CAGEE: Computational Analysis of Gene Expression Evolution.

Despite the increasing abundance of whole transcriptome data, few methods are available to analyze global gene expression across phylogenies. Here, we present a new software package (Computational Analysis of Gene Expression Evolution [CAGEE]) for inferring patterns of increases and decreases in gene expression across a phylogenetic tree, as well as the rate at which these changes occur. In contrast to previous methods that treat each gene independently, CAGEE can calculate genome-wide rates of gene expression, along with ancestral states for each gene. The statistical approach developed here makes it possible to infer lineage-specific shifts in rates of evolution across the genome, in addition to possible differences in rates among multiple tissues sampled from the same species. We demonstrate the accuracy and robustness of our method on simulated data and apply it to a data set of ovule gene expression collected from multiple self-compatible and self-incompatible species in the genus Solanum to test hypotheses about the evolutionary forces acting during mating system shifts. These comparisons allow us to highlight the power of CAGEE, demonstrating its utility for use in any empirical system and for the analysis of most morphological traits. Our software is available at https://github.com/hahnlab/CAGEE/.

Allele frequency divergence reveals ubiquitous influence of positive selection in Drosophila.

Resolving the role of natural selection is a basic objective of evolutionary biology. It is generally difficult to detect the influence of selection because ubiquitous non-selective stochastic change in allele frequencies (genetic drift) degrades evidence of selection. As a result, selection scans typically only identify genomic regions that have undergone episodes of intense selection. Yet it seems likely such episodes are the exception; the norm is more likely to involve subtle, concurrent selective changes at a large number of loci. We develop a new theoretical approach that uncovers a previously undocumented genome-wide signature of selection in the collective divergence of allele frequencies over time. Applying our approach to temporally resolved allele frequency measurements from laboratory and wild Drosophila populations, we quantify the selective contribution to allele frequency divergence and find that selection has substantial effects on much of the genome. We further quantify the magnitude of the total selection coefficient (a measure of the combined effects of direct and linked selection) at a typical polymorphic locus, and find this to be large (of order 1%) even though most mutations are not directly under selection. We find that selective allele frequency divergence is substantially elevated at intermediate allele frequencies, which we argue is most parsimoniously explained by positive-not negative-selection. Thus, in these populations most mutations are far from evolving neutrally in the short term (tens of generations), including mutations with neutral fitness effects, and the result cannot be explained simply as an ongoing purging of deleterious mutations.

Mutation bias can shape adaptation in large asexual populations experiencing clonal interference.

The extended evolutionary synthesis invokes a role for development in shaping adaptive evolution, which in population genetics terms corresponds to mutation-biased adaptation. Critics have claimed that clonal interference makes mutation-biased adaptation rare. We consider the behaviour of two simultaneously adapting traits, one with larger mutation rate U, the other with larger selection coefficient s, using asexual travelling wave models. We find that adaptation is dominated by whichever trait has the faster rate of adaptation v in isolation, with the other trait subject to evolutionary stalling. Reviewing empirical claims for mutation-biased adaptation, we find that not all occur in the 'origin-fixation' regime of population genetics where v is only twice as sensitive to s as to U. In some cases, differences in U are at least ten to twelve times larger than differences in s, as needed to cause mutation-biased adaptation even in the 'multiple mutations' regime. Surprisingly, when U > s in the 'diffusive-mutation' regime, the required sensitivity ratio is also only two, despite pervasive clonal interference. Given two traits with identical v, the benefit of having higher s is surprisingly small, occurring largely when one trait is at the boundary between the origin-fixation and multiple mutations regimes.

Density-dependent selection and the limits of relative fitness.

Selection is commonly described by assigning constant relative fitness values to genotypes. Yet population density is often regulated by crowding. Relative fitness may then depend on density, and selection can change density when it acts on a density-regulating trait. When strong density-dependent selection acts on a density-regulating trait, selection is no longer describable by density-independent relative fitnesses, even in demographically stable populations. These conditions are met in most previous models of density-dependent selection (e.g. "K-selection" in the logistic and Lotka-Volterra models), suggesting that density-independent relative fitnesses must be replaced with more ecologically explicit absolute fitnesses unless selection is weak. Here we show that density-independent relative fitnesses can also accurately describe strong density-dependent selection under some conditions. We develop a novel model of density-regulated population growth with three ecologically intuitive traits: fecundity, mortality, and competitive ability. Our model, unlike the logistic or Lotka-Volterra, incorporates a density-dependent juvenile "reproductive excess", which largely decouples density-dependent selection from the regulation of density. We find that density-independent relative fitnesses accurately describe strong selection acting on any one trait, even fecundity, which is both density-regulating and subject to density-dependent selection. Pleiotropic interactions between these traits recover the familiar K-selection behavior. In such cases, or when the population is maintained far from demographic equilibrium, our model offers a possible alternative to relative fitness.

Statistical patterns in tropical tree cover explained by the different water demand of individual trees and grasses.

Tree cover varies enormously across tropical ecosystems-from arid savannas to closed rain forests-and yet a general predictive theory of tropical tree cover remains elusive. Here we use the maximum-entropy method to predict the most likely sample frequency distribution of ecosystems with different tree and grass fractional cover if balance between water supply and demand were the dominant constraint on community assembly. Assuming a hierarchy of individual plant water demand in which trees require more water than grasses, we reproduce observed trends in the means and the upper and lower limits of tropical tree and grass cover across the entire spectrum of tropical ecosystem water supply. Finer details not captured by our predictions indicate the influence of additional factors, such as disturbance. Our results challenge the view that tropical tree-grass coexistence is largely sustained by disturbances in moist environments ("unstable" coexistence) with water supply playing a dominant role only in arid conditions ("stable" coexistence). More generally, they suggest that macroecological patterns can be understood and predicted as the most likely outcome of a large number of stochastic processes being played out within a relatively small number of ecological constraints.

Human deleterious mutation rate implies high fitness variance, with declining mean fitness compensated by rarer beneficial mutations of larger effect.

Each new human has an expected Ud = 2 - 10 new deleterious mutations. This deluge of deleterious mutations cannot all be purged, and therefore accumulate in a declining fitness ratchet. Using a novel simulation framework designed to efficiently handle genome-wide linkage disequilibria across many segregating sites, we find that rarer, beneficial mutations of larger effect are sufficient to compensate fitness declines due to the fixation of many slightly deleterious mutations. Drift barrier theory posits a similar asymmetric pattern of fixations to explain ratcheting genome size and complexity, but in our theory, the cause is Ud > 1 rather than small population size. In our simulations, Ud ~2 - 10 generates high within-population variance in relative fitness; two individuals will typically differ in fitness by 15-40%. Ud ~2 - 10 also slows net adaptation by ~13%-39%. Surprisingly, fixation rates are more sensitive to changes in the beneficial than the deleterious mutation rate, e.g. a 10% increase in overall mutation rate leads to faster adaptation; this puts to rest dysgenic fears about increasing mutation rates due to rising paternal age.

Evolution Rapidly Optimizes Stability and Aggregation in Lattice Proteins Despite Pervasive Landscape Valleys and Mazes.

The "fitness" landscapes of genetic sequences are characterized by high dimensionality and "ruggedness" due to sign epistasis. Ascending from low to high fitness on such landscapes can be difficult because adaptive trajectories get stuck at low-fitness local peaks. Compounding matters, recent theoretical arguments have proposed that extremely long, winding adaptive paths may be required to reach even local peaks: a "maze-like" landscape topography. The extent to which peaks and mazes shape the mode and tempo of evolution is poorly understood, due to empirical limitations and the abstractness of many landscape models. We explore the prevalence, scale, and evolutionary consequences of landscape mazes in a biophysically grounded computational model of protein evolution that captures the "frustration" between "stability" and aggregation propensity. Our stability-aggregation landscape exhibits extensive sign epistasis and local peaks galore. Although this frequently obstructs adaptive ascent to high fitness and virtually eliminates reproducibility of evolutionary outcomes, many adaptive paths do successfully complete the ascent from low to high fitness, with hydrophobicity a critical mediator of success. These successful paths exhibit maze-like properties on a global landscape scale, in which taking an indirect path helps to avoid low-fitness local peaks. This delicate balance of "hard but possible" adaptation could occur more broadly in other biological settings where competing interactions and frustration are important.

Poly(d,l-Lactic acid) Composite Foams Containing Phosphate Glass Particles Produced via Solid-State Foaming Using CO2 for Bone Tissue Engineering Applications.

This study reports on the production and characterization of highly porous (up to 91%) composite foams for potential bone tissue engineering (BTE) applications. A calcium phosphate-based glass particulate (PGP) filler of the formulation 50P2O5-40CaO-10TiO2 mol.%, was incorporated into biodegradable poly(d,l-lactic acid) (PDLLA) at 5, 10, 20, and 30 vol.%. The composites were fabricated by melt compounding (extrusion) and compression molding, and converted into porous structures through solid-state foaming (SSF) using high-pressure gaseous carbon dioxide. The morphological and mechanical properties of neat PDLLA and composites in both nonporous and porous states were examined. Scanning electron microscopy micrographs showed that the PGPs were well dispersed throughout the matrices. The highly porous composite systems exhibited improved compressive strength and Young's modulus (up to >2-fold) and well-interconnected macropores (up to ~78% open pores at 30 vol.% PGP) compared to those of the neat PDLLA foam. The pore size of the composite foams decreased with increasing PGPs content from an average of 920 µm for neat PDLLA foam to 190 µm for PDLLA-30PGP. Furthermore, the experimental data was in line with the Gibson and Ashby model, and effective microstructural changes were confirmed to occur upon 30 vol.% PGP incorporation. Interestingly, the SSF technique allowed for a high incorporation of bioactive particles (up to 30 vol.%-equivalent to ~46 wt.%) while maintaining the morphological and mechanical criteria required for BTE scaffolds. Based on the results, the SSF technique can offer more advantages and flexibility for designing composite foams with tunable characteristics compared to other methods used for the fabrication of BTE scaffolds.

Different mechanisms drive the maintenance of polymorphism at loci subject to strong versus weak fluctuating selection.

The long-running debate about the role of selection in maintaining genetic variation has been given new impetus by the discovery of hundreds of seasonally oscillating polymorphisms in wild Drosophila, possibly stabilized by an alternating summer-winter selection regime. Historically, there has been skepticism about the potential of temporal variation to balance polymorphism, because selection must be strong to have a meaningful stabilizing effect-unless dominance also varies over time ("reversal of dominance"). Here, we develop a simplified model of seasonally variable selection that simultaneously incorporates four different stabilizing mechanisms, including two genetic mechanisms ("cumulative overdominance" and reversal of dominance), as well as ecological "storage" ("protection from selection" and boom-bust demography). We use our model to compare the stabilizing effects of these mechanisms. Although reversal of dominance has by far the greatest stabilizing effect, we argue that the three other mechanisms could also stabilize polymorphism under plausible conditions, particularly when all three are present. With many loci subject to diminishing returns epistasis, reversal of dominance stabilizes many alleles of small effect. This makes the combination of the other three mechanisms, which are incapable of stabilizing small effect alleles, a better candidate for stabilizing the detectable frequency oscillations of large effect alleles.

Directional Selection Rather Than Functional Constraints Can Shape the G Matrix in Rapidly Adapting Asexuals.

Genetic covariances represent a combination of pleiotropy and linkage disequilibrium, shaped by the population's history. Observed genetic covariance is most often interpreted in pleiotropic terms. In particular, functional constraints restricting which phenotypes are physically possible can lead to a stable G matrix with high genetic variance in fitness-associated traits, and high pleiotropic negative covariance along the phenotypic curve of constraint. In contrast, population genetic models of relative fitness assume endless adaptation without constraint, through a series of selective sweeps that are well described by recent traveling wave models. We describe the implications of such population genetic models for the G matrix when pleiotropy is excluded by design, such that all covariance comes from linkage disequilibrium. The G matrix is far less stable than has previously been found, fluctuating over the timescale of selective sweeps. However, its orientation is relatively stable, corresponding to high genetic variance in fitness-associated traits and strong negative covariance-the same pattern often interpreted in terms of pleiotropic constraints but caused instead by linkage disequilibrium. We find that different mechanisms drive the instabilities along vs. perpendicular to the fitness gradient. The origin of linkage disequilibrium is not drift, but small amounts of linkage disequilibrium are instead introduced by mutation and then amplified during competing selective sweeps. This illustrates the need to integrate a broader range of population genetic phenomena into quantitative genetics.

A Shift in Aggregation Avoidance Strategy Marks a Long-Term Direction to Protein Evolution.

To detect a direction to evolution, without the pitfalls of reconstructing ancestral states, we need to compare "more evolved" to "less evolved" entities. But because all extant species have the same common ancestor, none are chronologically more evolved than any other. However, different gene families were born at different times, allowing us to compare young protein-coding genes to those that are older and hence have been evolving for longer. To be retained during evolution, a protein must not only have a function, but must also avoid toxic dysfunction such as protein aggregation. There is conflict between the two requirements: hydrophobic amino acids form the cores of protein folds, but also promote aggregation. Young genes avoid strongly hydrophobic amino acids, which is presumably the simplest solution to the aggregation problem. Here we show that young genes' few hydrophobic residues are clustered near one another along the primary sequence, presumably to assist folding. The higher aggregation risk created by the higher hydrophobicity of older genes is counteracted by more subtle effects in the ordering of the amino acids, including a reduction in the clustering of hydrophobic residues until they eventually become more interspersed than if distributed randomly. This interspersion has previously been reported to be a general property of proteins, but here we find that it is restricted to old genes. Quantitatively, the index of dispersion delineates a gradual trend, i.e., a decrease in the clustering of hydrophobic amino acids over billions of years.

Sry delivery to the adrenal medulla increases blood pressure and adrenal medullary tyrosine hydroxylase of normotensive WKY rats.

BACKGROUND: Our laboratory has shown that a locus on the SHR Y chromosome increases blood pressure (BP) in the SHR rat and in WKY rats that had the SHR Y chromosome locus crossed into their genome (SHR/y rat). A potential candidate for this Y chromosome hypertension locus is Sry, a gene that encodes a transcription factor that is responsible for testes development and the Sry protein may affect other target genes. METHODS: The following study examined if exogenous Sry would elevate adrenal Th, adrenal catecholamines, plasma catecholamines and blood pressure. We delivered 10 mug of either the expression construct, Sry1/pcDNA 3.1, or control vector into the adrenal medulla of WKY rats by electroporation. Blood pressure was measured by the tail cuff technique and Th and catecholamines by HPLC with electrochemical detection. RESULTS: In the animals receiving Sry there were significant increases after 3 weeks in resting plasma NE (57%) and adrenal Th content (49%) compared to vector controls. BP was 30 mmHg higher in Sry injected animals (160 mmHg, p < .05) compared to vector controls (130 mmHg) after 2-3 weeks. Histological analysis showed that the electroporation procedure did not produce morphological damage. CONCLUSION: These results provide continued support that Sry is a candidate gene for hypertension. Also, these results are consistent with a role for Sry in increasing BP by directly or indirectly activating sympathetic nervous system activity.