The Vampire Monologs: Ancient DNA and the un-dead?

Tuesday's news stories reveal that Bulgaria rather than Romania (Transylvania) has provided us with some skeletal remains of what are being claimed to have been vampires.  According to a story on the BBC, "Archaeologists in Bulgaria have found two medieval skeletons pierced through the chest with iron rods to supposedly stop them from turning into vampires."  Fortunately, once living, and then not-so living, they were thus driven, so to speak, from the un-dead to the really, truly dead.   We all (or at least young, nubile ladies with accessible necks) should be relieved at this news.  But it also portends  important science, if done carefully.

Vampire skeleton. Source: BBC

We're told by Bram Stoker in the classic 1897 Dracula that vampires are recruited from the living by other vampires. I don't recall if it's explained how the first vampire came to not-be.  Nor how the legendary vampires are mainly males.  I'll leave that to others to study.

What's actually relevant for MT readers is the genetic questions posed by these discoveries.  The skeletons are recent enough that the bones will contain DNA that is in good enough condition to be sequenced.  Normally this would be called 'ancient DNA' (denoted aDNA), but a more relevant term for these rather recently un-deceased would be vDNA.  What will it show?  Will we be able to find the gene 'for' vamping?  How will the scientists do this?

Source: Flickr CC photo by Mugley

Vampires pose serious problems for evolutionary genetics, that are too intricate to go into in a mere blog post, and I plan to write about this in the near future, and report the findings to the NY Times rather than this puny blog outlet.  But there are some less grandiose issues posed by vDNA.  First, what would one expect to see?  

The sequence should show clear similarity to modern eastern Europeans.  Overall, there should be no particular trait that would reveal the vampire status of the individual.  Indeed, if vampires are randomly recruited, what we need to know is whether some people (like Mina Harker) were genetically susceptible to being vamped, or not.  If not, of course we have the conundrum that, since we're routinely informed (by the NY Times and the major journals) that everything human must have a genetic cause.  So we must assume some genetic difference.

This is a challenge, because we now know that any two copies of the human genome--even the two that you carry--differ by millions of nucleotides.  Therefore, to find the vampire susceptibility variation we might be looking for a family of genes, call them Vam1, Vam2,..., and so on that are responsible.  Since all genes are already known from human DNA sequence, we must simply have mislabeled these genes.  Many genes' functions are not known, and the Vam genes must be among them.  However, why do they even exist if only some women ever become vamps (not to mention male vampires)?  This poses one of the key evolutionary questions raised by vampirehood, since our view of evolution is that it has no foresight, so Vam genes can't have evolved for their future adaptive value in the Caucasus.

This suggests that there aren't really any Vam genes after all.  Instead we must search for variation in known genes that yield susceptibility to being vamped.  It's easy to imagine how that could be. For example, genes conferring long, luscious necks on women, or that make a woman want to wear low-necked blouses, could easily have the allure that is needed for them to be among the Chosen.

Vampire, Edvard Munch

But we don't know the genes 'for' necks (or low-neck shirt wearing), and what GWAS have clearly shown without doubt is that such traits are complex with many contributing genes.  As a result, we need to identify many places in the genome, where variants will generally only contribute a minor amount.  As we know with other disorders like diabetes, heart disease, and the genetically based Gullibility Predilection to believing that Everything is Genetic (the high frequency GPEG allele), we need large samples to find the critical variants in the sea of millions of rare but useless variants each of us carries.  Rather than Vam genes, what we seek are, shall we call them, genetic V-ariants.

That means, of course, that we must first of all do whole-genome sequencing and collect very large case-control samples to ferret out the V-ariant elements, and therein lie two V-ery serious challenges!

First, how on earth will we find enough cases?  We need to find the skeletons (or undead cadavers in current dungeon coffin residences) of a huge number of vampires--these days, the state of the art requires that we ascertain hundreds of thousands!  But how on (or under the) earth, this side of the Styx, could we find such a horde?  We need to compare their un-dead vDNA with that of the not-yet-dead DNA of living people.  We can't just dig up graveyards, or rummage around everybody's  basement, because how would we know which corpses were, or might have been, vampires?  This exemplifies the second challenge, which is how can we even obtain adequate controls?

Reading vDNA: a real problem in genetic cryptography!
You might be aware (most geneticists don't seem to be) that while controls are defined as being unaffected by the trait in question, many of them will  become future cases--that is their DNA is susceptible even if classified as 'unaffected' or 'normal'.  That means that until we know who will become un-dead in the future, we don't know whose DNA doesn't contain V-ariants!

A typical GWAS kind of approach, to salvage this situation, might be to select as controls only women who typically wear turtlenecks.  They might be the least likely to carry the susceptibility variants (if indeed susceptibility is linked to making ones neck alluringly available).  Otherwise, how do we match our cases with adequate controls?

If it turns out, as it surely will, that hundreds or thousands of genes in vDNA as in living DNA contain V-ariants, then we will face the horrible, or horrifying, problem that most of us carry some of the V-ariants, but we can't really know who.  A geneticist, even the usual type seeking attention, may be reluctant to stick her neck out with only weak evidence.  So as we walk and work among the living, we have no way to know if, at the end of the day as the phrase goes, we'll later walk among the un-dead...

48th CoE

The 48th Carnival of Evolution is now up at PZ Myer's Pharyngula blog.  Lots of good evolution-related posts. 

No need to come in out of the rain

Now this is cool. Leave it to engineers.  A paper in the June 4 issue of the Proceedings of the National Academy of Sciences finally provides the answer to a question we've all been wondering about all our lives.  What happens to insects when they're hit by raindrops?

As Dickinson et al. point out, water drops can weigh more than 50 times what a mosquito weighs.  So, when hit by a water drop, does an insect crash to the ground?  Outfly it?  Not notice a thing?

In fact, they say

A mosquito’s strong exoskeleton and low mass renders it impervious to falling drops. The mosquito’s low mass causes raindrops to lose little momentum upon impact and so impart cor- respondingly low forces to the mosquitoes. Our findings demonstrate that small fliers are robust to in-flight perturbations. 

Mosquito and raindrop, Dickinson et al.

The effect of rain on larger flying objects like bats and planes is well understood, but not on smaller things.  The effect of in-flight perturbations such as wind on insects has been studied as well (bees extend their legs in an effort to stay upright and on course, e.g.), and it's not a surprise that it turns out that insects have numerous ways to correct for such perturbations in flight.  It is known that many insects are able to repel large water drops to some extent (which is why insecticides are generally sprayed as fine mists), but the effects of rain on flapping flight haven't yet been studied.  Until now.

The authors calculate that the probability of a mosquito being hit by a raindrop during heavy rain is high.  And the impact on the legs and wings is 3 times more probable than on the body, given the insect's body shape.  To evaluate the effect, they set up a contained space which they vibrated so that the mosquitoes wouldn't land on the walls, and sprayed water in from the top to emulate rain.

They first wanted to catch the effects of a 'terminal-velocity' drop, so they sprayed a jet of water into the container.  Getting drops to hit the insects was apparently quite a challenge, but they finally did see and record this event six times.

A mosquito is rapidly accelerated downward upon collision with the jet. Continued perturbations with the jet tumble the mosquito repeatedly... After tumbling a distance of 39 mm, or 13 body lengths, the mosquito finally separates laterally from the jet and lands on the side of the container. The six mosquitoes tested each separated from the jet before striking the bottom of the 20-cm tall chamber. It was noteworthy that all the mosquitoes survived the collision, as shown by their flight after a brief resting period. These experiments confirm that mosquitoes can survive impact with terminal-velocity raindrops, which have even less momentum than the jets used.

If you have access to the PNAS site, there's a lovely movie of all this in action, with explanations.

If a mosquito is hit by a water drop at lower velocity, the drop might cause the mosquito to yaw or pitch a bit, but it very quickly recovers.  And, as predicted, the wings and legs were more likely to be hit but if the insect receives a direct body blow, it falls 5-20 body lengths at the speed of the drop but then is able to separate itself from the water and continue its flight.  This suggests that the drop imparts very little of its force to the insect, but it also suggests that the mosquito shouldn't fly too low during a rainstorm.

Clearly, mosquitoes are able to survive impacts from both low- and high-speed drops. In the collision of two bodies, the outcome is known to be highly dependent on the masses involved. We thus hypothesize that mosquitoes survive drop impacts by virtue of their low mass: Specifically, the low mass of mosquitoes causes a falling drop to maintain most of its speed after impact and apply a correspondingly low impact force to the mosquitoes.  

They test this hypothesis in a number of ways using mosquito mimics.  They found that raindrops didn't splash, they deformed when they hit the mimic, and drop deformation is inversely proportional to drop size.  "A small drop suffers a larger change in speed and larger deformation than a large drop, keeping all other conditions the same." This allows the engineers to estimate the force of impact upon the mosquito.  And, they conclude that 

the momentum and force imparted to the insect is determined entirely by the insect’s mass relative to the drop. The mosquito is so lightweight that the resulting force imparted upon it is low, enabling a mosquito to survive flying in the rain. This result is in stark contrast to the resulting force on immobile surfaces for which splashing and large momentum transfers occur.   

Although the raindrop force imparted to a mosquitoes is low, the mosquito’s low mass causes the concomitant acceleration to be quite high. Insects struck by rain may achieve the highest survivable accelerations (100–300 g) in the animal kingdom. In comparison, the current champions of generating acceleration are fleas, which experience 135 g when jumping. The similarity between these maximal accelerations may suggest a fundamental limit to survival among organisms.

  The BBC cites one of the authors explaining why the impact of raindrops on insects is so minimal,

MAV

Describing the the results, Dr Hu cited the Chinese martial art of Tai chi.

"There is a philosophy that if you don't resist the force of your opponent, you won't feel it," he explained.

"That's why they don't feel the force; they simply join the drop, become one item and travel together."

But why would engineers be thinking about any of this at all?  OK, yeah, it's interesting to think about how insect flight evolved, and they do give a nod to this, but mostly it's because of flying robots (or rather, "micro-airborne flying vehicles"-- MAVs), envisioned for use in surveillance, search-and-rescue and who knows what else.  The concern is what will happen to these tiny flying objects when it rains.  "Not much" is the answer that will make engineers working on these things happy.

Steal This Book! Computer simulation and scientific theory

Abbie Hoffman

In the riotous protest times of the '70s, leading protester Abbie Hoffman published Steal This Book, "a manual of survival in the prison that is Amerika."  Of course, one must assume that Hoffman wasn't too opposed to the system to decline any royalties, nor that he really meant for copies to be stolen: presumably the idea was to read the book and understand the realities of society at the time.  Then you could choose to accept or fight the system, or at least understand it and what it's doing to you.

We devote a lot of effort in MT to commenting on and, yes, criticizing what we believe are deserving targets in contemporary science, especially as relates to genetics and evolution. We premised MT on ideas in our book of the same name, because we think evolution and an over stress on simplified genetic causal thinking diverts attention from many aspects of biology that we feel are at least as important.

People resist learning some lessons we think they should learn, perhaps largely out of ignorance (though in many ways intentionally not facing what might dampen various vested interests). 

With Brian Lambert, I have developed a highly general and flexible computer simulation program called ForSim, for simulating genetic causation and its evolution.  Its dual major purposes are first, to generate simulated, but realistic, data to test various theories and detection methods for complex phenotypes--such as those so intensely being pursued by GWAS and other methods.   Users can simulate the data and then sample it in various ways (families, case-control studies, etc.) to see how much and how one can find of what is known (because the simulation generates all the data required) to be the truth.  Secondly, the evolution of that genetic architecture within and between populations can be simulated, to understand how genetic effects change.

ForSim is a net-effects program, that omits many important aspects of genetic + environmental causation, such as those that make up the bulk of the book MT.  Thus, it greatly oversimplifies reality. But it tries to be natural in many ways (future additions will explicitly allow simulation of gene networks, developmental biology, and episodic traits like some diseases).

ForSim is a complex, intricate program and most readers of this blog would not be interested in or attempt to use it.  Fine, that's not our point. Our point in mentioning it is that just to see what is involved in complex traits and their evolution is a sobering lesson in why we object to simplistic ideas and rosy promises. 

ForSim execution flow

If one absorbs the message, one should be less sanguine or naive about what is being promised and found (or not) in the real world.  And one can get a sense of why we say what we do!  We did not invent biological complexity or the reasons why gene mapping (GWAS and similar approaches) are struggling as they are (as reflected rather clearly in the flood of papers aggressively praising their dramatic success).

We don't expect you to use ForSim, but if you're interested in seeing just what is involved in even a restricted evolutionary simulation, read the ForSim book!  You don't have to steal it, because the Manual can be downloaded here.  It's free (as is the program for any MT reader who might want to try it).

Again, we're not advertising anything from which we make any monetary or other gain.  We use the program, but just reading the Manual can be very instructive.  We wrote the program, and use it, and talk about it, because one way or another we think everyone, scientists and public alike, should be made aware of the realities of the causal complexity that so often is an inherent part of life.

But....wait!  What exactly is computer simulation?  Can't you simulate anything you want, the way a video game simulates Dungeons and Space Fighters?  Isn't what we really need an improved actual theory, some laws of life that really work well in terms of relating your genes to your traits?  Surprisingly, the answer is yes, you can simulate anything you want, but no, simulation isn't inferior to other kinds of theory even in this same respect.  We'll explain that next time.

Whole genome sequencing, yes or no?

We all should have our genomes sequenced
Does it strike anyone else as odd that Science has published an article recommending that everyone have their whole genome sequenced for medical purposes, written by the CEO of a DNA sequencing company? Odd as in conflict of interest? Of course the guy thinks everyone should have it done! And surely preferably by his company? How on Earth are we supposed to evaluate his arguments without taking into account his vested interest?

But, ok, let's soldier on anyway. He argues that rather than the ad hoc sequencing now being done for known causal variants or to look for novel ones, "[a] more effective approach might be to routinely sequence individuals' entire genome once, preferably early in life, and to continue to use this information to make health-care decisions throughout their lifetime."

Well, this might in fact be more useful than targeted genotyping or sequencing when the clinician is looking for a novel mutation in a known gene for a Mendelian disease, that is, one known to be caused by single genes. But a decade of experience with GWAS has shown that Mendelian diseases are much less common than polygenic diseases, for which the full suite of associated genes are proving to be difficult to identify. Never mind the full suite, any genes with more than small effect.

But, you say, eventually we'll figure those out, and it will prove useful to have our whole genome sequence.

Well, not necessarily. Not when everyone's genome is unique, and there are multiple genetic pathways it's probably safe to say to every disease or disorder, plus environmental factors, and the environment is impossible to predict. So, if we're going to be able to predict anything with whole genomes, it's most likely going to prove to be just about what we can now predict with much cheaper, much simpler, targeted tests for the maybe 3000 Mendelian diseases for which causal mutations are currently and clearly known.

What about people with apparently genetic disorders whose causal gene is not known? Can't those be identified with whole genome sequencing? Well, there are a number of "single-gene" disorders that are so-called even when a mutation in a known gene is not found in everyone with the same condition. In such cases, often we define the trait in terms of its causal gene (reminiscent of how the Obama administration defines a terrorist as being whoever they kill with a drone strike), leaving others with the same problem but no known gene without a diagnosis, or ignored by research. Or we may make the mistake of thinking the gene can only be causal if its protein-sequence is altered, whereas it's possible the cause is the gene's regulation in some people.

Such traits are often rather rare, with a substantial fraction not gene-specific as far as currently known, and hence many are not well understood, and don't attract much research money. Now, everyone has 3 - 4 million sequence variants relative to the reference human genome, which means that the likelihood of identifying the cause of such a disorder, particularly when it's not familial, even if we had whole genome sequence, is slim.

That is, even if the cause is simple, and genetic, the number of possible variants among different people, in various places in the genome, can be such that it will usually not be possible to identify a causal mutation from sequence data. Exceptions will be found, of course, and they'll be touted in Nature or Science or the New York Times as justifying the overall costly enterprise, when the funds could be much more usefully spent on things already known but without known treatment.

So, if a whole genome sequence can't be used to explain a disorder like one of these, nor to predict common diseases like heart disease, obesity, asthma, etc., and testing for Mendelian disorders is already possible and readily done, then why again should we all be paying people like the author of the Science paper to give us our whole genome sequence at birth?

Not so fast!
All that said, a second paper in the June 1 Science does urge constraint. The authors rightly say that "the vast majority of genomic data is, at this time, not medically actionable." And, the authors further point out, and obviously we agree, that how multiple risk variants combine in additive, multiplicative, or compensatory ways to inform clinical risk is largely unknown. In addition, data from studies of disease concordance in monozygotic twins suggest that for many common diseases, such as cancer, a negative test result from WGS data would not appreciably reduce an individual's risk relative to the baseline population risk and would therefore not enable meaningful medical intervention. The challenge is to identify and validate genotypes via WGS that are robustly associated with disease phenotype and with effect sizes, sensitivity, and specificity that enable counseling about risk beyond what is predicted by traditional clinical factors.

Oh, and look what else they say: "A particular concern is that some of those making claims about the application of WGS may not be considered objective or dispassionate because of their commercial or even academic interests."  Apparently we're not the only people who noticed.

The authors also say that there aren't nearly enough trained interpreters of the data, which will constrain making sense of it once it starts rolling. This, though, assumes that it can be made sense of! (See above.) But, they further point out that clinical reasoning is Bayesian, meaning it depends on prior knowledge of the patient's symptoms. Knowing symptoms can determine what the clinician gleans from a patient's sequence; the same sequence in a healthy patient might be interpreted quite differently.

And finally, they point out that with few exceptions, genetic testing rarely leads to improved health outcomes. Apologists for untrammeled big science regularly argue that, yes, it may be a while, but we'll eventually figure complex causation out using such data and reap its rewards long-term. That is possible but is also possibly a rationale--or excuse--for keeping the taps open. After all, there are other more likely successfully researchable problems that the same funds could make more with.

Note also that the genomic techniques will have most population impact on common diseases that develop during life. It's clear that these mainly require environmental effects, and risk estimates are perforce made after the fact. The same genotype's risk, if any, may be very different in the future because our lifestyles change so rapidly as is very, very well known. Current risk estimates are clearly off, perhaps way off, but we have literally no way to know since we can't predict future lifestyle exposures. So there is a serious built-in problem that nobody seems interested in acknowledging.

There are always nay-sayers and resistance to bold, arrogantly asserted futuristic claims, mostly associated with demand for lots of public resources. Some technologies unambiguosly aid science, and nobody can doubt that DNA sequencing is one of many like that. But that's not the same as saying it should be applied to everything someone has a whim for. Of course, there is huge momentum of all sorts, sincere but also heavily vested, to keep the foot on the accelerator--but the gas being used is yours.

A lot of people were unhappy when Ken suggested in an April post that the push for whole genome sequencing may be fading. Well, if it's not fading, we reiterate: it should at least be tempered, and we're gratified to see that the authors of one of these papers would agree.

Sexy...but

MT readers who are interested in fundamental aspects of evolution, and human evolution in particular, might find the post on the Molecular Evolution blog interesting.  There are a couple of posts on a kind of rat that has no Y chromosome, nor any SRY gene, both of which are assumed to be central to sex-determination in humans and mammals generally.

Sex determination is complex and variable among lineages of animals (and plants), but within major groups usually follows a particular pattern.  In mammals, the Y chromosome has some genes, but not many and few seem to be necessary for sex-determination (for example, they also exist on the X chromosome, which is present in both males and females).

Insects, birds, and so on determine sex in different ways, each interesting and presenting challenges to explain how the transition of one mechanism evolved from another.  I once wrote an article for Evolutionary Anthropology on this subject, in the context of the curious fact, at least as then known, that bdelloid rotifers had no sexual reproduction, which seemed quite strange.

Sex determination is to be distinguished from 'gender' (sex-associated behavior) or sexual preference, and there are many if not most sex-related traits not located on the X or Y chromosome.  But to have no Y chromosome and yet have sex and sex-related traits like behavior, means that the functions must have been adopted by other genetic mechanisms.  Apparently, judging from the ME post, these are not known for the spiny rats.

The specifics of rat genetics are of little direct relevance to humans, except to the extent that they raise a caution flag, warning us not to be too simplistic or categorical in our assertions about sex, even within our own species.  We seem pretty much married, so to speak, to our XX/XY system, but the evolutionary fluidity of sex-related genetic mechanisms, and the high variability of our own behaviors, suggest that things are far more variable and less clearly or simply determined than we might think.

Bright people and a coffee pot?

We've just finished a couple of posts on the nature or state of the kind of science that we're largely up to in the life and evolutionary sciences.  We gave a long list of reasons why our precision and rigor are simply far, far below that of physicists and chemists, who have long sneered at the imprecision of evolution and social science.

True, much of biology is not the same kind of science, but there are areas in which social, life, and evolutionary science are every bit as rigorous.  In the social sciences, some aspects of statistical sampling--as in birth and death rates and the like, are very sophisticated.  And of course in many different areas, the life sciences are just as rigorously molecular as chemistry and physics.  DNA does exist, after all, and does code for protein, and sequences do evolve phylogenetically, and so on.

But not just negative!
We complain about the business as usual, or even hyperbolic aspects of those areas of social, behavioral, evolutionary, and 'omic' sciences that are not up to snuff.  But this is not just being negative!  That's because what we know, and what it does not enable us to predict or explain precisely is real knowledge about the world.  That is positive knowledge, even if it's not what we'd like to have found.

But where what's afoot is interpretation and action based on 'judgment', as one of our Commenters suggested (correctly), with poor predictive power, and where our idea of prediction is really based on retrodiction (fitting causal ideas to existing data) and this is not yielding clearly powerful prediction, then this is not like physics and chemistry at the level of daily practice.  Those fields have their blurry edges, but more of a rigorous component.

There is no reason to think the same approaches we've been doing will solve the problem, if the complexity being discovered is real and being interpreted correctly, and the problem is our inability to make precisely specific predictions.  It's here where we question the investment in just keeping the system running, the belief people have in policy makers advised by the same professoriate, and the run o' the mill self-perpetuating university system.  We are not making these issues up!  We just harp on them, and we do that knowing few if any will listen, but perhaps of those who do, somebody will come up with a better way to do things.  You can go down the street and order up a cinnamon latte at Starbucks, but it's not possible to order up genius and transformative discovery just by putting out a request for proposals (RFP) for brilliant novelty! 

There is an historical model for how to stimulate it, however, and perhaps we could try it.

Bell Labs and Xerox
In the mid-20th century a few companies set up basic science labs. The companies had brilliant new products and plenty of ready money (or they were a monopoly and didn't have to worry about the profit bottom line).  The classic example was perhaps Bell Labs, but people also mention Xerox, Land (Polaroid) and a few others in the US, for being places that did manage to stimulate truly innovative thinking.

Basically, some bright (even wacky) people were put in a building where they couldn't avoid bumping into each other on a regular basis--e.g., they had access to only one bathroom. They were given a coffee pot.  And the door was shut.  "Just think about things," was their mandate.  From time to time the boss went in and asked if they'd been actually working, and if so had they discovered anything....even anything useful?   Of course the rest, as they say, was history.  Innovation, not just incremental changes, poured forth.

There are institutes for 'advanced' study (modestly self-named!) in various places.  Most famous is Princeton's because brilliant mathematicians and physicists including Einstein were there (but did real innovation arise, or were people there mainly after their guns had largely been fired?), and there's one at Stanford for the behavioral sciences.  Complexity became a watchword of our time, and the Santa Fe Institute, in which I have an external faculty appointment, were established with initially private funding to tackle the problem of complexity.  There's a new institute called the Evolution Institute  that we've just learned of and been in discussion with, that has innovative ambitions and internet presence, that aims to stimulate interactions designed to use 'evolutionary principles' to do good in the world.  How successful they will be as well as how such principles are decided on or evaluated remains to be seen, but at present they depend on grants and hustling donors, which is a warning sign, because that kind of dependency puts pressure to be predictable and in that sense safe, rather than truly innovative--as university research clearly shows.

Maybe these groups will succeed.  But in our view, success is more likely by attempting Bright People with a Coffee Machine in locked buildings, rather than the basically universal fancy PR, web sites, and the rest of the window dressing, often frankly self-promoting, rather than true, quiet risk-taking.  Endowment with substantial funding and few strings attached is the way at least to try to stimulate such things.  And it should not go to already well-known, award-winning scientists, but somehow work through the middle-class degree mill to find the odd-balls who can really think; many major new industries were founded by college drop-outs--and the distancing from the stultifying atmosphere of universities goes way back and includes some of the most brilliant scientists ever.  They include Einstein, Darwin, Wordsworth, and others.  There's a message there!  But there's absolutely no guarantee.

And if the result of the inhabitants' work is not a preponderance of failures, then they're not trying hard enough, and shut the place down!