB 444/544 F07 ISU Dobbs #4 - Sequence Alignment
Types of Databases
8/27/07
3 Major types of electronic databases:
Flat files - simple text files
no organization to facilitate retrieval
Relational - data organized as tables ("relations")
shared features among tables allows rapid search
Object-oriented - data organized as "objects"
objects associated hierarchically
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7. BCB 444/544 F07 ISU Dobbs #4 - Sequence Alignment
Biological Databases
8/27/07
Currently - all 3 types, but MANY flat files
What are goals of biological databases?
Information retrieval
Knowledge discovery
Important issue: Interconnectivity
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8. Types of Biological Databases
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Types of Biological Databases
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1- Primary
"simple" archives of sequences, structures, images, etc.
raw data, minimal annotations, not always well curated!
2- Secondary
enhanced with more complete annotation of sequences, structures, images, etc.
usually curated!
3- Specialized
focused on a particular research interest or organism
usually - not always - highly curated
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9. Examples of Biological Databases
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Examples of Biological Databases
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1- Primary
DNA sequences
GenBank - US
European Molecular Biology Lab - EMBL
DNA Data Bank of Japan - DDBJ
Structures (Protein, DNA, RNA)
PDB - Protein Data Bank
NDB - Nucleic Acid Data Bank
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10. Examples of Biological Databases
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Examples of Biological Databases
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2- Secondary
Protein sequences
Swiss-Prot, TreEMBL, PIR
these recently combined into UniProt
3- Specialized
Species-specific (or "taxonomic" specific)
Flybase, WormBase, AceDB, PlantDB
Molecule-specific,disease-specific
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11. Pitfalls of Biological Databases
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Pitfalls of Biological Databases
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Errors!
&
Lack of documentation re: quality or reliability of data
Limited mechanisms for "data checking" or preventing propagation of errors (esp. annotation errors!!)
Redundancy
Inconsistency
Incompatibility (format, terminology, data types, etc.)
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12. Information Retrieval from Biological Databases
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Information Retrieval from Biological Databases
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2 most popular retrieval systems:
ENTREZ - NCBI
will use a LOT - was introduced in Lab 1
SRS - Sequence Retrieval Systems - EBI
will use less, similar to ENTREZ
Both:
Provide access to multiple databases
Allow complex queries
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13. Web Resources: Bioinformatics & Computational Biology
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Web Resources: Bioinformatics & Computational Biology
NCBI - National Center for Biotechnology Information
ISCB - International Society for Computational Biology
JCB - Jena Center for Bioinformatics
Pitt - OBRC Online Bioinformatics Resources Collection
UBC - Bioinformatics Links Directory
UWash - BioMolecules
ISU - Bioinformatics Resources - Andrea Dinkelman
ISU - YABI = "Yet Another Bioinformatics Index"
(from BCB Lab at ISU)
Wikipedia: Bioinformatics
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14. ISU Resources & Experts
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ISU Resources & Experts
ISU Research Centers & Graduate Training Programs:
LH Baker Center - Bioinformatics & Biological Statistics
BCB - Bioinformatics & Computational Biology
BCB Lab - (Student-Led Consulting & Resources)
CIAG - Center for Integrated Animal Genomics
CCILD - Computational Intelligence, Learning & Discovery
IGERT Training Grant - Computational Molecular Biology
ISU Facilities:
Biotechnology - Instrumentation Facilities
PSI - Plant Sciences Institute
PSI Centers
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15. SUMMARY: #2- Biological Databases
#4 - Sequence Alignment
8/27/07
SUMMARY: #2- Biological Databases
BEWARE!
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16. Chp 3- Sequence Alignment
8/27/07
Chp 3- Sequence Alignment
SECTION II SEQUENCE ALIGNMENT
Xiong: Chp 3
Pairwise Sequence Alignment
Evolutionary Basis
Sequence Homology versus Sequence Similarity
Sequence Similarity versus Sequence Identity
Methods
Scoring Matrices
Statistical Significance of Sequence Alignment
Adapted from Brown and Caragea, 2007, with some slides from: Altman, Fernandez-Baca, Batzoglou, Craven, Hunter, Page.
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17. Motivation for Sequence Alignment
8/27/07
"Sequence comparison lies at the heart of bioinformatics analysis." Jin Xiong
Sequence comparison is important for drawing functional & evolutionary inferences re: new genes/proteins
Pairwise sequence alignment is fundamental; it used to:
Search for common patterns of characters
Establish pair-wise correspondence between related sequences
Pairwise sequence alignment is basis for:
Database searching (e.g., BLAST)
Multiple sequence alignment (MSA)
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18. BCB 444/544 F07 ISU Dobbs #4 - Sequence Alignment
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Why Align Sequences?
Databases contain many sequences with known functions
& many sequences with unknown functions.
Genes (or proteins) with similar sequences may have similar structures and/or functions.
Sequence alignment can provide important clues to the function of a novel gene or protein
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19. Examples of Bioinformatics Tasks that Rely on Sequence Alignment
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Genomic sequencing
(> 500 complete genomes sequenced!)
Assembling multiple sequence reads
into contigs, scaffolds
Aligning sequences with chromosomes
Finding genes and regulatory regions
Identifying gene products
Identifying function of gene products
Studying the structural organization of genomes
Comparative genomics
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20. BCB 444/544 F07 ISU Dobbs #4 - Sequence Alignment
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Evolutionary Basis
DNA, RNA and proteins are "molecular fossils"
they encode the history of millions of years of evolution
During evolution, molecular sequences accumulate random changes (mutations/variants)
some of which provide a selective advantage or disadvantage, and some of which are neutral
Sequences that are structurally and/or functionally important tend to be conserved
(e.g., chromosomal telomeric sequences; enzyme active sites)
Significant sequence conservation allows inference of evolutionary relatedness
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21. BCB 444/544 F07 ISU Dobbs #4 - Sequence Alignment
8/27/07
Homology
Homology has a very specific meaning in evolutionary & computational biology - & the term is often used incorrectly
For us:
Homology = similarity due to descent from a common evolutionary ancestor
But, HOMOLOGY ≠ SIMILARITY
When 2 sequences share a sufficiently high degree of sequence similarity (or identity), we may infer that they are homologous
We can infer homology from similarity (can't prove it!)
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22. BCB 444/544 F07 ISU Dobbs #4 - Sequence Alignment
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Orthologs vs Paralogs
2 types of homologous sequences:
Orthologs - "same genes" in different species; result of common ancestry; corresponding proteins have "same" functions
(e.g., human -globin & mouse -globin)
Paralogs - "similar genes" within a species; result of gene duplication events; corresponding proteins may (or may not) have similar functions
(e.g., human -globin & human -globin)
Speciation
Duplication B A C C'
A is the parent gene
Speciation leads to B & C
Duplication leads to C’
B and C are Orthologous
C and C’ are Paralogous
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23. Sequence Homology vs Similarity
#4 - Sequence Alignment
Sequence Homology vs Similarity
8/27/07
Homologous sequences - sequences that share a common evolutionary ancestry
Similar sequences - sequences that have a high percentage of aligned residues with similar physicochemical properties
(e.g., size, hydrophobicity, charge)
IMPORTANT:
Sequence homology:
An inference about a common ancestral relationship, drawn when two sequences share a high enough degree of sequence similarity
Homology is qualitative
Sequence similarity:
The direct result of observation from a sequence alignment
Similarity is quantitative; can be described using percentages
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24. Sequence Similarity vs Identity
#4 - Sequence Alignment
Sequence Similarity vs Identity
8/27/07
For nucleotide sequences (DNA & RNA), sequence similarity and identity have the "same" meaning:
Two DNA sequences can share a high degree of sequence identity (or similarity) -- means the same thing
Drena's opinion: Always use "identity" when making quantitative comparisons re: DNA or RNA sequences (to avoid confusion!)
For protein sequences, sequence similarity and identity have different meanings:
Identity = % of exact matches between two aligned sequences
Similarity = % of aligned residues that share similar characteristics (e.g, physicochemical characteristics, structural propsensities, evolutionary profiles)
Drena's opinion: Always use "identity" when making quantitative comparisons re: protein sequences (to avoid confusion!)
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25. What is Sequence Alignment?
8/27/07
What is Sequence Alignment?
Given 2 sequences of letters, and a scoring scheme for evaluating matching letters, find an optimal pairing of letters in one sequence to letters of other sequence.
Align:
1: THIS IS A RATHER LONGER SENTENCE THAN THE NEXT.
2: THIS IS A SHORT SENTENCE.
1: THIS IS A RATHER LONGER SENTENCE THAN THE NEXT.
2: THIS IS A ######SHORT## SENTENCE##############. OR
2: THIS IS A ##SHORT###SENT#EN###CE##############.
Is one of these alignments "optimal"?
Which is better?
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26. Goal of Sequence Alignment
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Find the best pairing of 2 sequences, such that there is maximum correspondence between residues
DNA letter alphabet (+ gap)
TTGACAC
TTTACAC
Proteins 20 letter alphabet (+ gap)
RKVA-GMA
RKIAVAMA
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27. BCB 444/544 F07 ISU Dobbs #4 - Sequence Alignment
Statement of Problem
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Given:
2 sequences
Scoring system for evaluating match (or mismatch) of two characters
Penalty function for gaps in sequences
Find: Optimal pairing of sequences that
Retains the order of characters
Introduces gaps where needed
Maximizes total score
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28. Types of Sequence Variation
#4 - Sequence Alignment
Types of Sequence Variation
8/27/07
Sequences can diverge from a common ancestor through various types of mutations:
Substitutions ACGA  AGGA
Insertions ACGA  ACCGA
Deletions ACGA  AGA
Insertions or deletions ("indels") result in gaps in alignments
Substitotions result in mismatches
No change? match
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29. BCB 444/544 F07 ISU Dobbs #4 - Sequence Alignment
Gaps
8/27/07
Indels of various sizes can occur in one sequence relative to the other
e.g., corresponding to a shortening of the polypeptide chain in a protein
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30. Avoiding Random Alignments with a Scoring Function
#4 - Sequence Alignment
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Avoiding Random Alignments with a Scoring Function
Introducing too many gaps generates nonsense alignments:
s--e-----qu---en--ce sometimesquipsentice
Need to distinguish between alignments that occur due to homology and those that occur by chance
Define a scoring function that accounts for mismatches and gaps
Scoring Function (F): e.g.
Match: + m +1
Mismatch: - s -1
Gap: - d -2
F = m(#matches) + s(#mismatches) + d(#gaps)
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31. Not All Mismatches are the Same
#4 - Sequence Alignment
Not All Mismatches are the Same
8/27/07
Some amino acids are more "exchangeable" than others; e.g., Ser and Thr are more similar than Trp and Ala
A substitution matrix can be used to introduce "mismatch costs" for handling different types of substitutions
Mismatch costs are not usually used in aligning DNA or RNA sequences, because no substitution is "better" than any other (in general)
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32. BCB 444/544 F07 ISU Dobbs #4 - Sequence Alignment
Substitution Matrix
8/27/07
s(a,b) corresponds to score of aligning character a with character b
Match scores are often calculated
based on frequency of mutations in very similar sequences
(more details later)
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33. BCB 444/544 F07 ISU Dobbs #4 - Sequence Alignment
Methods
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Global and Local Alignment
Alignment Algorithms
Dot Matrix Method
Dynamic Programming Method
Gap penalities
DP for Global Alignment
DP for Local Alignment
Scoring Matrices
Amino acid scoring matrices
PAM
BLOSUM
Comparisons between PAM & BLOSUM
Statistical Significance of Sequence Alignment
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34. Global vs Local Alignment
#4 - Sequence Alignment
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Global vs Local Alignment
Global alignment
Finds best possible alignment across entire length of 2 sequences
Aligned sequences assumed to be generally similar over entire length
Local alignment
Finds local regions with highest similarity between 2 sequences
Aligns these without regard for rest of sequence
Sequences are not assumed to be similar over entire length
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35. Global vs Local Alignment - example
#4 - Sequence Alignment
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Global vs Local Alignment - example
S = CTGTCGCTGCACG
T = TGCCGTG
CTGTCG-CTGCACG
-TGCCG--TG----
Global alignment
-TGC-CG-TG----
CTGTCGCTGCACG--
TGC-CGTG
Local alignment
Which is better?
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36. Global vs Local Alignment When use which?
#4 - Sequence Alignment
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Global vs Local Alignment When use which?
Both are important
but it is critical to use right method for a given task!
Global alignment:
Good for: aligning closely related sequences of approx. same length
Not good for: divergent sequences or sequences with different lengths
Local Alignment:
Good for: searching for conserved patterns (domains or motifs) in DNA or protein sequences
Not good for: generating alignment of closely related sequences
Global and local alignments are fundamentally similar and differ only in optimization strategy used in aligning similar residues
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37. BCB 444/544 F07 ISU Dobbs #4 - Sequence Alignment
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Alignment Algorithms
3 major methods for alignment:
Dot matrix analysis
Dynamic Programming
Word or k-tuple methods (later, in Chp 4)
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38. Dot Matrix Method (Dot Plots)
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Dot Matrix Method (Dot Plots)
Place 1 sequence along top row of matrix
Place 2nd sequence along left column of matrix
Plot a dot each time there is a match between an element of row sequence and an element of column sequence
For proteins, usually use more sophisticated scoring schemes than "identical match"
Diagonal lines indicate areas of match
Reverse diagonals (perpendicular to diagonal) indicate inversions A C G A C G
Exploring Dot Plots
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