Fundamentals of molecular evolution
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FUNDAMENTALS OF MOLECULAR EVOLUTION. The evolutionary thinking. Russel Wallace writes to Charles Darwin (June 17 th 1858). Ernst Haeckel (mid-19 th Century): the tree of life. The neo-synthesis (Fisher, Heldane, and Wright, 1930-1950). The molecular REvolution.

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FUNDAMENTALS OF MOLECULAR EVOLUTION

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Fundamentals of molecular evolution

FUNDAMENTALS OF MOLECULAR EVOLUTION


The evolutionary thinking

The evolutionary thinking

  • Russel Wallace writes to Charles Darwin (June 17th 1858)

  • Ernst Haeckel (mid-19th Century): the tree of life

  • The neo-synthesis (Fisher, Heldane, and Wright, 1930-1950)


The molecular revolution

The molecular REvolution

  • Nuttal, 1904: Serological cross-reactions to study phylogenetic relationships among various group of animals.

  • Watson and Crick beautiful helix!

  • Zuckerland and Pauling, 1965: molecular clocks.

  • Fitch & Margoliash, 1967: Construction of phylogenetic trees.A method based on mutation distances as estimated from cytochrome c sequences is of general applicability (Science, 155:279-284).

  • Kimura, 1968: Evolutionary rate at the molecular level (Nature, 217:624-626).

The birth of molecular evolution


Fundamentals of molecular evolution

Transitions and transversions

A

C

G

T

  • Transitions () are purine (A, G) or pyrimidine (C, T) mutations: Pu-Pu, Py-Py

  • Transversions () are purine to pyrimidine mutations or the reverse: (Pu-Py, or Py-Pu).


Fundamentals of molecular evolution

Point mutations and the genetic code

  • 4 possible transitions: AG, CT

  • 8 possible transversions: AC, AT, GC, GT

  • Thus if mutations were random, transversions are 2 times more likely than transitions.

  • Due to steric hindrance (as well as negative selection!), the opposite is true, transitions occur in general more often than transversions[2-15 times more, depending on the gene region and the species].


Transversions result in more disruptive amino acid changes

Transversions result in more disruptive amino acid changes.


Fundamentals of molecular evolution

Other mutations

  • Insertions and deletions (indels). Usually by 3 nucleotides in coding regions.

  • Recombination. Often in viruses.

  • Gene (or chromosome) duplication

  • Lateral gene transfer


Fundamentals of molecular evolution

Genetic variation in populations

  • Polymorphism: 2 (or more) mutations co-exist (alleles) in a population of organisms.

  • Diploid organisms can be homozygous (2 identical alleles) or heterozygous (2 different alleles) at a particular locus.

  • For viruses, the term quasispecies is often used.

  • The variation in a population can be described in allele frequencies or gene frequencies


Fundamentals of molecular evolution

Evolution and fixation of mutations

Evolutionary forces work at the level of populations

  • Evolution is the consecutive fixation of mutations

  • The fixation rate of such a polymorphism is in fact the evolutionary rate. This is dependant on:

    • Mutation rate

    • Generation time

    • Evolutionary forces, such as fitness, selective pressure, population size


Population genetics

Population genetics

  • Selective Pressure

  • Random Genetic drift

  • Effective Population size (Ne)

  • Mutation rate and evolutionary rate


Fundamentals of molecular evolution

Selective pressure

  • Positive selective pressure: mutant is more fit

  • Negative selective pressure: mutant is less fit

  • Balancing selection: heterozygote is more fit

  • Most synonymous mutations can be considered neutral

  • Non-synonymous mutations are always subject to selective pressure (?)


Fundamentals of molecular evolution

Population dynamics

1

fixed mutation

polymorphism maintained

ALLELE FREQUENCY

lost mutation

0

TIME


Fundamentals of molecular evolution

Effective population size

1st generation

N=10, Ne=5

2nd generation

N=10, Ne=4

3rd generation

N=10, Ne=3

4th generation

N=5, Ne=2

Bottleneck event

5th generation

N=3, Ne=2

Mutation event

6th generation

N=9, Ne=4

7th generation

N=11


Fundamentals of molecular evolution

Mutation and evolutionary rate

  • New mutation in a diploid population of N individuals

  • Fixation time t (Kimura and Otha 1969):

  • t = 2/s ln (2N)(s = selective advantage)

  • t = 4N for neutral mutations

  • Evolutionary Rate (or substitution rate), r:

  • number of mutants reaching fixation per unit time

  • Mutation Rate, m:

  • rate of mutation at the DNA level (biochemical concept)


Molecular clocks

Molecular clocks

  • In general the evolutionary rate r can be expressed as

    • r = f 

    • ffraction on neutral mutation

    •  mutation rate

  • If f is constant

    and

  •  is constant

    The rate of evolution is constant (molecular clock)

  • Under neutral evolution (f = 1)

    • r = 

      mutation rate = evolutionary rate (Kimura 1968)


  • A global molecular clock

    A global molecular clock?

    The hypothesis known as global clock was based on the observation that a linear relation seems to exist between the number of amino acid substitutions between homologous proteins of different species, and the species divergence times estimated from archaeological data.


    Fundamentals of molecular evolution

    Evolutionary rates of organisms

    nucleotide substitutions per site per year

    10 - 9

    10 - 8

    10 - 7

    10 - 6

    10 - 5

    10 - 4

    10 - 3

    10 - 2

    10 - 1

    cellular genes

    RNA viruses

    DNA viruses

    Human mtDNA


    Fundamentals of molecular evolution

    Why is the molecular clock attractive ?

    • If macromolecules evolve at constant rates, they can be used to date species-divergence times and other types of evolutionary events, similar to the dating of geological time using radioactive elements

    • Phylogenetic reconstruction is much simpler under constant rates that under nonconstant rates

    • The degree of rate variation among lineages may provide much insight into the mechanisms of molecular evolution (e.g. Kimura 1983; Gillespie 1991; Salemi et al., 1999).


    Fundamentals of molecular evolution

    Deterministic or stochastic model of evolution

    • Deterministic: fixation of mutations is entirely dependent on selective pressure. Alleles do not get lost or fixed by chance (by accident).

    • Stochastic: fixation is dependent on chance events. Chance effect is much larger than selective pressure, random genetic drift plays a big role.

    • Whether or not selective pressure plays a role can be tested by comparing synonymous with non-synonymous rates of substitution.


    Fundamentals of molecular evolution

    Neo-Darwinism - Neutral evolution

    • Neo-Darwinism:

      • Random mutations are source of variation.

      • A majority of non-synonymous mutations are deleterious, there is a strong negative selective pressure.

      • Most non-synonymous mutations become fixed because of positive selection

      • Most synonymous mutations become fixed because of random genetic drift

    • Neutral evolution (Kimura):

      • Random mutations are source of variation.

      • A majority of non-synonymous mutations are deleterious, there is a strong negative selective pressure.

      • Most mutations that become fixed are neutral, rarely positive selective pressure is strong enough to fix adaptive mutations.


    Phylogeny inference

    Phylogeny Inference


    Fundamentals of molecular evolution

    The data used for phylogenetic analysis

    • Morphological characters

    • Fossils (not for viruses)

    • Genetic data:

      • AA or NT sequences

      • RFLP

      • Allele frequencies

      • ...

    • A combination of these data


    Fundamentals of molecular evolution

    Rooted phylogenetic tree

    Branches can rotate freely. Branching order is called topology

    External node or

    Operational Taxonomic Units

    OTU

    (or Taxon)

    A

    G

    node

    H

    B

    J

    K

    C

    Internal node or

    Hypothetical Taxonomic Units

    HTU

    (or Ancestor)

    D

    I

    root

    E

    branch

    F

    TIME


    Fundamentals of molecular evolution

    Unrooted phylogenetic tree

    F

    D

    I

    J

    E

    C

    H

    G

    A

    B

    • Root node K disappeared

    • To root an unrooted tree:

      • root by outgroup, e.g. use F as outgroup

      • midpoint rooting

    Monophyletic taxa


    Fundamentals of molecular evolution

    Coalescence time on a rooted tree

    A

    G

    B

    H

    J

    C

    D

    I

    E

    F

    Most recent common ancestor of all taxa (MRCA)

    O

    r = OF/T1

    T2 = IE/r = ID/r

    T1 T2

    TIME

    Coalescence time of all taxa


    Fundamentals of molecular evolution

    Evolutionary rate estimates using viral strains of known isolation time

    • Fast evolving viruses (e.g. HIV, HCV) can be sampled over time from the same patients or from different patients at different time points (longitudinal sampling)

    • The evolutionary rate can be calculated by using the difference in evolutionary distance and the time interval of isolation

    • ML and Bayesian methods can estimate simultaneously branch lengths and evolutionary rate from a tree with longitudinally sampled sequences (Rambaut, 2000; Drummond et al., 2006)

    1983

    d

    T

    1995

    1997


    Fundamentals of molecular evolution

    Phylogeny Inference and the controversy over the origin of HIV


    Fundamentals of molecular evolution

    The retroviruses

    • small RNA genome (9-10 Kb)

    • Unique replication cycle

    • extremely fast evolutionary rate (10-5 - 10-2)

    • Isolated from most vertebrate species

    • Associated with human and animal diseases


    Fundamentals of molecular evolution

    Human immunodeficiency virus


    Fundamentals of molecular evolution

    R

    U5

    R

    U3

    R

    U5

    U3

    R

    U5

    Retroviral genome

    gag

    pol

    env

    pX

    ssRNA genome

    U3

    reverse transcription

    LTR

    LTR

    gag

    pol

    env

    pX

    dsDNA

    TM

    SU

    Protease

    Polymerase

    major encoded proteins

    Tax/Tat

    Rex/Rev

    gag-pol

    env

    mRNAs

    Rev /Rex

    Tat / Tax


    Global hiv 1 pandemic 1996 vs 2005

    Global HIV-1 Pandemic: 1996 vs. 2005

    300,000

    470,000

    780,000

    450,000

    270,000

    200,000

    4.8 million

    1.3 million

    14 million

    < 35,000

    2005 (~ 40 million people infected)

    1996 (~ 20 million people infected)


    Global distribution of hiv 1 subtypes 2005

    Global Distribution of HIV-1 Subtypes 2005


    No hiv 1 came from chimpanzees

    No, HIV-1 came from chimpanzees…

    Pan troglodytes

    (Gao et al., Science 1999)


    Where did the pandemic originate

    Where did the pandemic originate?

    (Gao et al., Science 1999)


    Fundamentals of molecular evolution

    The River: the “interesting” journey of E. Hooper

    • A controversial theory, described by Edward Hooper in his book "The River: a journey to the source of HIV and AIDS" (1999), claims that HIV-1 originated at the end of the 1950s when live oral polio vaccines (OPV), contaminated with SIV, were administered to African children.

    • Testing the Hooper’s hypothesis by dating the the most recent common ancestor (MRCA) of HIV-1/SIVcpz and of HIV-1 group M by molecular clock analysis (Korber et al. 2000, Salemi et al., 2001).


    Fundamentals of molecular evolution

    HIV-1 group M: 41 pol strains

    2DLn(l)

    Date

    140

    1940

    120

    1930

    100

    1920

    80

    1910

    60

    1900

    40

    1890

    20

    1880

    0

    1870

    SSCD Pol

    2Ln(L) )

    Date

    HIV-1 group M common ancestor

    # sites removed

    HIV-1 group M common ancestor: 1931 (1921 - 1941)

    0.1

    (nucleotide substitutions per site)

    Salemi et al., 2001


    Fundamentals of molecular evolution

    2DLn(l)

    Date

    HIV-1 group M: 61 env strains

    SSCD Env

    SIVCPZ

    A

    140

    1940

    G

    C

    120

    D

    1930

    100

    1920

    80

    Date

    2Ln(L)

    1910

    HIV-1 group M common ancestor

    60

    1900

    40

    B

    1890

    20

    0

    1880

    0

    5

    50

    55

    20

    25

    30

    45

    40

    10

    15

    35

    # sites removed

    HIV-1 group M common ancestor: 1933 (1918 - 1948)

    0.1

    (nucleotide substitutions per site)

    Salemi et al., 2001


    Fundamentals of molecular evolution

    Is the OPV campaign in Africa during the late 1950s to blame for the beginning of the AIDS epidemic?

    • In contrast with Hooper’s theory, our method do not support the “OPV scenario” since the radiation date for HIV-1 group M was around 1930.

    • An even older time for the separation of SIVcpz and HIV-1 can be calculated (~1700 A.D.) [Salemi et al. 2001]


    Hiv infection in benghazi libya

    HIV Infection in Benghazi, Libya…

    In May 1998, the Al-Fateh Children’s Hospital (AFH) in Benghazi, Libya1 noted their first case of HIV-1 infection. In September 1998, another 111 children who had been admitted to the hospital were found to be HIV-1 positive.

    In total 418 children resulted HIV-1 positive and 300 HCV positive…


    Fundamentals of molecular evolution

    HIV Infection in Benghazi, Libya…

    The outbreak was reported by local hospital authorities and representatives from the World Health Organization(WHO) were sent to AFH in December 1998 to examine the cause of the infections.

    WHO report suggests that there were multiple nosocomial HIV-1/HCV

    It also noted the lack of medical material in the hospital


    Libyan families pressure

    Libyan families pressure.

    Benghazi is the second biggest city and rebellious about Gaddafi…


    Trial begins medics in jail

    Trial begins… Medics in Jail.

    In March 1998 six foreign medics (five Bulgarian nurses and a doctor from Palestine) joined the medical staff at AFH. One year later (March 1999), these individuals were accused of purposefully infecting more than 400 children with HIV-1.


    Libyan court

    Libyan court

    However, the Libyan court found this report to be un-precise and lacking in evidence and therefore decided not to consider its findings in the trial4.

    In December 2003, a second scientific report produced by Libyan researchers was written for the court5.

    In May 2004, the foreign medical staff were sentenced to death.

    Libyan court.


    Scientists and nature involvement

    Scientists and Nature involvement…

    Nature magazine reporter Declan Butler becomes involved in the case.

    6 Nature editorials and news are published between September and November 2006.

    • A shocking lack of evidence (Nature 443, 888-889, 26 October 2006)

    • Protests mount against Libyan trial (Nature 443, 612-613, 12 October 2006)

    • Forgotten plights (Nature 443, 605-606, 12 October 2006)

    • Dirty needles, dirty dealings (Nature 443, 2 October 2006)

    • Libya's travesty (Nature 443, 245, 21 September 2006)

    • Lawyers call for science to clear AIDS nurses in Libya (Nature 443, 254 21 September 2006)


    Scientists around the world ask to fair trial and scientific facts

    Scientists around the world ask to fair trial and scientific facts.

    A new trial begins in October 2006, sentence by December 2006


    October 2007 setup of an international group to analyze the data

    October 2007: Setup of an International group to analyze the data

    defined together an analysis plan…

    • Marco Salemi (UF) on Bayesian and ML trees for HIV.

    • Oliver Pybus (Oxford, UK) to focus on HCV sequences.

    • Tulio de Oliveira (Cape Town, South Africa) and Andrew Rambaut (Edinburgh, UK) on timing the epidemic.


    Tree conclusions

    Tree Conclusions

    • The AFH HIV sequences form a well-supported monophyletic cluster within the CRF02_AG clade.

    • Indicating that the outbreak arose from a single CRF02_AG lineage. The cluster is closest to three West African (Blue) reference sequences

    • The branch leading to the AFH cluster is perfectly typical; hence the AFH strain is not unusually divergent as previously suggested

    HIV-1 ML phylogenetic tree


    Hcv ml phylogenetic trees

    HCV ML phylogenetic trees

    Cluster 1 origin from Egypt (green)

    Cluster 2 from West Africa (Blue)

    Cluster 3 from worldwide subtype 1a

    Genotype 1 HCV ML phylogenetic tree. Bootstrap and Bayesian probability values is shown in the internal branches.

    Libyan sequences are colored red. The clusters are annotated based on their subtype classification.


    I date of most recent ancestor

    (i) Date of Most Recent Ancestor

    No matter which model was used, the estimated TMRCA date of each cluster predated March 1998, sometimes by many years.


    Ii probability that mrca post dates 1 3 98

    (ii) Probability that MRCA post-dates 1/3/98

    In most analyses the probability that the AFH clusters originated after then was practically zero.

    95% HPD confidence limits are shown in parenthesis

    HKY = Hasegawa-Kishino-Yano model (1985); HKY+G = HKY model with gamma. SRD06 = One HKY+G model for codon positions 1 & 2, another HKY+G model for codon position 3

    Const = constant size; Expo = exponential growth; BSP = Bayesian Skyline Plot


    Iii the percentage of viral lineages that already existed before 1 3 98

    (iii) The percentage of viral lineages that already existed before 1/3/98.

    For the three HCV clusters, the percentage of lineages already present before March 1998 was ~70%.

    The percentage of HIV cluster lineages in existence before then was estimated at ~40%

    95% HPD confidence limits are shown in parenthesis

    HKY = Hasegawa-Kishino-Yano model (1985); HKY+G = HKY model with gamma. SRD06 = One HKY+G model for codon positions 1 & 2, another HKY+G model for codon position 3

    Const = constant size; Expo = exponential growth; BSP = Bayesian Skyline Plot


    Nature fast track review

    Nature Fast Track Review

    Giving the sensitivity of the paper Nature utilized nine (9) reviewers.

    4 anonymousand

    5 openreviewers

    All reviewers were very positive about the results.


    Timeline of paper

    Timeline of Paper…

    23 of October 2006 6 December 2006.

    Initial analysis (23 Oct 2006)

    Submit paper to Nature (6 of Nov 2006)

    Reviewers comments (14 Nov 2006)

    Submit second version as Brief Communication (17 Nov 2006)

    Paper Accepted (21 Nov 2006)

    Paper Published (6 Dec 2006)


    Medics arrive in libya in a french government plane and are pardoned

    Medics arrive in Libya in a French government plane and are pardoned…


    Biggest prize for a scientist

    Biggest prize for a Scientist !

    To get a kiss from the medics and to see the happiness in their face !


    Collaborators friends

    Collaborators & friends

    Maureen M. Goodenow, Rebecca Gray

    UF Gainesville, FL, USA

    Tulio de Oliveira

    Africa Centre for Health and Population Studies

    Cape Town, South Africa

    Oliver Pybus

    University of Oxford

    Oxford, UK

    Andrew Rambaut

    University of Edinburgh

    Edinburgh, UK


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