The "If"s of Natural Selection

We write a lot about genetic determinism here on MT because unfortunately it's everywhere, but we probably don't turn enough of our attention to its corollary, the assumed certainty that traits are here because of adaptive natural selection.  Everyone knows about 'survival of the fittest' and that therefore traits are here because they served a purpose, often if not usually treated as if a specific purpose, in our evolutionary past.  Even those who clearly recognize that selection, when it occurs, is usually highly probabilistic, still talk the talk of determinism as if the adaptationist assumption is latent in their thinking.

Bushy eyebrows (Darwin's)

It's easy to make up a story about how and why a trait evolved.  That's because if you assume everything has an adaptive explanation in order to be here, what is here must have such an explanation;  as scientists, of course, it's up to us to say what that is.  Thus, we've got bushy eyebrows to shield our eyes from the sun; East Africans are fast runners because they were cattle thieves and had to run fast in order to survive, and the story that appeared just last week in the Proceedings of the Royal Society B, that Neandertals had larger eye sockets to be able to see better in the long, dark northern nights, and so were out-competed by our more successful ancestors who, with smaller eyes, could devote more of their cortex to higher thought processes, specifically involving those required for social organization.

But it's fair to say that these kinds of explanations are usually Just-So stories.  Made up since there is no direct evidence for the distant past, and perhaps even plausible, but untestable.  We've said enough times to get into trouble that really, the most robust selection story we have is probably that of malaria and sickle cell (and other anemias that are protective), that these traits evolved as protection against malaria around 10,000 years ago.  Other stories running close behind are lactose tolerance and skin color -- early humans were all lactose intolerant until various groups domesticated dairy animals and adults began to subsist on dairy products, and skin color lightened as humans moved north because of the need for vitamin D.

But even those stories leak a bit.  Remember that for a trait to evolve by natural selection, those with the trait had to have more children than those without.  For many many generations.  But it's at least a bit forced to argue that lactose intolerance systematically lowers the number of children its carriers have.  It may cause occasional or even frequent discomfort, but it's rarely lethal. People report becoming accustomed to it.  It is argued that in times of food shortage, adults can gain nutrition by drinking milk.  But in times of drought what are the cows drinking?  And if there's inadequate food for agricultural humans who held cattle, why would there be cattle food?  Wouldn't the grass have died too?  Whether they or other arguments are true, the issues are not given very close consideration.  So even if there is a lot of good-looking circumstantial evidence, should we really conclude definitively that milk drinking was a strong selective force in the not so distant past?

Skin color lightened because of the need to make vitamin D in northern climes, when sunlight isn't as strong for much of the year?  But, we're able to store vitamin D for months at a time, so probably don't need to make it all year round.  Plus, estimates of required vitamin D levels differ wildly.  Further, darker skinned people tend to have lower vitamin D levels than lighter skinned, on average, yet they also have fewer bone breaks, a marker of bone density and a serious consequence of inadequate vitamin D.  Could the link between vitamin D and bone mineralization be more complex than we realize, or could there be an additional mineralization pathway, as yet unidentified?

Even if we were to grant that these issues can be resolved and the adaptive stories are correct, it is important to note that of all our traits, and our many thousands of functional genomic elements, there are precious few stories of such genetic adaptation that have persuasive documentation.  This is consistent with a much less deterministic view of adaptation, especially if one looks at the gene level.

Normally, estimates of fitness -- very, very difficult to identify directly even in the present, unless involving human activity like antibiotic or herbicide resistance -- are that the difference between the 'fitness' conferred by the better allele at a gene even under rather strong selective pressure is only about 1%.  If continuous, and deterministically systematic, a 1% advantage would indeed lead the 'good' allele to replace the 'bad' one.  But the advantage is that if I carry the good one, I have 100 children while my bad-allele-carrying neighbor has a mere 99!  This is not even testable in most natural human populations, which were in demes too small.

In our book, The Mermaid's Tale, we described natural selection this way:

Natural selection means the systematic differential reproductive success of competing organisms. The idea is simple: if a species over-reproduces so that not all individuals in the next generation can go on to successfully reproduce, and if there is variation in form among that species, and if some forms of an organism do better in a particular environment than other forms, and if the reason for this is included in their heritable genome, and if the environment remains stable long enough over time for this form to be favored persistently, and if the favorable forms are also lucky enough to produce offspring who go on to reproduce, and if they produce more offspring than their competition, then those forms can become ever more common over time at the expense of their competition. If all these contingencies do occur, indeed co-occur, then the more prolific life form will become more suited—better adapted—to the environment in question. If the forms are sequestered from each other by some mating barrier, then they would diverge over time, and this was the explanation Darwin and Wallace proposed for the origin as well as specialization of species.

This reasoning is beyond doubt, and is essentially what Darwin and Wallace were suggesting.  But it hinges on the many ifs. Clearly, natural selection is always possible, and often important, sometimes over-ridingly so. At the same time, it has been too easy to assume the ifs. But when the selective differences are small, or highly variable over time, selection is not as much like a systematic force of nature as its usual image. A force is forever, and it has both strength and direction. Instead, and aside from the importance of chance, it is more accurate and realistic to view natural selection as more nuanced, and as only one of many contributing ways in which life’s success is determined.

A force is infinitesimally divisible (and this, a kind of Newtonian-force model, was explicitly Darwin's idea), but there is far too much chance that affects survival and fertility for  selection to be that kind of force in nature, at least as a rule.

We are all too enamored of simple explanations.  We are happy when we learn that this gene is 'for' that trait, and that trait evolved 'for' this purpose. But that is sloppy thinking that is fundamentally inaccurate, and it is not good science, despite its appeal to the media looking for dramatic stories and simple dog-eat-dog explanations, and despite it being a widespread image of life in many health and life sciences.

Genomic scientists wanted: Healthy skepticism required

Everyone makes mistakes
...but geneticists make them more often.  A Comment in this week's Nature, "Methods: Face up to false positives" by Daniel MacArthur and accompanying editorial are getting a lot of notice around the web.  MacArthur's point is that biologists are too often too quick to submit surprising results for publication, and scientific journals too eager to get them into print.  Much more eager than studies that report results that everyone expected.

This is all encouraged by a lay press that trumpets these kinds of results often without understanding them and certainly without vetting them.  Often results are simply wrong, either for technical reasons or because statistical tests were inappropriate, wrongly done, incorrectly interpreted or poorly understood.  The evidence of this is that journals are now issuing many more retractions than ever before.

Peer review catches some of this before it's published, but not nearly enough; reviewers are often overwhelmed with requests and don't give a manuscript enough attention or sometimes aren't in fact qualified to do so adequately.  And journal editors are clearly not doing a good enough job.

But, as MacArthur says, "Few principles are more depressingly familiar to the veteran scientist: the more surprising a result seems to be, the less likely it is to be true."  And, he says, "it has never been easier to generate high-impact false positives than in the genomic era." And this is a problem because

Flawed papers cause harm beyond their authors: they trigger futile projects, stalling the careers of graduate students and postdocs, and they degrade the reputation of genomic research. To minimize the damage, researchers, reviewers and editors need to raise the standard of evidence required to establish a finding as fact.

It's, as the saying goes, a perfect storm.  The unrelenting pressure to get results that will be published in high-impact journals, and then The New York Times, which can make a career -- i.e., get a post-doc a job or any researcher more grants, tenure, and further rewards -- combined with journals' drive to be 'high-impact' and newspapers' need to sell newspapers all discourages time-consuming attention to detail.  And, as a commenter on the Nature piece said, in this atmosphere "any researcher who [is] more self-critical than average would be at a major competitive disadvantage."

That time-consuming attention to detail would include checking and rechecking data coming off the sequencer, questioning surprising results and redoing them, driven by the recognition that even the sophisticated technology biologists now rely on for the masses of data they are analyzing can and does make mistakes.  Which is why sequencing is often done 30 or more times before it's deemed good enough to believe.  But doing it right takes money as well as time.

Skepticism required
And a healthy skepticism (which we blogged about here), or, as the commenter said, some self-criticism.  You don't have to work with online genomic databases very long before it becomes obvious -- at least to the healthy skeptic -- that you have to check and recheck the data.  Long experience in our lab with these data bases has taught us that they are full of sequence errors that aren't retracted, annotation errors, incorrect sequence assemblies and so on.  And, results based on incorrect data are published and not retracted, but very obvious to, again, the healthy skeptic who checks the data. MacArthur cautions researchers to be stringent with quality control in their own labs, which is essential, but they also need to be aware that publicly available data are not error-free, so that results from comparative genomics must be approached with caution as well. 

We've blogged before about a gene mapping study we're involved in.  We've approached it as skeptics, and, we hope, avoided many common errors that way.  This of course doesn't mean that we've avoided all errors, or that we'll reach important conclusions, but at least our eyes are open.

But just yesterday we ran into another instance of why that's important, and how insidious database errors can be.  We are currently characterizing the SNPs (variants) in genes that differ between the strains of mice we're looking at to try to identify which are responsible for morphological differences between them.

The UCSC genome browser, an invaluable tool for bioinformatics, can show in one screen the structure of a gene of choice for numerous mammals.  One of the ways a gene is identified is by someone having found a messenger RNA 'transcript' (copy) of the DNA sequence.  That shows that the stretch of DNA that looks as if it might be a gene actually is one.  We were looking at a gene that our mapping has identified as a possible candidate of interest and noticed that it was much much shorter in mice than in any of the other mammals shown.  If we had just asked the data base for mouse genes in this chromosome region, we'd have retrieved just this short transcript.  We might have accepted this without thinking and moved on, but this is a very unlikely result given how closely related the listed organisms are so we knew enough to question the data.

But we checked the mouse DNA sequence and other data and, sure enough, longer transcripts corresponding more closely to what's been reported in other mammals have been reported in mice.  And additional parts of the possible gene, that correspond to what is known to be in other mammal transcripts, also exist in the mouse DNA.  This strongly suggests that nobody has reported the longer transcript, but that it most likely exists and is used by mice.  Thus, variation in the unreported parts of the mouse genome might be contributing to the evidence we found for an effect on head shape. But it took knowledge of comparative genomics and a healthy skepticism to figure out that there was something wrong with the original data as presented.

Not a new realization
There is a wealth of literature showing many reasons why first-reports of a new finding are likely to be misleading--either wrong or exaggerated. This is not a matter of dishonest investigators! But it is a matter of too-hasty ones. The reason is that if you search for things, those that by pure statistical fluke pop out are the ones that are going to be noticed. If you're not sufficiently critical of the possibility that they are artifacts of your study design, and you take the results seriously, you will report them to the major journals. And your career takes off!

A traditional football coach once said of forward passes, that there are three things that can happen (incomplete, complete, intercepted) and only one of them is good....so he didn't like to pass. Something similar applies here: If you are circumspect, you may

1. later have the let-down experience of realizing that there was some error--not carelessness, just aspects of luck or things like problems with the DNA sequencer's ability to find variants in a sample, and so on.

2. Then you don't get your first Big Story paper, much less the later ones that refine the finding (that is, acknowledge it was wrong without actually saying so).

3. Worse, if it's actually right but you wait til you've appropriately dotted your i's and crossed your t's, somebody else might find the same thing and report it, and they get all the credit! You may be wrong and later data dampens your results, but nobody remembers the exaggeration, Nature and the NY Times don't retract the story, your paper still gets all the citations (nobody 'vacates' them the way Penn State's football victories were vacated by the NCAA), you already got your merit raise based on the paper.....you win even when you lose!

So the pressures are on everyone to rush to judgment, and the penalties are mild (here, of course, we're not talking about any sort of fraud or dishonesty). Again, many papers and examples exist pointing the issues out, and the subject has been written about time and again. But in whose interest is it to change operating procedures?

Even so, it's refreshing to see this cautionary piece in a major journal. Will it make a difference? Not unless students are taught to be skeptical about results from the very start. And the journals' confessions aren't sincere: Tomorrow, you can safely bet that the same journals will be back to business as usual.

Reading the thoughts of a dead salmon: a poignant tale

How do our brains translate sound waves into information about how far away the sound generator is from our ears?  The direction a sound is coming from is pretty easy to decipher because the sound hits our ears at different times; the difference is minute but enough for our brains to make sense of with respect to where the sound originates.  Distance is another question.  And what about soft-but-nearby vs loud-but-distant?  How does our brain distinguish between these two?

A Scientific American blog, The Scicurious Brain, posted on just this subject the other day, and we're happy it caught our eye.  Scicurious describes a new paper in PNAS by Kopco et al., "Neuronal representations of distance in human auditory cortex."  That is, it's basically an fMRI (functional magnetic resonance imaging) study of where activity happens in the brain when people hear sounds at different distances.

The researchers exposed 12 subjects to sounds of different intensities in a 'virtual reverberant environment', simulating sound coming from 15-100 cm away.  They conclude that neurons in a particular part of the brain (posterior nonprimary auditory cortices, that is a part of the brain already known to be involved in making sense of sound waves) are "sensitive to intensity-independent sound properties relevant for auditory distance perception".  I.e., this part of the brain determines the distance of a sound, at least within 100 centimeters.  How it does so is another question entirely.

fMRI results, Kopco et al.

So, this study doesn't really tell us a whole lot more than we knew before, and Scicurious points out that fMRI studies should be interpreted with caution.  Indeed, she says -- and this is why we love her post -- you can get fMRI signal from a dead fish.  Alas, that finding was reported in 2009 -- so sorry we didn't know about it until now!

Neuroscientist Craig Bennett purchased a whole Atlantic salmon, took it to a lab at Dartmouth, and put it into an fMRI machine used to study the brain. The beautiful fish was to be the lab’s test object as they worked out some new methods.

So, as the fish sat in the scanner, they showed it “a series of photographs depicting human individuals in social situations.” To maintain the rigor of the protocol (and perhaps because it was hilarious), the salmon, just like a human test subject, “was asked to determine what emotion the individual in the photo must have been experiencing."

If that were all that had occurred, the salmon scanning would simply live on in Dartmouth lore as a “crowning achievement in terms of ridiculous objects to scan.” But the fish had a surprise in store. When they got around to analyzing the voxel (think: 3-D or “volumetric” pixel) data, the voxels representing the area where the salmon’s tiny brain sat showed evidence of activity. In the fMRI scan, it looked like the dead salmon was actually thinking about the pictures it had been shown.

“By complete, random chance, we found some voxels that were significant that just happened to be in the fish’s brain,” Bennett said. “And if I were a ridiculous researcher, I’d say, ‘A dead salmon perceiving humans can tell their emotional state.’”

One readily criticizes seances and crystal balls, because we feel that conjuring is a scam rather than a science.  It is not possible to read someone else's thoughts, certainly not if they are among the dearly departed.  Or so we had thought.  Because if dead salmon can think, why not dead Aunt Mazie? 

We are not psychologists or neuroscientists, though we are scientists of a sort and we perhaps have a lot of nerve.  But we don't have enough nerve to challenge the usefulness of fMRI, not after universities have all bought their $1 Million instruments and boasted about how modern they now are.  We feel we should temper our tendency to think that salmon can't really have afterthoughts.  People have, we must admit, often reported 'near-death' experiences, but they weren't actually totally dead at the time!  But a salmon that was cold as a dead fish should not be sending out brain waves.  Of course we are assuming that there wasn't a short in the investigators' fMRI machine. An alternative of course is that there really is an afterlife, and its afterglow appears in the brain for a while--at least thinkers at seminaries should pay close attention to these startling findings.

We cannot personally attest to whether one can communicate with salmon by seance, because it has never crossed our minds to attempt it.  Nor have we any views on whether the cadavers of other fish (or amphibian) species might have similar postmortem brainwaves.  For the same reason, we must cease our glib assertions that "dead men tell no tales," and remain mute about your ability to get in touch with old Aunt Mazie.

Many many fMRI scans have been done since 2009 when the dead salmon results were publicized, so clearly dead fish thinking haven't dimmed researchers' enthusiasm for or faith in the method.  No test is perfect, and every test is at risk of yielding false positives or false negatives, and fMRIs are obviously no exception.   Nor are seances.  There are statistical corrections that can be made to fMRI results -- we don't know of any for seance results -- because fMRI readings have a lot of 'natural noise.'  But added to all the other caveats about fMRI's -- and the fact that whether or not we accept the fMRI findings about where in the brain we process information about how far away a sound is coming from, we still don't know how the brain does it -- we'll retain our skepticism about how much fMRI's can really tell us about ourselves.