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Return Midterm: Discuss

Assignment for Friday: Go over Spreadsheet tutorial / exercise in computer competency module. Read chapter 10.

For Monday: read excerpts from Li's Molecular Evolution Textbook (Reading materials number 17 and 18 on huskyCT)

 

Studies on the Origin of Life

Top down approaches (fossil and molecular records, retrodiction of biochemical pathways)

Bottom up (prebiotic chemistry)

Primordial Soup (Miller -> see reading assignment) or Primordial Pizza (Wächtershäuser -> see reading assignments)

 

The RNA world

The currently favored scientific scenarios for the transition from chemistry to biology is somewhat as follows:

prebiotic chemistry either on Earth or in Space, in solution or on surfaces or in the gas phase
(autocatalytic chemical cycles and chemical networks)
?
self-replicating biopolymer
?
Emergence of cells, hypercycles or other means to co-select different genes
RNA world
??
Invention of protein biosynthesis

 

The existence of the RNA world as a transitory stage is supported by the following:

  • RNA molecules have catalytic activity. Famous ribozymes are the group I self splicing intron from Tetrahymena (ciliate) and the RNA portion of the E.coli Ribonuclease P (involved in tRNA processing)

  • RNA molecules have the potential to function as genetic material and as enzymes, or ribozymes (this solves the chicken vs. egg problem). This also allows for comparatively easy schemes to evolve RNAs in vitro to have new or different catalytic function (blind design by evolution).

  • Many enzymatic cofactors are nucleotides or nucleotide derived (FAD, ATP). Ribosomal protein synthesis relies on RNAs. RNA is an important part of the catalytic machinery that forms the peptide bond (see Noller et al.), tRNAs contain many strange bases suggesting that the catalytic potential of RNA molecules can go beyond what is possible with four bases only.

In vitro evolution has succeeded to evolving RNA's with novel properties, e.g. ATP binding. Jack Szostak's lab is working to evolve RNAs with template directed RNA polymerization capabilities. The principle selection scheme is depicted in this diagram at Szostak's web page.

In vitro selection became famous with Sol Spiegelman's experiments on the vitro replication of the Phage Qbeta RNA. In this case selection was for the fastest replicating molecules - they become shorter and lost their ability to infect bacteria.

Later inventions are the SELEX procedure to select for RNA with very specific binding properties (see left), and the selection of ribozymes with altered or new properties. In the latter case growth and selection can be either discrete or continuous. See reading materials for further discussion.

How can evolution be improved?

Genetic drift or the co-selection of slightly deleterious mutations lead to the fixation of deleterious mutations. These mutations can be eliminated if recombination occurs between different members of the population. Another advantage of recombination is that positive properties that arose independently in different parts of the molecules can be combined by recombination, molecular breeding, and sexual PCR.

Illustration for the power of recombination: Molecular Computation -> the traveling salesman problem Adleman's Science paper (JSTORE link)

In vitro evolution of proteins
Problem:
How to couple the functional protein to the genetic material.

Biological solution: cells contain the genetic material and the encoded proteins. Selection of cell that contain the more successful protein, will also select the gene encoding the protein.

Alternative: Link protein to encoding RNA. (see O'Keefe and Szostak's scheme h on RNA display here)
If time discuss sequence space (.ppt)

 

 

 

Selection versus genetic drift.

Selection

Deterministic models to describe selection:  (diploid organisms, two alleles A1 and A2)

    codominance (kind of logistic equation) q=frequency of allele, 

Genotype:                                     A1A1        A1A2        A2A2

Relative number of offspring           1             1+s          1+2s

Fitness                                            w11          w12          w22

Change in frequency (approximately):  
dq/dt= s* q*(1-q) and

q(t)=1/(1+((1-q0)/q0)*e-st)

    over dominance

Genotype:                                          A1A1    A1A2    A2A2

 Relative number of offspring                1         1+s1     1+s2

          s1>s2  :   balancing selection (try it)

Go to Kent Holsinger's collection of JAVA applets here and explore some of the time courses with different values of s1 and s2.  

Under which conditions of w11, w12, and w22 can one maintain both alleles over long periods of time?

Stochastic approaches -- random drift - neutral evolution:

Law of the gutter (see also Steven J Gould?s interpretation on the trend to increasing complexity)

Explore some simulations: 
     Drift only (vary the population size N),

How does the survival of multiple alleles in a population depend on the population size.

     Drift and Selection (interesting setting: P=0.01, N=50)

Note: Even though the allele conveys a strong selective advantage of 10%, the allele has a rather large chance to go extinct quickly.

     This simulation follows many populations (with the selected parameters) over time. It plots a histogram that shows how many of the populations have the allele frequency indicated on the y-axis. If you set the mutation rate to 0, this provides a nice illustration of the law of the gutter. (In the presence of the alleles converting back and forth, fixation does not occur.)

Mutation rate versus Substitution rate

The following assumes co-dominance or no selection:

s=0:  Probability of fixation, P, is equal to frequency of allele in population, q

mutation rate (per gene/per unit of time) = u ;  

frequency with which new alleles are generated in a diploid population size N equals to u*2N

Probability of fixation for each new allele = 1/(2N)

Substitution rate = frequency with which allele is generated * Probability of fixation= u*2N *1/(2N) = u

Therefore:
The substitution rate is independent of population size if s=0 and equal to the mutation rate!!!!
This is the reason that there is hope that the molecular clock might sometimes work.

For advantageous mutations: 
      Probability of fixation, P, is approximately equal to 2s;
      e.g., if selective advantage s = 1% then P = 2%

      Does this correspond to the simulations you performed above?

Fixation time

Neutral mutations:  tav=4*Ne generations 
(Ne=effective population size; For n discrete generations Ne= n/(1/N1+1/N2+?..1/Nn)

S unequal to 0:  tav= (2/s) ln (2N) generations  (also true for mutations with negative s --  How can this be??)

E.g.:  N=106, s=0:  average time to fixation: 4*106 generations

N=106, s=0.01:  average time to fixation: 2900 generations

Neutral theory: 

The vast majority of observed sequence differences between members of a population are neutral (or close to neutral). These differences can be fixed in the population through random genetic drift. Some mutations are strongly counter selected (this is why there are patterns of conserved residues). Only very seldom is a mutation under positive selection. 

The neutral theory does not say that all evolution is neutral and everything is only due to to genetic drift.

(Nearly neutral theory:  Even synonymous mutations do not lead to random composition but to codon bias.  Small negative selection might be sufficient to produce this bias. )

Note: the larger the population the better selection works, and the closer to neutral a mutation needs to be in order to be fixed by genetic drift. (If N*s<<1 the mutation behaves as neutral, and the fixation probability is 1/N; if N*s~1 then fixation probability is only about 2s, which is small, but seems to work.)

Is Evolution in humans only neutral? Does selection still play a role? E.g., here , the distribution of alleles that encode a protein presumably involved in brain development (here for the article, in case you are interested to read more, a similar case reported here), here for a comment that argues the haplotype frequencies might be due to drift and small founder populations and not reflect selection.