Transcript Phylogenetics workshop

Phylogenetics workshop:
Protein sequence phylogeny
Darren Soanes
Parts of a tree
plural of taxon = taxa
Phylogenetic tree: evolutionary family tree
Nodes in the tree represent speciation
events, where an ancestral lineage gives rise
to daughter lineages.
Relationships in trees
Rooting a tree
outgroup
Root - most recent
common ancestor of
all the taxa in a tree
outgroup — a taxon outside the group of interest. All the members of the
group of interest are more closely related to each other than they are to
the outgroup. Used to root the tree.
Outgroup
Rooted and unrooted trees
rooted tree
unrooted tree
Cladogram
Phylogram
Evolution of Amino Acid Sequences
• Amino acid sequences change due to
mutations in DNA sequence.
• Amino acid sequences evolve more
slowly than DNA sequences.
• Evolutionary selection occurs on protein
sequences.
• Gene trees created using protein
sequences.
DNA mutations (1)
• Synonymous substitution – change in DNA
sequence that does not affect the amino acid
sequence, often in the third position of a codon,
e.g. CCG (Pro)→CCA (Pro).
• Non-synonymous substitution - change in DNA
sequence that does affect the amino acid
sequence, often in the first or second position of
a codon, e.g. CCG (Pro)→CAG (Gln).
Genetic Code
DNA mutations (2)
• Non-synonymous substitution also called
missense mutation.
• Nonsense mutation – where a a stop codon is
introduced into the middle of a sequence, e.g.
TGG (Trp)→ TAG (Stop)
• Insertion / deletion (indel), causes a frame shift if
not a multiple of three bases.
• Nonsense and frame-shift mutations usually
produce non-functional proteins.
Amino acid substitution matrices (1)
• Substitutions between amino acids that
are similar in properties are more
common.
• Cysteine, glycine and tryptophan rarely
change.
• Substitution matrices measure the
likelihood that one amino acid is likely to
change to another.
Families of amino acids
Amino acid substitution matrices (2)
• Amino acid substitution matrices are empirically
derived by alignment of sets of closely related
protein sequences.
• Examples include Dayhoff, BLOSUM (used in
BLAST searches), WAG, JTT, LG.
• Different matrices suitable for looking at proteins
encoded by mitochondrial genome e.g. MtREV.
BLOSUM 62 Matrix
Rates of amino acid change
• Rate of substitution varies at different positions
in an amino acid sequence.
• A proportion of sequences are likely to be
invariant, generally have an essential role in the
function of a protein.
• A gamma distribution models the variation of
rates at different sites.
• Sites are sorted into gamma rate categories.
Structure of thrombin showing catalytic
triad (conserved in serine proteases)
Phylogenetic analysis
• Phylogenetic analysis programs take an alignment of
protein sequences and attempt to produce a
phylogenetic tree showing evolutionary relationships
between the sequences.
• User can select amino acid substitution matrix and
number of gamma rate categories, the program will
estimate the proportion of invariant sites.
• Programs use these parameters and protein alignment
to estimate evolutionary distance between sequences.
• They calculate topology and branch length of final tree.
Distance Methods
• Evolutionary distance calculated for all pairs of
taxa.
• UPGMA - assumes rate of substitution is
constant.
• Least squares – allows different rates of
substitution in different branches.
• Minimum evolution (ME)– topology chosen
where the sum of branch lengths is the smallest.
Can take a long time to compute, neighbour
joining (NJ) method is simplified version of ME –
much quicker.
Maximum parsimony
• For each topology the smallest number of
amino acid substitutions are calculated
that could explain the evolutionary
process.
• The topology that requires the smallest
number of substitutions is chosen as the
best one.
Maximum likelihood (ML)
• For each topology the likelihood is calculated that the
known sequences could have evolved on that tree
(branch lengths and substitution rate parameters
optimised).
• Topology with the best likelihood score is chosen.
• Takes a long time to compute ML of every possible tree.
• Heuristic methods such as quartet puzzling reduce the
number of candidate trees.
• Programs that use ML methods: PhyML, RAxML,
TreePuzzle (uses quartet puzzling).
Bootstrapping
• Tests the reliability of a tree.
• Initial protein alignment is randomised (by
sampling columns at random).
• Tree construction repeated for each randomised
alignment.
• For each group of taxa in the original tree it is
determined what percentage of the randomised
trees contain the same group.
• Alternative: Approximate likelihood-ratio test
Bayesian methods
• A sample is taken of a large number of trees with
high ML.
• Posterior probabilities calculated for different
events of interest.
• Markov Chain Monte Carlo method used to
generate samples of trees.
• Mr Bayes uses these methods.
Taxon sampling
• Take initial protein sequence.
• Decide which range of species you are
interested in.
• Use BLAST to find homologous sequences in
databases, either NCBI database or individual
genome databases.
FASTA formatted file
•
•
>YJL052W_Saccharomyces_cerevisiae
MIRIAINGFGRIGRLVLRLALQRKDIEVVAVNDPFISNDYAAYMVKYDSTHGRYKGTVSH
DDKHIIIDGVKIATYQERDPANLPWGSLKIDVAVDSTGVFKELDTAQKHIDAGAKKVVIT
APSSSAPMFVVGVNHTKYTPDKKIVSNASCTTNCLAPLAKVINDAFGIEEGLMTTVHSMT
ATQKTVDGPSHKDWRGGRTASGNIIPSSTGAAKAVGKVLPELQGKLTGMAFRVPTVDVSV
VDLTVKLEKEATYDQIKKAVKAAAEGPMKGVLGYTEDAVVSSDFLGDTHASIFDASAGIQ
LSPKFVKLISWYDNEYGYSARVVDLIEYVAKA*
>YJR009C_Saccharomyces_cerevisiae
MVRVAINGFGRIGRLVMRIALQRKNVEVVALNDPFISNDYSAYMFKYDSTHGRYAGEVSH
DDKHIIVDGHKIATFQERDPANLPWASLNIDIAIDSTGVFKELDTAQKHIDAGAKKVVIT
APSSTAPMFVMGVNEEKYTSDLKIVSNASCTTNCLAPLAKVINDAFGIEEGLMTTVHSMT
ATQKTVDGPSHKDWRGGRTASGNIIPSSTGAAKAVGKVLPELQGKLTGMAFRVPTVDVSV
VDLTVKLNKETTYDEIKKVVKAAAEGKLKGVLGYTEDAVVSSDFLGDSNSSIFDAAAGIQ
LSPKFVKLVSWYDNEYGYSTRVVDLVEHVAKA*
Multiple sequence alignment
• Take FASTA file of sequences you are
interested in.
• Align sequences using ClustalW, Muscle,
TCoffee.
Sampling of conserved blocks
• To get reliable trees non-aligned and poorly
conserved areas of sequence need to be
removed.
• Gblocks samples highly conserved blocks of
sequence.
Sequence alignment and sampling
conserved block
Which substitution model should I use?
• ModelGenerator takes your sequence alignment
and calculates the best amino acid substitution
model to use.
Creating tree
• Take alignment produced by Gblocks and use
program of choice to generate a tree (using
substitution model suggest by ModelGenerator
and specifying number of gamma rate
categories, 4 is sufficient).
• File format problems, different programs use
different file formats – use Readseq to convert
between file formats.
• Use tree viewing program to look at graphical
representation of tree (TreeView, TreeDyn).
TOR gene duplication events in fungi
TOR: protein kinase,
subunit of a complex
that regulate cell growth
in response to nutrient
availability and cellular
stresses
Workshop task
Looking at evolution of genes encoding two types
of phosphoglycerate mutase in fungi.
Two types of phosphoglycerate mutase
(PGM)
•
Both catalyse the same overall reaction:
– 3-phosphoglycerate → 2-phosphoglycerate
•
cofactor-dependent PGM (dPGM) uses 2,3bisphosphoglycerate (2,3BPG) as a cofactor:
•
3PG + P-Enzyme → 2,3BPG + Enzyme → 2PG + P-Enzyme
•
cofactor-independent PGM (iPGM) has two
bound Mn(II) ions at its active site.
•
3PG + Enzyme → PG + P-Enzyme → 2PG + Enzyme
Two types of phosphoglycerate mutase
(PGM)
• dPGM found in yeasts and vertebrates
• iPGM found in filamentous fungi, plants and
some invertebrates
• Both can be found in bacteria.
• No sequence similarity between the two
forms of the enzyme.
Structure of iPGM
Structure of dPGM
Task
• Use BLAST search to find PGM protein
sequences in a sample of fungal species.
• Use these to create phylogenetic trees
showing the evolution of genes encoding
these enzymes.
Taxon sampling (get sequences – BLAST)
Alignment (ClustalW)
Sampling conserved positions (GBlocks)
Determine substitution model (ModelGenerator)
Create tree (PhyML)
Visualise tree (TreeDyn)