1. Sequence Alignments
Chi-Cheng Lin, Ph.D. Associate Professor Department of Computer Science Winona State University – Rochester Center

2. Sequence Alignments Cornerstone of bioinformatics What is a sequence?
Nucleotide sequence
Amino acid sequence
Pairwise and multiple sequence alignments
What alignments can help
Determine function of a newly discovered gene sequence
Determine evolutionary relationships among genes, proteins, and species
Predicting structure and function of protein
Intro to Bioinformatics – Sequence Alignment
Acknowledgement: This notes is adapted from lecture notes of both Wright State University’s Bioinformatics Program.

3. DNA Replication
Prior to cell division, all the genetic instructions must be “copied” so that each new cell will have a complete set
Intro to Bioinformatics – Sequence Alignment

4. Over time, genes accumulate mutations
Environmental factors
Radiation
Oxidation
Mistakes in replication or repair
Deletions, Duplications
Insertions, Inversions
Translocations
Point mutations
Intro to Bioinformatics – Sequence Alignment

5. Deletions Codon deletion: ACG ATA GCG TAT GTA TAG CCG…
Effect depends on the protein, position, etc.
Almost always deleterious
Sometimes lethal
Frame shift mutation: ACG ATA GCG TAT GTA TAG CCG… ACG ATA GCG ATG TAT AGC CG?…
Almost always lethal
Intro to Bioinformatics – Sequence Alignment

6. Indels
Comparing two genes it is generally impossible to tell if an indel is an insertion in one gene, or a deletion in another, unless ancestry is known: ACGTCTGATACGCCGTATCGTCTATCT ACGTCTGAT---CCGTATCGTCTATCT
Intro to Bioinformatics – Sequence Alignment

7. The Genetic Code
Substitutions are mutations accepted by natural selection.
Synonymous:
CGC  CGA
Non-synonymous:
GAU  GAA
Intro to Bioinformatics – Sequence Alignment

8. Point Mutation Example: Sickle-cell Disease
Wild-type hemoglobin
DNA
3’----CTT----5’
mRNA
5’----GAA----3’
Normal hemoglobin
------[Glu]------
Mutant hemoglobin
DNA
3’----CAT----5’
mRNA
5’----GUA----3’
------[Val]------
Intro to Bioinformatics – Sequence Alignment

9. Intro to Bioinformatics – Sequence Alignment
image credit: U.S. Department of Energy Human Genome Program,

10. Comparing Two Sequences
Point mutations, easy: ACGTCTGATACGCCGTATAGTCTATCT ACGTCTGATTCGCCCTATCGTCTATCT
Indels are difficult, must align sequences: ACGTCTGATACGCCGTATAGTCTATCT CTGATTCGCATCGTCTATCT ACGTCTGATACGCCGTATAGTCTATCT ----CTGATTCGC---ATCGTCTATCT
Intro to Bioinformatics – Sequence Alignment

11. Why Align Sequences? The draft human genome is available
Automated gene finding is possible
Gene: AGTACGTATCGTATAGCGTAA
What does it do?
One approach: Is there a similar gene in another species?
Align sequences with known genes
Find the gene with the “best” match
Intro to Bioinformatics – Sequence Alignment

12. Scoring a Sequence Alignment
Match score: +1
Mismatch score: +0
Gap penalty: –1 ACGTCTGATACGCCGTATAGTCTATCT ||||| ||| || |||||||| ----CTGATTCGC---ATCGTCTATCT
Matches: 18 × (+1)
Mismatches: 2 × 0
Gaps: 7 × (– 1)
Score = +11
Intro to Bioinformatics – Sequence Alignment

13. How can we find an optimal alignment?
Finding the alignment is computationally hard: ACGTCTGATACGCCGTATAGTCTATCT CTGAT---TCG-CATCGTC--T-ATCT
There are ~888,000 possibilities to align the two sequences given above.
Algorithms using a technique called “dynamic programming” are used – out of the scope of this workshop.
Intro to Bioinformatics – Sequence Alignment

14. Global and Local alignments
Global alignments – score the entire alignment
Local alignment – find the best matching subsequence
Why local sequence alignment?
Subsequence comparison between a DNA sequence and a genome
Protein function domains
Exons matching
Intro to Bioinformatics – Sequence Alignment

15. Example Compare the two sequences: TTGACACCCTCCCAATT
ACCCCAGGCTTTACACAG
Global alignment (does it look good?)
TTGACACCCTCC-CAATT
|| || ||
Local alignment (does it look good?)
TTGACACCCTCCCAATT
|| ||||
ACCCCAGGCTTTACACAG
Intro to Bioinformatics – Sequence Alignment

16. Dot Plots
One of the simplest and oldest methods for sequence alignment
Visualization of regions of similarity
Assign one sequence on the horizontal axis
Assign the other on the vertical axis
Place dots on the space of matches
Diagonal lines means adjacent regions of identity
Intro to Bioinformatics – Sequence Alignment

17. A Simple Example Construct a simple dot plot for TAGTCGATG TGGTCATC
The alignment is
TAGTCGATG TGGTC-ATC T A G C *
Intro to Bioinformatics – Sequence Alignment

18. What else can it do (and how)?
Gaps
Inverse substring
Repeat
Palindrome
Gene conservation and order study
Intro to Bioinformatics – Sequence Alignment