jerrywickey

Thanks I will look for other answers too. Jerry

http://www.sciencemag.org/cgi/content/abstract/319/5867/1214?HITS=10&sortspec=date&hits=10&maxtoshow=&FIRSTINDEX=0&resourcetype=HWCIT&fulltext=rain+bacteria&searchid=1&RESULTFORMAT= "[ world wide ]... 69 to 100% [of precipitation nucleates] were biological, ..." While dust and fireworks displays do nucleate parcipitation, the long held belief that biology has little to do with rain is apparently incorrect. It seems that perhaps far more than half of rain world wide is a direct consequence of bacteria "deciding" to express a gene coding for a protein which is perfectly suited for nucleation. Jerry Other sources http://appl003.lsu.edu/unv002.nsf/9faf000d8eb58d4986256abe00720a51/d807d7193ca91738862573fe004e8ff8?OpenDocument http://www.wired.com/science/planetearth/news/2008/02/bacteria_clouds http://www.eurekalert.org/pub_releases/2008-02/msu-abm022808.php This is an extraordinary opportunity! A protein well suited as a precipitation nucleate arising by evolutionary processes allows a great insight into the workings of evolution. This is a great opportunity. One which we do not often have. I would love to begin a concentrated, collaborative, informal discussion of this. Here are some things we know with certainty. 1) The organism expressing this protein must have "tested" millions of permutations of this protein to find one this well suited. How many permutations exist? Is the coding identical or are there variations in each species? 2) The evolutionary pressure which selects the protein effectiveness exists in the cycle of organisms falling to earth with rain, thereby benefiting ground plants. There must then be some mechanism where organisms which later become airborne benefit indirectly by the ground plants advantage. How responsive could this process be? 3) The evolutionary selection of the protein must have been responsive enough to provide for the observed variations or lack of variation in this protein. This is very interesting stuff. Any takers? Anyone interested in investigating this? Jerry

Just a dumb question. Is the useful side of cDNA reversed 5' to 3'? Is ribosomal RNA transcribed from the same side of DNA as mRNA? I think it would have to be. If so, how would a cDNA transcription of 16s rRNA be different from the DNA template from which the rRNA was originally transcribed? Or is sequencing the 16s rRNA needed in order to find the DNA template among possible splices? Because the cDNA transcription of the rRNA would not have the introns? Sorry for the dumb question. Its just not sitting right in my head for some reason. Jerry

It is most likely that the organisms are not extratarrestial. Although I do not discount panspermia, I suspect interplanetary DNA would be greatly limited. There really is no good evolutionary explaination for organisms which are specialized for mid air life. But none the less, stranger has happened. Jerry

Both questions are insightful. I have considered both these things. First, this is a computer model. But it is not like other models which deal with the specific advantage or disadvantage. I looked at these models and realized the problems they introduce. My model accurately models mutations and accurately maintains at equilibrium an average sequence length of 15 nucleotides. This is the length MIT suggests might be the length of nucleotides which are assembled prebiotically. That was the major motivation to write the software. I wanted the simulation to actually simulate mutations not the effects mutations might have. Second, you are right, we do not know what RNA sequences could express activity. We have a few examples. An MIT study found GGAAAAAGACAAAUCUGCCCUCAGAGCUUGAG AACAUAUUCGGAUGCAGAGGAGGCAGCCUCCG GUGGCGCGAUAGCGCCAACGUUCUCAACAGGC GCCCAAUACUCCCGCUUCGGCGGGUGGGGAU AACACCUGACGAAAAGGCGAUGUUAGACACGC CAAGGUCAUAAUCCCCGGAGCUUCGGCUCC carries on some limited replication activity with out any additional biology. What we know with certainty is that some sequences endow the activity of replication, some sequences enhance replication, and some make replication less likely. But we do not know what these sequences are and we do not know what the exact mechanism of these sequences might be. So I am simply arbitrarily assigning the sequences, ignoring the chemical activity and modeling the net effect of the activity. i.e. a replicated sequence and increased or decreased likelihood of successful replication. Third, by arbitrarily assigning sequences which endow activity, the user has complete control over the environment in which these theoretical organisms exist. The user might simply make a world where no advantageous sequence exist and see what would happen. By adjusting these parameters until the results match observations, we can find what these parameters must have been. You just have to play with the simulations to see what I mean. Dr. Alex Aller helped me to validate the software. We spent a lot of time, simulating lab work that he had actually done. The results of my software, matched his lab results almost perfectly. The most exciting thing I found yet, playing with the software is that replication alone will grow a genome and that advantageous mutations cause an emergent process which organizes information. Organizing information was the most consistent objection to the theory of evolution. My software, clearly shows information being collected and organized. Studying the mechanisms which cause this emergent process is very interesting to me. Jerry

In runs of First Colony where advantageous mutations were assigned zero probability, the length of organisms containing sequences expressing replicative ability grew in length. The average number of nucleotides increased despite zero advantageous mutations. Screen capture of a run where advantageous mutation are suppressed to zero, showing genome growth of nearly 200%. Disadvantageous mutations are allowed but were suppressed by replication. Software available free at http://www.satellitemagnet.com/firstcolony Screen capture of control simulation run where advantageous mutations are not suppressed, showing genome growth of the same nearly 200%. Again disadvantageous mutations were suppressed by replication. Screen capture showing extreme genome growth of over a 880% after a run of ten times the length of time for development. Suppressing advantageous mutation. Notice disadvantageous mutations are again suppressed to nearly zero by the activity of replication. Dr. Aller and I spent two hours trying to find the mechanism. We found it! Normally, advantageous sequence find their way into a genome by random mutation, causing greater likelihood of replication as well as simultaneously adding nucleotides to the genome of that organism. In other words, a larger genome is statistically more likely to contain more advantageous and disadvantageous sequences. But the genomes containing disadvantageous sequences are disadvantaged replicators. The advantaged organisms are the only ones which survive. But, with activity of advantageous mutations artificially suppressed by the software parameters, the genome still grew. This was astounding to me and Dr. Aller. The power of replication alone to gather information defied reason. We found the answer! We found the mechanism. It is surpassingly mathematical. Prior to the influence of more developed and complex biologic activity, the connection between early evolution and the math of prebiotic chemistry is accentuated. Let x represent the length of a given genome in nucleotides. Let r represent the number of nucleotides which constitute the RNA sequence which endows replication activity. Then x+1 and x-1 represent the random addition or deduction of one nucleotide to the length of the genome. Advantageous and disadvantageous characteristics of these mutations are ignored because we are examining genome growth with out the aid of advantageous mutation. But the addition or deduction of a nucleotide may effect the sequence endowing replication activity. This sequence must reside with in the genome of the organism. The likelihood of a mutation which adds a nucleotide disrupting the replication sequence by randomly adding a nucleotide to the sequence endowing replicative activity is 1 in r / (x+2) A random nucleotide might be added to the beginning or the end of the entire genome. The replicative sequence is just as statistically likely to reside at the end or any where in the middle. While, the likelihood of a mutation which subtracts a nucleotide disrupting the replication sequence by deducting a nucleotide to the sequence endowing replicative activity is only 1 in r / x. Therefore a random mutation which deducts a nucleotide is statistically more likely to disrupt replicative activity then a random mutation which adds a nucleotide. Lengthening occurs with out replication disruption at a rate of (x - r) / (x +2) Reduction occurs with out replication disruption at a rate of (x-r) / (x) (x-r)/(x+2) is always less than (x-r)/(x) Random lengthening is statistically less disruptive to replication than random reduction. Jerry

Anybody going to see the total solar eclipse in Shanghai July 2009? More than six minutes of totality! Anyone know of a group of Americans or other English speaking groups that are going? I am interested in joining or organizing a group for travel to Shanghai for the event. Jerry jerrywickey@comcast.net

Dec 2007 study shows that the vast majority of rain and snow precipitated out of vapor condensing around a micro organism, instead of organic or inorganic inanimate condensation seed. This organism has a density which allows it to float in air indefinitely and contains a gene coding for a protein that is a superior water vapor condensation nucleate. I read it and can not find it now. Does anyone know the study or have link? Jerry

My First Colony early evolution simulation software is spitting out some very interesting results. As some of you may know from following my previous posts, I wrote this software to explore the immediate precursor protein of Myoglobin. The software has since taken on a life of its own. Dr. Alex Aller validated my software in a very interesting discussion with him at his home in our home town of Key West FL. I have been running many simulations and reviewing the results. My software outputs a file logging the entirety of the genome of every organism in every generation and tags each with a serial number so that it can be traced back to its original replicator and follow each and every mutation. I naively believed that I could simply open this output file and look over the genomes to discover how many different specie of first replicator arose after a thousand generations and after ten thousand and so forth. Here, one can see the new replicators have nearly dominated all the available nutrients. I should have realized but I soon found out, this output file quickly grows to hundreds of mega bytes and contains the genomes of millions of organisms. So now I am writing software that sorts out the millions of bugs into respective species and counts the populations. So that I can compare the resulting populations with the run parameters to discover what effects what. Here, the second advantageous mutation (in bright green) has taken strong hold and nearly wiped out the weaker replicators (dark green) with only one mutation endowing replicative advantage. The weaker species is now nearing extinction. It has evolved to its limit of evolution, but has not demonstrated nearly as much variation as I had expected. So far it does seem that evolution, when pressured by limited resources likes to find a superior organism and favors it so strongly as to possibly deselect all weaker ones. Which seems counter intuitive, since pre-Cambrian O2 producers would then have been expected to have produced prolific numbers of evolutionary interspecie offspring. This is however, not what we observe. www.satellitemagnet.com/firstcolony Since we do not know what the RNA sequence endowing replicative activity actually was in the first replicator, the user can arbitrarily assign the sequence as well as assign advantageous and disadvantageous activity to specified sequences. The software logs to a user specified file the entire genome of every organism in each generation. It assigns each a serial number so that any organism can be traced back to its original replicator. Be careful, this output file can easily be over 100 megabytes. Mutation rates are completely user alterable. Robustness of replication is user alterable. The number of nucleotides is user alterable. I have not written a manual. You are welcome to email any questions. The web site provides a short tutorial. Jerry

What bioactivity would have been required to free oxygen? Could this have been done entirely by RNA? Or would protein function, perhaps, the earliest protein domains, with catalytic activity have been required? Some process which ultimately enhanced reproductive success, and which had oxygen liberation as a byproduct, could be very complex. But what ever it was must have been simple enough to have arisen with out well evolutionarily developed genetic regulation for protein domain recombination. The likes of which we observe today. Are you aware of any protein domain transfer or recombination mechanisms which are not regulated by well evolutionarily developed genetic regulatory systems? How simple could these bugs have been? Jerry

Thanks, That clears some things up. (apparently, I misspoke, is Cambrian the period from half billion years ago to about 1 billion years. I intended to refer to the three billion years prior) What quantity over what period of time would cyano-bacteria need to produce the atmospheric reservoir of O2 we see today? Would it have taken the entire 3 billion years? Or did the cyano-bacteria produce the current level of O2 long before the Cambrian? I am trying to find just how early these O2 producers must have existed. I would like to see just how early this must have taken place. I am learning so much from my early evolution simulation software. I am trying to find a plausible model for entire genetic sequences to be borrowed and exchanged. A process which must have been as common and robust as O2 production is a good starting point for this model. Jerry

Cambrian was the evolutionary advantage of Cambrian micro-organism's ability to liberate oxygen from CO2? Of course we breathe O2 which in does not prebiotically, due to its strong affinity to carbon or hydrogen. Early Cambrian organisms must have liberated oxygen from carbon to give us what we breath today. This process had to be extremely robust to accumulate the tremendous current atmospheric oxygen reservoir in only a few billion years, essentially exhausting atmospheric CO2. Oxygen was a waste product for some very successful organism. However, as the atmospheric CO2 level dropped to half what it started, this theoretical organism must have found an evolutionary advantage to reordering its oxygen producing biochemistry. It had to make this evolutionary choice over much more likely evolutionary choices, given the dwindling CO2 levels. But in fact it did make the evolutionary choice, selecting to continue producing a waste product under increasingly scarce CO2. Any one have any ideas what the evolutionary advantage of producing Cambrian O2? Jerry

Dr DNA Sorry I did not have time to respond more carefully before. You might be missing my point. I don't know. I am attempting to see the emergent patterns of early replications. I am not trying to solve the chemistry. One of the most exciting things I found the very first night I completed the program and the most interesting as well to Dr. Aller was that it turns out that replication alone in an environment conducive on.y to mutation with no possibility of advantageous or disadvantageous activity will by itself generate genome growth. This revelation could only have come from a model where the parameters can be completely controlled. Neither I nor Dr. Aller could understand the mechanism. The output of the software made this phenomena obvious. But neither of us realized it would happen. What comes out is not what I put in. What I put in are only the rules which govern the process. The process unfolds according to those rules and often surprises us. Being able to model the chemistry directly would be wonderful. If we had the computing power to do this, we would already know exactly what the first replicator sequence is. We would already know exactly what the conducive chemistry was. But we don't so we still do not know. I am not referring to any extra natural involvement. I am suggesting that if e.n.i. was not involved then an accurate model must be available. MIT is Massachusetts Institute of Technology. And the chemistry then was the same as chemistry is now. We will not likely find that some sort of new chemistry was operating long ago. DNA is what the earliest replicators must have gravitated toward, because DNA is all we see now. We can sufficiently hypothesis about what conditions might have been long ago. And we can investigate those conditions. However, any replicator of any kind under any conditions, must have made a switch to DNA at some time. Unless we presume an implausibly complex molecular system that jumps to DNA, RNA is our only option. Do you have another in mind or are you supposing that Darwin's black box holds another secret possibility? The motivation for writing this software was in fact my review of other evolution software. All I reviewed is exactly as you describe. Nothing comes out that they did not put in. Dr. Aller and I spend several hours testing my software against his lab observations. My software accurately duplicated every empirical lab result, we tested. I have confidence that it will predict accurately otherwise untested values for parameters. I used simple logical constructions, the output is an emergence of these simple rules. The results of true emergence often surprise the author of the simple rules. This was exactly the case when the Dr. and I observed the sim engines telling us that replication alone with out advantageous mutation did in fact increase genome size. When we tested advantageous mutations only, it grew faster. And grew fastest with advantageous mutations. We expected this but the growth with out advantageous or disadvantageous activity was not input and was a surprise. It took us an hour, to discover the bio mechanism which accounts for this. This the first thing this model taught me.. Jerry

Thanks Jerry

That post does fit well with this one. I am just not used to forum members actually following a thread. I am new here. I hope this is the case. Thanks swansont Jerry

I understand your concern. And I give you my word I put nothing harmful in the code. Of course, I wrote every line in fcolony.exe When you download the exe it will create one or two files in the directory in which you downloaded it. The fcout.txt file will get very large 50 megabytes sometimes. But simply deleting the name fcout.txt from its place in the fcini.txt file will stop its creations and you can delete fcout.txt as often as you like. enjoy, Jerry

I have the good fortune of living on the sunny sub-tropical island of Key West, FL. A town I share with Dr. Alex Aller, molecular biologist whose work, among other things, involved developing the process of tagging cancer cell genomes with the bio-luminescent protein coding gene of fireflies. I am very happy to report that First Colony was informally validated in its ability to accurately model nucleotide sequence replication behavior by Dr. Aller. The new ini parameter file which the Dr. and I optimized this afternoon is available for download. I have also improved the visualization option to make each wave of advantageous mutation more obvious from the panorama view. Simply erase the current ini file, FCINI.TXT and the fcolony.exe file and download the program again. http://www.satellitemagnet.com/fcolony.exe Also the source code is also available http://www.satellitemagnet.com/fcolony.sor I called him this morning to discuss my new early evolution software. And I would not be writing this had our lunch not have gone well. Dr. Aller had a hundred questions about the assumptions and the parameters of the simulation software. As he agreed one by one with logic of the parameters, we also discussed the many values which might be used in these parameters and the various possible results. By the end of the lunch, he invited me back to his home to attempt some simulation runs that we had discussed over lunch. We ran several simulations values for the parameters with which Dr. Aller had empirical lab experience. We wanted to see if my simulations software, actually reported accurately when posed with values for the parameters which the Dr., had actually observed in the lab. Every single one returned results well with in the statistical variation of the results observed in the lab. Please everyone, be encouraged to play with the values for the parameters. Please post interesting results. There is always the chance that you will make an observation which directs new discoveries. And... even if none of us make a new break through discovery, no one ever went wrong taking the time to learn. Jerry

It's ready! You can download -First Colony- early evolution simulation software at www.satellitemagnet.com/fcolony.exe Download it and double click it. If it fails to start the first time, It just ran into a little problem writing an ini file for itself. Opening that file with note pad will allow you to adjust all of the parameters. Just double click Fcolony again to see it run. Press enter to get through the welcome screen and both parameters screens. It will begin the simulation by displaying the detail of every nucleotide of every random sequence in a theoretical primordial pool where we assume that the chemical environment was conducive to catalyzation of random nucleotide assembly. Then press the zero key to see a panoramic view of early evolution. After you press 0, you will see a white X for each random sequence that can not replicate. A red O for any that can. You will see white X, random RNA sequences, slowly give way to red O, simple replicators. Then you will see the red O give way to more advantaged green repicators with longer genomes. As you can see in the (len) indicator, the average genome length is getting larger and larger, contrary to what random mutations can cause. The O and X will turn green if a random mutation has resulted in a nucleotide sequence which the sim engine has identified as advantageous and blue if disadvantageous. As the simulation continues in front of you, you will see that the red replicators will slowly take hold. Sometimes random mutations will kill all of them before they get the chance. Just press Q on your keyboard to end the simulation and double click Fcolony.exe again. As the replicators begin to consume all of the resources, you will notice that the info bar at the top, (explained below) shows expected number of advantageous and disadvantageous mutations in all of the random sequences including the sequences capable of replication. You also see that the average length of all sequences is about 15 as one would expect by random activity. But as the replicators take over and natural selection begins to select out disadvantaged sequences, the numbers of each shown on the info bar at the top start to be very distorted compared to the values which random mutations caused before replicators took over. After about a thousand generations you will find nearly no resources available to random sequences and advantaged organisms have actually grown the average length of their genomes, having packed them with advantageous sequences. Jerry What you see is an info bar at the top. Across the top from left to right. Displaying the current generation / total generations to model. Total number of random sequences which the simulation is tracking. They are not organisms yet. But they will be when they assume replicate capability. Total number of sequences which can replicate themselves Total number of sequences which have acquired advantageous RNA sequences by random mutation. Total number of sequences which have acquired disadvantageous sequences by random mutation. Last the average number of nucleotides among all the sequences being tracked. I will guide you through the first run and show you what is most interesting. After the first run is done, you will find two additional files in the same directory as the First Colony file. FCINI.TXT and FCOUT.TXT. FCOUT will be replaced every run. So if you saw something interesting in a run, rename this file before executing another run. This file contains the entire sequence of every critter in every generation complete with a serial number that references its parent sequence. So that you can follow the genealogy of any interesting evolved "bug" back to the first replicate and see each of the intermediate steps. FCINI.TXT must be opened with note pad. Because its exact DOS file name is important. You can change any or all of the parameters in that file. Save it and run Fcolony.exe again to see what changes occur. When you run it for the first time, press enter to get past the welcome screen then read the default run parameters. The important things to read are that advantageous nucleotide sequences are set to be three times more likely than advantageous sequences. You will find that life is tenacious. This apparent disadvantage is meaningless to life taking a foot hold. The other values you can play with on other runs. Press enter again, This screen simply shows you a sample of the nucleotide sequences which have been arbitrarily assigned functionality. This screen's purpose is merely to allow the user to verify by random sample. Now the simulation begins. press the space bar to begin the simulation one frame at a time. That way you will be able to follow along reading the description while it is running. You now see the first 40 random sequences in a pool of 1300 random sequences. You can read the nucleotide sequence for each one, if you want. I selected an average of 15 nucleotides because researchers at MIT suggested that current understanding of prebiotic chemistry suggests this to be the upper limit of random prebiotically assembled nucleotides. The very first two sequences contain within them a sequence which the simulation engines have been told endows replication functionality. These two were seeded by the ini file. In later runs you don't have to seed any first replicators, if you want to see it happen randomly. The info bar at the top of the window shows the generation number of the total generations which will be simulated, the number of sequences that the sim engines are keeping track of. Imagine a pond or ice sheet or deep ocean environment where conditions are catalytic for the random assembly of nucleotides. Imagine that this "pool" has the materials to support 1300 sequences of about 15 nucleotides each. All these conditions can be altered by accessing FCINI.TXT for later runs. Now imagine that the law of chance continually assemble and disassemble these sequences. That as soon as more than 15 to 20 nucleotides come to gether that the same chance chemistry that brought them together takes them apart and the average sequence length is about 15 nucleotides. This is what you are about to see, but first take note of the other four numbers They are the number of sequences being monitored that contain the replication sequence, the number of sequences which contain more than one advantageous sequence, the number of sequence being monitors that contain disadvantageous sequences and finally the average length of the sequences being monitored. press the space bar a few times to see the details of the first 40 sequences effected by random mutations. The ini file tells the sim engines that random mutations will occur at a rate of 5 sequence per 100 per generation. So as you can imagine only about two of the sequences on the screen right now will be effected by each press of the space bar. You also notice that the first number labeled repl. shows 2 and the top two have turned red. This is because the sim engine has identified them as containing the replication sequence CUCGGCUC Look for it. Actually current science believes that a nucleotide sequence of this length is far too small to express any functionality at all. But also we never actually observed nucleotide sequences do any thing at all that was not in support or close association with a ribosomally translated protein. But we know that nucleotide sequences alone can exhibit functionality and have demonstrated such in the lab. We have no catalog of sequences which might exhibit functionality. So my sim engine simply arbitrarily assigns functionality to some sequences. You can change the frequency and assignment ratios of this in the ini file. That second number will always show the total number of the 1300 sequences being tracked that contain the sequence which endows replication functionality. The second and third numbers show the number of sequences which contain sequences the sim engines have assigned as advantageous and disadvantageous. The advantage of any sequence is to reproduction. This is very early evolution. No organism is capable of expressing predatory characteristics or camouflage. A plausible advantageous sequence might be one that binds to chemicals present in the environment which prohibits the functionality of the reproductive sequence. A plausible example of a disadvantageous sequence might be one which causes the sequence to bend around itself, obscuring the reproducing sequence making replication less likely. These hypothetical but very plausible sequence have been randomly generated and randomly assigned functionality according to the parameters found in the FCINI file. The numbers will be about 1 2 or 3 replicators, less than 10 advantageous sequences found in the 1300 sequences being tracked and perhaps as many as 20 or so disadvantageous sequences as well as an average sequence length of 15 or so. The numbers on your screen may differ. This is a real time random simulation. But come close. The organisms containing disadvantageous sequences number nearly three time the number of organisms which contain advantageous sequences. And the average length of all organisms is about 15 nucleotides. Keep pressing the space bar. The simulation engines will process each generations. Keep pressing it until there are about 10 replicators. The generations will pass and you will notice that the number of replicators will increase. On occasion the first replicators will succumb to random mutations which interrupts their functional replication nucleotide sequence. If this happens you can end the simulation by pressing q or wait to see if another replicator arises randomly. Once the replicator have taken hold nothing will stop them. You will see their numbers increase. Now press 0 (the zero key) this will take you to a broad view of the entire pond. random sequences will be represented by whites X repliators by red O . The sequences will often turn green or blue briefly. Green if they contain advantageous sequences acquired by mutation and blue if disadvantageous sequences. By the hundredth or two hundredth generation, replicators may number nearly a thousand already. Nearly taking over the entire primordial ponds resources. Take notice that the random sequences, which are now organisms because they are daughters of a replicator and can replicate themselves, look at the ratio of advantageous and disadvantageous sequences which are contained inside these organisms. They still remain at the original ratio which was dictated by random chemical activity. As does the length of the average sequence. It remains at near 15. But soon this will change as the replicators take over. you can press space bar to proceed a generation at a time. You can press any of the number keys except zero to return to a detailed view of about forty random organisms Or 0 will take you to a panoramic representation. pressing enter will cause the simulation to proceed as fast as possible. Watch the magic of life. As the replicators which now steal all resources from organism which retain a lower rate of replication and nucleotide acquisition start to alter conditions. As the generations proceed you find that the random distribution of advantageous and disadvantageous sequences gets skewed wildly toward the advantageous. And watch the average length grow as replicators which are endowed with advantageous sequences push out weaker competitors and the replication of their longer genomes outweighs the random manipulation of the original sequences. If you let the simulation go on for its 5000 generations you will find that not only have replicators taken over but that they have evolved genomes ten times their original size and have adopted strongly advantaged sequences. It is remarkable to watch the red take over and then more slowly green creep across the screen. Life has begun. The default parameters demonstrate activity exactly as predicted by evolution. I hope you enjoy and have as much opportunity to learn from using First Colony as I had writing the software. Please comment negative or positive. Especially positively. Jerry

You are correct that DNA and its necessary polymerase complex of proteins could not plausibly be the first occurrence of life. DNA must have come much later. At the first occurrence of DNA, there was no ribosome, but there must have been some form of functional ribozyme. The polymerase protein system must also have been present, for DNA and the polyerase system to have tried many combinations before two complimentary RNA sequences could have been utilized as a storage media. Earliest life must have been RNA. The only alternative is to assume that some prebiotic replicator made an implausible jump directly to DNA. RNA has to be the answer. This fact alone, however does not prove RNA world theory. However, for a plausible pathway to DNA, which of course is not only dominate but all self contained RNA systems have been eliminated. agent change Yes I agree the probability of additional single nucleotides and segments of sequences are essential parameters. But, happily there is no mRNA, tRNA or DNA to deal with in this changeover from the prebiotic to evolution. All those things are still millions of years in the future for the First Colony. foodchain, Your point shows you appreciate the challenges. Remember that I am not even attempting to model the actual chemistry. The computing power is simply not yet available. Should this level of computing power currently be available, we would already have the exact RNA sequence of the first replicator. But of course we do not. Think of it this way. Many popular games simulate battles between opposing armies by throwing a die and weighting its outcome in accordance with the opposing armies strengths and weaknesses. For instance I assume an RNA replicating sequence. We all know it is not the one. We all know that it is too short. But we all know that one did exists. My model simply makes the assumption that we do know it was this one. And instead of modeling the chemistry that makes it work. It simply applies the net result of a RNA replicase sequence. That is it replicates the entire sequence including junk sequences, advantageous sequences and disadvantageous sequences that are attached to the replicase sequence. So I don't need to model the chemistry to see what would happen if we did know the exact sequence and could model its chemical activity. Jerry

Well, some of the results anyway. I didn't notice is was 2 am this morning when I stopped working on the model. I was excited because even though I still do not have a user interface to look at the simulation engines output, I am skilled enough to understand the output if I take a little time. And you bet, I was excited to try some runs. MUTATION RATE RESULTS I knew that the mutation rate was important, but the results of these early runs suggest that it is even more important than I thought. It is the relationship between the replication rate and the mutation frame shift plus and the mutation frame shift minus rates that needs careful balance. The effects three have on the success of a replicator becoming a colony seems to be closely interrelated. It is one thing to reason this. But I tell you it is exciting to actually see the interactions in the thousands of daughter RNA sequences. SURVIVABILITY OF ANY REPLICATOR Another eye opener: I had assumed that if one replicator didn't make it, one of its daughters would be able to have another go at it. What I didn't realize until I actually saw the process on the printouts, is that the whole of the colony shares a recursive relations ship with each individual organism. It is like a fractal relationship. Each successive larger construct is more similar to a bigger copy of its smaller components, than it is different. The whole colony acted more like a single organism than individuals of a colony. Wow! Jerry

Thank you INow. I don't hold any grudge against you. And your pointed comments do show you thought about the distinction between abiogenesis and evolution. If you can help, please know that I value your suggestions. agentchange Excellent comments I need more of these 1) yes the arbitrary sequence I chose to endow reproductive characteristics is ridiculously small. But the software does not model chemical activity. It models the effects of small mutations on sequences which ultimately endow relatively complex functionality. To do this with out addressing the chemistry allows the software to replace chemistry with logical math. Similar to popular complex war games where two army fight based on the role of a die by weighting the die's outcome with considerations for the opposing army's strengths and weaknesses. 2) If evolution of the first abiogenic replicator actually took place, then this perfect chemical soup must have exists at some place and in some time. My model assumes this very soup as its starting point. 3) My software will go no where near anything that approaches a cell. It will only model the first several hundred, thousand or ten of thousands of generations after the first replicator. I expect to see patterns that are similar to what millions of years later will become protein evolution. I expect to see patterns of development which show overlapping function of sequences. This is one of the most exciting processes I hope to observe. Else where in these posts I comment on other things I hope to elucidate. First Colony software development progress update 2/16/08 I have neglected other work to do this. I am going on 19 hours total work on the software now. The choice of programming language was tough. I am very sure that experienced programmers will bitch about my final choice. The language I chose is archaic. But I wanted to use a language that intuitive to novice programmers. I was not interested in writing the software for programmers. Many people whose primary interest is biology not programming will find this software interesting. So I certainly did not want to use a programming language which was intuitive for people not up to date on the latest fun new programming language. So if you are a programmer, you will surely have no problem fiddling with the source code. If you have little programming experience, the language I chose was originally designed with novice programmers in mind. It has intuitive instructions and structure. It shuns any contrived programming structure which is attractive to professional programmers but usually difficult for novices to understand with out experience The speed of the executable does not suffer at all compared to the more advanced programming languages. So there is no down side. There are four math engines in the software 1 mutation of sequences 2 disadvantageous effects of some sequences 3 advantageous effects of some sequences 4 reproductive effects all successful sequences There are also housekeeping routines 1 generating the arrays that keep the organism data and the sequence assignments 2 keeping track of each organism and shuttling it through the engines at the appropriate time. I have finished both housekeeping routines and tested them I have written all 4 of the simulation engines 1, 2 and 3 are written but not tested 4 the repo engine is proving challenging. I have not begun the generate report routine yet Jerry I forgot to mention that if you are not interested in fiddling with the programming, you can use the executable alone. It will give the user the opportunity to alter the values for all of the parameters, run any number of simulations, and review the complete "genome" of every organism of every generation of as many generations as you chose. And do this with out ever looking at a single programming instruction. Jerry Here is the ini file for the software. It makes the parameters much more understandable. I hope that anyone interested will better understand the purpose and scope of the software by a quick review of this information. FCINI001.TXT First Colony Initialization file. no ,< has this ini file already run? 1 ,< total number of initialization files FCOUT001.TXT ,< file name for output. 8 characters or less 1 ,< replication rate 1000 ,< limit of resources 10 ,< frequency of frame shift plus mutations 10 ,< frequency of frame shift minus mutations 10 ,< frequency of single point nucleotide mutations 5 ,< ratio of advantageous RNA sequences 50 ,< ratio of disadvantageous RNA sequences 5 ,< ratio of fatal RNA sequences 0.2 ,< percentage of RNA sequences expressing activity Explanations below. First Colony Software simulation of very early evolution. Software written by Jerry Wickey, 800 353 0056, Key West, FL jerrywickey@comcast.net Version 1.0 Feb. 16, 2008 This is a simulation of the first generations after the occurrence of a prebiotic RNA first replicator sequence. This simulation assumes a chemical environment conducive to random nucleotide assembly, and which catalyzes such random assemblies. Prebioticaly synthesized RNA nucleotides and enzymatic activity of some RNA sequences is assumed. Characteristics of nucleotide assembly and activity are alterable by the following parameters. Do not change the order of the values. Change only the number. If the program yields wildly unexpected results and you suspect ini file corruption, simply delete all ini files and run the software again. A default ini file will be written by the software. no ,< has this ini file already run? if this value is yes, First Colony will not run this ini and will instead look for the next ini file in the sequence up to the total number of ini files. 1 ,< of total number of initialization files Leaving this value one, will cause the software to run once, using the values found in fcini001.txt You may use a value as high as 999. The software will make consecutive runs for each ini file labeled fcini001.txt fcini002.txt fcini003.txt etc. Each may contain related parameter values or completely different unrelated values. FCOUT001.TXT ,< file name for output 8 characters or less This will be the file name of the output file. If running successive ini files, 001 002 003 will be appended to the output file name. 1 ,< replication rate Zero or a negative number will always result in no replication at all. It is a base probability. Positive values are augmented or reduced by other factors, including random factors and the number of advantageous and the number of disadvantageous sequences each organism Acquired by random mutation of single or multiple nucleotides in its RNA "'genome'. 1000 ,< limit of resources this is the number of organisms our assumed pond can sustain. The number of organisms can not exceed this number. If replication causes this number to be exceeded, an organism chosen at random will be extinguished to make room. The weaker the member the more likely to be chosen the stronger the less likely. This is representative of a competition for limited resource. The maximum value out theoretical pond can support is 1000 organisms. 1 ,< frequency of frame shift plus mutations All three mutation ratio values are comparative. So that if one desires to model evolution such that frame shift plus mutations occur three times as often as frame shift minus and two times as often as exchange mutations then one would enter 3, 2, 1 respectively Frame shift plus mutations are mutations which add random nucleotides at random points along an organisms RNA 'genome.' Only one nucleotide is added most often, but multiple nucleotides may be added. The number of nucleotides added is randomly calculated on a logarithmic scale favoring fewer nucleotides. 1 ,< frequency of frame shift minus mutations frame shift minus are mutations which remove a random nucleotide. One only is always removed. 1 ,< frequency of single point nucleotide mutations exchange mutations are the random change of a single nucleotide to anther random along the RNA 'genome' 1 ,< frequency of advantageous RNA sequences All three sequence generator ratio values are comparative. So that if one desires to model evolution such that advantageous sequences occur three times as often as disadvantageous sequences and two times as often as deadly sequences then one would enter 3, 2, 1 respectively Advantageous sequences are assigned arbitrarily. The software generates random sequences and assigns its activity as advantageous to an organism in some unspecified manner. This same sequence will be advantageous to any organism which acquires it by random mutation. 10 ,< ratio of disadvantageous RNA sequences Disadvantageous sequences are assigned arbitrarily. The software generates random sequences and assigns its activity as disadvantageous to an organism in some unspecified manner. This same sequence will be disadvantageous to any organism which acquires it by random mutation. 1 ,< ratio of fatal RNA sequences Fatal sequences are assigned arbitrarily. The software generates random sequences and assigns its activity as fatal to an organism in some unspecified manner. This same sequence will be fatal to any organism which acquires it by random mutation. 0.2 ,< percentage of sequences expressing activity This value is the percentage (per 100) of sequences which express activity of any kind. Not all RNA sequences do anything. In fact perhaps very few permutations express activity at all of any kind. They simply are inactive. If one desires to model very early evolution where 2 RNA sequences of any given reasonable length per thousand express activity of some kind, one would enter this value as 0.2 -end-

Modeling the chemistry would require Sci Fi like computing power. Modeling with out addressing the chemistry allows the software to replace chemistry with logical math. Similar to popular complex war games where two army's fight based on the role of a die by weighting the die's outcome with considerations for the opposing army's strengths and weaknesses. The arbitrary sequence I chose to endow reproductive characteristics is ridiculously small. This is obvious, reading the MIT paper on the 195nt replicase. But the software does not model chemical activity. It models the theorized effects of small mutations on sequences which ultimately endow relatively complex functionality. In the resulting runs, I expect to see patterns that are similar to what millions of years later will become protein evolution. I expect to see patterns of development which show overlapping function of sequences. This is one of the most exciting processes I hope to observe. Else where in these posts I comment on other things I hope to the model will illuminate. Jerry

Please, people if you believe that I am a kook, don't bother reading the post and surely do not post reply. But if you would like to see a model of the first generations of the first replicator, after its emergence, post any ideas you have regarding the consistency of the model's parameters to the parameters which must have governed those first generations of replication. INow, You need to read the post before you comment again. INow wrote: "abiogenesis ... is not crucial to a valid theory of evolution any more than a solid knowledge of the internal combustion engine is required to successfully drive a motorized vehicle. " Dude, 1) If there is no internal combustion motor to put in vehicle, driving it successfully should prove difficult. On what did evolution act, if abiogenesis, (advent of a first replicator by an entirely naturalistic means,) couldn't have occurred? We study evolution with the certain assumption that abiogenesis did take place with out extra nature involvement. Should this be discovered to be in error, we have a great deal of rethinking to do. If you take each of my 4 sentences above and evaluate it, no reasonable person could disagree with even one of them. Try it! And if you feel I am in error, post the sentence and explain how it is in error. 2) If you read the post, you would have realized, I am not dealing with abiogenesis in the modal at all. The model assumes that has already taken place with out posing any source for it. I am not studying abiogenesis. This model does not address abiogenesis. Abiogenesis or any of the variables associated with it, purple unicorns not with standing, are not addressed in the model. INow;s post illustrates exactly my point regarding evolutionists similar affinity to irrationality as we are used to associating with creationists. INow has clearly not read the description of the simulations engines. If he has, he did not understand it. When he read the word abiogenesis, his thought process became completely derailed. He clearly did not understand any thing he read after that word abiogenesis. INow, please, Lets leave this level of irrationality up to people of faith. After all faith is defined as the belief in something which has no proof. Faith is by definition, irrational. I am not knocking faith. Love is also irrational. And who wants to be with out love. But don't let irrationality derail, a study of the first generations of an assumed abiogenic first replicator. Shall we? Please, people if you believe that I am a kook, don't bother reading the post and surely do not post reply. But if you would like to see a model of the first generations of the first replicator, after its emergence, post any ideas you have regarding the consistency of the model's parameters to the parameters which must have governed those first generations of replication. Jerry

Like I said in the sister thread to this one. I am not pulling any punches. I want to see what the values for the parameters I identified must be such that a viable colony could have arise from a single first replicator. I understand the difference between abiogenesis and evolution. I understand it very well. This simulation is the crux of that change over, the advent of an abiotic first replicator taking on the characteristics we define as evolving life. The problematic definition of life not withstanding. The reason for the post is to engage help in identifying any inconsistencies between the parameters my simulations engines will use to model these few generations and the actual parameters which might have actually applied. The values of the parameters are not important. Fiddling with the values and evaluating the results of each simulation run will yield the greatest gain. I am not attempting to prove anything or change anyone's mind of anything. I claim that I am guided only by empirical evidence and the logical evaluation of it. Positions I hold relevant to this discussion and germane to your question regarding your query about my objective follow. The following might flesh out an image of me for you. But my goal is as stated above. Abiogenesis is crucial to a valid theory of evolution. If no naturalistic means can be demonstrated to provide a plausible first replicator, we might assume an extra natural means. IF that IS the case, we have some very new and very powerful new information directly relevant to the forces which apply to evolution. Namely if an extra natural force was involved, is it still involved? What might be its motive? And what effect might it still have on the forces which guide evolution? I have tried very hard, but am still unable to find a plausible first replicator of any kind. RNA, RNP, prebiotic, Clay theory, Crystal theory. None. I do not subscribe to negative proofs. i.e. "A naturalistic process must have given rise to the first replicator because it could not have been an extra naturalistic process." Just show me the evidence and a plausible step by step process. Then we can talk. However, I have no interest in discussing the possible nature of any such extra natural force in this thread. This software and this discussion, are not concerned with the origin of the first replicator. I would entertain any discussion regarding it. But in another thread. And I have no interest in supposing the possible nature of any such force. This thread and its sister is confined to the assumption of the first replicator. My software begins with the assumption the first replicator has already assembled itself with out regard for the means of its assembly. I don't know if you are asking about my education. I am an electronics engineer, with a strong pension for molecular biology. But I made my living in real estate. I also hold credentials in finance and equities trading. That all makes me sound way more educated than I am. You can find my most successful electronics product at http://www.satellitemagnet.com The picture on the site is of me. I peddle this product myself. Of course, I designed the satellite tracking system electronics myself. This product is actually one of my simpler designs. But it is the most marketable. I enjoy designing esoteric electronics which really have no market. Hence my living in real estate. I find the logic required to design electronic devises from scratch helps me immensely in separating the relevant from the irrelevant in other disciplines including molecular biology. Oh,... and I am a bit verbose. Jerry To keep this thread on track, Please let me know what parameters might be relevant in the first generation after the advent of a first replicator. And if the parameters I chose are consistent.

The MIT RNA quote: "If emergence of the first RNA replicase ribozyme coincided with the origin of life, it would have had to arise in a single step from prebiotically synthesized RNA, ..." --- Dr.s Wendy K. Johnston, Peter J. Unrau, Michael S. Lawrence, Margaret E. Glasner, David P. Bartel at Whitehead Institute for Biomedical Research, and Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 18 May 2001: Vol. 292. no. 5520, pp. 1319 - 1325 DOI: 10.1126/science.1060786 And the amino adenosine triacid ester (AATE). Take a look at http://w3.mit.edu/newsoffice/tt/1990/may09/23124.html This ain't my first Rodeo. I am not trying to pull any punches. I know what I am doing. Would you like to help? Would reviewing a simulation of the first generations of an RNA first replicator be interesting and revealing to you? Jerry