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Layers and layers….

There is the fact of evolution. And then there is the long-standing debate of how it proceeds. The former is a settled question with little intellectual juice left. The latter is the focus of evolutionary genetics, and evolutionary biology more broadly. The debate is an old one, and goes as far back as the 19th century, where you had arch-selectionists such as Alfred Russel Wallace (see A Reason For Everything) square off against pretty much the whole of the scholarly world (e.g., Thomas Henry Huxely, “Darwin’s Bulldog,” was less than convinced of the power of natural selection as the driving force of evolutionary change). This old disagreement planted the seeds for much more vociferous disputations in the wake of the fusion of evolutionary biology and genetics in the early 20th century. They range from the Wright-Fisher controversies of the early years of evolutionary genetics, to the neutralist vs. selectionist debate of the 1970s (which left bad feelings in some cases). A cartoon-view of the implication of the debates in regards to the power of selection as opposed to stochastic contingency can be found in the works of Stephen Jay Gould (see The Structure of Evolutionary Theory) and Richard Dawkins (see The Ancestor’s Tale): does evolution result in an infinitely creative assortment due to chance events, or does it drive toward a finite set of idealized forms which populate the possible parameter space?*

But ultimately these 10,000 feet debates are more a matter of philosophy than science. At least until the scientific questions are stripped of their controversy and an equilibrium consensus emerges. That will only occur through an accumulation of publications whose results are robust to time, and subtle enough to convince dissenters. This is why Enard et al.’s preprint, Genome wide signals of pervasive positive selection in human evolution, attracted my notice. With the emergence of genomics it has been humans first in line to be analyzed, as the best data is often found from this species, so no surprise there. Rather, what is so notable about this paper in light of the past 10 years of back and forth exploration of this topic?**

By taking a deeper and more subtle look at patterns of the variation in the human genome this group has inferred that adaptation through classic positive selection has been a pervasive feature of the human genome over the past ~100,000 years. This is not a trivial inference, because there has been a great deal of controversy as to the population genetic statistics which have been used to infer selection over the past 10 years with the arrival of genome-wide data sets (in particular, a tendency toward false positives). In fact, one group has posited that a more prominent selective force within the genome has been “background selection,” which refers to constraint upon genetic variation due to purification of numerous deleterious mutations and neighboring linked sites.

The sum totality of Enard et al. may seem abstruse, and even opaque, in terms of the method. But each element is actually rather simple and clear. The major gist is that many tests for selection within the genome focus on the differences between nonynonymous and synonymous mutational variants. The former refer to base positions in the genome which result in a change in the amino acid state, while the latter are those (see the third positions) where different bases may still produce the same amino acid. The ratio between substitutions, replacements across lineages for particular base states, at these positions is a rough measure of adaptation driven by selection on the molecular level. Changes at synonymous positions are far less constrained by negative selection, while positive selection due to an increased fitness via new phenotypes is presumed to have occurred only via nonsynonymous changes. What Enard et al. point out is that the human genome is heterogeneous in the distribution of characteristics, and focusing on these sorts of pairwise differences in classes without accounting for other confounding variables may obscure dynamics on is attempting to measure. In particular, they argue that evidence of positive selective sweeps are masked by the fact that background selection tends to be stronger in regions where synonymous mutational substitutions are more likely (i.e., they are more functionally constrained, so nonsynonymous variants will be disfavored). This results in elevated neutral diversity around regions of nonsynonymous substitutions vis-a-vis strongly constrained regions with synonymous substitutions. Once correcting for the power of background selection the authors evidence for sweeps of novel adaptive variants across the human genome, which had previous been hidden.

There are two interesting empirical findings from the 1000 Genomes data set. First, the authors find that positive selection tends to operate upon regulatory elements rather than coding sequence changes. You are probably aware that this is a major area of debate currently within the field of molecular evolutionary biology. Second, there seems to be less evidence for positive selection in Sub-Saharan Africans, or, less background selection in this population. My own hunch is that it is the former, that the demographic pulse across Eurasia, and to the New World and Australasia, naturally resulted in local adaptations as environmental conditions shifted. Though it may be that the African pathogenic environment is particularly well adapted to hominin immune systems, and so imposes a stronger cost upon novel mutations than is the case for non-Africans. So I do not dismiss the second idea out of hand.

Where this debate about the power of selection will end is anyone’s guess. Nor do I care. Rather, what’s important is getting a finer-grained map of the dynamics at work so that we may perceive reality with greater clarity. One must be cautious about extrapolating from humans (e.g., the authors point out that Drosophila genomes are richer in coding sequence proportionally). But the human results which emerge because of the coming swell of genomic data will be a useful outline for the possibilities in other organisms.

Citation: Genome wide signals of pervasive positive selection in human evolution

* The cartoon qualification is due to the fact that I am aware that selection is stochastic as well.

** Voight, Benjamin F., et al. “A map of recent positive selection in the human genome.” PLoS biology 4.3 (2006): e72., Sabeti, Pardis C., et al. “Detecting recent positive selection in the human genome from haplotype structure.” Nature 419.6909 (2002): 832-837., Wang, Eric T., et al. “Global landscape of recent inferred Darwinian selection for Homo sapiens.” Proceedings of the National Academy of Sciences of the United States of America 103.1 (2006): 135-140., Williamson, Scott H., et al. “Localizing recent adaptive evolution in the human genome.” PLoS genetics 3.6 (2007): e90., Hawks, John, et al. “Recent acceleration of human adaptive evolution.” Proceedings of the National Academy of Sciences 104.52 (2007): 20753-20758., Pickrell, Joseph K., et al. “Signals of recent positive selection in a worldwide sample of human populations.” Genome research 19.5 (2009): 826-837., Hernandez, Ryan D., et al. “Classic selective sweeps were rare in recent human evolution.” Science 331.6019 (2011): 920-924.

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Genetics has numerous uses. There are some biologists for whom genetics implies very specific chemical and physical properties of a particular flavor of DNA molecule. Consider a scientist focused on the biophysical properties of zinc finger proteins and the ZYF gene. Then there are biologists for whom genetics is a more abstract and evolutionary enterprise. David Haig and the late W. D. Hamilton fall into this class of thinkers. This is a way of looking at genetics as the scaffold or currency of evolutionary process. Finally, there are those for whom genes are simply discrete convenient markers to trace out historical and spatial patterns. The field of molecular ecology describes this attitude, though the application of phylogenetic techniques from the life sciences in linguistics illustrates the generality of these methodologies.

A new paper in PNAS, Biophysical mechanisms for large-effect mutations in the evolution of steroid hormone receptors, is neat because it breaks down these sorts of artificial barriers spectacularly. Here’s the abstract:

The genetic and biophysical mechanisms by which new protein functions evolve is a central question in evolutionary biology, biochemistry, and biophysics. Of particular interest is whether major shifts in protein function are caused by a few mutations of large effect and, if they are, the mechanisms that mediate these changes. Here we combine ancestral protein reconstruction with genetic manipulation and explicit studies of protein structure and dynamics to dissect an ancient and discrete shift in ligand specificity in the steroid receptors, a family of biologically essential hormone-controlled transcription factors. We previously found that the ancestor of the entire steroid receptor family was highly specific for estrogens, but its immediate phylogenetic descendant was sensitive only to androgens, progestogens, and corticosteroids. Here we show that this shift in function was driven primarily by two historical amino acid changes, which caused a ∼70,000-fold change in the ancestral protein’s specificity. These replacements subtly changed the chemistry of two amino acids, but they dramatically reduced estrogen sensitivity by introducing an excess of interaction partners into the receptor/estrogen complex, inducing a frustrated ensemble of suboptimal hydrogen bond networks unique to estrogens. This work shows how the protein’s architecture and dynamics shaped its evolution, amplifying a few biochemically subtle mutations into major shifts in the energetics and function of the protein.

The paper spans several fields, and I can’t comment too much about the biophysics, though it is broadly comprehensible (a long time ago I studied biochemistry, so I have a reasonable background in chemistry). In short you have two lineages of these receptors which are implicated in modulating the expression of specific genes associated with particular hormones. This is normally the domain of molecular genetics and biochemistry, as you focus on proximate biomolecular pathways in a series of cascades, which often operate through regulation of genes in specific tissues and at specific times. The interesting aspect of this paper is that they baked into interpretation and analysis evolutionary and phylogenetic insights, which serve as a framing background for the biophysics. In short it looks as if the two different lineages of receptors are differentiated by very subtle, but functionally highly significant, changes. To test the implications of the evolutionary reconstruction they used both simulations and experimental methods.

The major take away is that what seems like a minor change which results in minimal changes to the amino acid sequence and little visible structural shifts in the steroid nevertheless perturbs the affinities of the proteins radically. This is not theoretically implausible, but, it is excellent to actually examine the phenomenon from all directions as they have here. The evolutionary aspect of the paper is just the skeleton, the real flesh is illustrating biophysically how the substitutions resulted in energetic alternations and shifts in the nature of molecular interactions. Too often when we think of evolutionary process we focus on coarse morphology which is human scale comprehensible. But one could argue that such radical biochemical changes in organisms, over two orders of magnitude, are themselves macroevolutionary changes.

An implication of this result may be that evolution mediated by genetic changes is far more slippery a phenomenon than we may have imagined. Changes in morphology are relatively amenable to our intuition in terms of the fitness implications (e.g., changes in size and shape suited to climates or relevant for intra-specific competition). Not only are they human scaled, but they are often preserved by fossilization, and so are accessible for paleontology. In contrast evolutionary shifts on the molecular scale leave only telltale markers in the genome which we have to infer. The complexity of protein-protein interactions are such that robust analytical models are hard to come by (at least last I checked). If a major focus of evolutionary biology in the future is going to be on large effect mutations altering macromolecular function, then we may be flying somewhat blind for a while. But that’s alright, science proceeds by admissions of ignorance before the long crawl back up the hill.

Citation: Harms, Michael J., et al. “Biophysical mechanisms for large-effect mutations in the evolution of steroid hormone receptors.” Proceedings of the National Academy of Sciences (2013).

🔊 Listen RSS One of the great things about evolutionary theory is that it is a formal abstraction of specific concrete aspects of reality and dynamics. It allows us to squeeze inferential juice from incomplete prior knowledge of the state of nature. In other words, you can make predictions and models instead of having to observe every last detail of the natural world. But abstractions, models and formalisms often leave out extraneous details. Sometimes those details turn out not to be so extraneous. Charles Darwin’s original theory of evolution had no coherent or plausible mechanism of inheritance. R. A. Fisher and others imported the empirical reality of Mendelism into the logic of evolutionary theory, to produce the framework of 20th century population genetics. Though accepting the genetic inheritance process of Mendelism this is original synthesis was not informed by molecular biology, because it pre-dated molecular biology. After James Watson and Francis Crick uncovered the biophysical basis for Mendelism molecular evolution came to the fore, and neutral theory emerged as a response to the particular patterns of genetic variation which new molecular techniques were uncovering. And yet through this much of R. A. Fisher’s image of an abstract genetic variant floating against a statistical soup of background noise variation persisted, sometimes dismissed as “bean bag genetics”.

We’ve come a long way from the first initial wave of discussions which were prompted by the molecular genetic revolution. We have epigenetics, evo-devo and variation in gene regulation. None of these processes “overthrow” evolutionary biology, though in some ways they may revolutionize aspects of it. Science is over the long haul after all an eternal revolution, as the boundaries of comprehension keep getting pushed outward. A few days ago I pointed to Sean Carroll’s recent work, which emphasizes that one must think beyond the sequence level, and focus on particular features such as cis-regulartory elements. Here we’ve been tunneling down to the level of the gene, but what about the traits, the phenotypes, which are affected by genetic variation?

It is well known that the sparest abstraction of genotypic-phenotypic relationship can be illustrated like so:

genetic variation → phenetic variation

But each element of this relation has to be examined greater detail. What type of genetic variation? Sequence level variation? Epigenetic variation? The second component is perhaps the most fraught, with the arrow waving away the myriad details and interactions which no doubt lurk between genotype and phenotype. And finally you have the phenotype itself. Are they all created alike in quality so that we can ascribe to them dichotomous values and quantities?

A new paper in PNAS examines the particulars of morphological phenotypes and physiological phenotypes, and their genetic control, as well as rates of evolution. Contrasting genetic paths to morphological and physiological evolution:

The relative importance of protein function change and gene expression change in phenotypic evolution is a contentious, yet central topic in evolutionary biology. Analyzing 5,199 mouse genes with recorded mutant phenotypes, we find that genes exclusively affecting morphological traits when mutated (dubbed “morphogenes”) are grossly enriched with transcriptional regulators, whereas those exclusively affecting physiological traits (dubbed “physiogenes”) are enriched with channels, transporters, receptors, and enzymes. Compared to physiogenes, morphogenes are more likely to be essential and pleiotropic and less likely to be tissue specific. Morphogenes evolve faster in expression profile, but slower in protein sequence and gene gain/loss than physiogenes. Thus, morphological and physiological changes have a differential molecular basis; separating them helps discern the genetic mechanisms of phenotypic evolution.

Morphology here refers to gross anatomical features. The sort of traits and characteristics which a paleontologist or anatomist might take interest in. Physiology is more about function, and the physical structures which enable that function. It is naturally closer to the scale of molecular biology as physiology melts into biochemistry. Of course at the other end physiology also merges with anatomy as physiology occurs within features of interest to the anatomist. By way of generalization perhaps physiology may be considered more granular, while morphology more gross, in the context of this paper.

They used the mouse because it’s a species which has long served as a model organism, and there are a host of well known and characterized mutations for both physiology and morphology. Utilization of mice in these fields in the context of evolutionary research dates back to the early 20th century. So systems biologists have a lot of research that’s already been done to work with. They found 5199 mouse genes with known phenotypes in the Mouse Genome Informatics database. 821 affected only morphological traits and 912 affected only physiological traits.

Figure 1 shows the breakdown by Gene Ontology:


Going by what little I know about these topics the second to the fourth panels aren’t surprising. Morphological traits are built from molecular structures, while the transporter activity classes are a more cellular scale, and so would seem to be below the threshold of salience for morphological traits. The first panel is not something I’d expected, but it makes sense after the fact. Figure 2 clarifies. The right panels have proportions, the left counts.


The primary point is this: morphogenes seem to affect more traits than physiogenes, and, their affect is less tissue specific when it comes to a particular trait. When this pattern is highlighted the enrichment toward transcriptional regulation makes more sense to me it is transcriptional regulation might allows for more trait by trait level control of variation. If there is a relationship of many traits to one gene that would probably impose a constraint on the sequence level to a greater extent than if the gene was implicated in variation on one trait. The gap in pleiotropy is closed somewhat when you constrain to essential genes, those whose mutation results in decrease of fitness to zero (through death or lack of ability to reproduce). Pleiotropy presumably is constraining the genetic landscape toward particular fitness peaks. Tissue specificity seems understandable when you consider the localization of many physiological processes, and their biochemical complexities (I’m thinking of the vagaries of gene expression in the liver here).

But they looked at more than how the traits and genes distribute now, they tried to sniff out if there were differences in the rate of evolution of morphogenes and physiogenes contingent upon the class of genetic variants. Remember that you have sequent level changes on exons which can alter proteins. You have cis-acting elements as critical cogs in gene regulation. And you have more gross genomic features such as gene duplication or deletion.

morphfig3Figure 3 shows the differences between mice and humans on particular genes in relation to sequence level substitutions as well as gene expression profiles. Specifically in the case of the former you want to know the rate of nonsynonymous substitution, those substitutions at base pairs which change the amino acid translated, standardized by the overall mutation rate. So panel C is the one to focus on. Note that physiogenes seem to have evolved more since the last divergence between human and mice lineages than morphogenes. Why might this be? An immediate thought that comes to mind is that tissue-specific expressing physiological processes are liable to be modulated more often than gross morphology, which might be controlled by genes with a lot of pleiotropic effects and so constrained. Even when you control to tissue-specificity the pattern remains, as evident in panel D. The pattern seems somewhat inverted in relation to rate of evolution when it comes to gene expression profiles, as you can see in the last three panels. Evolution happens, but by somewhat different genetic means in these cases. The authors finger pleiotropy in particular as the problem for sequence level evolution in morphogenes, as changes in proteins are much more likely to be problematic if those proteins are upstream from many more traits.

In a way these results show that evolution has to be a versatile designer. When it comes to physiogenes the illustrator is in charge, creating new traits from the most basic genetic raw material, changes in a base pair here and a base pair there. But for morphogenes evolution has to use the tools and tricks of photoshopping, making recourse to extant elements and rearranging or tweaking things here and there so as not to upset the complex applecart while modulating on the margins.

What about cis-acting regulatory elements? In the paper they allude to the argument of Sean Carroll that cis-acting regulatory elements are critical for the evolution of morphological traits. That would imply that morphogenes should be enriched vis-a-vis physiogenes for changes on these elements. They didn’t find that in figure 4. On the contrary.


But I don’t think they perceive their result as a rock-solid refutation of Carroll because it was somewhat indirect. I’ll quote from the paper:

…Because experimentally confirmed mammalian cis elements are few, are likely to have been confirmed in only one species, and are potentially biased toward certain classes of genes,we tested the above hypothesis by using cis-elements that were predicted exclusively by motif sequence conservation among a set of vertebrate genome sequences and recorded in the cisRED database (20). In cisRED, 8,440 predicted mouse cis-elements and 7,688 predicted human cis-elements were found to be in the proximity of 586 mouse morphogenes and their human orthologs, respectively. Similarly, 7,082 mouse cis-elements and 7,215 human cis-elements were predicted for 621 physiogenes….

I’m inclined to accept this result and its generalizability, but there’s a layer of analysis and modeling in this case which doesn’t exist in the others. Additionally, Carroll’s thesis is about the whole animal kingdom and a mouse-human comparison may be atypical.

Finally they wanted to look at gene duplication. They found:

Together with the D fam result, our analyses show that, whereas physiogene families expand/contract faster than morphogene families, the rate of expansion/contraction is relatively constant across lineages for a given family.

I wonder if the duplication here might have something to do with modulating dosages of various substrates in biochemical processes. This may have more direct relevance to physiological processes.

It is important to note as they did that the category “morphogene” and “physiogene” is somewhat artificial, as is the distinction between morphology and physiology. Nature is fundamentally one, and we break it apart as particular joints for ease of our own abstractions and categorizations. Additionally all genes presumably have some effect on morphology and physiology, and though this exploration looks under the hood a bit more than some of the older abstractions it too is a simplification. The key is that the argument here seems to be that these breaking apart of categories and processes gives us useful marginal return in comprehension of evolutionary dynamics. A trait is not always just a trait. Different classes of phenotypes may have different evolutionary genetic implications by their very nature. Some of this is common sense, those traits which are less functionally significant will exhibit more genic variation. But distinctions in terms of form and function themselves are at a further level of detail. And, I presume that generalizations that we make from mouse-human comparisons as here have some limitations across the tree of life.

Citation: Liao BY, Weng MP, & Zhang J (2010). Contrasting genetic paths to morphological and physiological evolution. Proceedings of the National Academy of Sciences of the United States of America PMID: 20368429

Razib Khan
About Razib Khan

"I have degrees in biology and biochemistry, a passion for genetics, history, and philosophy, and shrimp is my favorite food. If you want to know more, see the links at"