CS 177 Phylogenetics I

CS 177 Phylogenetics I

Taxonomy and phylogenetics

Phylogenetic trees

Cladistic versus phenetic analyses

Model of sequence evolution

Phylogenetic trees and networks

Cladistic and phenetic methods

Computer software and demos


Phylogenetic trees


Homology and homoplasy

Phylogenetic Inference I

A science primer: Phylogeneticshttp://www.ncbi.nlm.nih.gov/About/primer/phylo.html

Brown, S.M. (2000) Bioinformatics, Eaton Publishing, pp. 145-160

Brown, S.M.: Molecular Phylogeneticswww.med.nyu.edu/rcr/rcr/course/PPT/phylogen.ppt

Hillis, D.M.; Moritz, G. & Mable, B.K. (1996) Molecular Systematics, 2. Edition, Sinauer Associates, 655 pp.

Mount, D.W. (2001) Bioinformatics,Cold Spring Harbor Lab Press, pp.237-280

Recommended readings

(very) basic

advanced


Phylogenetic trees



CS 177 Phylogenetic Inference I

The theory of evolution is the foundation upon which all of modern biology is built

Evolution

From anatomy to behavior to genomics, the scientific method requires an appreciation of changes in organisms over time

It is impossible to evaluate relationships among gene sequences without taking into consideration the way these sequences have been modified over time

Ernst Haeckel (1834-1919)


Phylogenetic trees



CS 177 Phylogenetic Inference I

Similarity searches and multiple alignments of sequences naturally lead to the question

“How are these sequences related?”

and more generally:

“How are the organisms from which these sequences come related?”

Relationships


Phylogenetic trees



Classifying Organisms

Nomenclature is the science of naming organisms

Evolution has created an enormous diversity, so how do we deal with it?

Names allow us to talk about groups of organisms.

- Scientific names were originally descriptive phrases; not practical

- Binomial nomenclature

> Developed by Linnaeus, a Swedish naturalist

> Names are in Latin, formerly the language of science

> binomials - names consisting of two parts

> The generic name is a noun.

> The epithet is a descriptive adjective.

- Thus a species' name is two words e.g. Homo sapiens

Carolus Linnaeus (1707-1778)


Phylogenetic trees




Taxonomy is the science of the classification of organisms

Taxonomy deals with the naming and ordering of taxa.

The Linnaean hierarchy:

1. Kingdom

2. Division

3. Class

4. Order

5. Family

6. Genus

7. Species

Ta xo no m ic C la ssific a tio n o f M a n Ho m o sa p ie ns

Sup e rking d o m : Euka ryo ta King d o m : M e ta zo a Phylum : C ho rd a ta C la ss: M a m m a lia O rd e r: Prim a ta Fa m ily: Ho m inid a e G e nus: Sp e c ie s:

Ho m osa p ie ns

Sub sp e c ie s: sa p ie ns Evol u

tionary

di s

tanc e


Phylogenetic trees



Systematics is the science of the relationships of organisms

Systematics is the science of how organisms are related and the evidence for those relationships

Systematics is divided primarily into phylogenetics and taxonomy

Speciation -- the origin of new species from previously existing ones

- anagenesis - one species changes into another over time

- cladogenesis - one species splits to make two


Reconstruct evolutionary history

Phylogeny


Phylogenetic trees



Phylogenetics

Review of protein structures

Need for analyses of protein structures

Sources of protein structure information

Computational Modeling

Phylogenetics is the science of the pattern of evolution.

A. Evolutionary biology is the study of the processes that generate diversity, while phylogenetics is the study of the pattern of diversity produced by

those processes.

B. The central problem of phylogenetics:

1. How do we determine the relationships between species?

2. Use evidence from shared characteristics, not differences

3. Use homologies, not analogies

4. Use derived condition, not ancestral

a. synapomorphy - shared derived characteristic

b. plesiomorphy - ancestral characteristic

C. Cladistics is phylogenetics based on synapomorphies.

1. Cladistic classification creates and names taxa based only on synapomorphies.

2. This is the principle of monophyly

3. monophyletic, paraphyletic, polyphyletic

4. Cladistics is now the preferred approach to phylogenyThe phylogeny and classification of life as proposed by Haeckel (1866)

Phylogenetics

Evolutionary theory states that groups of similar organisms are descendedfrom a common ancestor.

Phylogenetic systematics is a method of taxonomic classification basedon their evolutionary history.

It was developed by Hennig, a German entomologist, in 1950.

Willi Hennig (1913-1976)


Phylogenetic trees



Phylogenetics

Phylogenetics is the science of the pattern of evolution

Evolutionary biology versus phylogenetics

- Evolutionary biology is the study of the processes that generate diversity

- Phylogenetics is the study of the pattern of diversity produced by those processes


Phylogenetic trees



Phylogenetics

Who uses phylogenetics? Some examples:

Evolutionary biologists (e.g. reconstructing tree of life)

Systematists (e.g. classification of groups)

Anthropologists (e.g. origin of human populations)

Forensics (e.g. transmission of HIV virus to a rape victim)

Parasitologists (e.g. phylogeny of parasites, co-evolution)

Epidemiologists (e.g. reconstruction of disease transmission)

Genomics/Proteomics (e.g. homology comparison of new proteins)


Phylogenetic trees



Phylogenetic trees

The central problem of phylogenetics:

how do we determine the relationships between taxa?

in phylogenetic studies, the most convenient way of presenting evolutionary relationships among a group of organisms is the phylogenetic tree


Phylogenetic trees



Phylogenetic trees

Sp e c ie s A

Sp e c ie s E

Sp e c ie s D

Sp e c ie s C

Sp e c ie s B

Node: a branchpoint in a tree (a presumed ancestral OTU)

Branch: defines the relationship between the taxa in terms of descent and ancestry

Topology: the branching patterns of the tree

Branch length (scaled trees only): represents the number of changes that have occurred in the branch

Root: the common ancestor of all taxa

Clade: a group of two or more taxa or DNA sequences that includes both their common ancestor and all their descendents

Operational Taxonomic Unit (OTU): taxonomic level of sampling selected by the user to be used in a study, such as individuals, populations, species, genera, or bacterial strains

Root

Branch

CladeNode


Phylogenetic trees



Phylogenetic trees

There are many ways of drawing a tree

A

E

D

C

B

A EDCB


Phylogenetic trees



Phylogenetic trees


=

A EDCB E DC B A


Phylogenetic trees



=

E CD B A

Phylogenetic trees


A EDCBA EDCB

= =

A EDCB


Phylogenetic trees



no meaning

Phylogenetic trees


A EDCB A EDCB

Bifurcation

Trifurcation

=/


Phylogenetic trees



Bifurcation versus Multifurcation (e.g. Trifurcation)

Multifurcation (also called polytomy): a node in a tree that connects more than three branches. A multifurcation may represent a lack of resolution because of too few data available for inferring the phylogeny (in which case it is said to be a soft multifurcation) or it may represent the hypothesized simultaneous splitting of several lineages (in which case it is said to be a hard multifurcation).

Phylogenetic trees

Trees can be scaled or unscaled (with or without branch lengths)

A

E

D

C

B

A

E

D

C

B

A

E

D

C

B

A

E

D

C

B

unit

unit


Phylogenetic trees



Phylogenetic trees

Trees can be unrooted or rooted


Phylogenetic trees



D

A C

B

Unrooted tree

A CB D

Root

Rooted tree

D

A C

B

Root

A CB D

Root

Root

Phylogenetic trees

Trees can be unrooted or rooted


Phylogenetic trees



Unrooted tree

A C

B D

4

3

5

2

1

These trees show five different evolutionary relationships among the taxa!

Rooted tree 1

B

A

C

D

Rooted tree 2

A

B

C

D

Ro oted tree 3

A

B

C

D

Rooted tree 4

C

D

A

B

Ro oted tree 5

D

C

A

B

Phylogenetic trees

Possible evolutionary trees

Taxa (n) Unrooted/rooted

2

2 1/1

3 1/3

4 3/15

43


Phylogenetic trees



Taxa (n):

Phylogenetic trees

Possible evolutionary trees

Taxa (n) rooted(2n-3)!/(2n-2(n-2)!)

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

2 1 1

3 3 1

4 15 3

5 105 15

6 954 105

7 10,395 954

8 135,135 10,395

9 2,027,025 135,135

10 34,459,425 2,027,025


Phylogenetic trees



Phylogenetic trees

How to root?

Use information from ancestors


Phylogenetic trees



In most cases not available

A C

B D

4

3

5

2

1

Phylogenetic trees

How to root?

Use statistical tools will root trees automatically (e.g. mid-point rooting)


Phylogenetic trees



A C

B D

4

3

5

2

1

This must involve assumptions … BEWARE!

A

B

C

D

10

2

3

5

2

d (A ,D ) = 10 + 3 + 5 = 18

M idpoint = 18 / 2 = 9

Phylogenetic trees

How to root?

Using “outgroups”


Phylogenetic trees



A C

B D

4

3

5

2

1

outgroup

- the outgroup should be a taxon known to be less closely related to the rest of the taxa (ingroups)

- it should ideally be as closely related as possible to the rest of the taxa while still satisfying the above condition

Phylogenetic trees

Exercise: rooted/unrooted; scaled/unscaled

A EDCB

A

E

D

C

B

AE

DC

BA

E

D

C

B

A

E

D

C

B

A EDCB

A

ED

CB

F


Phylogenetic trees



Phylogenetics

What are useful characters?

Use homologies, not analogies!

- Homology: common ancestry of two or more character states

- Analogy: similarity of character states not due to shared ancestry

- Homoplasy: a collection of phenomena that leads to similarities in character states for reasons other than inheritance from a common ancestor (e.g. convergence, parallelism, reversal)

Homoplasy is huge problemin morphology data sets!

But in molecular data sets, too!

Cactaceae and Euphorbiaceae


Phylogenetic trees



Phylogenetics

Molecular data and homoplasy

260 * 280 * 300 * 320 0841r : CCTTCAATTTTTATT-----------------------AGAGTTTTAGGAGAAATAAGTATGTG : 2720992r : CCTCCAATTTTTATTAGCTTGCCTACTCCTTTGGGCACAGAGTTTTAGGAGAAATAAGTATGTG : 2133803r : CCTCCAATTTTTATTAGCTTGCCTACTCCTTTGGGCACAGAGTTTTAGGAGAAATAAGTATGTG : 3054062r : CCTCCAATTTTTATTAGCTTGCCTACTCCTTTGGGAACAGAGTTTTAGGAGAAATAAGTATGTG : 3193802r : CCTCCAATTTTTATTAGTTTGCCTACTCCTTTGGGCACAGAGTTTTAGGAGAAATAAGTATGTG : 282ph2f : CCTCCAATTTTTATTAGCTTGCCTACTCCTTTGGGCACAGAGTTTTAGGAGAAATAAGTATGTG : 306 CCTcCAATTTTTATTag ttgcctactcctttggg acAGAGTTTTAGGAGAAATAAGTATGTG

gene sequences represent character data

characters are positions in the sequence (not all workers agree; some say one gene is one character)

character states are the nucleotides in the sequence (or amino acids in the case of proteins)

Problems:

the probability that two nucleotides are the same just by chance mutation is 25%

what to do with insertions or deletions (which may themselves be characters)

homoplasy in sequences may cause alignment errors


Phylogenetic trees



Phylogenetics

Molecular data and homoplasy: Orthologs vs. Paralogs

When comparing gene sequences, it is important to distinguish between identical vs. merely similar genes in different organisms

Orthologs are homologous genes in different species with analogous functions

Paralogs are similar genes that are the result of a gene duplication

A phylogeny that includes both orthologs and paralogs is likely to be incorrect

Sometimes phylogenetic analysis is the best way to determine if a new gene is an ortholog or paralog to other known genes


Phylogenetic trees



Phylogenetics

What are useful characters?

Use derived condition, not ancestral

- Synapomorphy (shared derived character): homologous traits share the same character state because it originated in their immediate common ancestor

- Plesiomorphy (shared ancestral character”): homologous traits share the same character state because they are inherited from a common distant ancestor


Phylogenetic trees



a na lo g y

syna p o m o rp hy(sha re d d e rive d

c ha ra c te r)

p le sio m o rp hy(sha re d a nc e stra l

c ha ra c te r)

a uta p o m o rp hy(uniq ue d e rive d

c ha ra c te r)

Phenetic methods construct trees (phenograms) by considering the current states of characters without regard to the evolutionary history that brought the species to their current phenotypes;phenograms are based on overall similarity

Cladistic methods construct trees (cladograms) rely on assumptions about ancestral relationships as well as on current data;cladograms are based on character evolution (e.g. shared derived characters)

Within the field of taxonomy there are two different methods and philosophies of building phylogenetic trees: cladistic and phenetic

Cladistics is becoming the method of choice; it is considered to be more powerfuland to provide more realistic estimates, however, it is slower than phenetic algorithms

Phenetics versus cladistics

Phenetics vs. cladistics

An example


Phenetic (overall similarity)

A

B

Coverall similarityoverall similarity

C B A

3

4

5

characteristics identity

critter A 4 limbs meta.kidney

hair endothermy vivip. nocloaca

placental

critter B 4 limbs meta.kidney

hair endothermy ovip. cloaca echidna

critter C 4 limbs meta.kidney

feathers endothermy ovip. cloaca bird

ancestor 4 limbs meta.kidney

nohair/feathers

ectothermy ovip. cloaca turtle


Cladistics (character evolution; e.g. shared derived characters)

A

B

C

shared derived charactersshared derived characters

A B C

1

2

1


The problem

- A basic process in the evolution of a sequence is change in that sequence over time

- Now we are interested in a mathematical model to describe that

- It is essential to have such a model to understand the mechanisms of change and is required to estimate both the rate of evolution and the evolutionary history of sequences

260 * 280 * 300 * 320 0841r : CCTTCAATTTTTATT-----------------------AGAGTTTTAGGAGAAATAAGTATGTG : 2720992r : CCTCCAATTTTTATTAGCTTGCCTACTCCTTTGGGCACAGAGTTTTAGGAGAAATAAGTATGTG : 2133803r : CCTCCAATTTTTATTAGCTTGCCTACTCCTTTGGGCACAGAGTTTTAGGAGAAATAAGTATGTG : 3054062r : CCTCCAATTTTTATTAGCTTGCCTACTCCTTTGGGAACAGAGTTTTAGGAGAAATAAGTATGTG : 3193802r : CCTCCAATTTTTATTAGTTTGCCTACTCCTTTGGGCACAGAGTTTTAGGAGAAATAAGTATGTG : 282ph2f : CCTCCAATTTTTATTAGCTTGCCTACTCCTTTGGGCACAGAGTTTTAGGAGAAATAAGTATGTG : 306 CCTcCAATTTTTATTag ttgcctactcctttggg acAGAGTTTTAGGAGAAATAAGTATGTG


Pyrimidine (C4N2H4) Purine (C5N4H4)

Nucleotide base + sugar + phosphate

O

sug a r

P OO -

O -

P O 4--

Guanine

AdenineThymine

Cytosine

5 ’

3 ’

3 ’

3 ’

3 ’

3 ’

5 ’

3 ’

3 ’

3 ’

3 ’

3 ’

A

C T

G

Models of sequence evolution

Examples

Jukes-Cantor model (1969)

All substitutions have an equal probability and base frequencies are equal

A

C T

G


Examples

Felsenstein (1981)

All substitutions have an equal probability, but there are unequal base frequencies

APurines

Purym idines C T

G


Examples

Kimura 2 parameter model (K2P) (1980)

Transitions and transversions have different probabilities

APurines

Purym idines C T

G


Examples

Hasegawa, Kishino & Yano (HKY) (1985)

Transitions and transversions have different probabilities,base frequencies are unequal

A

C T

G


Examples

General time reversible model (GTR)

Different probabilities for each substitution,base frequencies are unequal

A

C T

G


GTR

HKY

A

C T

G

A

C T

G

A

C T

G

A

C T

G

Jukes-Cantor

Felsenstein K2P

More models of sequence evolution …

Currently, there are more than 60 models described

- plus gamma distribution and invariable sites

- accuracy of models rapidly decreases for highly divergent sequences

- problem: more complicated models tend to be less accurate (and slower)

How to pick an appropriate model?

- use a maximum likelihood ratio test

- implemented in Modeltest 3.06 (Posada & Crandall, 1998)

More models of sequence evolution …

Example for Modeltest file

JC = 3158.0095

F81 = 3121.2188

K80 = 2994.6611

HKY = 2924.4182

TrNef = 2994.5491

TrN = 2923.6340

K81 = 2987.6548

K81uf = 2923.5620

TIMef = 2987.6196

TIM = 2922.9878

TVMef = 2983.3450

TVM = 2922.1970

SYM = 2983.3069

GTR = 2921.1187

A Equal base frequencies

Null model = JC -lnL0 = 3369.2803

Alternative model = F81 -lnL1 = 3342.5513

2(lnL1-lnL0) = 53.4580 df = 3

P-value = <0.000001

B

Model selected: TVM+G

-lnL = 2911.3660

C

helix

sheet

Did the Florida dentist infect his patients with HIV?


Phylogenetic trees



DENTIST

DENTIST

Patient D

Patient F

Patient C

Patient A

Patient G

Patient BPatient E

Patient A

Local control 2

Local control 3

Local control 9

Local control 35

Local control 3

From Ou et al. (1992) and Page & Holmes (1998)

N oN o

N oN o

Yes

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CS 177 Phylogenetics I

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