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As few as 19 000 human protein-coding genes?

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From Human Molecular Genetics :

Abstract: Determining the full complement of protein-coding genes is a key goal of genome annotation. The most powerful approach for confirming protein-coding potential is the detection of cellular protein expression through peptide mass spectrometry (MS) experiments. Here, we mapped peptides detected in seven large-scale proteomics studies to almost 60% of the protein-coding genes in the GENCODE annotation of the human genome. We found a strong relationship between detection in proteomics experiments and both gene family age and cross-species conservation. Most of the genes for which we detected peptides were highly conserved. We found peptides for >96% of genes that evolved before bilateria. At the opposite end of the scale, we identified almost no peptides for genes that have appeared since primates, for genes that did not have any protein-like features or for genes with poor cross-species conservation. These results motivated us to describe a set of 2001 potential non-coding genes based on features such as weak conservation, a lack of protein features, or ambiguous annotations from major databases, all of which correlated with low peptide detection across the seven experiments. We identified peptides for just 3% of these genes. We show that many of these genes behave more like non-coding genes than protein-coding genes and suggest that most are unlikely to code for proteins under normal circumstances. We believe that their inclusion in the human protein-coding gene catalogue should be revised as part of the ongoing human genome annotation effort. Open access

See also: The Science Fictions series at your fingertips (human evolution)

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Comments
There are a few issues, and I have to correct some of my own conflations -- apologies to the readers. 1. number of "genes" are not the number of proteins 2. low numbers of genes are not necessarily an indication of any more than the fact there are only 4 DNA bases are an indication of biological simplicity The paper conflated the number of proteins and protein isoforms with genes. I unfortunately went for the bait. That is a major strike against the paper. There are 50,000 to 500,000 protein isoforms (no one knows the number) for humans, and I seriously doubt Mass Spec has catalogued every one of them, so how then can we even say how many genes code for proteins when we don't even know the protein count? That said, I'm not averse to thinking there might be a limited number of fundamental protein types but millions of protein isoforms, in fact for the Immuno Globulin proteins, it is a relatively established fact there are around 10 million protein isoforms. There would be great organizational reasons for having a relatively small number of proteins (say 20,000) and millions of isoforms as this would enable beautiful hierarchical organization. This researcher believes there are millions of protein isoforms (probably in addition to immune globulin forms). http://www.northwestern.edu/newscenter/stories/2011/10/proteomics-kelleher.htmlscordova
July 11, 2014
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Of related interest to wd400's claim that,,,
But it doesn’t mean you can’t fix multiple mutations in genes (indeed the expectation is that yo will get multiple mutations in genes without selection),,,
is this 'unexpected' fact:
A hidden genetic code: Researchers identify key differences in seemingly synonymous parts of the structure - January 21, 2013 Excerpt: (In the Genetic Code) there are 64 possible ways to combine four bases into groups of three, called codons, the translation process uses only 20 amino acids. To account for the difference, multiple codons translate to the same amino acid. Leucine, for example, can be encoded in six ways. Scientists, however, have long speculated whether those seemingly synonymous codons truly produced the same amino acids, or whether they represented a second, hidden genetic code. Harvard researchers have deciphered that second code,,, Under some stressful conditions, the researchers found, certain sequences manufacture proteins efficiently, while others—which are ostensibly identical—produce almost none. "It's really quite remarkable, because it's a very simple mechanism," Subramaniam said. "Many researchers have tried to determine whether using different codons affects protein levels, but no one had thought that maybe you need to look at it under the right conditions to see this.",,, While the system helps cells to make certain proteins efficiently under stressful conditions, it also acts as a biological failsafe, allowing the near-complete shutdown in the production of other proteins as a way to preserve limited resources. http://phys.org/news/2013-01-hidden-genetic-code-key-differences.html Sounds of silence: synonymous nucleotides as a key to biological regulation and complexity. - Jan 2013 Excerpt: Silent or synonymous codon positions, which do not determine amino acid sequences of the encoded proteins, define mRNA secondary structure and stability and affect the rate of translation, folding and post-translational modifications of nascent polypeptides.,,, Synonymous positions of the coding regions have a higher level of hybridization potential relative to non-synonymous positions, and are multifunctional in their regulatory and structural roles. http://www.ncbi.nlm.nih.gov/pubmed/23293005 'Snooze Button' On Biological Clocks Improves Cell Adaptability - Feb. 17, 2013 Excerpt: Like many written languages, the genetic code is filled with synonyms: differently spelled "words" that have the same or very similar meanings. For a long time, biologists thought that these synonyms, called synonymous codons, were in fact interchangeable. Recently, they have realized that this is not the case and that differences in synonymous codon usage have a significant impact on cellular processes,, http://www.sciencedaily.com/releases/2013/02/130217134246.htm
Also of interest to wd400's claim is this:
Proteins with cruise control provide new perspective: Excerpt: “A mathematical analysis of the experiments showed that the proteins themselves acted to correct any imbalance imposed on them through artificial mutations and restored the chain to working order.” http://www.princeton.edu/main/news/archive/S22/60/95O56/
Thus, in contrast to the reductive materialism (central dogma) that undergirds Darwinian thought, it is found that mutations are secondary to the overall structure of a protein. Moreover, that an entire protein would be involved in maintaining the primary shape of a protein is evidence that information must be shared along the entirety of the protein structure so that it can maintain its basic functional shape despite deleterious mutations. And when we look close at proteins, we find that quantum information/entanglement is indeed shared along the entirety of the protein structure:
Coherent Intrachain energy migration at room temperature - Elisabetta Collini and Gregory Scholes - University of Toronto - Science, 323, (2009), pp. 369-73 Excerpt: The authors conducted an experiment to observe quantum coherence dynamics in relation to energy transfer. The experiment, conducted at room temperature, examined chain conformations, such as those found in the proteins of living cells. Neighbouring molecules along the backbone of a protein chain were seen to have coherent energy transfer. Where this happens quantum decoherence (the underlying tendency to loss of coherence due to interaction with the environment) is able to be resisted, and the evolution of the system remains entangled as a single quantum state. http://www.scimednet.org/quantum-coherence-living-cells-and-protein/
Quantum information performing Quantum computation in proteins, would go a long ways towards explaining the protein folding enigma:
Physicists Discover Quantum Law of Protein Folding – February 22, 2011 Quantum mechanics finally explains why protein folding depends on temperature in such a strange way. Excerpt: First, a little background on protein folding. Proteins are long chains of amino acids that become biologically active only when they fold into specific, highly complex shapes. The puzzle is how proteins do this so quickly when they have so many possible configurations to choose from. To put this in perspective, a relatively small protein of only 100 amino acids can take some 10^100 different configurations. If it tried these shapes at the rate of 100 billion a second, it would take longer than the age of the universe to find the correct one. Just how these molecules do the job in nanoseconds, nobody knows.,,, Their astonishing result is that this quantum transition model fits the folding curves of 15 different proteins and even explains the difference in folding and unfolding rates of the same proteins. That's a significant breakthrough. Luo and Lo's equations amount to the first universal laws of protein folding. That’s the equivalent in biology to something like the thermodynamic laws in physics. http://www.technologyreview.com/view/423087/physicists-discover-quantum-law-of-protein/ Speed Test of Quantum Versus Conventional Computing: Quantum Computer Wins - May 8, 2013 Excerpt: quantum computing is, "in some cases, really, really fast." McGeoch says the calculations the D-Wave excels at involve a specific combinatorial optimization problem, comparable in difficulty to the more famous "travelling salesperson" problem that's been a foundation of theoretical computing for decades.,,, "This type of computer is not intended for surfing the internet, but it does solve this narrow but important type of problem really, really fast," McGeoch says. "There are degrees of what it can do. If you want it to solve the exact problem it's built to solve, at the problem sizes I tested, it's thousands of times faster than anything I'm aware of. If you want it to solve more general problems of that size, I would say it competes -- it does as well as some of the best things I've looked at. At this point it's merely above average but shows a promising scaling trajectory." http://www.sciencedaily.com/releases/2013/05/130508122828.htm
bornagain77
July 11, 2014
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wd400 "(1) there is only one way to get from one phenotype to the next" This, along with your comment on the malaria parasite question, seems to hint at larger considerations then. Too narrow a focus for ultimate conclusions? Thanks again for your answers.willh
July 11, 2014
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Hi willh, I guess the point is that the numbers they caclulate are under some assumptions. Namely, (1) there is only one way to get from one phenotype to the next (2) That path requires two mutations in a single short section of DNA (3) The first mutation is selectively neutral So, they can show there has only been time for a few processes like this in the evolution of humans from our common ancestor with chimps. But it doesn't mean you can't fix multiple mutations in genes (indeed the expectation is that yo will get multiple mutations in genes without selection), or that such such specified pathways are common (indeed - there is good reason to think they don't apply even to the malaria parasite Behe cites)wd400
July 11, 2014
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Don't Mess With ID (Overview of Behe's 'Edge' and Durrett and Schmidt's paper at the 20:00 minute mark) - Paul Giem - video http://www.youtube.com/watch?v=5JeYJ29-I7obornagain77
July 10, 2014
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Here Dr. Behe responds to Durrett and Schmidt's attempted rebuttal" in a 5 part essay: http://behe.uncommondescent.com/2009/03/ summary at the end of part 5 is here: as I show above, when simple mistakes in the application of their model to malaria are corrected, it agrees closely with empirical results reported from the field that I cited. This is very strong support that the central contention of The Edge of Evolution is correct: that it is an extremely difficult evolutionary task for multiple required mutations to occur through Darwinian means, especially if one of the mutations is deleterious. And, as I argue in the book, reasonable application of this point to the protein machinery of the cell makes it very unlikely that life developed through a Darwinian mechanism. http://behe.uncommondescent.com/2009/03/waiting-longer-for-two-mutations-part-5/bornagain77
July 10, 2014
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wd400 Much appreciate your considered response; thankyou for answering directly. As you may have concluded from my limited contributions, I favour the 'other' explanation in the relevant discussions; but do wish to understand clearly what each is saying. If I may, given your second point: "Evolutionary pathways requiring more than one mutation are unreachable". Perhaps unreachable would have to be assessed over the aggregate? Even if you discount the conclusions wrought in "Edge of Evolution", and Behe's criticism of Durret and Schmidt's paper, is not the time factor that Durret and Schmidt proposed suggesting a much bigger dimension across the board for Darwinian evolutions current dating of the fossil record? Or do you see problems With Durret and Schmidts conclusions perhaps?willh
July 10, 2014
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Well that certainly didn’t help. How about if just try to help evolution out a little and saturate entire genomes with mutations until we can finally see some ‘evolution’ in action?
Response to John Wise – October 2010 Excerpt: A technique called “saturation mutagenesis”1,2 has been used to produce every possible developmental mutation in fruit flies (Drosophila melanogaster),3,4,5 roundworms (Caenorhabditis elegans),6,7 and zebrafish (Danio rerio),8,9,10 and the same technique is now being applied to mice (Mus musculus).11,12 None of the evidence from these and numerous other studies of developmental mutations supports the neo-Darwinian dogma that DNA mutations can lead to new organs or body plans–because none of the observed developmental mutations benefit the organism. http://www.evolutionnews.org/2010/10/response_to_john_wise038811.html
Shoot that doesn’t seem to be helping either! Perhaps we just have to give the almighty power of neo-Darwinism a little ‘room to breathe’ so as to work its magic? How about we ‘open the floodgates’ to the almighty power of Darwinian Evolution and look at Lenski’s Long Term Evolution Experiment and see what we can find after 50,000 generations, which is equivalent to somewhere around 1,000,000 years of human evolution???
Richard Lenski’s Long-Term Evolution Experiments with E. coli and the Origin of New Biological Information – September 2011 Excerpt: The results of future work aside, so far, during the course of the longest, most open-ended, and most extensive laboratory investigation of bacterial evolution, a number of adaptive mutations have been identified that endow the bacterial strain with greater fitness compared to that of the ancestral strain in the particular growth medium. The goal of Lenski’s research was not to analyze adaptive mutations in terms of gain or loss of function, as is the focus here, but rather to address other longstanding evolutionary questions. Nonetheless, all of the mutations identified to date can readily be classified as either modification-of-function or loss-of-FCT. (Michael J. Behe, “Experimental Evolution, Loss-of-Function Mutations and ‘The First Rule of Adaptive Evolution’,” Quarterly Review of Biology, Vol. 85(4) (December, 2010).) http://www.evolutionnews.org/2011/09/richard_lenskis_long_term_evol051051.html Lenski's Long-Term Evolution Experiment: 25 Years and Counting - Michael Behe - November 21, 2013 Excerpt: Twenty-five years later the culture -- a cumulative total of trillions of cells -- has been going for an astounding 58,000 generations and counting. As the article points out, that's equivalent to a million years in the lineage of a large animal such as humans. Combined with an ability to track down the exact identities of bacterial mutations at the DNA level, that makes Lenski's project the best, most detailed source of information on evolutionary processes available anywhere,,, ,,,for proponents of intelligent design the bottom line is that the great majority of even beneficial mutations have turned out to be due to the breaking, degrading, or minor tweaking of pre-existing genes or regulatory regions (Behe 2010). There have been no mutations or series of mutations identified that appear to be on their way to constructing elegant new molecular machinery of the kind that fills every cell. For example, the genes making the bacterial flagellum are consistently turned off by a beneficial mutation (apparently it saves cells energy used in constructing flagella). The suite of genes used to make the sugar ribose is the uniform target of a destructive mutation, which somehow helps the bacterium grow more quickly in the laboratory. Degrading a host of other genes leads to beneficial effects, too.,,, - http://www.evolutionnews.org/2013/11/richard_lenskis079401.html
Now that just can’t be right!! Man we should really start to be seeing some neo-Darwinian fireworks by 50,000 generations!?! Hey I know what we can do! How about we see what happened when the ‘top five’ mutations from Lenski’s experiment were combined??? Surely now the Darwinian magic will start flowing now???!!!
Mutations : when benefits level off – June 2011 – (Lenski’s e-coli after 50,000 generations) Excerpt: After having identified the first five beneficial mutations combined successively and spontaneously in the bacterial population, the scientists generated, from the ancestral bacterial strain, 32 mutant strains exhibiting all of the possible combinations of each of these five mutations. They then noted that the benefit linked to the simultaneous presence of five mutations was less than the sum of the individual benefits conferred by each mutation individually. http://www2.cnrs.fr/en/1867.htm?theme1=7
Now something is going terribly wrong here!!! Tell you what, let’s just forget trying to observe evolution in the lab, I mean it really is kind of cramped in the lab you know, and now let’s REALLY open the floodgates and let’s see what the almighty power of neo-Darwinian evolution can do with the ENTIRE WORLD at its disposal??? Surely now almighty neo-Darwinian evolution will flex its awesomely powerful muscles and forever make those IDiots, who believe in Intelligent Design, cower in terror!!!
A review of The Edge of Evolution: The Search for the Limits of Darwinism The numbers of Plasmodium and HIV in the last 50 years greatly exceeds the total number of mammals since their supposed evolutionary origin (several hundred million years ago), yet little has been achieved by evolution. This suggests that mammals could have “invented” little in their time frame. Behe: ‘Our experience with HIV gives good reason to think that Darwinism doesn’t do much—even with billions of years and all the cells in that world at its disposal’ (p. 155). http://creation.com/review-michael-behe-edge-of-evolution "The immediate, most important implication is that complexes with more than two different binding sites-ones that require three or more proteins-are beyond the edge of evolution, past what is biologically reasonable to expect Darwinian evolution to have accomplished in all of life in all of the billion-year history of the world. The reasoning is straightforward. The odds of getting two independent things right are the multiple of the odds of getting each right by itself. So, other things being equal, the likelihood of developing two binding sites in a protein complex would be the square of the probability for getting one: a double CCC, 10^20 times 10^20, which is 10^40. There have likely been fewer than 10^40 cells in the world in the last 4 billion years, so the odds are against a single event of this variety in the history of life. It is biologically unreasonable." - Michael Behe - The Edge of Evolution - page 146 Michael Behe, The Edge of Evolution, pg. 162 Swine Flu, Viruses, and the Edge of Evolution “Indeed, the work on malaria and AIDS demonstrates that after all possible unintelligent processes in the cell–both ones we’ve discovered so far and ones we haven’t–at best extremely limited benefit, since no such process was able to do much of anything. It’s critical to notice that no artificial limitations were placed on the kinds of mutations or processes the microorganisms could undergo in nature. Nothing–neither point mutation, deletion, insertion, gene duplication, transposition, genome duplication, self-organization nor any other process yet undiscovered–was of much use.” http://www.evolutionnews.org/2009/05/swine_flu_viruses_and_the_edge020071.html
Now, there is something terribly wrong here! After looking high and low and everywhere in between, we can’t seem to find the almighty power of neo-Darwinism anywhere!! Shoot we can’t even find ANY power of neo-Darwinism whatsoever!!! It is as if the whole neo-Darwinian theory, relentlessly sold to the general public as it was the gospel truth, is nothing but a big fat lie!!!bornagain77
July 10, 2014
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Contrary to what wd400 'professes' to believe, (I have a hard time thinking he ACTUALLY believes it), In science, experimental evidence trumps models/theories all the time. Models/Theories do not trump empirical evidence. It is simply insane to insist that a model is impervious to empirical falsification. To repeat:
The Scientific Method – Richard Feynman – video Quote: ‘If it disagrees with experiment, it’s wrong. In that simple statement is the key to science. It doesn’t make any difference how beautiful your guess is, it doesn’t matter how smart you are who made the guess, or what his name is… If it disagrees with experiment, it’s wrong. That’s all there is to it.” https://www.youtube.com/watch?v=OL6-x0modwY
But I can see where someone such as wd400, who earns his bread and butter as a professional evolutionist, would want to switch the evidential priority completely around for Darwinism,,,, Darwinism, Neo-Darwinism in particular, simply has no empirical support in which to verify its grand claims.
“On the other hand, I disagree that Darwin’s theory is as `solid as any explanation in science.; Disagree? I regard the claim as preposterous. Quantum electrodynamics is accurate to thirteen or so decimal places; so, too, general relativity. A leaf trembling in the wrong way would suffice to shatter either theory. What can Darwinian theory offer in comparison?” (Berlinski, D., “A Scientific Scandal?: David Berlinski & Critics,” Commentary, July 8, 2003) Lynn Margulis Criticizes Neo-Darwinism in Discover Magazine (Updated) - Casey Luskin April 12, 2011 Excerpt: Population geneticist Richard Lewontin gave a talk here at UMass Amherst about six years ago, and he mathemetized all of it--changes in the population, random mutation, sexual selection, cost and benefit. At the end of his talk he said, "You know, we've tried to test these ideas in the field and the lab, and there are really no measurements that match the quantities I've told you about." This just appalled me. So I said, "Richard Lewontin, you are a great lecturer to have the courage to say it's gotten you nowhere. But then why do you continue to do this work?" And he looked around and said, "It's the only thing I know how to do, and if I don't do it I won't get grant money." - Lynn Margulis - biologist http://www.evolutionnews.org/2011/04/lynn_margulis_criticizes_neo-d045691.html
Further notes as to the sheer poverty of evidence for Darwinism:
Multiple Overlapping Genetic Codes Profoundly Reduce the Probability of Beneficial Mutation George Montañez 1, Robert J. Marks II 2, Jorge Fernandez 3 and John C. Sanford 4 - May 2013 Excerpt: It is almost universally acknowledged that beneficial mutations are rare compared to deleterious mutations [1–10].,, It appears that beneficial mutations may be too rare to actually allow the accurate measurement of how rare they are [11]. 1. Kibota T, Lynch M (1996) Estimate of the genomic mutation rate deleterious to overall fitness in E. coli . Nature 381:694–696. 2. Charlesworth B, Charlesworth D (1998) Some evolutionary consequences of deleterious mutations. Genetica 103: 3–19. 3. Elena S, et al (1998) Distribution of fitness effects caused by random insertion mutations in Escherichia coli. Genetica 102/103: 349–358. 4. Gerrish P, Lenski R N (1998) The fate of competing beneficial mutations in an asexual population. Genetica 102/103:127–144. 5. Crow J (2000) The origins, patterns, and implications of human spontaneous mutation. Nature Reviews 1:40–47. 6. Bataillon T (2000) Estimation of spontaneous genome-wide mutation rate parameters: whither beneficial mutations? Heredity 84:497–501. 7. Imhof M, Schlotterer C (2001) Fitness effects of advantageous mutations in evolving Escherichia coli populations. Proc Natl Acad Sci USA 98:1113–1117. 8. Orr H (2003) The distribution of fitness effects among beneficial mutations. Genetics 163: 1519–1526. 9. Keightley P, Lynch M (2003) Toward a realistic model of mutations affecting fitness. Evolution 57:683–685. 10. Barrett R, et al (2006) The distribution of beneficial mutation effects under strong selection. Genetics 174:2071–2079. 11. Bataillon T (2000) Estimation of spontaneous genome-wide mutation rate parameters: whither beneficial mutations? Heredity 84:497–501. http://www.worldscientific.com/doi/pdf/10.1142/9789814508728_0006 “The First Rule of Adaptive Evolution”: Break or blunt any functional coded element whose loss would yield a net fitness gain – Michael Behe – December 2010 Excerpt: In its most recent issue The Quarterly Review of Biology has published a review by myself of laboratory evolution experiments of microbes going back four decades.,,, The gist of the paper is that so far the overwhelming number of adaptive (that is, helpful) mutations seen in laboratory evolution experiments are either loss or modification of function. Of course we had already known that the great majority of mutations that have a visible effect on an organism are deleterious. Now, surprisingly, it seems that even the great majority of helpful mutations degrade the genome to a greater or lesser extent.,,, I dub it “The First Rule of Adaptive Evolution”: Break or blunt any functional coded element whose loss would yield a net fitness gain. http://behe.uncommondescent.com/2010/12/the-first-rule-of-adaptive-evolution/
Michael Behe talks about the devastating implications for Darwinism highlighted by the preceding paper in this following podcast:
Michael Behe: Challenging Darwin, One Peer-Reviewed Paper at a Time – December 2010 http://intelligentdesign.podomatic.com/player/web/2010-12-23T11_53_46-08_00
How about the oft cited example for neo-Darwinism of antibiotic resistance?
List Of Degraded Molecular Abilities Of Antibiotic Resistant Bacteria: Excerpt: Resistance to antibiotics and other antimicrobials is often claimed to be a clear demonstration of “evolution in a Petri dish.” ,,, all known examples of antibiotic resistance via mutation are inconsistent with the genetic requirements of evolution. These mutations result in the loss of pre-existing cellular systems/activities, such as porins and other transport systems, regulatory systems, enzyme activity, and protein binding. http://www.trueorigin.org/bacteria01.asp
That doesn't seem to be helping! How about we look really, really, close at very sensitive growth rates and see if we can catch almighty evolution in action???
Unexpectedly small effects of mutations in bacteria bring new perspectives – November 2010 Excerpt: Most mutations in the genes of the Salmonella bacterium have a surprisingly small negative impact on bacterial fitness. And this is the case regardless whether they lead to changes in the bacterial proteins or not.,,, using extremely sensitive growth measurements, doctoral candidate Peter Lind showed that most mutations reduced the rate of growth of bacteria by only 0.500 percent. No mutations completely disabled the function of the proteins, and very few had no impact at all. Even more surprising was the fact that mutations that do not change the protein sequence had negative effects similar to those of mutations that led to substitution of amino acids. A possible explanation is that most mutations may have their negative effect by altering mRNA structure, not proteins, as is commonly assumed. http://www.physorg.com/news/2010-11-unexpectedly-small-effects-mutations-bacteria.html
Shoot that doesn’t seem to be helping either! How about if we just try to fix a ‘beneficial’ mutation in a multi-cellular creature:
Experimental Evolution in Fruit Flies (35 years of trying to force fruit flies to evolve in the laboratory fails, spectacularly) – October 2010 Excerpt: “Despite decades of sustained selection in relatively small, sexually reproducing laboratory populations, selection did not lead to the fixation of newly arising unconditionally advantageous alleles.,,, “This research really upends the dominant paradigm about how species evolve,” said ecology and evolutionary biology professor Anthony Long, the primary investigator. http://www.arn.org/blogs/index.php/literature/2010/10/07/experimental_evolution_in_fruit_flies
bornagain77
July 10, 2014
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(and now I see D&S summarized these mis-readings themeseves rather better than I did above: http://www.genetics.org/content/181/2/821.full)wd400
July 10, 2014
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Hi Willh, The most common mistakes people make with D&S relate to skipping over the assumption in the model and concluding * It would take prohibitively long time for two mutations to fix in the same gene at all * Evolutionary pathways requiring more than one mutation are unreachable * Evolutionary pathways requiring more than one mutation are unreachable when the first mutation is selectively neutral * Because some pre-defined evolutionary events would take a long time to occur in pre-defined gene that won't happen at all in the genome BA's quotes show another sort of confusion -- the idea that Behe's calculation doesn't have a model of popgen underlying it. In fact, as is often the case when people make these claims, there is an implicit popgen model in Behe's claim. Have a formal model rather than the implicit one Behe worked from is an advanatge, as a pretty great statistician ones say “The great advantage of the model-based over the ad hoc approach, it seems to me, is that at any given time we know what we are doing.”wd400
July 10, 2014
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podcast - Michael Behe: The Limit in the Evolution of Proteins (Thorton 2014 paper) http://intelligentdesign.podomatic.com/entry/2014-07-09T16_35_28-07_00bornagain77
July 10, 2014
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So they seem to dismiss the idea that it is tissue restriction, yet much of what these databases and papers they cite, have come from analysis of cultured cells that are immortalised. This is not representative at all. Cells that are in 2-d growth, immortalised, in DMEM or RPMI supplemented with fetal calf serum, antibiotics and l-glutamine have very different characteristics and look very different to real, normal primary cells. From what I can see, most of the data they have taken comes from cell lines that will have been treated in this way... What the paper seems to suggest to me, is that when you look at the common datasets that the most conserved proteins generate the most reliable data and are most commonly found. That is not a surprise. We also know that it is NOT simply tissue expression where differential gene expression occurs – it is also environmental stresses. This has recently been shown with many 100s-1000s of new genes identified in Drosophila due to various stresses, such as alcohol, temperature, etc, etc. This analysis is very much unlikely to be able to even start to address this question.
As far as I understand, the idea would be that we are finding more ancient, conserved genes with protein features because these are the proteins that tend to be expressed by the cancer cell cultures that are used for proteomics experiments? I don’t believe that at all. First of all, I would have thought that it was equally likely that non-biological conditions that the immortalised cells were in would have lead cell cultures to express a range of unusual proteins. Is there any data at all that shows that immortalised cells cease to produce any proteins other than housekeeping proteins? Second, the data comes from a wide-range of sources. While the large-scale experiments from the Matthias Mann groups do fit this profile, the CNIO, PeptideAtlas and NIST analyses come from a huge range of different experiments. Third there is little reliable evidence that carrying out tissue-based experiments expands the number of identified genes by much. See the HPP paper by Lane in JPR this year (ref 25). Clearly there have been two recent very high profile papers based on experiments on multiple tissues that have made incredible claims for the number of genes they have identified, but in these experiments it definitely wasn’t the number of tissues used that inflated the gene numbers. Probably varying the digestion enzymes would be the most efficient form of detecting new proteins. Ultimately the identification (or not) of a gene in the proteomics analyses is a bit of a red herring. The proteomics evidence can only be used as a means of positive identification. It can’t be used to confirm non-expression. There are approximately 8,500 genes that we don’t find peptides for and the majority of these genes will be either multiple trans-membrane helix proteins, have short half-lives or are expressed in certain tissues or certain cellular conditions. If you look at each gene it is usually quite clear which category it fits into, but 8,500 are rather a lot to investigate one by one. The annotation of the human genome is in constant flux, and although much work has been done by human annotators, they are still working based on the initial automatic annotation from 10 years ago. There are still many loci defined as protein coding genes in the Ensembl database that were put there by automatic prediction programs that have no basis for being there, and that will almost certainly be removed over the next couple of years. So, tissue restriction will be PART of the reason that we don’t find evidence for the 6,500 genes that we believe are likely to be protein coding genes), but will play little role for the 2,001 genes in the potential non-coding set, many of which we believe will not code for proteins under any circumstances. In any case, it is not us who have the final say in this, it will be the genome annotators in GENCODE and Ensembl.Starbuck
July 10, 2014
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"The difficulty with models such as Durrett and Schmidt’s is that their biological relevance is often uncertain, and unknown factors that are quite important to cellular evolution may be unintentionally left out of the model. That is why experimental or observational data on the evolution of microbes such as P. falciparum are invaluable,,," - Behe http://www.discovery.org/a/9461bornagain77
July 10, 2014
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As to wd400's claim that,,, "you just don't understand Durret and Schmidt" :) ,,it is interesting to note Dr. Behe's gripe about Durret and Schmidt's mathematical model:
Waiting Longer for Two Mutations - Michael J. Behe Excerpt: Citing malaria literature sources (White 2004) I had noted that the de novo appearance of chloroquine resistance in Plasmodium falciparum was an event of probability of 1 in 10^20. I then wrote that 'for humans to achieve a mutation like this by chance, we would have to wait 100 million times 10 million years' (1 quadrillion years)(Behe 2007) (because that is the extrapolated time that it would take to produce 10^20 humans). Durrett and Schmidt (2008, p. 1507) retort that my number ‘is 5 million times larger than the calculation we have just given’ using their model (which nonetheless "using their model" gives a prohibitively long waiting time of 216 million years). Their criticism compares apples to oranges. My figure of 10^20 is an empirical statistic from the literature; it is not, as their calculation is, a theoretical estimate from a population genetics model. http://www.discovery.org/a/9461
I agree with Dr. Behe's gripe against their Durret and Schmidt's mathematical model:
The Scientific Method - Richard Feynman - video Quote: 'If it disagrees with experiment, it’s wrong. In that simple statement is the key to science. It doesn’t make any difference how beautiful your guess is, it doesn’t matter how smart you are who made the guess, or what his name is… If it disagrees with experiment, it’s wrong. That’s all there is to it.” https://www.youtube.com/watch?v=OL6-x0modwY
bornagain77
July 9, 2014
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w400: "It usually comes from Behe’s mistakes or a misreading of Durret and Schmidt" If you can, briefly what is the misreading of Durret and Schmidt?willh
July 9, 2014
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Therefore, evolution has to act out on much more than simply bringing about a new gene randomly, it has to do so in an appropriate spatiotemporal positioning that is tightly regulated in different tissue types in response to different other cellular cues.
Dr JDD, if the differences between closely related species are 'just' the variations, regulations and timings of existing genes, then the empirical measure of ID (500 bits of specified information, a.k.a new genes) may represent only a fraction of detectable ID events. Have you given this any thought, and if so, what other empirical methods might be used?rhampton7
July 9, 2014
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I forgot to reply to this comment
(why do you think they estimated originally over 100,000 genes in humans prior to the human genome project?
This is one of those fact-like ideas that get's cicrulated but isn't quite true. The human genome project itself estimated 100,000, but this wasn't the consensus view of biologists. Most molecular biologists predicted fewer (the mean of the Enseble sweepstake was about 60,000), evolutionary biologists did even better (Ohno predicted 30,000 genes in 1972, King & Jukes and Crow also made similar predictions)wd400
July 9, 2014
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I don't recognise the argument you present in the start of your comment, so wont' defend it. All I've said is that people who have made a great deal out of the supposedly high number of ORFan genes should consider the evidence that many of them don't make proteins. For those that don't, there is not particular reason to think they are genes at all (they are annotated due to their genomic sequence or presence in transcripts, but there is no reason to think everything that is transcribed is functional), and good reason to think a lot of transcribed sequences aren't. The "it's all very complex so evolution didn't do it" refrain is very common, but I don't really understand it. All the classes of sequence you mention are genes (or are controlled by gene products). It's going to take a long time to understand all the details, and extract the signal from the noise, but the idea (in your own words) protein coding genes by themselves were a "holy grail" for evolutionary biology and functional RNAs make it all wrong is very strange. Finally, it's certainly true that "2 coordinated amino acid changes" is a shiboleth that reveals speaker has a shaky understanding of evolutionary biology. It usually comes from Behe's mistakes or a misreading of Durret and Schmidt - though you don't provide enough details in this case to make clear what you are driving at.wd400
July 9, 2014
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Reproducibility. Proteomics experiments conducted in one laboratory are not easily reproduced in another. For instance, Peng et al.[12] have identified 1504 yeast proteins in a proteomics experiment of which only 858 were found in a similar previous study.[13] Further, the previous study identified 607 proteins that were not found by Peng et al. This translates to a reproducibility of 57% (Peng vs. Washburn) to 59% (Washburn vs. Peng). http://en.wikipedia.org/wiki/Proteomics
Moral of the story: It is premature to say there are only 19,000 proteins.scordova
July 9, 2014
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BA77 I'm used to that response as I am sure you are however I actually don't understand evolution, just not in the same way that evolutionists use that term! ID is full of people who don't understand evolution - we don't understand how 19,000 functional proteins could randomly be generated through blind chance given that we know what probability it takes just 2 coordinated amino acid changes to make!!!Dr JDD
July 9, 2014
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Dr JDD, nice overview of the overall state of evidence, and to save wd400 the inevitable comeback,,, 'You just don't understand evolution' :)bornagain77
July 9, 2014
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Dopey, speculative paper just rehashing existing databases of known experimental results with their own spin. They only made their inferences on what proteins have been detected. It's like those folks who said no black swans existed because they haven't seen any! There are in the range of 1 to 10 billion physical protein instances in a human cell and 200 trillion adult cells and even more from all stages of development. If some proteins classes are rare, they could easily escape detection. Not to mention, there are proteins specific to stages of the cell cycle! From http://www.mcponline.org/content/3/1/1.full
No structural or sequence inferences can be based on the failure to observe a specific peptide; such a peptide may arise from proteolysis but simply not be detected, it may have an unexpected mass due to one or more modifications, or the residues may indeed be present in the sequence but the proteolysis may not proceed as anticipated. It is equally important to note that the absence of evidence for the presence of a particular protein does not definitively establish the absence of the protein.
Why wasn't this paper published in a Proteomics journal? Instead it was in a genetics journal, and it wasn't new experimental data, just spin of known databases. One could have just as easily said, "the absences of detection indicates we need for improved detection methods." But noooooo, they just make a grand pronouncement that there are fewer and fewer proteins in human development cycle because we haven't yet found them.scordova
July 9, 2014
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Of course I accept many of the apparent ORFan genes may not produce proteins but I am also saying this study is not sufficient evidence to suggest ORFans aren't a thing as was your original implication. In fact, let's play your game you are playing here. 1) IDists harp on about ORFan genes as evidence for ID etc 2) This paper shows virtually no/very low evidence of ORFan genes giving protein products 3) Therefore, IDists are wrong in using ORFan genes as support of ID So here is my turn: 1) Evolutionists harp on about pseudogenes being remnants of dead genes, byproducts of wasteful evolution 2) The paper I cite above (last one) finds 12 genes annotated on Chr12 as being pseudogenes actually are real genes giving protein products 3) Therefore, evolutionists are wrong to use Pseudogenes as a support of evolution Now the same arguments will ensue from you why this is not valid - "its only 12 genes" and I say "well it is a MS peptide approach which has sensitivity issues and it also found 10% of genes not previously identified as proteins" blah blah blah. The point is, there may well be ORFans that do not express protein products. But again, the point is do they need to be? Maybe they are regulatory RNAs or other functional sequences. The other point is maybe many pseudogenes are duplicated genes or broken genes. So? Does that refute ID? No, of course not. Neither of these papers in themselves refute or prove one view or the other. That is the point I am making. In summary: - There ARE ORFan genes that are translated to give protein products - There MAY be ORFan genes that are not translated to give proteins - There ARE pseudogenes that are actually functional translatable genes - There MAY WELL be pseudogenes which are broken genes with little/no function These papers do not prove either view nor disprove the other. Which is why I say it is interesting, but the mathematical probability behind all of this information is the real question, ORFan or no ORFan, pseudogene or no pseudogene. Finally, of course people have been saying for many years that regulation may make the difference, but my point is we are now more certain than ever (why do you think they estimated originally over 100,000 genes in humans prior to the human genome project?) that it is more about spatiotemperal regulation. And my extension about that point is the regulation is a lot more complex than thought of in 1975 which would have been more focused on other proteins such as transcription faactors as they did not have knowledge of the plethora of regulatory molecules and processes now known in the genome such as siRNA, modification of DNA and histones/epigenetic control (e.g. methylation), lncRNA, lincRNA, and the many more regulatory molecules involved in the genome that we are just scratching the surface of. A lot of these things have only come to light in the last few years and they require a further layer of complexity for random generation through naturalistic processes which is not straight forward as those involved with simply generating a novel protein.Dr JDD
July 9, 2014
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Re the study, Of course proteomic studies have less power than genomic ones at present, an it's likely that there are at least some human-specific protein coding genes. It reamins the case, however, that anyone trying to make something from "ORFans" has to deal with the fact many of the apparent-ORFan genes may in fact not produce proteins (and analyses beyond the proteomic ones support this). I don't know what to make of the claim
[the genetic] code is what is the supposed holy grail for evolution to do its work on
Care to offer a citation for this view? Somewhere in all that link spam BA mentioned King and Wilson who made the point much of the evolutionary difference between human and chimp would be explained by gene regulation and that was 1975! Same goes for this
Evolutionists have always focused on the evolution of proteins through mutation in the DNA to give new amino acid changes and new protein functions. However it seems that this is not a shrinking problem for them as there is a whole other random mutation “space” for evolution to account for and that is the plethora of regulatory molecules that are quite different to the simple DNA–>RNA–>protein central dogma.
wd400
July 9, 2014
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OT: here is a look at that recent ribosome paper: Imagine How It Happened! "Evolution Presents" the Ribosome, "Nature's Masterpiece" - July 9, 2014 Excerpt: There are even more reasons to reject the evolutionary hypothesis in the PNAS paper on which the film was based. The authors provide no evidence that the "common core" (Phase 1 in the film) of the large ribosomal subunit (LSU) was able to do anything on its own. There is a small ribosomal subunit (SSU) that has to match it. Even more important, a ribosome is useless without a genome! How do they handle that? "In our model, the LSU has evolved in distinct phases," the paper speculates. "This process started with the formation of the P site, possibly in an RNA world, and continues today in eukaryotes." So they lean on the RNA world scenario, which we have shown many times is untenable. This is recognized even by evolutionists, such as Niles Lehman, whom Casey Luskin quoted as saying, "The odds of suddenly having a self-replicating RNA pop out of a prebiotic soup are vanishingly low." This stops the tale before it even starts. The authors try to make the "common core" look small and simple, but the LSU of the simplest bacterium contains on the order of 3,000 nucleotides. The small rRNA subunit (SSU) contains another 1,500 more. These are much larger (and more complex) than anything that origin-of-life researchers could ever hope for in an RNA world. Even more problematic for evolution, both ribosomal subunits for the simplest bacterium contain dozens of protein parts integrated with the RNA parts. But the proteins had to be translated by the very ribosome the evolutionists are trying to explain! It's a profound chicken-and-egg problem that Williams and his co-authors gloss over http://www.evolutionnews.org/2014/07/imagine_how_it2087611.htmlbornagain77
July 9, 2014
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Thanks for the positive comments, and I am glad what I said has made some sense. I should clarify that I am not dismissing the study. However, it has to be seen for what it is: Firstly, the data it used and the limitations of the technology; Secondly, in light of other recent data that demonstrates evidence for peptides from novel proteins and alludes to the fact these are difficult to detect. Again I will say the best data from these studies comes from using primary normal tissue, as opposed to the use of cultured cell lines and even cultured normal primary cells. Much of the public domain data and even publications use such cells and these are very poorly representative of reality (i.e. in vivo). Additionally, we must remember that we need to follow the trail of evidence and we need not to get hung up on one particular strand of an argument. Wd400 raised this issue as a blow perhaps for the ORFan fans. Indeed, it appeared that way and perhaps I have tried to argue that due to the limitations and design of the study, and taking all things into account that this is not a blow for ORFans, at least from my understanding of the study. However what is often failed to be acknowledged in my opinion is that little arguments like ORFans while they can support the increased complexity and variability between species and hence can be argued as support for ID, this is not the crux of the ID argument. It is a small fragment. Like I said in my earlier post at the end, when we step back and look at the big picture, what we see is that in 6-7million years, what man is compared to counterparts that have apparently evolved from chimpanzees (other primates) is quite staggering, in particular to our intelligence, our processing abilities and all other various skills, talents and abilities (complex reasoning, typing out this post…etc). If we generally use the majority of the same proteins – and not just as primates, but also as much more simpler organisms – then we must conclude that the separation of what makes species different is far beyond the genetic code. That code is what is the supposed holy grail for evolution to do its work on. That code provides evolution the mechanism of simple random mutation can lead to a selected benefit and over time new function can occur. Yet the biggest differences are likely to not be simply presence of a gene or not, but more likely timing, regulation, and other events we have not yet encountered or fully described/understood. Therefore, evolution has to act out on much more than simply bringing about a new gene randomly, it has to do so in an appropriate spatiotemporal positioning that is tightly regulated in different tissue types in response to different other cellular cues. Then when we consider the real crux of the evolution vs ID argument, which is the mathematical modelling and how the sequence search space for random mutations to generate functionality (apart from any regulation of such a gene in timing and amounts and turn-over), we are only adding to that problem as we have a whole host of regulatory molecules and events to randomly produce, alongside our randomly produced novel genes/proteins in parallel to allow proper functionality. This is where evolution is perceived by us in the ID camp as incredibly falling short of the mark and that does not in any way hinge upon whether ORFans are real or not. This is why I am pleased to see an article like this posted here on UCD. It allows us to examine our own understanding of the arguments used for and against, and follow what the evidence seems to be saying. I don’t want to use a very poor argument for ID just for the sake of supporting ID as then I am no better than the evolutionist that when confronted with a complex, incredible mechanism simply says, “Evolution is amazing, look at what it has done!” which is not really a valid explanation if the process truly is naturalistic. In this case however, I quite strongly believe that this publication does not supply sufficient evidence to question the presence of ORFan proteins or similar issues that it apparently may raise.Dr JDD
July 9, 2014
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Dr JDD: Very good work! Thank you.gpuccio
July 8, 2014
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Thanks for the detailed analysis, Dr JDD.JoeCoder
July 8, 2014
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PaV (13) I suppose you’re trying to say that the lineage-specific sequences (ORFans) found in humans is “non-coding.” But this is exactly as IDists would have predicted. How is this predicted by ID? It would appear to me that ORFans that produce genes playing a critical role would produce a much better case for ID.Moose Dr
July 8, 2014
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