Thursday, October 27, 2016

Causal complexity in life

Evolution is the process that generates the relationships between genomes and traits in organisms.  Although we have written extensively and repeatedly about the issues raised by causal complexity,  we were led to write this post by a recent paper, in the 21 October 2016 issue of Science, which discusses molecular pathways to hemoglobin (Hb) gene function.  Although one might expect this to be rather simple and genomically direct, it is in fact complex and there are many different ways to achieve comparable function.

The authors, C Nataragan et al.,  looked at the genetic basis of adaptation to habitats at different altitude, focusing on genes coding for Hb molecules, that transport oxygen in the blood to provide the body's tissues with this vital fuel.  As a basic aspect of our atmosphere, oxygen concentrations differ at different altitudes, being low in mountainous regions compared to lowlands.  Species must somehow adapt to their localities, and at least one way to to this is for oxygen transport efficiency mechanisms to differ at different elevations.  Bird species have moved into and among these various environments on many independent occasions.

The affinity of Hb molecules for, that is, ability to bind oxygen, depends on their amino acid sequence, and the authors found that this varies by altitude.  The efficiency is similar among species at similar altitudes, even if due to independent population expansions. But when they looked at the Hb coding sequences in different species, they found a variety of species-specific changes.  That is, there are multiple ways to achieve similar function, so that parallel evolution at the functional level, which is what Nature detects, is achieved by many different mutational pathways.  In that sense, while an adaptation can be predicted, a specific genetic reason cannot be.

The authors looked only at coding regions, but of course evolution also involves regulatory sequences (among other functional regions in DNA), so there is every reason to expect that there is even more complexity to the adaptive paths taken.

Important specific documentation....but not conceptually new, though unappreciated
The authors also looked at what they call 'resurrected ancestral' proteins, by experimentally testing the efficacy of some specific Hb mutations, and they found that genomic background made a major difference in how, or whether, a specific change would affect oxygen binding.  This shows that evolution is contingent on local conditions, and that a given genomic change depends on the genomic background.  The ad hoc, locally contingent nature of evolution is (or should be) a central aspect of evolutionary world views, but there is a widespread tendency to think in classical Mendelian terms, of a gene for this and a gene for that, so that one would expect similar results in similar, if independent areas or contexts.  This is a common, if often tacit, view underlying much of genome mapping to find genes 'for' some human trait, like important diseases.  But it is quite misleading, or more accurately, is very wrong.

In 2008 we wrote about this in Genetics, as we've done before and since here on MT and in other papers.  In the 2008 article we used the following image to suggest metaphorically the nature of this complex causation, with its alternative pathways and the like, where the 'trait' is the amount of water passing New Orleans on the Mississippi River.  The figure suggests how difficult it would be to determine 'the' causal source of the water, how many different ways there are to get the same river level.

Drainage complexity as a metaphor for genomic causal complexity.  Map by Richard Weiss and ArcInfo
One can go even further, and note that this is exactly the kind of findings that are to be expected from and documented by the huge list of association studies done of human traits.  These typically find a great many genome regions whose variation contributes to the trait, usually each with a small individual effect, and mainly at low frequency in the population.  That means that individuals with similar trait values (say, diabetes, obesity, tall, or short stature, etc.) have different genotypes, that overlap in incomplete and individually unique ways.

We have written about aspects of this aspect of life, in what we called evolution by phenotype, in various places.  Nature screens on traits directly and only on genes very indirectly in most situations in complex organisms.  This means that many genotypes yield the same phenotype, and these will be equivalent in the face of natural selection and will experience genetic drift among them even in the fact of natural selection, again because selection screens the phenotype.  This is the process we called phenogenetic drift.  These papers were not 'discoveries' of ours but just statements of what is pretty obvious even if inconvenient for those seeking simple genetic causation.

The Science paper on altitude adaptation shows this by stereotypical sequences from one individual each from a variety of different species, rather than different individuals within each species, but that one can expect must also exist.  The point is that a priori prediction of how hemoglobin adaptation will occur is problematic, except that each species must have some adaptation to available oxygen.  Parallel phenotype evolution need not be matched by parallel genotypic evolution because selection 'sees' phenotypes and doesn't 'care' about how they are achieved.

The reason for this complexity is simple: it is that this is how evolution working via phenotypes rather than genotypes molds the genetic aspects of causation.

6 comments:

Ken Weiss said...

I realize that in writing this post, I had neglected to thank Mike Joyner for pointing out the bird adaptation story (and noting the similarity to my Mississippi map analogy).

brainmoleculermarketing.com said...

Nice piece

Jim Gudgeon said...

Ken, the Mississippi river drainage metaphor is excellent. It helps me get closer to wrapping my brain around the challenges of extending genomic testing into "healthy" populations; my current concern with "extended" gene panels on wanna be parents to weed out bad eggs and sperm or, when applied prenatally, to guide termination of pregnancies that are otherwise healthy. I've tried to simulate (modeling) the rate of false positives in contrast to true positives, but have failed to understand to assign plausible numbers to the various nodes in the model. Your explanation helps me understand, i think, why this is so difficult.

Ken Weiss said...

Thanks, Jim. You might find a paper by John Edwards from the 1960s interesting: 'The Simulation of Mendelism'. If you can't find it, I can send you a reprint. Falconer, in the 1960's edition of his book on quantitative genetics (or somewhere) has a figure making a similar point (I can send that, too if you want): parent offspring correlations can lead a qualitative trait, that's the result of an underlying quantitative phenotype, appear 'Mendelian'

Allan Hotti said...

Just as faces and fingerprints are phenotypic and unique to an individual, might not an individual's conglomerate of particular biologic pathways (biology in toto) be a unique phenotype as well? (assuming it can be described)

Ken Weiss said...

I would say clearly, yes.