Assignments for Wednesday's class:

  1. Start work on take-home exam #1 (due next Monday, link is posted on the homepage; ask question on Wednesday)
  2. Review the box below on Evolution through Natural Selection.
  3. Draw a sketch for the relation between the number substitutions that occurred in evolution and the the percent identity of the two sequences. (I.e. how does the observed similarity change, as more and more substitutions occur?)
  4. How does this relationship change, if some parts of the sequence are so important that the protein becomes non-functional, if a mutation occurs in these positions (i.e., these parts of the sequence are never observed to undergo any change?
  5. If substitution were to occur at a rate of 10^-8 per year and per site, how long would it take for two sequences to by less than 50% identical? (do a rough estimate ignoring multiple substitutions and back mutations.)
  6. If you were to do a realistic calculation and you were to consider a nucleotide sequence, how long would it take to arrive at 20% identity? (tip: how similar are to random sequences that have not been aligned?) (Note: answering this should not require the use of a calculator or a formula, just common sense.)

Goals class 3:

 

Today's outline

Questions:

Honors conversion?

Slides on ancient paralogs

Why is molecular evolution important in general and in bioinformatics in particular? (discussion)

Is there a definition of life? NASA's working definition of life: "life is a self-sustaining system capable of Darwinian evolution"

Does Darwinian evolution depend on a biopolymer that acts as genetic material?

Gaia hypothesis, levels od selection. Are viruses alive?

Can living systems be divided in smaller sub-systems that are themselves alive? Or, is life a property of the larger system? The ecosystem of the Sargasso sea that includes algae, bacteria and phage (viruses that live on bacteria). The cyanophage play an important role in the system as predators of the primary producers. They lyze the cells allowing for recycling of limiting elements. The phage are part of a living system, but usually are not cindered alive themselves.

The Gaia hypothesis argues that the whole biosphere should be regarded as a single organism, with its own homeostatic feed back loops.
Problems of the hypothesis:

* Lovelock and Watson developed the Daisyworld model (simulation here), in which black and white Daisies stabilize the climate of the model planet. The release of DMS heat stressed algae creates a Daisyworld like feed back loop, because it acts as nucleating agent in cloud formation.

 

What is life?

Traditional criteria:

  • Uptake and dissipation of Energy
  • Metabolism
  • Responsiveness
  • Gestalt (distinctive shape, separate from environment)
  • Growth
  • Reproduction with variation - Ability to evolve

See essay on definitions of life: The Seven Pillars of Life by Daniel E. Koshland
(does not go much beyond the traditional multi-point characterization)

NASA's working definition of life: "life is a self-sustaining system capable of Darwinian evolution"

von Neumann's computers - alive? A-life?

Turing machines and universal computers (Turing's biography)

Cellular automata: A'life; John Conway's game of life. [rules: a cell survives if it has two or three living neighbors. A new cell is created on a "dead" square if it has exactly three living neighbors.] The game was popularized by Martin Gardner in Scientific American in 1970.

Question: Nucleic acid and computer code can be copied. Could this be also said for autocatalytic reaction netweorks? (See Günter Wächtershäuser's prebiotic reverse TCA cycle and Stuart Kaufman's autocatalytic sets

Examples:

More information on digital life is at Digital evolution homepage at MSU.
Karl Sims' virtual creatures
are worth a look, movie here. He describes his work as follows:

"A population of several hundred creatures is created within a supercomputer, and each creature is tested for their ability to perform a given task, such the ability to swim in a simulated water environment. Those that are most successful survive, and their virtual genes containing coded instructions for their growth, are copied, combined, and mutated to make offspring for a new population. The new creatures are again tested, and some may be improvements on their parents. As this cycle of variation and selection continues, creatures with more and more successful behaviors can emerge. The creatures shown are results from many independent simulations in which they were selected for swimming, walking, jumping, following, and competing for control of a green cube."

A similar approach to evolution in silico is here.

Genetic Algorithms in engineering: Ingo Rechenberg and others used "natural selection" in the computer to optimize aerodynamic profiles. Biased walk through "sequence" space. Finding optimal solutions. (To avoid local maxima: use demes with limited migration). For more information you can check a comprehensive collection of links on Evolutionary Computation and its application to art and design. It is amazing that GA work fine with rather small populations.

Eigen_Rechenberg Sequence Space

Evolution and sequence space

What is necessary for evolution to occur?

Natural Selection and Evolution

When does "evolution" occur? An algorithmic approach.

"Darwin's Dangerous Idea" by Daniel C. Dennett, Chapter on Evolution as algorithm is a reading assignment for Monday, Sept. 13. [available through WebCT]

What is needed for evolution to occur?

(Note, this is different from stating that this is all that occurs in evolution)

  • Offspring not identical to parents
  • More offspring than necessary
  • Competition for resources, mates => survival of the fittest.

What processes in biological evolution go beyond inheritance with variation and selection? (We'll discuss many of the following later in the semester.)

  • Horizontal gene transfer and recombination
  • Polyploidization (angiosperm and vertebrate evolution) see here and here
  • Fusion and cooperation of organisms (Kefir, lichen, also the eukaryotic cell)
  • Evolution of the holobiont (host + symbionts)
  • Targeted mutations (?), genetic memory (?) (see Foster's and Hall's reviews on directed/adaptive mutations; see here for a counterpoint)
  • Random genetic drift
  • Gratuitous complexity
  • Selfish genes (who/what is the subject of evolution?)
  • Parasitism, altruism, gene transfer agents
  • Mutationism, hopeful monsters

If time, go through coral of life ppt slides.

Goals class 4: