Once upon a time, I was one of those nerds who hung around Radio Shack and played about with LEDs and resistors and capacitors; I know how to solder and I took my first old 8-bit computer apart and put it back together again with “improvements.” In grad school I was in a neuroscience department, so I know about electrodes and ground wires and FETs and amplifiers and stimulators. Here’s something else I know: those generic components in this picture don’t do much on their own. You can work out the electrical properties of each piece, but a radio or computer or stereo is much, much more than a catalog of components or a parts list.
Electronics geeks know the really fun stuff starts to happen when you assemble those components into circuits. That’s where the significant work lies and where the actual function of the device is generated—take apart your computer, your PDA, your cell phone, your digital camera and you’ll see similar elements everywhere, and the same familiar components you can find in your Mouser catalog. As miniaturization progresses, of course, more and more of that functionality is hidden away in tiny integrated circuits…but peel away the black plastic of those chips, and you again find resistors and transistors and capacitors all strung together in specific arrangements to generate specific functions.
We’re discovering the same thing about genomes.
The various genome projects have basically produced for us a complete parts list—a catalog of bits in our toolbox. That list is incredibly useful, of course, and represents an essential starting point, but how a genome produces an organism is actually a product of the interactions between genes and gene products and the cytoplasm and environment, and what we need next is an understanding of the circuitry: how Gene X expression is connected to Gene Y expression and what the two together do to Gene Z. Some scientists are suggesting that an understanding of the circuitry of the genome is going to explain some significant evolutionary phenomena, such as the Cambrian explosion and the conservation of core genetic processes.
First, though, a little caveat. As in my introduction above, Davidson and Erwin use the language of electronic circuitry to explain what they are seeing. Metaphors are very dangerous things, and I have a feeling that they are pushing the metaphor a little too hard, at the risk of obscuring substantial differences between fluid gene interactions in a cytoplasm and a layout of wires and widgets on a circuit board. Metaphors are also powerful communication tools, an effective way to get an idea across, so I’m indulging in it here…just be warned, at some point we’ve also got to leave this metaphor behind and treat the epigenetic activity of the cell on its own terms. Just not today.
The idea of genetic circuitry refers to interactions between genes: how genes communicate with one another to turn on one pattern of gene expression in one cell, and turn on a different pattern in a different cell. For instance, while you want the keratin gene turned on in your skin cells (it makes the tough fibrous protein that makes our skin both supple and leathery), you probably want that gene inactivated in your red blood cells. The way this is done involves transcription factors and cis regulatory regions. The diagram below will help explain what these are.
There are certain kinds of genes in the genome that are, like other genes, transcribed into messenger RNA and translated into proteins, like gene X above, and their protein products are called transcription factors. Transcription factors are proteins that enter the nucleus of the cell and bind to DNA at specific sites—they typically recognize certain short sequences of DNA, for example, GCGTGGGCG. In the diagram, gene X produces a transcription factor, the red ball, that can bind to sequences near the genes A, B, C, D, and E, within the cis regulatory regions of those cells. The cis regulatory regions are simply sequences that aren’t actually part of the coding region of the gene, but are near it on the same strand of DNA (that’s what the “cis” part means), and control (the “regulatory” part) whether the transcriptional machinery of the cell will make messenger RNA copies of the gene. Gene X in this case is responsible for activating expression of genes A, B, C, and E, and turning off gene D.
The logic of regulating genes can get very tangled. Gene X will also have a cis regulatory region which is sensitive to the presence of other transcription factors, so its expression is also controlled. Some of its targets may also be transcription factors; gene C, for instance, could also code for a transcription factor, which could affect the expression of genes F, G, H, and I. Cis regulatory regions are rarely as simple as portrayed here, with one factor binding to them and simply controlling whether it is off or on—there will be many potential binding sites for many different transcription factors, and they will interact in complex and dosage dependent ways. Gene C might actually be turned on only if transcription factor X and transcription factor Y are present, or if transcription factor X or transcription factor Y are present, or if transcription factor X and transcription factor Y but not transcription factor Z are present. The interactions are typically wonderfully intricate examples of the same kind of Boolean logic you will find in computer programs and chip designs (I recommend the book Endless Forms Most Beautiful (amzn/b&n/abe/pwll) if you find this subject interesting—it has an excellent section introducing the basic ideas of regulatory logic.)
Much of molecular genetics is involved in teasing apart these patterns of interactions between genes. It’s not information you can simply extract from the gene sequence, but instead requires careful observation and painstaking experiments, examining patterns of gene expression over development and in animals with mutations that knock out transcription factors or modify cis regulatory regions. The work ends up with nicely tangled spaghetti diagrams of networks of genes, like the classic one from work on nematode vulva induction to the right, which are suggestive of circuit diagrams. It’s a short jump from there to calling these genetic circuits.
Eric Davidson has been a major figure in studying these kinds of circuits, focusing most of his work on the developing echinoderm. The echinoderm exhibits a pattern of stereotyped divisions in its early development to create a ball of cells, and that ball will eventually turn into the more elaborate larval form, with a gut and external epidermis and simple internal skeleton. In order to do this, different cells have to turn on different sets of genes—some cells have to activate the genetic circuitry to make endomesoderm, the red cells of the diagram at the left, while others have to turn off the endomesoderm circuit. What exactly is the endomesoderm circuit?
In a key part of that one circuit, there are six genes: Delta, Blimp1/Krox, Otx, Bra, Foxa, and Gatae. All except Delta are genes for transcription factors; Delta is part of a signal transduction pathway, that is, it receives signals from the environment and triggers changes in gene activity in the cell. All of the transcription factors have multiple targets, and one thing you can readily see here is that many of their targets are each other: this is a highly recursive network. An incoming signal from Delta triggers a whole mutually synergistic pattern of activity within a whole bank of genes.
Examples of putative GRN kernels. Networks were constructed and portrayed using BioTapestry software. Endomesoderm specification kernel, common to sea urchin and starfish, the last common ancestor of which lived about half a billion years ago. The relevant area of the sea urchin network is shown at the top; the corresponding starfish network is shown at the bottom. Horizontal lines denote cis-regulatory modules responsible for the pregastrular phase of expression considered, in endoderm (yellow), mesoderm (gray), or both endoderm and mesoderm (striped gray and yellow). The inputs into the cis-regulatory modules are denoted by vertical arrows and bars. The gray box surrounding the foxa input indicates that this repression occurs exclusively in mesoderm.
The diagram above illustrates two similar networks, one from sea urchin and one from starfish. There are differences, but most notable is their similarity—and these are two animals that have been separated evolutionarily for over a half billion years. Davidson and Erwin identify the common elements that have been conserved in both circuits, and note that the overall arrangement of elements is nearly identical. They call this kind of conserved circuit (note that what is being assessed is the pattern of interactions in addition to just the similarity in sequence of the genes) a Gene Regulatory Network kernel, or GRN kernel.
The network architecture, which has been exactly conserved since divergence—i.e., the kernel—for the endomesoderm specification kernel.
They identify several GRN kernels. Some of the properties of these kernels are that they are highly recursive and highly conserved—they are core molecular/genetic pathways that set up specific early domains of gene expression. They are conserved because they define basic ontogenetic processes: a mutation that disrupted the circuitry of the endomesoderm kernel, for instance, would mean that the population of cells that make endomesoderm could never be activated, and a whole broad set of tissue derivatives in the embryo would never form. Obviously, mutations can occur—the urchin and starfish circuits have differences—but mutations that perturb the general layout of the circuit are selected against.
Here’s another example of a kernel from Drosophila and a vertebrate. This is one that specifies where the heart will form in an animal; again, it’s function is very basic, but it is conserved because major changes would prevent the heart from forming at all.
Possible heart specification kernels; assembled from many literature sources. Dashed lines show possible interactions. Some aspects of the GRN that may underlie heart specification in Drosophila are shown at the top; the approximately corresponding vertebrate relationships are shown at the bottom. Absence of a linkage simply means that this linkage is not known to exist, not that it is known not to exist. Many regulatory genes participate in vertebrate heart formation for which orthologous Drosophila functions have not been discovered, and the hearts themselves are of very different structure. However, as pointed out by many authors, a core set of regulatory genes are used in common and are now known to be linked in a similar way in a conserved subcircuit of the gene network architecture, as shown.
This is an even more tangled circuit, and is also less well characterized than the endomesoderm pathways, but even so some common patterns fall out of it. The major players, like the fly tinman (tin) gene, have homologs in the vertebrate (Nkx2.5), the circuit is activated by homologous inputs (Dpp/BMP), have similar outputs (recruiting contractile proteins, for instance), and exhibit that familiar recursive topology.
(click for larger image)
The shared linkages of the heart specification pathway for vertebrates and invertebrates. The gray boxes represent in each case different ways that the same two nodes of the network are linked in Drosophila and vertebrates.
There are differences, though, that are highlighted in the grey boxes—the system still evolves. For instance, look at the central grey box showing a linkage from Tin/Nkx2.5 to Pnr/Gata4. In Drosophila, it’s simple: Tin activates Pnr directly. In the vertebrate, Nkx2.5 also activates a new intermediate, Gata6, which activates Gata4. This is clearly a case of gene duplication in a pathway, something I’ve described before.
What does it all mean? Davidson and Erwin propose that there are these highly conserved GRN kernels, which obtain their functionality from the particular linkages between the genes that make them up. It’s those connections that are important and maintained over evolutionary history, even as gene sequences may change and minor elaborations on the linkages may occur, and while the outputs of the circuit (which they call differentiation gene batteries) may be much more labile. GRN kernels are modular circuits associated with elements of the body plan, such as the specification of the heart, determination of the anterior-posterior and dorsal-ventral body axes, eyefield localization, and gut regionalization…and almost certainly many more. The authors predict that there will be a GRN kernel to specify the domain and initial developmental steps for each phylum-specific body part in the embryo. These circuits would have evolved prior to the Cambrian, and represent the formation of new modules that fueled Cambrian diversity but also subsequently imposed developmental constraints that suppressed the evolution of novel body plans thereafter. The price of success in the Cambrian radiation was reliance on a fixed set of proven modules. As the authors put it,
Critically, these kernels would have formed through the same processes of evolution as affect the other components, but once formed and operating to specify particular body parts, they would have become refractory to subsequent change. Molecular phylogeny places this evolutionary stage in the late Neoproterozoic when Bilateria begin to appear in the fossil record (47â51), between the end of the Marinoan glaciation at about 630 million years ago and the beginning of the Cambrian. Therefore the mechanistic explanation for the surprising fact that essentially no major new phylum-level body parts have evolved since the Cambrian may lie in the internal structural and functional properties of GRN kernels: Once they were assembled, they could not be disassembled or basically rewired, only built on to.
One significant thing about this explanation is that it is based solidly on molecular and developmental genetics; since these are fields that have only really taken off in the last 25 or 30 years, it represents a class of explanation that is not represented in classical neo-Darwinian theory. That’s good and novel and expected—trust me, biology has not been sitting still since Fisher and Wright and Simpson and Dobzhansky—but while it represents another example of an ongoing revolution in how development informs our understanding of evolution, it is no consolation to the creationists. Paul Nelson seems to think the exciting news here is that it highlights a deficiency in a theory formulated 60 years ago, in a post titled Neo-Darwinism Doesn’t Work for the Cambrian Explosion (ably knocked down at Deinonychus antirrhopus, so I won’t need to waste time on it), but that’s putting a phony spin on it. What it is is a mechanistic explanation and testable hypothesis for the patterns of animal morphology that we see in the Cambrian and afterwards…one soundly based on the data, and unfortunately for the Designists, one that is fully natural and requiring no assist from a designer of any kind. That’s how the authors conclude the paper:
We believe that experimental examination of the conserved kernels of extant developmental GRNs will illuminate the widely discussed but poorly understood problem of the origination of animal body plans in the late Neoproterozoic and Cambrian and their remarkable subsequent stability.
It’s a productive hypothesis that will fuel further research and analysis. It fits in perfectly with modern evolutionary biology, in which we emphasize genes as actors in a dynamic process…and that you can’t understand what’s going on by studying genes in isolation, but must follow how they interact with one another.
Davidson EH, Erwin DH (2006) Gene regulatory networks and the evolution of animal body plans. Science 311:796-800.
I may be mistaken here, but hasnt the idea of gene regulatory networks been around for sometime now? I recall that Stuart Kauffman had done some work on them in the 70’s and 80’s; and that he had used boolean networks to create mathematical models of GRNs…
Yes. That part is nothing new. What Davidson and Erwin are claiming is that there are these conserved modules, the GRN kernels, and that it is the organization of the network that imposes phylogenetic constraints on morphology.
Wow.
That’s all – just wow . . .
These sorts of concepts of networks are starting to be applied to medicine. For example, this article develops a rather complex map of the regulatory networks that are altered in leukocytes during inflammation.
This is really fascinating. I’m not a scientist of any kind, let alone a biologist, but I’m going to try to keep up with where this research is going. Even if their prediction doesn’t ultimately pan out, it should generate some interesting experiments – and a lot of knowledge.
i’m not a scientist either (i’m a programmer, a technician only at best), but this still strikes me as absolutely awesome. it’s the sort of thing that seems like it should be patently obvious in hindsight; i imagine, if i were a molecular biologist, i’d be slapping my forehead and going “of course!” right about now.
way cool. now let’s see if there’s any sort of abstraction mechanisms in there anywhere. my guesstimate is that there likely aren’t, that would be more like how humans design things, and unlikely to arise without conscious planning… which makes me really, really glad i’m not a molecular biologist, ‘cos i’d hate to have to understand and maintain the sort of horrid spaghetti-code mess these networks are likely to turn out to really be!
This is a major issue. As an eletronics tech, I appreciate the metaphor, but I understand that it is limited. There are some people who will not, or (more probably) will ignore those limits. They will deliberately try to confuse the issue. (My prediction is the “junk DNA does not exist” argument will be exhumed.
Anyway, this is facinating, and I am going to read Endless Forms Most Beutiful as soon as I can find a copy.
What! An Eric Davidson without a Roy Britton? I suppose this is a name-dropper situation – Glenn got his PhD under Eric in 1975.
Great read. Thanks ;)
Times like this make me wish I had taken more biology in college heh.
Fascinating. Reminds me of neural networks, where neuron A will fire off a transmitter that alters the voltage potential of neuron B, making it more likely to fire and affect neurons C,D,E, etc. But meanwhile, neuron F is also firing an inhibitory transmitter at neuron B, making it less likely to fire. It’s not the individual actions of A or F that makes B fire, but how both of their chemicals interact with B, and this in turn affects the likelyhood that B will in turn interact with C,D, and E.
So let’s say that you introduce a chemical stimulus that causes neuron A to release more of its exitatory transmitter into the synapse with neuron B. This increase in activity might then make neuron B more likely to fire. But suppose that neuron B then fires off an inhibitory neurotransmitter, like GABA, and this then lowers the voltage potential of C,D, and E, making them less likely to fire. So in this manner, a drug that stimulates neuron A and increases levels of an excitatory transmitter could still wind up inhibiting the actions of our downstream neurons C,D, and E.
Of course, it’s not a perfect corrolary, and it certainly lacks the snappyness of the “computer circuitry” analogy, but I’d love to see ID “scientists” try to abuse this metaphor.
Fascinating. Reminds me of neural networks, where neuron A will fire off a transmitter that alters the voltage potential of neuron B, making it more likely to fire and affect neurons C,D,E, etc. But meanwhile, neuron F is also firing an inhibitory transmitter at neuron B, making it less likely to fire. It’s not the individual actions of A or F that makes B fire, but how both of their chemicals interact with B, and this in turn affects the likelyhood that B will in turn interact with C,D, and E.
So let’s say that you introduce a chemical stimulus that causes neuron A to release more of its exitatory transmitter into the synapse with neuron B. This increase in activity might then make neuron B more likely to fire. But suppose that neuron B then fires off an inhibitory neurotransmitter, like GABA, and this then lowers the voltage potential of C,D, and E, making them less likely to fire. So in this manner, a drug that stimulates neuron A and increases levels of an excitatory transmitter could still wind up inhibiting the actions of our downstream neurons C,D, and E.
Of course, it’s not a perfect corrolary, and it certainly lacks the snappyness of the “computer circuitry” analogy, but I’d love to see ID “scientists” try to abuse this metaphor.
This actually fits into a theme that has come up time and time again in debates about evolution: evolution is actually surprising characteristically conservative in many ways: it has some pretty noticable macro-scale constraints and patterns that it rarely deviates outside of.
That’s what this whole business about “nested clades” is all about: descendants almost never go back and undo the major deviations that set their ancestors apart as a group. Think about the cell: for billions of years, evolution worked on the basic mechanisms of the cell, eventually ending up with eukaryotes. And that basic idea hasn’t changed all that much! How did it innovate? Not by rethinking existing concepts: they were in fact at that point basically IC, produced by evolution! No: they innovated by finding a completely different dimension of change, multicellularity. Likewise, once the basic multi-cellular bodyplans got laid down and a lot of different interlocking structures got invested in a particular layout, evolution had locked itself in again: diversity could be found in all sorts of specialized traits and organs and proteins and so on, but not by rethinking the basic chordate body.
The whole taxonomic system basically only works the way it does because of this conservatism: almost no modern animal has “left” the taxonomic groups its ancestors represented the basal forms of. Even the rare exceptions: like “untetrapodness” of snakes, still betray tell-tale features and atavisms that rat them out on their ancestry.
Thanks for the link PZ and thanks for a nice explanation of what is going on here. When I first read Paul Nelson’s post I thought, “man that is just too good (from his point of veiw) to be true.” So I e-mailed Prof. Davidson and, yup it was.
I also like your discussion of the metaphor. It definitely is a doubled edged sword give how the IDers grab onto the mechanistic terminology and then use it to (dishonestly) make analogies to man-made structures.
In the early ’80’s a colleague of mine and I began working on developing a 4-bit machine that would be able to run genetic algorithms as code. We experimented with a variety of hybrid types of 2-bit systems acting in combination to perform 4-bit operations but without much success. By the late ’80’s my colleague gave up in despair. I have not given up and some hope exists that a 4-bit machine will be possible in the future. (Quantum computers using both spin and charge).
Assuming we have a four bit machine, the next necessary step is to endow it with an instruction set that simulates the biochemical mechanisms of gene translation and expression. Such an instruction set would have to be multi-layered with its own logic to conform to the chemical mechanisms already known and those yet to be discovered. Moreover these simulations must result in an output stream that contains the necessary parameters to determine bonding angles and bond radii such that molecules can be assembled in a meaningful way that roughly at least, represent the actual protein chemistry. (several steps omitted for simplicity).
I don’t really know if anyone else is working on this sort of thing though it would surprise me very much if no one was, however, if there is interest I would be pleased to hear about it in this thread. Most programming types tend to react by tossing in their hat after a bout with the problems, they are indeed vexing. Moreover, my own personal expertise is no where near adequate to guide a large scale project in this direction, it is just something that I have been plinking away at for 25 years without making much headway but without giving up either.
I see the research you report here as working backwards towards the more fundamental goal of some form of genetic computer by elucidating the existing chemical processes such that we now have other design goals to meet. Admittedly the design goals far exceed our present capacity given that we do not yet have even a basic machine that can simulate the process. However, assuming that we ultimately can devise some computing system that is a good simulation of the biochemistry, it should enable some spectacular results. One would be the ability to formulate compounds with great speed and make some reasonable assessment of their potential efficacy without ever invoking any real wet chemicals. Another would be, given some proven effectiveness, the ability to iterate many millions of cycles of a simulation and thereby explore the multidimensional variable space in a more empirical way, albeit, only as simulations. Moreover the possibility exists – assuming that somehow we can manage to implement this on existing computing platforms, that population dynamics can be modeled by invoking hereditary processes through a large population of computers. A little like SETI but instead called, dare I? GENI.
At any rate, there’s nothing here to excite any one much I don’t think, but it has been a great boost to me to see these algorithmic patterns “on the other side” so to speak, something that we more or less assumed had to be present.
There is a great deal to attack here admittedly – so have at it, I won’t necessarily attempt to defend any particular point of view because frankly, I don’t know all that much about it, I only know a certain amount about what doesn’t work. I have no particular qualifications for this other than that I try to be logical and address the available knowledge base head on.
I do not either mean to imply in any way that this kind of approach would supplant the work of real biochemistry, but that it might enhance it somewhat.
Not withstanding that disclaimer, I will go way out on a limb and speculate that a similar approach might well ultimately be able to devise “artificial life”. Maybe only able to live witin computers….
This was a fantastic post… the kind of thing some lurkers search for with the determination of bereaved mothers. I speak for no one but myself, but in reality, the greatest utility of the global reach of the net is to bring together those who are thoughtful and trying to understand. If we can collaborate, we might improve our progress. To those whose only purpose is to deny and disrupt, I have nothing but contempt. Unable to contribute, they seek to emasculate the efforts of others out of nothing more than spite.
PZ, thank you for an insightful and inspiring post. Thank you for holding science dear, for knowing its true character and sharing it with me.
Ciao –
Nice post. Thank you.
OT, but have you seen this? Bible Guides Tour Museums to Counter Science
Yea, you seem to be dragging yourself away from certain anachronistic antiquities and endeavouring to take cognizance of advances in human discovery. This is encouraging. The obvious miscarriages of logic we brush aside in anticipation of this brave new Origins Education World in which facts are applied and quasi-religious indoctrination is layed aside. I have many technical questions, some of which may be deduced from my Site; one obvious area of enquiry relates to the processes involved in information exchange between DNA and the environment in which the organism is living. I suspect it’s early days yet, human knowledge being so embryonic.. If you can tell the readership anything technically accurate in layman’s terms along lines such as this, please do. There were real, describable events involved in species actuation. Your heading gives a hint. I suspect knowledge is still too limited to allow anything approaching precision. I would be in your debt if you were to provide me with anything usefull in this groundbreaking but complicated area of biochem.. Thankyou. Philip Heywood.
Great post!
(And Dembski’s objections are totally lame. It leads one to wonder why people take him seriously. Astrology, anyone?)
Steve Verdon, I wonder if you’d care to share Davidson’s response to Paul Nelson’s quote about “Neo-Darwinism is dead.”
Oh, traditional creationists, as well as the Johnsonist-Dembskiists, have been abusing this metaphor for a long time. It’s the “God of the Parts-Bin Argument.”
Since God whimsically chose to make humans and gorillas and chimpanzees look alike and fit in similar niches, He just chose the appropriate parts and fit them together in similar ways. We just don’t quite know why He chose a broken ascorbic acid gene, but there must be some good reason.
fusilier
James 2:24
Nice post. But the connections between the genes don’t tell the whole story either. The one gene–one protein hypothesis is breaking down. A number of genes have been found to have splice variants which may have different, even opposing, functions from the full length gene. Compare the actions of Ikaros 1 (the full length gene product) with Ik6 (a shortened splice variant). Not only do they have opposite actions (ie among other actions, Ik1 mildly promotes apoptosis whereas Ik6 inhibits apoptosis and can produce a leukemic phenotype), the shortened version can inhibit the action of the full length protein. So ultimately to understand biology we’ll have to understand not only the genes and the connections between the genes, but the various products that a single gene can produce and the reasons for splice variation. Then, of course, there’s siRNA…
I’ve wondered for a while why we regard genes as uninterrupted sequences of nucleotides (if that’s correct?). It occurred to me way back when that regulatory effects and interactions would suggest instead of the usual functional relationship between nucleotides and proteins given was instead between the power set in question and protein. (I’m not sure how quite to render this.)
I’ve wondered for a while why we regard genes as uninterrupted sequences of nucleotides (if that’s correct?). It occurred to me way back when that regulatory effects and interactions would suggest instead of the usual functional relationship between nucleotides and proteins given was instead between the power set in question and protein. (I’m not sure how quite to render this.)
PZ, you really should be using Digikey. Not only is it a Minnesota company, but those people are freaking saints.
Reading this excellent post and comments made it stand out to me when Slashdot pointed to GeneDesign over here http://slam.bs.jhmi.edu/gd/. Sew your own genes online! I want a comfy cut pair and a warm summer day.
Sure, I asked Prof. Davidson about that and he replied witht he following:
1. It was 8 years ago, so his memory isn’t pefect, but
2. He wouldn’t say something that blunt,
3. It was probably out of context.
I think the latter is almost surely the case. I can see something like “neo-Darwinism is dead in terms of explaining phenomenon X.” A bit different from the blanket death sentence.
His response to ID was much better: dishonest medevalist crap.
I gotta admit I still chuckle at that one.
Look! The Trolls have their own blog on you PZ!
http://www.uncommondescent.com/index.php/archives/837
If Dembski ever had any credibility, he lost it by promoting someone like DaveScot to be his co-poster on his own blog. It’s turned into the silliest sort of meglomaniacal circus imaginable. The best part is where one of the commenters suggests that the site refrain from linking or discussing PT or PZ articles with a discussion. You know, why dignify those people with a response!
Steve wrote:
“Sure, I asked Prof. Davidson about that and he replied…”
A LITTLE FISH
CHALLENGES A GIANT OF SCIENCE
The Boston Globe, May 30, 2000, Tuesday, Pg. E1 A LITTLE FISH CHALLENGES A GIANT OF SCIENCE By Fred Heeren, GLOBE CORRESPONDENT
” “NeoDarwinism is dead,” said Eric Davidson, a geneticist and textbook writer at the California Institute of Technology. He joined a recent gathering of 60 scientists from around the world near Chengjiang, where Chen had found his first impressions of Haikouella five years ago.”
http://www.omniology.com/A-LittleFish.html
Davidson said it, Heeren reported it (in quotes).
Neo-darwinism is dead
Deal with it…
Was going to say, “Cue Charlie”, but seems he beat me too it…
Instead I will take a cue from the old tuna commercials and just say, “Sorry Charlie!” lol
They have. Read the trackback.
Was going to say, “Cue Charlie”, but seems he beat me too it…
Instead I will take a cue from the old tuna commercials and just say, “Sorry Charlie!” lol
They have. Read the trackback.
From http://www.omniology.com/A-LittleFish.html
“The idea that neoDarwinism is missing something fundamental about evolution is as scandalous to Americans as it is basic to the Chinese.”
Refining theories to incoroprate new data is what science is all about. Calling new data a scandal is sensationalism at best. As for “Davidson said it, Heeren reported it (in quotes),” quotations are often cut short to make “good” sound bites.
A number of genes have been found to have splice variants which may have different, even opposing, functions from the full length gene…Then, of course, there’s siRNA…
Add in polymorphisms which knock out splice acceptor sites (PubMed ID:16400609), and you’re playing a whole new ball game.
plunge wrote:
“….evolution is actually surprising characteristically conservative in many ways: it has some pretty noticable macro-scale constraints and patterns that it rarely deviates outside of.”
Good point. It appears that the mechanism works AGAINST random mutation.
Plunge, the language you use imbues too much “thinking” and “intelligence” to the random, undirected, directionless process:
“descendants almost never go back…” as if they are choosing NOT to do so.
“evolution worked on the basic mechanisms of the cell…” as if it is something like the nerd PZ says she was, working in a garage to put a 4-bit processor together.
“And that basic idea hasn’t changed all that much!” What idea? Intelligence has ideas. Eukaryotes aren’t an idea, they are simply an happenstance set of whirling electrons and protons.
“How did it innovate? Not by rethinking existing concepts:” as if Eukaryotes guide themselves by thoughtful, purposeful intellect to arrive foreknown, planned genetic arrangements hundreds of thousands of generations in the future! “Rethinking” implies evolution was “thinking” in the first place on how to create a eukaryote. Evolution doesn’t think! It is blind and purposeless reaction to environment.
“No: they innovated by finding a completely different dimension of change, multicellularity.” Plunge, sorry, this is just crazy talk. If the Creationists see this sort of language, they will have a field day. What you are saying is the eukaryotes are “intelligently designed”. Stop it! Stop it now!
It seems to me that Mendelian genetics is a problem for evolution for the simple reasons that (1) harmful mutations are never completely eliminated by natural selection and (2) there are so many more harmful mutation than beneficial one, by a factor of what? 100 to one?
With this complex circuitry, isn’t the problem the same?
who says harmful mutations are never completely eliminated? most of the really harmful kinds are lethal before adulthood. many of the mutations we humans would consider harmful, would be so considered because they tend to be fatal even before the end of gestation. those ones most certainly don’t get fixed in a population, no.
in fact, a case can be made that mutations which do end up common in a population can’t reasonably be as harmful as all that, considering they let their carriers survive and reproduce, after all.
i’m not sure i see your analogy with these networks of genes, either. i could kinda-sorta see a connection if i squinted hard enough, but that might just as easily be just me; better if you stated more specifically what you think the similarity might be.
Carriers of genetic diseases (a defective allel paired with a normal one) do not show any effects of the disease that they can pass on. Negative selection will keep the frequency very low, but it will never eliminate the defect. I believe there are in excess of 5000 known genetic diseases and many genes are suspect in vulnerabilities to disease. Often genetic diseases can be traced to a defective gene from each parent so that one protein is missing. So, would not a defect in a gene that controls other parts of the genome be even more devastating? And could such a gene be inherited from two non-affected carriers? I am not a scientist, so please correct me.
This stuff bugs me-a CS person or an EE takes a look at this, finds the obvious, and declares he’s discovered fire. Simple genetic regulatory circuts conserved? Of course, local interactions are typically conserved.
Two and three gene regulatory pathways that involve basic units of positive and negative feedback? Duh! I’ve seen a few of these articles now, and they find that most of the combinatoric possibilities for assembling a few genes together do in fact occur! What a surprise! What a discovery! The details are interesting of course, but what you have is the _discovery_ of these simple systems trumpeted as major news when its not.
Charlie,
Again, you still haven’t provided the context. I bet you can’t either.
if a genetic disorder can be carried without showing symptoms of it, then i for one would define that disorder as “not all that bad”. the really bad ones don’t allow for any non-symptomatic carriers, but rather are dominant in every instance. the kinds of genes you speak of are by definition recessive. (which is not to say they don’t have an impact. sickle cell anemia behaves much like what you describe, except that for non-symptomatic, single-allele carriers, it is actually mildly beneficial.)
and in truth, many genetic disorders probably do impact a complex regulatory network like this new research describes. that’s likely the only way for most mutations to effect complex phenotypic changes in their target individuals.
Incredible post!!
You must have a LONG string of ex-students who consider you the best science teacher they ever had!
“Harmful” and “beneficial” are relative terms in the context of genetics and evolution. The environment and interaction with other genes can play a decisive role in whether a gene is harmful, neutral, or beneficial.
A classic example is the sickle gene. A person with SS hemoglobin (two sickle genes) is generally very sick, rarely makes it to reproductive age without medical intervention, making it a fatal genetic abnormality in the “wild”. Sickle trait (SA, one normal gene, one sickle gene), on the other hand, is a beneficial trait in an area where malaria is endemic since it confers some resistance to malaria.
Another example might be the mutation that cause the melanocytes to shrink, producing lighter skin tones. This is a useful mutation in far northern regions where light is scarce in the winter and vitamin D deficiency is a real possibility. Near the equator, on the other hand, it can be very detrimental indeed.
I’ve wondered about the problem of mildly detrimental genes for a long time. Is it possible that some apparently detrimental mutations have advantages we don’t fully understand? For example, is there an advantage to the Rh negative gene, perhaps seen only in heterozygotes, that keeps it from dying out, even though it is quite detrimental without medical intervention? If anyone knows of any models of this sort of phenomenon, I’d appreciate it if you could point me in the right direction.
It really would be cheaper if diodes reproduced themselves, wouldn’t it? Or at least had diode sex with each other?
Hello science folks,
I learnt that in the course of mating many sperms are set to meet the egg. Only one sperm will contact the egg to produce the baby.
My questions: do all the sperms identical? do the characterstics of the baby depend on which sperm contact the egg?
Thanks in advance.
No. Sperm are haploid, and contain only half the father’s genetic material. You have two copies of each gene, and which copy of each gets into the sperm is random. Eggs similarly contain a random set of alleles.
Yes. That’s why brothers and sisters aren’t identical.
If that is the case even if species are is ‘created’, chance and randomness is playing a role in the birth of each individual (unless the Creator is intervening in each and every individuals sperm+egg selection). I see why it is a tough argument for the ID or creationists.
Thanks PZ.
I have a couple of problems with this “most mutations are detrimental” dogma.
First, when you intentionally make mutations in proteins by site directed mutatgenesis, very commonly you discover that many regions of a protein will accept a wide range of different amino acids with modest or undetectable effects on function. Even when you knock out an entire gene, very often you get slight or undetectable phenotypic changes. I’ve never seen a systematic enumeration, but I suspect that most mutations are neutral or close to neutral.
Moreover, if the environment is changing relatively slowly, one would expect most proteins to be pretty well optimized for the average environment, which by definition means that changes would appear to be deleterious or at best neutral in a “typical” environment. However, some of those supposedly deleterious variants might confer the ability to succeed in atypical environments. This would be a significant advantage due to reduced competition, and could turn out to be crucial in times of rapid environmental change.
I might be reading this wrong but this sounds so elitist. Condescending. Like we’re children. Gawd. Thanks for giving us no credit to distinguish a metaphor from the underlying idea. You know Einstein used metaphors to explain his theories. You should read him sometime. ;)
Other than that, great post.
A quick check on internet: 6000 plus single point mutation genetic diseases. I think most of them are autosomal recessive, which means parents are carriers with no expression of the disease. Natural Selection will keep the rate of serious (up to fatal) recessive genes very low, but I have never heard of the mechanism that eliminates these recessive genes. Otherwise, it seems to me that recessive mutations build up in the gene pool. The more serious the defect, the lower the rate due to NS, but I don’t know how the defective genes are removed so that they do not accumulate.
All the caveats about metaphors notwithstanding…
It may not be obvious to the lay observer, but there is a great deal of continuity with modification between, say, the wireless card in your laptop and a 1930s Atwater-Kent six-tuber. Some functions will be identical, and carried out in very similar ways. Some will look utterly different, but the recent will be the descendent of the old through various changes.
“Ah yes,” says the obtuse creatid, “but that’s because intelligent designers were involved every step of the way. You never see a 1950s Bell telephone change BY ITSELF into a Nokia cellphone, do you?” Well, aside from the fact that no one person designed the entire chain from Marconiphone to Motorola Razr, electronics lends itself rather well to creation through genetic algorithm. Google for ‘evolvable hardware’.
I’m pretty convinced that, much as DNA is proving too tough a nut for fundy mormonism to crack, simulated evolution will see off a lot of the creatids. The only arguments against it are so weak they collapse under their own weight in five sentences…
R
it seems to me that once the frequency of an allele drops low enough, simple genetic drift might eliminate it by pure chance alone. it seems to me, also, that if the frequency of an allele is low enough to not threaten the population with whatever deleterious effects the allele might have, it really doesn’t matter if it’s never eliminated.
plus, of course, the whole complex issue of the term “deleterious” being wholly dependent on environmental context. an allele may be harmful to me today, yet helpful to my sister tomorrow. weeding them all out might be a very bad idea, no matter how much we may dislike them.
1. An allele that mutates into a protein that does not function is detrimental in all environments.
2. The environment for most proteins is the cell in which they function.
Are these two statements basicly correct?
The problem that I see is not a particular defective allele, but the accumulation, over millions of years of defective genes, masked by a normal allele. Eventually, would not a gamete paired with any other gamete produce an organism with at least one fatally flawed pair of alleles? I know that there must be a mechanism that reliably removes defective alleles from the gene pool, because in the words of Donald Johansen, “We’re here aren’t we?”
Would someone who understands this question please tell me the answer?
So, it’s about historically contingent events becoming locked, i.e. the irreversibility of evolution. While Dr. Davidson’s idea is not all that new (one could encounter similar notions during many a labs’ beer-hours), he does supports it with data and provides examples by which the hypothesis can be evaluated.
BTW – Digikey *is* a great source for many electronic components (considerately packed by Norwegian bachelor farmers with nary an “Uff da!” in complaint). But for cheapo hobbyists, places like Marlin P. Jones & Alltronics rock!
Merlin: I see several misconceptions behind your questions, but I’ll try to sort out the points:
Often, but not always! These “knockout” mutations may be “covered” by redundancy within the genome, the organism, or even the environment. Both the diploid structure of our genome, and the common duplications of genes, tend to fill in for knockouts, which is why they’re usually recessive. There can also be alternate biochemical paths for doing whatever the missing protein would have done. And the environment may make some traits unnecessary. (For example, I would guess that the “reason” we can’t synthesize Vitamin C, is simply that our ancestors reliably got a good supply from their diet, so “nobody noticed” when the knockout spread through the population.)
As described above, this isn’t necessarily so either. The cell actually has subsections of its own, and various signals can reach up to the organismic level or beyond.
Well, yes. Most of the blatantly fatal genetic conditions are probably “early lethals”, where the embryo never makes it to proper fetus stage. This is generally not a problem (aside from reducing fertility), as they just get added to the routine lossage from chromosomal misarrangements. In fact, this is exactly what does tend to “weed out” such genes, as two “carriers” can produce non-carrier children, among the carriers and “non-starters”. The same reasoning goes to varying degrees for disabilities caused by genetic problems.
But notice that selection of this sort *doesn’t* “wipe out” genes entirely, it just makes them very rare. Indeed, most of us have several lethal mutations scattered though our genome, but most of those are so ideosyncratic, that the only way we could manage to “double” them, would be to have a child by a blood relative. (Only one reason why incest is a bad idea!) But this sort of genetic chaff isn’t all bad, as it provides a reservoir of “pseudo-genes” whose later mutations (still protected by all that redundancy) might yield something useful.
Drat, my quotes didn’t! Hopefully, you should be able to pick out his comments from mine.
“evolution is actually surprising characteristically conservative in many ways”
Not at all surprising. The aim is survival, not evolution (in the sense of “progress” such as from fish to mammal). The best way to survive is to find a good niche and stay there, and to find good algorithms and stick with them.
A large proportion of organisms has hardly changed for billions of years.
The sequences were interesting but I was wondering if how often the organism’s environment is in could effect the gene switch’s/sequences. Would these changes be passed along to the next generation?