Introduction to evolution and phylogeny

Nomenclature of trees

Four stages of molecular phylogeny:[1] selecting sequences[2] multiple sequence alignment[3] tree-building[4] tree evaluation

Practical approaches to making trees

Molecular PhylogeneticsMolecular Phylogenetics

At the molecular level, evolution is a process ofmutation with selection.

Molecular evolution is the study of changes in genesand proteins throughout different branches of the tree of life.

Phylogeny is the inference of evolutionary relationships.Traditionally, phylogeny relied on the comparisonof morphological features between organisms. Today,molecular sequence data are also used for phylogeneticanalyses.

Introduction

Millions of years since divergence

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Dickerson (1971)

Fibrinopeptides 9.0Kappa casein 3.3Lactalbumin 2.7Serum albumin 1.9Lysozyme 0.98Trypsin 0.59Insulin 0.44Cytochrome c 0.22Histone H2B 0.09Ubiquitin 0.010Histone H4 0.010

Molecular clock for proteins:rate of substitutions per aa site per 109 years

If protein sequences evolve at constant rates,they can be used to estimate the times that sequences diverged. This is analogous to datinggeological specimens by radioactive decay.

Molecular clock hypothesis: implications

If protein sequences evolve at constant rates,they can be used to estimate the times that sequences diverged. This is analogous to datinggeological specimens by radioactive decay.

Molecular clock hypothesis: implications

N = total number of substitutionsL = number of nucleotide sites compared

between two sequences

K = = number of substitutionsper nucleotide site

NL

Rate of nucleotide substitution r and time of divergence T

r = rate of substitution= 0.56 x 10-9 per site per year for hemoglobin alpha

K = 0.093 = number of substitutionsper nucleotide site (rat versus human)

r = K / 2TT = .093 / (2)(0.56 x 10-9) = 80 million years

An often-held view of evolution is that just as organismspropagate through natural selection, so also DNA andprotein molecules are selected for.

According to Motoo Kimura’s 1968 neutral theoryof molecular evolution, the vast majority of DNAchanges are not selected for in a Darwinian sense.The main cause of evolutionary change is randomdrift of mutant alleles that are selectively neutral(or nearly neutral). Positive Darwinian selection doesoccur, but it has a limited role.

Neutral theory of evolution

Phylogeny can answer questions such as:

Goals of molecular phylogeny

• How many genes are related to my favorite gene?• Was the extinct quagga more like a zebra or a horse?• Was Darwin correct that humans are closest to chimps and gorillas?• How related are whales, dolphins & porpoises to cows?• Where and when did HIV originate?• What is the history of life on earth?

Woese PNAS

There are two main kinds of information inherentto any tree: topology and branch lengths.

We will now describe the parts of a tree.

Molecular phylogeny: nomenclature of trees

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Molecular phylogeny uses trees to depict evolutionaryrelationships among organisms. These trees are basedupon DNA, RNA, and protein sequence data.

chronogramchronogram phylogramphylogram

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Tree nomenclature

taxon

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Tree nomenclature

taxon

operational taxonomic unit (OTU) such as a protein sequence

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Tree nomenclature

branch (edge)

Node (intersection or terminating pointof two or more branches)

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Tree nomenclature

Branches are unscaled... Branches are scaled...

…branch lengths areproportional to number ofamino acid changes

…OTUs are neatly aligned,and nodes reflect time

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Tree nomenclature

bifurcatinginternal node

multifurcatinginternalnode

Examples of multifurcation: failure to resolve the branching orderof some metazoans and protostomes

Rokas A. et al., Animal Evolution and the Molecular Signature of RadiationsCompressed in Time, Science 310:1933, 23 December 2005, Fig. 1.

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Tree nomenclature: clades

Clade ABF (monophyletic group)

A group is monophyletic (Greek: "of one race") if it consists of a common ancestor and all its descendants.(http://en.wikipedia.org/wiki/)

The root of a phylogenetic tree represents thecommon ancestor of the sequences. Some treesare unrooted, and thus do not specify the commonancestor.

A tree can be rooted using an outgroup (that is, ataxon known to be distantly related from all otherOTUs).

Tree roots

Tree nomenclature: roots

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Rooted tree(specifies evolutionarypath)

Unrooted tree

Tree nomenclature: outgroup rooting

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Cavalii-Sforza and Edwards (1967) derived the numberof possible unrooted trees (NU) for n OTUs (n > 3):

NU =

The number of bifurcating rooted trees (NR)

NR =

For 10 OTUs (e.g. 10 DNA or protein sequences),the number of possible rooted trees is 34 million,and the number of unrooted trees is 2 million.Many tree-making algorithms can exhaustively examine every possible tree for up to ten to twelvesequences.

Enumerating trees

(2n-5)!2n-3(n-3)!

(2n-3)!2n-2(n-2)!

Molecular evolutionary studies can be complicatedby the fact that both species and genes evolve.speciation usually occurs when a species becomesreproductively isolated. In a species tree, eachinternal node represents a speciation event.

Genes (and proteins) may duplicate or otherwise evolvebefore or after any given speciation event. The topologyof a gene (or protein) based tree may differ from thetopology of a species tree.

Species trees versus gene/protein trees

species 1 species 2

speciationevent

Species trees versus gene/protein trees

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Species trees versus gene/protein trees

Gene duplicationevents

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Species trees versus gene/protein trees

Gene duplicationevents

OTUs

Orthology/paralogy

Orthologous genes are homologous (corresponding) genes in different species (genomes)

Paralogous genes are homologous genes within the same species (genome)

Molecular phylogenetic analysis may be describedin four stages:

[1] Selection of sequences for analysis

[2] Multiple sequence alignment

[3] Tree building

[4] Tree evaluation

Four stages of phylogenetic analysis

The fundamental basis of a phylogenetic tree isa multiple sequence alignment.

(If there is a misalignment, or if a nonhomologoussequence is included in the alignment, it will stillbe possible to generate a tree.)

Stage 2: Multiple sequence alignment

Two Major Approaches to Phylogeny Two Major Approaches to Phylogeny InferenceInference

1)1) Distance Matrix MethodsDistance Matrix Methods

Calculate matrix of pairwise distances from all Calculate matrix of pairwise distances from all data, then infer tree using a clustering algorithm.data, then infer tree using a clustering algorithm.

2) Character Based Methods (maximum parsimony)2) Character Based Methods (maximum parsimony)

Inspect columns of characters, infer trees from Inspect columns of characters, infer trees from columns that contain “informative” characters, and columns that contain “informative” characters, and use these to infer most likely tree given the data. use these to infer most likely tree given the data.

Reality: Not all sites are free to change, the same sites change Reality: Not all sites are free to change, the same sites change multiple timesmultiple times

Distance Matrix MethodsDistance Matrix Methods(matrix calculation)(matrix calculation)

The simplest model is that of Jukes & Cantor

Jukes & Cantor: dxy = -(3/4) ln (1-4/3 D)

• dxy = distance between sequence x and sequence y expressed as the number of changes per site

• (note dxy = r/n where r is number of replacements and n is the total number of sites. This assumes all sites can vary and when unvaried sites are present in two sequences it will underestimate the amount of change which has occurred at variable sites) (i.e., previous reality check)

• D = is the observed proportion of nucleotides which differ between two sequences (fractional dissimilarity)

• ln = natural log function to correct for superimposed substitutions (in general logging tends to convert exponential trends to linear trends)

• The 3/4 and 4/3 terms reflect that there are four types of nucleotides and three ways in which a second nucleotide may not match a first - with all types of change being equally likely (i.e. unrelated sequences should be 25% identical by chance alone)

The natural logarithm ln is used to correct for superimposed changes at the same site

• If two sequences are 95% identical they are different at 5% or 0.05 (D) of sites thus:

– dxy = -3/4 ln (1-4/3 0.05) = 0.0517

• Note that the observed dissimilarity 0.05 increases only slightly to an estimated 0.0517 - this makes sense because in two very similar sequences one would expect very few changes to have been superimposed at the same site in the short time since the sequences diverged apart

• However, if two sequences are only 50% identical they are different at 50% or 0.50 (D) of sites thus:

– dxy = -3/4 ln (1-4/3 0.5) = 0.824

• For dissimilar sequences, which may diverged apart a long time ago, the use of ln infers that a much larger number of superimposed changes have occurred at the same site

UPGMA is unweighted pair group methodusing arithmetic mean

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Distance Matrix MethodsDistance Matrix Methods(tree construction)(tree construction)

Tree-building methods: UPGMA

Step 1: compute the pairwise distances of allthe proteins. Get ready to put the numbers 1-5at the bottom of your new tree.

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Tree-building methods: UPGMA

Step 2: Find the two proteins with the smallest pairwise distance. Cluster them.

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Tree-building methods: UPGMA

Step 3: Do it again. Find the next two proteins with the smallest pairwise distance. Cluster them.

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Tree-building methods: UPGMA

Step 4: Keep going. Cluster.

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Tree-building methods: UPGMA

Step 4: Last cluster! This is your tree.

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UPGMA is a simple approach for making trees.

• An UPGMA tree is always rooted.• An assumption of the algorithm is that the molecular clock is constant for sequences in the tree. If there are unequal substitution rates, the tree may be wrong.• While UPGMA is simple, it is less accurate than the neighbor-joining approach (described next).

Distance-based methods: UPGMA trees

• Fast - suitable for analysing data sets which are too large for other more computationally intensive methods such as maximum likelihood

• A large number of models are available with many parameters -improves estimation of distances

Distance method: Advantages

• Information is lost - given only the distances, it is impossible to derive the original sequences

• Only through character based analyses can the history of sites be investigated; e.g., most informative positions be inferred

Distance method: Disadvantages

Character Based Methods: Character Based Methods: Maximum ParsimonyMaximum Parsimony

The best tree: should be the one that The best tree: should be the one that requires the smallest number of requires the smallest number of substitutions to explain the substitutions to explain the differences among the sequences differences among the sequences being studied.being studied.

Occam's razor: Among his statements (translated from his Latin) are: "Plurality is not to be assumed without necessity" and "What can be done

with fewer [assumptions] is done in vain with more." One consequence of this methodology is the idea that the

simplest or most obvious explanation of several competing ones is the one that should be preferred until it is proven wrong.

• informative sites - nucleotide (or amino acid) columns that are represented by at least two different character states found in at least two different sequences, these sites allow the distinction between alternative trees.

• uninformative sites - nucleotide (or amino acid) columns that do not allow the distinction between two trees (e.g., constant)

Not all Characters are Used in Parsimony Analysis

Maximum Parsimony (4-taxon case)Maximum Parsimony (4-taxon case) 1 2 3 4 5 6 7 8 9 101 2 3 4 5 6 7 8 9 10

1 - A G G G T A A C T G1 - A G G G T A A C T G

2 - A C G A T T A T T A2 - A C G A T T A T T A

3 - A T A A T T G T C T3 - A T A A T T G T C T

4 - A A T G T T G T C G4 - A A T G T T G T C G

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How may informative sites are there How may informative sites are there in this data set?in this data set?

Maximum Parsimony (4-taxon case)Maximum Parsimony (4-taxon case) 1 2 3 4 5 6 7 8 9 101 2 3 4 5 6 7 8 9 10

1 - A 1 - A GG G G T A A C T G G G T A A C T G

2 - A 2 - A CC G A T T A T T A G A T T A T T A

3 - A 3 - A TT A A T T G T C T A A T T G T C T

4 - A 4 - A AA T G T T G T C G T G T T G T C G

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Maximum ParsimonyMaximum Parsimony 1 2 3 4 5 6 7 8 9 101 2 3 4 5 6 7 8 9 10

1 - A G 1 - A G GG G T A A C T G G T A A C T G

2 - A C 2 - A C GG A T T A T T A A T T A T T A

3 - A T 3 - A T AA A T T G T C T A T T G T C T

4 - A A 4 - A A TT G T T G T C G G T T G T C G

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Maximum ParsimonyMaximum Parsimony 1 2 3 4 5 6 7 8 9 101 2 3 4 5 6 7 8 9 10

1 - A G G 1 - A G G GG T A A C T G T A A C T G

2 - A C G 2 - A C G AA T T A T T A T T A T T A

3 - A T A 3 - A T A AA T T G T C T T T G T C T

4 - A A T 4 - A A T GG T T G T C G T T G T C G

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Maximum ParsimonyMaximum Parsimony

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Maximum ParsimonyMaximum Parsimony

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2 - A C G A T T A T T A2 - A C G A T T A T T A

3 - A T A A T T G T C T3 - A T A A T T G T C T

4 - A A T G T T G T C G4 - A A T G T T G T C G

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Parsimony - advantages

• is a simple method - easily understood operation

• does not seem to depend on an explicit model of evolution

• gives both trees and associated hypotheses of character evolution

• should give reliable results if the data is well structured and homoplasy is either rare or widely (randomly) distributed on the tree

Parsimony - disadvantages• May give misleading results if homoplasy is common or concentrated in

particular parts of the tree, e.g:- thermophilic convergence- base composition biases- long branch attraction

• Underestimates branch lengths (Why?)• Model of evolution is implicit - behaviour of method not well understood• Parsimony often justified on purely philosophical grounds - we must

prefer simplest hypotheses - particularly by morphologists• For most molecular systematists, this is uncompelling

Parsimony can be inconsistent

• Felsenstein (1978) developed a simple model phylogeny including four taxa and a mixture of short and long branches

• Under this model parsimony will give the wrong tree

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• With more data the certainty that parsimony will give the wrong tree increases - so that parsimony is statistically inconsistent

• Advocates of parsimony initially responded by claiming that Felsenstein’s result showed only that his model was unrealistic

• It is now recognised that the long-branch attraction (in the “Felsenstein Zone”) is one of the most serious problems in phylogenetic inference

Long branches are attracted but the similarity is homoplastic

Summary and recommendationsSummary and recommendations

• Remember that molecular phylogenetics yields gene treesRemember that molecular phylogenetics yields gene trees

• Accurate gene trees may not be accurate organismal trees Accurate gene trees may not be accurate organismal trees

• Gene duplications and paralogy, and lateral transfer can Gene duplications and paralogy, and lateral transfer can produce mismatches between gene and organismal produce mismatches between gene and organismal phylogeniesphylogenies

• Use congruence between separate gene trees to identify robust Use congruence between separate gene trees to identify robust organismal phylogenies or mismatches that require further organismal phylogenies or mismatches that require further informationinformation

The most famous case of LBA misleading biologists…

The Universal SSU rRNA TreeThe Universal SSU rRNA TreeWheelis et al. 1992 PNAS 89: 2930Wheelis et al. 1992 PNAS 89: 2930

ArchezoaArchezoa

The SSU Ribosomal RNA Tree for EukaryotesThe SSU Ribosomal RNA Tree for Eukaryotes

Mitochondria?Mitochondria?

Prokaryotic Prokaryotic outgroupoutgroup

Animals

Fungi

Ciliates + ApicomplexaStramenopiles

Euglenozoa

GiardiaTrichomonas

Plants / green algae

Red algae

Entamoebae

Choanozoa

Dictyostelium

Physarum

Microsporidia

Percolozoa