Homology:

Two sequences are homologous,
       if there existed an ancestral molecule in the past that is ancestral to both of the sequences.

For Evolutionary Biologists Homology is a "yes" or "no" characteristic (don't know is also possible).

Either sequences (or characters) share ancestry or they don't (like pregnancy).

Molecular biologist sometimes use homology as synonymous with similarity of percent identity.
One often reads: sequence A and B are 70% homologous.
To an evolutionary biologist this sounds as wrong as 70% pregnant.

exponential functions: (Figs. 1, 2, 3) (More data at the GOLD database here)

• Exponential growth, decay?
• log vs ln?
• dn/dt = k*n ?

.ppt on BLAST, Pangenomes, and Kezdy Swinebourne plot is here

Life and Evolution

Traditional criteria for life:

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

Is being made out of cells a good criterion?

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

Turings test for intelligence in computers

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.

Examples:

• http://www.pbs.org/opb/intimatestrangers/game/index.html
• http://www.mindspring.com/~alanh/life/ (this lets you specify living cells)

"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."

Genetic Algorithms in engineering: Ingo Rechenberg and Co. Check the collection of links on Evolutionary Computation and its application to art and design. It is amazing that GA work fine with rather small populations. (Subpopulations - demes - help to find global optima.)

One way that the question "What is life?" arises is to contemplate artificial intelligence or today's organisms and their means to package and exchange genetic information.

Another way that the question "What is life?" arises is studies of the historical transition from prebiotic chemistry to living system in the origin of life. Many scientist like the following: "the transition to biology occurs when a biopolymer arises that encodes a catalytic function (selfreplication) and is subject to Darwinian evolution.

(Aside: Using the traditional 5 criteria for life a phage or virus is not a living organism, but the phage is definitely part of a living system - in a similar way the individual honey-bee doesn't fulfill the 5 criteria, but the bee hive does. In a similar way the larger ecosystem might need to be considered, and not the individual unit. -> see the Gaia hypothesis)

Natural Selection and Evolution

When does "evolution" occur? An algorithmic approach.

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 (botany, vertebrate evolution) see here
• Fusion and cooperation of organisms (Kefir, lichen, also the eukaryotic cell)
• 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, Morons

How old is life on Earth?

• The Earth is about 4.5 Ga old, but no crustal rocks has survived from that time. The oldest rocks are no older than 4.0 Ga.

• For about a decade the oldest microfossils were considered to be about 3.5 Ga old (see here). The fossils (as interpreted by Bill Schopf) look like "modern" Cyanobacteria. Compare the time to to molecular trees of life: Is this a problem? However, the evidence for these fossils was questioned.
  
• 3.2Ga old filamentous fossils, probably of thermophilic chemotrophic prokaryotes (Rasmussen, 2000)
  
• 1.8Ga old fossils from Gunflint formation: iron-loving bacteria and cyanobacteria

• Oldest geological evidence for life - 3.8 Ga ago - is based on ¹³C discrimination (carbon derived from living systems often have lower delta ¹³C values than inorganic carbonates) [here]. The rocks are from Akilia island off the coast of Greenland, and severely altered by metamorphism. However, the evidence for that was reassessed.
  
• 2.7Ga old: probable biomarkers of cyanobacteria and of eukaryotes (Roger Summons, Roger Buick and Jochen Brocks) - again controversial.
  

Assignments:

For Friday:

• Explore GenBank formatted sequence files. An annotated sample is here. The important features are cross linked to explanations. Try to find the differences between a locus name, an accession number and the GI number. (Other formats are described here).
• Read through the blast query and normal BLAST search tutorials (NOTE: the latter has red arrows at the bottom of the first and second page, that links to the next page!)

For Monday: 

• Read the last box (green) above and Olga Zhaxybayeva's version of  the Timeline of the Universe.
• Check out the toilet paper version of Earth's history at http://www.worsleyschool.net/science/files/toiletpaper/history.html to help erase the logarithmic scale that most of us have in our head when considering Earth's history.
• Read the following on the analogy between language and sequence.
• Read chapter 3 up to p38 end of the first paragraph
• Finish takehome quiz number 1

The following excerpt is from the pandas thumb bulletin board (http://www.pandasthumb.org).  The complete post is available here - The broken link to the pairwise blast is already part of the original, but any of the pairwise comparisons from last Friday would provide the same illustration.)

2. Meyer compares DNA sequences to human language.  In this he follows Denton's (1986) Evolution: A Theory in Crisis.  Denton (1986) argued that meaningful sentences are isolated from each other: it is usually impossible to convert one sentence to another via a series of random letter changes, where each intermediate sentence has meaning. Like Denton (1986), Meyer applies the same argument to gene and protein sequences, concluding that they, like meaningful sentences, must have been produced by intelligent agents.  The analogy between language and biological sequence is poor for many reasons; starting with the most obvious point of disanalogy, proteins can lose 80% or more of their sequence similarity and retain the same structure and function (a random example is here). Let's examine an English phrase where four out of five characters have been replaced with a randomly generated text string.  See if you can determine the original meaning of this text string:

Tnbpursutd euckilecuitn tiioismdeetneia niophvlgorciizooltccilhseema er [1]

Eighty percent loss of sequence identity is fatal to English sentences. Clearly proteins are much less specified than language.

3. Meyer cites Denton (1986) unhesitatingly.  This is surprising because, while Denton advocated in 1986 that biology adopt a typological view of life, he has abandoned this view (Denton 1998).  Among other things, Denton wrote, “One of the most surprising discoveries which has arisen from DNA sequencing has been the remarkable finding that the genomes of all organisms are clustered very close together in a tiny region of DNA sequence space forming a tree of related sequences that can all be interconverted via a series of tiny incremental natural steps.” (p. 276)  Denton now accepts common descent and disagrees with the “intelligent design” advocates who conjecture the special creation of biological groups, regularly criticizing them for ignoring the overwhelming evidence (Denton 1999).

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However, some idea of the diversity of protein solutions to any given enzymatic “problem” is given at the NCBI's Analogous Enzymes webpage, which includes hundreds of examples.  There is more than one way to skin a cat, and there are many more ways to evolve a solution to any given functional “problem” in biology.

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1. The original phrase was: “The origin of biological information and the higher taxonomic categories”, the title of Meyer's paper.  The random text was generated at the random text generator webpage: http://barnyard.syr.edu/monkey.html…