Evolution: The Story of Life on Earth

Have you got kids? Are you tangentially related to any young people? Are you young yourself? Do you know anyone who just likes a good story and interesting science?

Well, then, I’m sorry, but reading this article will cost you $12.89. Jay Hosler has a new book out (illustrated by Kevin Cannon and Zander Cannon), Evolution: The Story of Life on Earth(amzn/b&n/abe/pwll), and I’m afraid it’s going to be required reading for everyone, and you’re also all probably going to end up buying multiple copies for gifts.

Really, it’s that good. It’s a comic book about aliens from Glargalia explaining the history of life on earth to young Prince Floorsh by going over the fundamental concepts and hitting a few of the details. It’s entertaining and fun, and sneakily informative.

If you don’t simply trust me, check out the extensive excerpts at the NCSE and at Scientific American.

Hey, and if you don’t like comic books, don’t know any young people, and don’t want to read it yourself, buy a copy anyway and give it to your local library. For America.

The new phrenology

Morphological variation is important, it’s interesting…and it’s also common. It’s one of my major scientific interests — I’m actually beginning a new research project this spring with a student and I doing some pilot experiments to evaluate variation in wild populations here in western Minnesota, so I’m even putting my research time where my mouth is in this case. There has been some wonderful prior work in this area: I’ll just mention a paper by Shubin, Wake, and Crawford from 1995 that examined limb skeletal morphology in a population of newts, and found notable variation in the wrist elements — only about 70% had the canonical organization of limb bones.

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I’ve also mentioned the fascinating variation in the morphology of the human aorta. Anatomy textbooks lay out the most common patterns, but anyone who has taught the subject knows that once you start dissecting, you always find surprises, and that’s OK: variation is the raw material of evolution, so it’s what we expect.

The interesting part is trying to figure out what causes these differences in populations. We can sort explanations into three major categories.

  1. Genetic variation. It may be the the reason different morphs are found is that they carry different alleles for traits that influence the developmental processes that build features of the organism. Consider family resemblances, for instance: your nose or chin might be a recognizable family trait that you’ve inherited from one of your parents, and may pass on to your children.

  2. Environmental variation. The specific pattern of expression of some features may be modified by environmental factors. In larval zebrafish, for instance, the final number of somites varies to a small degree, and can be biased by the temperature at which they are raised. They’re also susceptible to heat shock, which can generate segmentation abnormalities.

  3. Developmental noise. Sometimes, maybe often, the specific details of formation of a structure may not be precisely determined — they wobble a bit. The limb variation Shubin and others saw, for example, was almost entirely asymmetric, so it’s not likely to have been either genetic or environmental. They were just a consequence of common micro-accidents that almost certainly had no significant effect on limb function.

When I see variation, the first question that pops into my head is which of the above three categories it falls into. The second question is usually whether the variation does anything — while some may have consequences on physiology or movement or sexual attractiveness, for instance, others may really be entirely neutral, representing equivalent functional alternatives. Those are the interesting questions that begin inquiry; observing variation is just a starting point for asking good questions about causes and effects, if any.

I bring up this subject as a roundabout introduction to why I find myself extremely peeved by a recent bit of nonsense in the press: the claim that liberal and conservative brains have a different organization, with conservatives having larger amygdalas (“associated with anxiety and emotions”) and liberals having a larger anterior cingulate (“associated with courage and looking on the bright side of life”).

Gag.

I don’t deny the existence of anatomical variation in the brain — I expect it (see above). I don’t question the ability of the technique, using MRI, to measure the dimensions of internal structures. I even think these kinds of structural variations warrant more investigation — I think there are great opportunities for future research to use these tools to look for potential effects of these differences.

What offends me are a number of things. One is that the interesting questions are ignored. Is this variation genetic, environmental, or simply a product of slop in the system? Does it actually have behavioral consequences? The authors babble about some correlation with political preferences, but they have no theoretical basis for drawing that conclusion, and they can’t even address the direction of causality (which they assume is there) — does having a larger amygdala make you conservative, or does exercising conservative views enlarge the amygdala?

I really resent the foolish categorization of the functions of these brain regions. Courage is an awfully complex aspect of personality and emotion and cognition to simply assign to one part of the brain; I don’t even know how to define “courage” neurologically. Are we still playing the magical game of phrenology here? This is not how the brain works!

Furthermore, they’re picking on a complex phenomenon and making it binary. Aren’t there more than one way each to be a conservative or a liberal? Aren’t these complicated human beings who vary in an incredibly large number of dimensions, too many to be simply lumped into one of two types on the basis of a simple survey?

This is bad science in a number of other ways. It was done at the request of a British radio channel; they essentially wanted some easily digestible fluff for their audience. The investigator, Geraint Rees, has published quite a few papers in credible journals — is this really the kind of dubious pop-culture crap he wants to be known for? The data is also feeble, based on scans of two politicians, followed by digging through scans and questionnaires filled out by 90 students. This is blatant statistical fishing, dredging a complex data set for correlations after the fact. I really, really, really detest studies like that.

And here’s a remarkable thing: I haven’t seen the actual data yet. I don’t know how much variation there is, or how weak or strong their correlations are. It’s because I can’t. This work was done as a radio stunt, is now being touted in various other media, and the paper hasn’t been published yet. It’ll be out sometime this year, in an unnamed journal.

We were just discussing the so-called “decline effect”, to which my answer was that science is hard, it takes rigor and discipline to overcome errors in analysis and interpretation, and sometimes marginal effects take a great deal of time to be resolved one way or the other…and in particular, sometimes these marginal results get over-inflated into undeserved significance, and it takes years to clear up the record.

This study is a perfect example of the kind of inept methodology and lazy fishing for data instead of information that is the root of the real problem. Science is fine, but sometimes gets obscured by the kind of noise this paper is promoting.

I have to acknowledge that I ran across this tripe via Blue Girl, who dismisses it as “sweeping proclamations about the neurophysiological superiority of the liberal brain”, and Amanda Marcotte, who rejects it because “This kind of thing is inexcusable, both from a fact-based perspective and because the implication is that people who are conservative can’t help themselves.” Exactly right. This kind of story is complete crap from the premise to the data to the interpretations.

Why there are no missing links

This topic came up earlier this week: creationists are always yammering about the “missing link” and how it’s missing and therefore evolution is unsupported by the evidence. It’s total nonsense, since evolution doesn’t predict a “missing link”, but it seemed worthwhile to explain why, since there was a recent publication of some exciting data that demonstrates the real complexity of the situation.

Jim Foley and John Hawks and Carl Zimmer have written up the story of the Denisovans. To summarize, another group of Pleistocene humans have been sequenced, called the Denisovans — their identity is murky, as they’ve only been recognized by a few bones, but the results show that they were genetically distinct from both modern humans and Neandertals, another Pleistocene group that has been sequenced. Like the Neandertal story, in which some Neandertal genes (less than 5%) were introduced into some modern human (European and Asian) populations, what we know about the Denisovans is that some of their genes, about 5%, also spread into a subset of modern human populations, in this case the Melanesians.

That’s awesome stuff. There are all these splintered bits of ancestry that come together in complex ways to produce the human species, and that’s why there is no missing link. Many people have this false notion that our evolution was a matter of a panmictic gemisch of people rolling fatefully down the smooth channel of history, everyone mingling, all of them tracing a common lineage back and back to a discrete ancestor. It wasn’t. Our river of time looked more like this, a braided stream:

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This is what we mean when we talk about populations having structure. Branches emerge, whether we call them Neandertals or Denisovans or modern humans, and they are distinct but there can still be genes flowing between them to some degree. Even within modern humans we have structure, where groups maintain a kind of genetic integrity over space and time; I can look at my own recent lineage and see how my mother’s Scandinavian connections were maintained through several generations in America, or I can look at my father’s pedigree that goes back about 400 years in the New World and see that even though they were constantly scudding along at the very edge of the American frontier, mingling with Native Americans and black slaves and freedmen and Chinese railroad workers and Japanese farmers, somehow in their marriages, nothing but Scots/Irish/Anglo-Saxon names turn up.

That’s the nature of a species: many channels, many populations, not just one, separating and merging with circumstance. It’s always been this way; when humans and chimps first diverged from their common ancestors, it wasn’t like one tribe went left, one went right, and they never talked to each other again — it was many streams of ancient ape populations twisted about amongst each other, gradually disentangling to each form a spectrum of divergent channels for each separated species.

When a creationist demands to see the “missing link”, it’s like looking at the picture of a river above and asking for the one drop of water that started it all. There wasn’t one. The question doesn’t even make sense. It’s why BioLogos looks so ridiculous when they worry over whether we can trace our ancestry back to two people, Adam and Eve — of course we can’t, humanity has never been represented by just two unique individuals, and even considering the issue seriously reveals an absence of understanding of how populations evolve. It’s so confused, it’s not even wrong.

(I notice that Greg Laden comes to a similar conclusion, that using the term “missing link” should be avoided, but the nature of his argument looks about as tangled and discursive as the picture of the braided stream above…so maybe it’s more true to the reality?)

How to afford a big sloppy genome

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My direct experience with prokaryotes is sadly limited — while our entire lives and environment are profoundly shaped by the activity of bacteria, we rarely actually see the little guys. The closest I’ve come was some years ago, when I was doing work on grasshopper embryos, and sterile technique was a pressing concern. The work was done under a hood that we regularly hosed down with 95% alcohol, we’d extract embryos from their eggs, and we’d keep them alive for hours to days in tissue culture medium — a rich soup of nutrients that was also a ripe environment for bacterial growth. I was looking at the development of neurons, so I’d put the embryo under a high-powered lens of a microscope equipped with differential interference contrast optics, and the sheet of grasshopper neurons would look like a giant’s causeway, a field of tightly packed rounded boulders. I was watching processes emerging and growing from the cells, so I needed good crisp optics and a specimen that would thrive healthily for a good long period of time.

It was a bad sign when bacteria would begin to grow in the embryo. They were visible like grains of rice among the ripe watermelons of the cells I was interested in, and when I spotted them I knew my viewing time was limited: they didn’t obscure much directly, but soon enough the medium would be getting cloudy and worse, grasshopper hemocytes (their immune cells) would emerge and do their amoeboid oozing all over the field, engulfing the nasty bacteria but also obscuring my view.

What was striking, though, was the disparity in size. Prokaryotic bacteria are tiny, so small they nestled in the little nooks between the hopper cells; it was like the opening to Star Wars, with the tiny little rebel corvette dwarfed by the massive eukaryotic embryonic cells that loomed vastly in the microscope, like the imperial star destroyer that just kept coming and totally overbearing the smaller targets. And the totality of the embryo itself — that’s no moon. It’s a multicellular organism.

I had to wonder: why have eukaryotes grown so large relative to their prokaryotic cousins, and why haven’t any prokaryotes followed the strategy of multicellularity to build even bigger assemblages? There is a pat answer, of course: it’s because prokaryotes already have the most successful evolutionary strategy of them all and are busily being the best microorganisms they can be. Evolving into a worm would be a step down for them.

That answer doesn’t work, though. Prokaryotes are the most numerous, most diverse, most widely successful organisms on the planet: in all those teeming swarms and multitudinous opportunities, none have exploited this path? I can understand that they’d be rare, but nonexistent? The only big multicellular organisms are all eukaryotic? Why?

Another issue is that it’s not as if eukaryotes carry around fundamentally different processes: every key innovation that allowed multicellularity to occur was first pioneered in prokaryotes. Cell signaling? Prokaryotes have it. Gene regulation? Prokaryotes have that covered. Functional partitioning of specialized regions of the cell? Common in prokaryotes. Introns, exons, endocytosis, cytoskeletons…yep, prokaryotes had it first, eukaryotes have simply elaborated upon them. It’s like finding a remote tribe that has mastered all the individual skills of carpentry — nails and hammers, screws and screwdrivers, saws and lumber — as well as plumbing and electricity, but no one has ever managed to bring all the skills together to build a house.

Nick Lane and William Martin have a hypothesis, and it’s an interesting one that I hadn’t considered before: it’s the horsepower. Eukaryotes have a key innovation that permits the expansion of genome complexity, and it’s the mitochondrion. Without that big powerplant, and most importantly, a dedicated control mechanism, prokaryotes can’t afford to become more complex, so they’ve instead evolved to dominate the small, fast, efficient niche, leaving the eukaryotes to occupy the grandly inefficient, elaborate sloppy niche.

Lane and Martin make their case with numbers. What is the energy budget for cells? Somewhat surprisingly, even during periods of rapid growth, bacteria sink only about 20% of their metabolic activity into DNA replication; the costly process is protein synthesis, which eats up about 75% of the energy budget. It’s not so much having a lot of genes in the genome that is expensive, it’s translating those genes into useful protein products that costs. And if a bacterium with 4400 genes is spending that much making them work, it doesn’t have a lot of latitude to expand the number of genes — double them and the cell goes bankrupt. Yet eukaryotic cells can have ten times that number of genes.

Another way to look at it is to calculate the metabolic output of the typical cell. A culture of bacteria may have a mean metabolic rate of 0.2 watts/gram; each cell is tiny, with a mass of 2.6 x 10-12g, which means each cell is producing about 0.5 picowatts. A eukaryotic protist has about the same power output per unit weight, 0.06 watts/gram, but each cell is so much larger, about 40,000 x 10-12g, that a single cell has about 2300 picowatts available to it. So, more energy!

Now the question is how that relates to genome size. If the prokaryote has a genome that’s about 6 megabases long, that means it has about 0.08 picowatts/megabase to spare. If the eukaryote genome is 3,000 megabytes long, that translates into about 0.8 picowatts of power per megabase (that’s a tenfold increase, but keep in mind that there is wide variation in size in both prokaryotes and eukaryotes, so the ranges overlap and we can’t actually consider this a significant difference — they’re in the same ballpark).

Now you should be thinking…this is just a consequence of scaling. Eukaryotic power production per gram isn’t any better than what prokaryotes do, all they’ve done is made their cells bigger, and there’s nothing to stop prokaryotes from growing large and doing the same thing. In fact, they do: the largest known bacterium, Thiomargarita, can reach a diameter of a half-millimeter. It gets more metabolic power in a similar way to how eukaryotes do it: we eukaryotes carry a population of mitochondria with convoluted membranes and a dedicated strand of DNA, all to produce energy, and the larger the cell, the more mitochondria are present. Thiomargarita doesn’t have mitochondria, but it instead duplicates its own genome many times over, with 6,000-17,000 nucleoids distributed around the cell, each regulating its own patch of energy-producing membrane. It’s functionally equivalent to the eukaryotic mitochondrial array then, right?

Wrong. There’s a catch. Mitochondria have grossly stripped down genomes, carrying just a small cluster of genes essential for ATP production. One hypothesis for why this mitochondrial genome is maintained is that it acts as a local control module, rapidly responding to changes in the local membrane to regulate the structure. In Thiomargarita, in order to get this fine-tuned local control, the whole genome is replicated, dragging along all the baggage, and metabolic expense, of all of those non-metabolic genes.

Because it is amplifying the entire genomic package instead of just an essential metabolic subset, Thiomargarita‘s energy output per gene plummets in comparison. That difference is highlighted in this illustration which compares an ‘average’ prokaryote, Escherichia, to a giant prokaryote, Thiomargarita, to an ‘average’ eukaryotic protist, Euglena.

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The cellular power struggle. a-c, Schematic representations of a medium sized prokaryote (Escherichia), a very large prokaryote (Thiomargarita), and a medium-sized eukaryote (Euglena). Bioenergetic membranes across which chemiosmotic potential is generated and harnessed are drawn in red and indicated with a black arrow; DNA is indicated in blue. In c, the mitochondrion is enlarged in the inset, mitochondrial DNA and nuclear DNA are indicated with open arrows. d-f, Power production of the cells shown in relation to fresh weight (d), per haploid gene (e) and per haploid genome (power per haploid gene times haploid gene number) (f). Note that the presence or absence of a nuclear membrane in eukaryotes, although arguably a consequence of mitochondrial origin70, has no impact on energetics, but that the energy per gene provided by mitochondria underpins the origin of the genomic complexity required to evolve such eukaryote-specific traits.

Notice that the prokaryotes are at no disadvantage in terms of raw power output; eukaryotes have not evolved bigger, better engines. Where they differ greatly is in the amount of power produced per gene or per genome. Eukaryotes are profligate in pouring energy into their genomes, which is how they can afford to be so disgracefully inefficient, with numerous genes with only subtle differences between them, and with large quantities of junk DNA (which is also not so costly anyway; remember, the bulk of the expense is in translating, not replicating, the genome, and junk DNA is mostly untranscribed).

So, what Lane and Martin argue is that the segregation of energy production into functional modules with an independent and minimal genetic control mechanism, mitochondria with mitochondrial DNA, was the essential precursor to the evolution of multicellular complexity — it’s what gave the cell the energy surplus to expand the genome and explore large-scale innovation.

As they explain it…

Our considerations reveal why the exploration of protein sequence space en route to eukaryotic complexity required mitochondria. Without mitochondria, prokaryotes—even giant polyploids—cannot pay the energetic price of complexity; the lack of true intermediates in the prokaryote-to-eukaryote transition has a bioenergetic cause. The conversion from endosymbiont to mitochondrion provided a freely expandable surface area of internal bioenergetic membranes, serviced by thousands of tiny specialized genomes that permitted their host to evolve, explore and express massive numbers of new proteins in combinations and at levels energetically unattainable for its prokaryotic contemporaries. If evolution works like a tinkerer, evolution with mitochondria works like a corps of engineers.

That last word is unfortunate, because they really aren’t saying that mitochondria engineer evolutionary change at all. What they are is permissive: they generate the extra energy that allows the nuclear genome the luxury of exploring a wider space of complexity and possible solutions to novel problems. Prokaryotes are all about efficiency and refinement, while eukaryotes are all about flamboyant experimentation by chance, not design.

Lane N, Martin W. (2010) The energetics of genome complexity. Nature 467(7318):929-34.

The molecular foundation of the phylotypic stage

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When last we left this subject, I had pointed out that the phenomenon of embryonic similarity within a phylum was real, and that the creationists were in a state of dishonest denial, arguing with archaic interpretations while trying to pretend the observations were false. I also explained that constraints on morphology during development were complex, and that it was going to take something like a thorough comparative analysis of large sets of gene expression data in order to drill down into the mechanisms behind the phylotypic stage.

Guess what? The comparative analysis of large sets of gene expression data is happening. And the creationists are wrong, again.

Again, briefly, here’s the phenomenon we’re trying to explain. On the left in the diagram below is the ‘developmental hourglass’: if you compare eggs from various species, and adults from various species, you find a diversity of forms. However, at one period in early development called the phylytypic stage (or pharyngula stage specifically in vertebrates), there is a period of greater similarity. Something is conserved in animals, and it’s not clear what; it’s not a single gene or anything as concrete as a sequence, but is instead a pattern of interactions between developmentally significant genes.

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The diagram on the right is an explanation for the observations on the left. What’s going on in development is an increase in complexity over time, shown by the gray line, but the level of global interactions does not increase so simply. What this means is that in development, modular structures are set up that can develop autonomously using only local information; think of an arm, for instance, that is initiated as a limb bud and then gradually differentiates into the bones and muscle and connective tissue of the limb without further central guidance. The developing arm does not need to consult with the toes or get information from the brain in order to grow properly. However, at some point, the limb bud has to be localized somewhere specific in relation to the toes and brain; it does require some sort of global positioning system to place it in the proper position on the embryo. What we want to know is what is the GPS signal for an embryo: what it looks like is that that set of signals is generated at the phylotypic stage, and that’s why this particular stage is relatively well-conserved.

One important fact about the diagram above: the graph on the right is entirely speculative and is only presented to illustrate the concept. It’s a bit fake, too—the real data would have to involve multiple genes and won’t be reducible to a single axis over time in quite this same way.

Two recent papers in Nature have examined the real molecular information behind the phylotypic stage, and they’ve confirmed the molecular basis of the conservation. Of course, by “recent”, I mean a few weeks ago…and there have already been several excellent reviews of the work. Matthew Cobb has a nice, clean summary of both, if you just want to get straight to the answer. Steve Matheson has a three part series thoroughly explaining the research, so if you want all the details, go there.

In the first paper by Kalinka and others, the authors focused on 6 species of Drosophila that were separated by as much as 40 million years of evolution, and examined quantitative gene expression data for over 3000 genes measured at 2 hour intervals. The end result of all that work is a large pile of numbers for each species and each gene that shows how expression varies over time.

Now the interesting part is that those species were compared, and a measure was made of how much the expression varied: that is, if gene X in Drosophila melanogaster had the same expression profile as the homologous gene X in D. simulans, then divergence was low; if gene X was expressed at different times to different degrees in the two species, then divergence was high. In addition, the degree of conservation of the gene sequences between the species were also estimated.

The prediction was that there ought to be a reduction of divergence during the phylotypic period. That is, the expression of genes in these six species should differ the least in developmental genes that were active during that period. In addition, these same genes should show a greater degree of evolutionary constraint.

Guess what? That’s exactly what they do see.

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Temporal expression divergence is minimized during the phylotypic period. a, Temporal divergence of gene expression at individual time points during embryogenesis. The curve is a second-order polynomial that fits best to the divergence data. Embryo images are three-dimensional renderings of time-lapse embryonic development of D. melanogaster using Selective Plane Illumination Microscopy (SPIM).

That trough in the graph represents a period of reduced gene expression variance between the species, and it corresponds to that phylotypic period. This is an independent confirmation of the morphological evidence: the similarities are real and they are an aspect of a conserved developmental program.

By the way, this pattern only emerges in developmental genes. They also examined genes involved in the immune system and metabolism, for instance, and they show no such correlation. This isn’t just a quirk of some functional constraint on general gene expression at one stage of development, but realy is something special about a developmental and evolutionary constraint.

The second paper by Domazet-Loso and Tautz takes a completely different approach. They examine the array of genes expressed at different times in embryonic development of the zebrafish, and then use a comparative analysis of the sequences of those genes against the sequences of genes from the genomic databases to assign a phylogenetic age to them. They call this phylostratigraphy. Each gene can be dated to the time of its origin, and then we can ask when phylogenetically old genes tend to be expressed during development.

The prediction here is that there would be a core of ancient, conserved genes that are important in establishing the body plan, and that they would be expressed during the phylotypic stage. The divergence at earlier and later stages would be a consequence of more novel genes.

Can you guess what they saw? Yeah, this is getting predictable. The observed pattern fits the prediction.

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Transcriptome age profiles for the zebrafish ontogeny. a, Cumulative transcriptome age index (TAI) for the different developmental stages. The pink shaded area represents the presumptive phylotypic phase in vertebrates. The overall pattern is significant by repeated measures ANOVA (P = 2.4 3 10-15, after Greenhouse-Geisser correction P = 0.024). Grey shaded areas represent ± the standard error of TAI estimated by bootstrap analysis.

So what does this all tell us? That the phylotypic stage can be observed and measured quantitatively using several different techniques; that it represents a conserved pattern of development gene expression; and that the genes involved are phylogenetically old (as we’d expect if they are conserved.)

Domazet-Loso and Tautz propose two alternative explanations for the phenomenon, one of which I don’t find credible.

Adaptations are expected to occur primarily in response to altered ecological conditions. Juvenile and adults interact much more with ecological factors than embryos, which may even be a cause for fast postzygotic isolation. Similarly, the zygote may also react to environmental constraints, for example, via the amount of yolk provided in the egg. In contrast, mid-embryonic stages around the phylotypic phase are normally not in direct contact with the environment and are therefore less likely to be subject to ecological adaptations and evolutionary change. As already suggested by Darwin, this alone could explain the lowered morphological divergence of early ontogenetic stages compared to adults, which would obviate the need to invoke particular constraints. Alternatively, the constraint hypothesis would suggest that it is difficult for newly evolved genes to become recruited to strongly connected regulatory networks.

They propose two alternatives, that the phylotypic stage is privileged and therefore isn’t being shaped by selection, or that it is constrained by the presence of a complicated gene network, and therefore is limited in the amount of change that can be tolerated. The first explanation doesn’t make sense to me: if a system is freed from selection, then it ought to diverge more rapidly, not less. I’m also baffled by the suggestion that the mid-stage embryos are not in direct contact with the environment. Of course they are…it’s just possible that that mid-development environment is more stable and more conserved itself.

What we need to know more about is the specifics of the full regulatory network. A map of the full circuitry, rather than just aggregate measures of divergence, would be nice. I’m looking forward to it!

The creationists aren’t, though.

Domazet-Loso, T., & Tautz, D. (2010). A phylogenetically based transcriptome age index mirrors ontogenetic divergence patterns. Nature 468 (7325): 815-818. DOI: 10.1038/nature09632

Kalinka, A., Varga, K., Gerrard, D., Preibisch, S., Corcoran, D., Jarrells, J., Ohler, U., Bergman, C., Tomancak, P. (2010). Gene expression divergence recapitulates the developmental hourglass model. Nature 468 (7325): 811-814 DOI: 10.1038/nature09634

There’s plenty of time for evolution

This is a familiar creationist argument, stated in this case by a non-creationist:

Consider the replacement processes needed in order to change each of the resident genes at L loci in a more primitive genome into those of a more favorable, or advanced, gene. Suppose that at each such gene locus, the argument runs, the proportion of gene types (alleles) at that gene locus that are more favored than the primitive type is K−1. The probability that at all L loci a more favored gene type is obtained in one round of evolutionary “trials” is K−L, a vanishingly small amount. When trials are carried out sequentially over time, an exponentially large number of trials (of order KL) would be needed in order to carry out the complete transformation, and from this some have concluded that the evolution-by- mutation paradigm doesn’t work because of lack of time.

Basically, what creationists argue is that the evolution of new genes is linear and sequential — there is no history, no selection, it works entirely by random replacement of the whole shebang, hoping that in one dazzling bit of luck that the entire sequence clicks into the right sequence, and then it all works. If that were the way the process occurred, then they’d be right, and evolution would be absurdly improbable and would take an untenable length of time.

Another way to think of it is a bizarre version of the hangman guessing game, where one person thinks of a word, and the second person has to guess what it is. In the normal version of the game, the second person guesses letters one by one, and they’re placed in the appropriate spot. In the creationist version, you only get to guess a whole sequence of letters in each round, and you are only told if you are right or wrong, not which letters are in the correct position in the word. Not only does it become a really boring game, but it also becomes extremely unlikely that anyone can solve it in a reasonable amount of time.

Evolution does not work like that. It works in parallel, changing and testing each variant simultaneously in many individuals, and then selection for the most favorable subset of changes latches them in place, making the matching letters more likely to be fixed. Or, as the paper by Wilf and Ewens explains,

But a more appropriate model is the following. After guessing each of the letters, we are told which (if any) of the guessed letters are correct, and then those letters are retained. The second round of guessing is applied only for the incorrect letters that remain after this first round, and so forth. This procedure mimics the “in parallel” evolutionary process. The question concerns the statistics of the number of rounds needed to guess all of the letters of the word successfully.

That’s the question. If purely random changes would require a ridiculous length of time to match a target, proportional to KL, how long would it take if we actually use more reasonable, biologically relevant model? Wilf and Ewens state the model in mathematical terms and derive a theoretical answer, and you won’t be surprised that it’s significantly shorter; you might be impressed at how much shorter the operation would take.

Instead of a time proportional to KL, it will take a time proportional to K log L.

That’s very much shorter! To put some representative numbers on it, imagine a protein that is 300 amino acids long, made up of 20 possible amino acids, and I’m going to ask you to guess the sequence. Under the creationist model, you wouldn’t even want to play the game — it would take you on the order of 20300 trials to hit that one specific arrangement of amino acids. On the other hand, if you took a wild guess, writing down a random 300 amino acids, and I then told you which amino acids in which position were correct, you’d be able to progressively work out the exact sequence in only 20 log 300 trials, or around 50 guesses.

Notice that this is not a concrete estimate of the time it would take for something to evolve! It’s a grossly simplified version of the story: the example overstates the power of selection (amino acids won’t be locked in, but will only be less likely to change), and overstates the required accuracy of matching to a target (there would be more tolerance for variation), and the whole idea of meeting a specific target is not necessarily a good model. As a guide to short-circuiting the invalid assumptions of creationists, though, it’s handy to have a simple mathematical formula to remove that naive combinatorial model from the table.

Wilf HS, Ewens WJ (2010) There’s plenty of time for evolution. arXiv:1010.5178v1.

It’s not an arsenic-based life form

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Oh, great. I get to be the wet blanket.

There’s a lot of news going around right now about this NASA press release and paper in Science — before anyone had read the paper, there was some real crazy-eyed speculation out there. I was even sent some rather loony odds from a bookmaker that looked like this:

WHAT WILL NASA ANNOUNCE?

NASA HAS DISCOVERED A LIFE FORM ON MARS +200 33%
DISCOVERED EVIDENCE OF LIFE ON ONE OF SATURNS MOON +110 47%
ANNOUNCES A NEW MODEL FOR THE EXISTENCE OF LIFE -5000 98%
UNVEILS IMAGES OF A RECOVERED ALIEN SPACECRAFT +300 25%
CONFESSES THAT AREA 51 WAS USED FOR THE ALIEN STUDIES +500 16%

[The +/- Indicates the Return on the Wager. The percentage is the likelihood that response will occur. For Example: Betting on the candidate least likely to win would earn the most amount of money, should that happen.]

I think the bookie cleaned up on anyone goofy enough to make a bet on that.

Then the stories calmed down, and instead it was that they had discovered an earthly life form that used a radically different chemistry. I was dubious, even at that. And then I finally got the paper from Science, and I’m sorry to let you all down, but it’s none of the above. It’s an extremophile bacterium that can be coaxed into substiting arsenic for phosphorus in some of its basic biochemistry. It’s perfectly reasonable and interesting work in its own right, but it’s not radical, it’s not particularly surprising, and it’s especially not extraterrestrial. It’s the kind of thing that will get a sentence or three in biochemistry textbooks in the future.

Here’s the story. Life on earth uses six elements heavily in its chemistry: carbon, hydrogen, nitrogen, oxygen, phosphorus, and sulfur, also known as CHNOPS . There are other elements used in small amounts for specialized functions, too: zinc, for instance, is incorporated as a catalyst in certain enzymes. We also use significant quantities of some ions, specifically of sodium, potassium, calcium, and chloride, for osmotic balance and they also play a role in nervous system function and regulation; calcium, obviously, is heavily used in making the matrix of our skeletons. But for the most part, biochemistry is all about CHNOPS.

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Here’s part of the periodic table just to remind you of where these atoms are. You should recall from freshman chemistry that the table isn’t just an arbitrary arrangement — it actually is ordered by the properties of the elements, and, for instance, atoms in a column exhibit similar properties. There’s CHNOPS, and notice, just below phosphorous, there’s another atom, arsenic. You’d predict just from looking at the table that arsenic ought to have some chemical similarities to phosphorus, and you’d be right. Arsenic can substitute for phosphorus in many chemical reactions.

This is, in fact, one of the reasons arsenic is toxic. It’s similar, but not identical, to phosphorus, and can take its place in chemical reactions fundamental to life, for instance in the glycolytic pathway of basic metabolism. That it’s not identical, though, means that it actually gums up the process and brings it to a halt, blocking respiration and killing the cell by starving it of ATP.

Got it? Arsenic already participates in earthly chemistry, badly. It’s just off enough from phosphorus to bollix up the biology, so it’s generally bad for us to have it around.

What did the NASA paper do? Scientists started out the project with extremophile bacteria from Mono Lake in California. This is not a pleasant place for most living creatures: it’s an alkali lake with a pH of close to 10, and it also has high concentrations of arsenic (high being about 200 µM) dissolved in it. The bacteria living there were already adapted to tolerate the presence of arsenic, and the mechanism of that would be really interesting to know…but this work didn’t address that.

Next, what they did was culture the bacteria in the lab, and artificially jacked up the arsenic concentration, replacing all the phosphate (PO43-) with arsenate (AsO43-). The cells weren’t happy, growing at a much slower rate on arsenate than phosphate, but they still lived and they still grew. These are tough critters.

They also look different in these conditions. Below, the bacteria in (C) were grown on arsenate with no phosphate, while those in (D) grew on phosphate with no arsenate. The arsenate bacteria are bigger, but thin sections through them reveal that they are actually bloated with large vacuoles. What are they doing building up these fluid-filled spaces inside them? We don’t know, but it may be because some arsenate-containing molecules are less stable in water than their phosphate analogs, so they’re coping by generating internal partitions that exclude water.

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What they also found, and this is the cool part, is that they incorporated the arsenate into familiar compounds*. DNA has a backbone of sugars linked together by phosphate bonds, for instance; in these baceria, some of those phosphates were replaced by arsenate. Some amino acids, serine, tyrosine, and threonine, can be modified by phosphates, and arsenate was substituted there, too. What this tells us is that the machinery of these cells is tolerant enough of the differences between phosphate and arsenate that it can keep on working to some degree no matter which one is present.

So what does it all mean? It means that researchers have found that some earthly bacteria that live in literally poisonous environments are adapted to find the presence of arsenic dramatically less lethal, and that they can even incorporate arsenic into their routine, familiar chemistry.

It doesn’t say a lot about evolutionary history, I’m afraid. These are derived forms of bacteria that are adapting to artificially stringent environmental conditions, and they were found in a geologically young lake — so no, this is not the bacterium primeval. This lake also happens to be on Earth, not Saturn, although maybe being in California gives them extra weirdness points, so I don’t know that it can even say much about extraterrestrial life. It does say that life can survive in a surprisingly broad range of conditions, but we already knew that.

So it’s nice work, a small piece of the story of life, but not quite the earthshaking news the bookmakers were predicting.

*I’ve had it pointed out to me that they actually didn’t fully demonstrate even this. What they showed was that, in the bacteria raised in arsenates, the proportion of arsenic rose and the proportion of phosphorus fell, which suggests indirectly that there could have been a replacement of the phosphorus by arsenic.

Wolfe-Simon F,
Blum JS,
Kulp TR,
Gordon GW,
Hoeft SE,
Pett-Ridge J,
Stolz JF,
Webb SM,
Weber PK,
Davies PCW,
Anbar AD, Oremland RS (2010) A Bacterium That Can Grow by Using Arsenic Instead of Phosphorus. Science DOI: 10.1126/science.1197258.

Lungs with taste, or lungs with a fortuitous receptor?

Researchers in Maryland have discovered an interesting quirk: lung smooth muscle expresses on its surfaces a protein that is the same as the bitter taste receptor. This could be useful, since they also discovered that activating that receptor with bitter substances causes the muscle to relax, opening up airways, and could represent a new way to treat asthma. That’s a fine discovery.

But man, it really tells us something about human psychology. I’m getting all this mail right now, and just about all of it asks the same question: Why do lungs have taste receptors? What is the purpose of sensing taste with the lungs? Even the investigators speculate this way:

Most plant-based poisons are bitter, so the researchers thought the purpose of the lung’s taste receptors was similar to those in the tongue — to warn against poisons. “I initially thought the bitter-taste receptors in the lungs would prompt a ‘fight or flight’ response to a noxious inhalant, causing chest tightness and coughing so you would leave the toxic environment, but that’s not what we found,” says Dr. Liggett.

Weird. I guess the teleological impulse really is etched deep into most people’s minds. I’m going to suggest that everyone just relax, let go, and embrace a simpler assumption.

There is no purpose.

That should be our default assumption. Gene regulatory networks are complicated, with expression of all kinds of genes coupled to other genes, so my first thought was that this was a simple biological accident, and totally unsurprising. I’ve looked at enough developmental gene expression papers to know that genes get switched on and off in all kinds of complicated patterns that have nothing to do with proximal function and everything to do with the network of connections between them; sometimes if gene A is active, the only ‘purpose’ is because A is coregulated by factor X which also switches on gene B, and B is the next step in a physiological or developmental program that is adaptive for the organism.

Another way to think of it: the handle on your teapot is wobbling loose, so you bring the home toolbox into the kitchen to tighten it up with your screwdriver. Your toolbox also contains wrenches and a hammer, but we don’t speculate that the reason you brought the hammer is that you need it right then to fix the teapot. The purpose of bringing the hammer is that it’s in the same handy toolbox as your screwdriver, which is not really a purpose at all.

Now the way evolution works is that this purposeless variation may fortuitously find a purpose — a gene in the T2R family of G-protein coupled receptors is uselessly misexpressed in the lungs, but a clever doctor finds a way to take advantage of it to treat asthma, or you may spot a vagrant mouse skittering across your kitchen counter, and suddenly the hammer becomes a useful implement of pest control — but the root of that innovation isn’t purpose, but purposelessness and serendipity.

There’s another reason to be unimpressed with the purpose of the expression of this gene in the lungs. Many of you may already be familiar with another quirk of the bitter receptor — its expression is variable in people. A common observation to make in genetics labs is the existence of non-tasters, tasters, and super-tasters to a substance called phenylthiocarbamide, or PTC. The mechanism of that is variability in this same kind of receptor gene now found to be expressed in lung tissue. Shouldn’t we be used to the random element of the expression of this gene by now?

Attenborough alert

Right now on Discovery…it’s First Life with David Attenborough, which is supposed to be about the origin of life on Earth. There’s a pretty severe metazoan bias, unfortunately, so it’s really about the origin of animals, but still it’s cool stuff about the Cambrian.

So that’s why Koch funded a major evolution exhibit

I was mystified why Chief Teabagger David Koch would invest so much in a Smithsonian exhibit on human evolution — usually those knuckledraggers object to people putting their ancestry on display. An explanation is at hand, though: his big issue is denying the significance of global climate change, and the exhibit is tailored to make climate change look like a universal good.

There are some convincing examples of the subterfuge being perpetrated. There is a big emphasis on how evolutionary changes were accompanied by (or even caused by) climate shifts, which evolutionary biologists would see as almost certainly true, and so it slides right past us. But, for instance, what they do is illustrate the temperature changes in a graph covering the last 10 million years, which makes it easy to hide the very abrupt and rapid rise in the last few centuries. They also elide over an obvious fact: we’d rather not experience natural selection. Climate change may have shaped our species, but it did so by killing us, by pushing populations around on the map, by famine and disease, by conflict and chaos. Evolution happened. That doesn’t mean we liked it.

I suppose it wouldn’t leap out at an evolutionary biologist because it is true: there have been temperature fluctuations and long term changes that have hit our species hard, and nobody is denying it. However, it’s a bit of a stretch to suggest that we should therefore look forward to melting icecaps and flooding seaboards and intensified storms. It’s probably also worth pointing out that our technological civilization is certainly more fragile than anything we’ve had before. The fact that we could be knocked back to a stone age level of technology without going extinct is not a point in favor of welcoming global warming.

Now we have a new question: how did this devious agenda get past the directors of the Smithsonian?