1. Bioinformatics An introduction1

2. DNA - the basics 2

3. 3

4. Drew Berry – DNA animations 4

5. Organisation of DNA DNA is packed in chromosomes
Karyotype: chromosome set of a species
Chromosomes are dynamic structures
The Human karyotype
23 pairs of chromosomes
46 DNA molecules 5

6. The Genetic Code In general:
Amino acids that share the same biosynthetic pathway tend to have the same first base in their codons
Amino acids with similar physical properties have similar codons causing conservative substitutions in the case of mutations or mistranslation 6

7. DNA replication
The ability of DNA to replicate itself is a fundamental driver of life
DNA copy is catalysed by enzymes (DNA polymerases)
The complementary strand is synthesised from a template strand, using deoxynucleotides and a primer
Synthesis is directional (5’->3’)
Deoxyribonucleotides
dNTPs
Template DNA strand
Primer A C
T G
DNA polymerase
Template 5’
TCAG 3’ 3’ 5’ T C G A
reverse complement copy 7

8. Genetic mutation
The genetic code can be changed by a variety of processes
Small scale:
Damage to DNA (radiation or chemical damage)
Translation errors
Large scale:
Duplication of sections of DNA
Deletion of sections of DNA
Transposition of sections of DNA
These errors in replication cause DNA
Base substitutions
Insertions
Deletions
Frameshifts
Look at the web site 8

9. Single nucleotide polymorphisms (SNPs)
Defined as cases where 1% of the population has a variation in a single nucleotide
Are mostly unique
Can occur in coding or non-coding regions of DNA
Can result in a change in the translated amino acid sequence or be silent (synonymous)
Why are SNPs important?
Aubundant – the most common form of genetic variation
When comparing two human DNA sequences there is a SNP every 1–2,000 nucleotides
2-3 million SNPs per genome
Cause genetic variation
Inherited and can be used to trace ancestry 9

10. The rate of genetic mutation
The mutation rate (per year or per generation) differs between species and even between different sections of the genome
Different types of mutations occur with different frequencies
The average mutation rate is estimated to be ~2.5 × 10−8 mutations per nucleotide site or 175 mutations per diploid genome per generation
Ref: Nachman, M. W.; Crowell, S. L. Estimate of the Mutation Rate Per Nucleotide in Humans. Genetics, 156, 297 (2000). 10

11. Amino acid substitution matrices
Ala Arg Asn Asp Cys Gln Glu Gly His Ile Leu Lys Met Phe Pro Ser Thr Trp Tyr Val
A R N D C Q E G H I L K M F P S T W Y V
Ala A
Arg R
Asn N
Asp D
Cys C
Gln Q
Glu E
Gly G
His H
Ile I
Leu L
Lys K
Met M
Phe F
Pro P
Ser S
Thr T
Trp W
Tyr Y
Val V
Interconversion between amino acids is not equally likely – this is governed by the DNA code itself and the physicochemical properties of the encoded amino acids (polar, nonpolar, large, small, etc)
Substitution matrices describe the probability that one aa is converted to another and ‘accepted’ (after some period of time)
Above is the PAM1 matrix for comparison of 10,000 codons (corresponds to a period of time where 1% of bases have changed).
Using such matrices allows us to estimate the probability that two sequences have a common ancestor 11

12. PAM and BLOSUM matrices
Scoring matrices are used to:
produce sequence alignments and score similarity between two or more protein
to search a database to find sequences similar to a test sequence
Commonly used families of matrices:
PAM (Accepted Point Mutation) matrices (Dayhof)
Derived from global alignments of entire proteins
Better for closely related proteins
BLOSUM (BLocks SUbstitution Matrices) matrices (Steven and Henikof)
Derived from local alignments of blocks of sequences
Better for evolutionally divergent sequences 12

13. The polymerase chain reaction
Replication requires a DNA polymerase
Thermostable DNA polymerase. E.g. Taq polymerase from the Thermus aquaticus, a thermophilic bacterium that lives in hot springs
Efficient DNA amplification
No error correction
Kary Mullis Nobel prize in chemistry: 1993
Melt DNA
(94-98 °)
Anneal primers (50-65 °)
Elongation (72 °)
Exponential replication 13

14. DNA Sequencing (Sanger)
PCR Reaction is terminated using randomly incorporated dideoxynucleosides (ddNP)
Older methods use radiolabelled phosphate
Newer methods use ddNP incorporating dyes
Truncated DNA strands are separated on a gel or by capillary electrophoresis 14

15. Next Generation Sequencing
Next generation sequencing refers to methods newer than the Sanger approach
A variety of techniques developed by different companies
DNA is generally immobilized on a solid support
Very large numbers of small reads
Multiple reads of a each section of genomic DNA (eg 30x)
Assembling the genome becomes a significant computational problem
Some ‘single molecule’ methods do not require PCR (reduces errors)
Cost has reduced substantially  the $1000 genome!
Refs: Metzker, M. L. Sequencing Technologies — the Next Generation. Nat. Rev. Genet. 2009, 11, 31–46. 15

16. Next-gen Sequencing Overview
Ref: 16

17. The Human Genome Project
Funded by US government
The human genome was published in February 2001
Project completed in 2003
Cost $US 2.7 billion in 1991 dollars
Hierarchical shotgun sequencing (genome is broken down into many smaller fragments)
Automated Sanger type sequencing
Ref: 17

18. Human gene function
The human genome contains about 21K genes (about 100K were expected!)
98% of the human genome is noncoding DNA
Noncoding DNA can code for regulatory RNAs or otherwise regulate transcription
Ref: Häggström, Wikiversity Journal of Medicine 1 (2). DOI: /wjm/ ISSN 18

19. Human genome resources
Three useful sites providing a huge number of resources such as genome browsers
NCBI: National center of biological information
UCSC genome browser
Ensembl: European site at the Sanger centre 19

20. Multiple Genomes
Ref: McVean et al. An Integrated Map of Genetic Variation From 1,092 Human Genomes. Nature 2012, 491, 20

21. Genomic data
Sequencing technologies produce enormous amounts of sequence data. What do we want to do with this?
Identify genes
Identify functions of gene products (proteins)
Compare genes between species
Identify relationships (similarities) between species
Identify relationships between changes in sequences and disease/disorders
Pharmacogenomics – find relationships between drug behaviour/metabolism and the genome
Cancer – identify relationships between sequence and disease. E.g. mutations in the BRCA1 and BRCA2 greatly increase a women’s risk of breast cancer (See NIH BRCA fact sheet) 21

22. BLAST - Searching genomes
BLAST is a rapid method for searching protein or DNA sequences in large databases
Can search on nucleotide or protein sequences
Sequences are divided into groups of k amino acids or bases
PGFHJIQMQVVS  PGF, GFH, FHJ, HJI, etc (k=3)
Common or repeated sequences are discarded
Sections of exact sequence match are searched for
The sequence alignment is expanded from sections that are exact matches
Blast can miss difficult matches 22

23. Blast at NIH NCBI 23

24. 24

25. 25

26. Sequence alignment Protein or DNA sequences can be aligned
Differences between sequences are interpreted as mutations, insertions or deletions
Substitution matrices are used to score the likelihood of a match
Alignment scores are calculated between pairs of sequences
Multiple alignments can be performed
Many alignment programs: Clustal, T-coffee, 26

27. Clustal 27

28. Sequence alignments and protein structural similarity
Sequence alignments are based on protein/DNA sequence similarity and not on structural similarity
High sequence similarity implies (but does not guarantee) structural similarity
High sequence similarity implies (but does not garuantee) similar protein function
Comparison of RMSD when pairs of similar proteins are superimposed using the sequence alignment (X axis) and the protein 3D structures (Y axis)
Ref: Kosloff, M.; Kolodny, R. Sequence-Similar, Structure-Dissimilar Protein Pairs in the PDB. Proteins 2008, 71, 891 28

29. Key learning questions
DNA
Organisation
Function
Replication
Mutations and inheritance
DNA sequencing
The polymerase chain reaction (how does it work, benefits, limitations)
Sanger sequencing (how? Limitations)
Next gen sequencing (in general, how does it differ from older methods, why is it better)?
The human genome
What’s in it?
Why sequence it?
Genomic data
Sequence alignments (what are they estimating, what are the limitations?)
BLAST searching (what can it do for us, what are the limitations here?) 29

30. Good resources
The NIH provides a genetics primer which is available online
- hgp
or as a pdf
The NIH BRCA fact sheet: