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The point of my question is not to talk about events that are uncontrolled by living organisms. My question is about controlled randomness, or I'd like to say adaptive random process. Process that are random because it was selected in order to be random.

The first thing that pop in my mind when thinking of "adaptive random process" in biology is Fair Meiosis. Do you have other examples of "adaptive random process"? An individual might display a random behaviour in order to avoid that others to predict its future behaviour. Is there any evidence for such things? Do you know any other evidence on what I called "adaptive random process"?

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Randomness might arise due to ever changing chemical composition of cells and the environment where the process takes place. – biogirl Aug 7 '13 at 17:33
I find your computer example inconsistent with the rest of the question. If you are not interested in randomness at the molecular/sub-mulecular level, then you can say that, as PRNG in computers, also biological processes are deterministic. You make a "random" choice between A and B because (as an extremely simplistic example) your neuron "A" fired more than your neuron "B"... – nico Aug 7 '13 at 18:12
@nico Thks for the comment. I'm not sure I get your point though. Would you think my question to be improved if I asked what type of PRNG does nature use? – Remi.b Aug 7 '13 at 18:24
@nico I modified my post shortening the computer example. – Remi.b Aug 7 '13 at 18:26
@nico After more thinking, I kinda aggree that my question might not make much sense. I'll shorten it to keep only the "Do you have other examples?" part – Remi.b Aug 7 '13 at 18:32
up vote 2 down vote accepted

In an evolution mutations are often random and lead to differences in phenotype that can be adaptive under certain pressures. A lot of times mutation is a random process, but here are three cases I can think of off of the top of my head where I would say the organism is 'trying' to do it:

HIV is a retrovirus, which means in its viral form its genome is single stranded RNA, which is then converted into double stranded DNA within the host. That conversion is carried out by a virally encoded reverse transcriptase. This enzyme has a much higher error rate when making the RNA into DNA because it cannot proofread like our DNA polymerases. This means that HIV mutates incredibly fast. Many of these mutants are not very fit, but since there is so much selective pressure against staying the same due to attack from the immune system, some mutants will be much more fit if they can avoid that attack. Its a numbers game, and by making lots of random mutants HIV is very good at it.

A related, but different case is found in the diversity generating retroelements of certain bacteriophages. These are double stranded DNA viruses that infect bacteria. The bacteria these viruses infect could mutate to escape the viruses by losing a certain receptor that the virus binds to. It was observed however that the the virus would mutate incredibly quickly to bind to a different receptor, a lot faster than would be expected for a DNA virus. Also, it was found that these viruses contained reverse transcriptases, which is bizarre, since there is no reverse transcription step in a dsDNA viral life-cycle (so we thought). To make a long story short, this virus will transcribe the DNA that codes for its binding proteins into RNA, then use its reverse transcriptase to turn that RNA BACK into DNA, but uses a sophisticated targeting strategy so that it only mutates the region that is used for binding to the bacteria. It will only mutate adenine residues, leaving the C's, T's and G's alone. This is a much more clever system than HIV, because this virus uses site-specific mutations on its binding feet, and doesn't mutate its core proteins, the mutation of which would probably just lead to viruses that couldnt replicate. Here a reference for the interested:

Just so you dont think this is reserved to viruses, we do this as well with our immune system. In order to recognize antigens in attacking pathogens, our immune cells have two methods for making diverse, random, receptors. First is V(D)J recombination, where the multiple diverse copies of the V, D and J regions of antibodies and receptors are combined at random to make one set. Wiki says theres 3x10^11 possible combinations here. After that, theres also somatic hypermutation during the proliferation of B cells. In this process, the random mutation rate is hugely increased in the region of the B cell receptor gene, specifically for making slightly different versions of the already 'OK' receptor to make it a great receptor.

General theme: raising your mutation rate, either across the board(HIV) or specifically (DGRE and SHM) is a good way to intentionally add randomness for a beneficial purpose (to the extent that you can attribute 'intent' to a viral particle).

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Thks a lot for these examples. The article for which you provide a link seems very interesting btw. You examples are interesting. As you say at the end, all the examples you provided are examples where the mutation rate (which is a non-adaptive random process) is raised (which is a non-random adaptive process). It is interesting though. But I would call an "adaptive random process" a process which adaptative process which is directly random but does not use an underlying already existing process. Does it make sense? Thks – Remi.b Aug 7 '13 at 19:04
Hmm, sorry, I'm not exactly sure what you mean then. In Meiosis you get the random segregation of chromosomes, after a random cross-over that makes hybrid chromosomes. In the DNA mutations you randomly change a basepair to one of the other three, and in V(D)J recombination you randomly splice together one of each of the segments. Each process seems fairly random, and results in an offspring or cell or virus that is slightly different. Whether that random difference is a good adaptation is for the environment to decide. – gchadwick Aug 7 '13 at 19:33

I know of an example in development biology. Here is an example where noise in retinoic acid gradients is required for the boundaries in the developing hindbrain to sharpen. A related result is that the zebrafish hindbrain has a protein to modulate noise, but does not reduce the noise to zero. Together these results show that noise in the retinoic acid gradient is beneficial to hindbrain development. So in some sense the amount of crabp2a (the noise modulator) evolved to control randomness (noise/stochasticity) in the morphogen gradient, but was selected to not eliminate it.

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