The divergence of mean phenotypes under persistent directional selection

Numerous organismal traits, particularly at the cellular level, are likely to be under persistent directional selection across phylogenetic lineages. Unless all mutations affecting such traits have large enough effects to be efficiently selected in all species, gradients in mean phenotypes are expected to arise as a consequence of differences in the power of random genetic drift, which varies by approximately five orders of magnitude across the Tree of Life. Prior theoretical work examining the conditions under which such gradients can arise focused on the simple situation in which all genomic sites affecting the trait have identical and constant mutational effects. Here, we extend this theory to incorporate the more biologically realistic situation in which mutational effects on a trait differ among nucleotide sites. Pursuit of such modifications leads to the development of semi-analytic expressions for the ways in which selective interference arises via linkage effects in single-effects models, which then extend to more complex scenarios. The theory developed clarifies the conditions under which mutations of different selective effects mutually interfere with each others' fixation and shows how variance in effects among sites can substantially modify and extend the expected scaling relationships between mean phenotypes and effective population sizes.

Genome-wide detection of changes in allelic frequency in Landrace pigs selected for resistance to mycoplasma pneumonia of swine

Closed-pig line breeding could change the genetic structure at a genome-wide scale because of the selection in a pig breeding population. We investigated the changes in population structure among generations at a genome-wide scale and the selected loci across the genome by comparing the observed and expected allele frequency changes in mycoplasma pneumonia of swine (MPS)-selected pigs. Eight hundred and seventy-four Landrace pigs, selected for MPS resistance without reducing average daily gain over five generations, had 37,299 single nucleotide polymorphisms (SNPs) and were used for genomic analyses. Regarding population structure, individuals in the first generation were the most widely distributed and then converged into a specific group, as they were selected over five generations. For allele frequency changes, 96 and 14 SNPs had higher allele frequency changes than the 99.9% and 99.99% thresholds of the expected changes, respectively. These SNPs were evenly spread across the genome, and a few of these selected regions overlapped with previously detected quantitative trait loci for MPS and immune-related traits. Our results indicated that the considerable changes in allele frequency were identified in many regions across the genome by closed-pig line breeding based on estimated breeding value.

A dynamic ancestral graph model and GPU-based simulation of a community based on metagenomic sampling

In this paper we present an ancestral graph model of the evolution of a guild in an ecological community. The model is based on a metagenomic sampling design in that a random sample is taken at the community, as opposed the taxon, level and species are discovered by genetic sequencing. The specific implementation of the model envisions an ecological guild that was founded by colonization at some point in the past that then potentially undergoes diversification by natural selection. Within the graph, species emerge and evolve through the diversification process and their densities in the graph are dynamic and governed by both ecological drift and random genetic drift, as well as differential viability. We employ the 3% sequence divergence rule at a marker locus to identify Operational Taxonomic Units. We then explore approaches to see if there are indirect signals of the diversification process, including population genetic and ecological approaches. In terms of population genetics, we study the joint site frequency spectrum of OTUs, as well its associated statistics. In terms of ecology, we study the species (or OTU) abundance distribution. For both we observe deviations from neutrality, which indicates that there may be signals of diversifying selection in metagenomic studies under certain conditions. The model is available as a GPU-based computer program in C/C++ and using OpenCL, with the long-term goal of adding functionality iterativelyto model large-scale eco-evolutionary processes for metagenomic data.

Genetic Diversity and Evolution of Viral Populations

Population genetic diversity plays a prominent role in viral evolution, pathogenesis, immune escape, and drug resistance. Different mechanisms are responsible for creating and maintaining genetic diversity in viruses, including error-prone replication, repair avoidance, and genome editing, among others. This diversity is subsequently modulated by natural selection and random genetic drift, whose action in turn depends on multiple factors including viral genetic architecture, viral demography, and ecology. Understanding these processes should contribute to the development of more efficient control and treatment strategies against viral pathogens.

The Ingenuity of Bacterial Genomes

The genomes of bacteria contain fewer genes and substantially less noncoding DNA than those of eukaryotes, and as a result, they have much less raw material to invent new traits. Yet, bacteria are vastly more taxonomically diverse, numerically abundant, and globally successful in colonizing new habitats compared to eukaryotes. Although bacterial genomes are generally considered to be optimized for efficient growth and rapid adaptation, nonadaptive processes have played a major role in shaping the size, contents, and compact organization of bacterial genomes and have allowed the establishment of deleterious traits that serve as the raw materials for genetic innovation.

The evolutionary scaling of cellular traits imposed by the drift barrier

Owing to internal homeostatic mechanisms, cellular traits may experience long periods of stable selective pressures, during which the stochastic forces of drift and mutation conspire to generate variation. However, even in the face of invariant selection, the drift barrier defined by the genetic effective population size, which is negatively associated with organism size, can have a substantial influence on the location and dispersion of the long-term steady-state distribution of mean phenotypes. In addition, for multilocus traits, the multiplicity of alternative, functionally equivalent states can draw mean phenotypes away from selective optima, even in the absence of mutation bias. Using a framework for traits with an additive genetic basis, it is shown that 1) optimal phenotypic states may be only rarely achieved; 2) gradients of mean phenotypes with respect to organism size (i.e., allometric relationships) are likely to be molded by differences in the power of random genetic drift across the tree of life; and 3) for any particular set of population-genetic conditions, significant variation in mean phenotypes may exist among lineages exposed to identical selection pressures. These results provide a potentially useful framework for understanding numerous aspects of cellular diversification and illustrate the risks of interpreting such variation in a purely adaptive framework.

The evolution of recombination rates in finite populations during ecological speciation

Recombination can impede ecological speciation with gene flow by mixing locally adapted genotypes with maladapted migrant genotypes from a divergent population. In such a scenario, suppression of recombination can be selectively favoured. However, in finite populations evolving under the influence of random genetic drift, recombination can also facilitate adaptation by reducing Hill-Robertson interference between loci under selection. In this case, increased recombination rates can be favoured. Although these two major effects on recombination have been studied individually, their joint effect on ecological speciation with gene flow remains unexplored. Using a mathematical model, we investigated the evolution of recombination rates in two finite populations that exchange migrants while adapting to contrasting environments. Our results indicate a two-step dynamic where increased recombination is first favoured (in response to the Hill-Robertson effect), and then disfavoured, as the cost of recombining locally with maladapted migrant genotypes increases over time (the maladaptive gene flow effect). In larger populations, a stronger initial benefit for recombination was observed, whereas high migration rates intensify the long-term cost of recombination. These dynamics may have important implications for our understanding of the conditions that facilitate incipient speciation with gene flow and the evolution of recombination in finite populations.

Incongruent range dynamics between co-occurring Asian temperate tree species facilitated by life history traits

Postglacial expansion to former range limits varies substantially among species of temperate deciduous forests in eastern Asia. Isolation hypotheses (with or without gene flow) have been proposed to explain this variance, but they ignore detailed population dynamics spanning geological time and neglect the role of life history traits. Using population genetics to uncover these dynamics across their Asian range, we infer processes that formed the disjunct distributions of Ginkgo biloba and the co-occurring Cercidiphyllum japonicum (published data). Phylogenetic, coalescent, and comparative data suggest that Ginkgo population structure is regional, dichotomous (to west-east refugia), and formed ˜51 kya, resulting from random genetic drift during the last glaciation. This split is far younger than the north-south population structure of Cercidiphyllum (~1.89 Mya). Significant (recent) unidirectional gene flow has not homogenized the two Ginkgo refugia, despite 2Nm > 1. Prior to this split, gene flow was potentially higher, resulting in conflicting support for a priori hypotheses that view isolation as an explanation for the variation in postglacial range limits. Isolation hypotheses (with or without gene flow) are thus not necessarily mutually exclusive due to temporal variation of gene flow and genetic drift. In comparison with Cercidiphyllum, the restricted range of Ginkgo has been facilitated by uncompetitive life history traits associated with seed ecology, highlighting the importance of both demography and lifetime reproductive success when interpreting range shifts.

Evolutionary meandering of intermolecular interactions along the drift barrier

Many cellular functions depend on highly specific intermolecular interactions, for example transcription factors and their DNA binding sites, microRNAs and their RNA binding sites, the interfaces between heterodimeric protein molecules, the stems in RNA molecules, and kinases and their response regulators in signal-transduction systems. Despite the need for complementarity between interacting partners, such pairwise systems seem to be capable of high levels of evolutionary divergence, even when subject to strong selection. Such behavior is a consequence of the diminishing advantages of increasing binding affinity between partners, the multiplicity of evolutionary pathways between selectively equivalent alternatives, and the stochastic nature of evolutionary processes. Because mutation pressure toward reduced affinity conflicts with selective pressure for greater interaction, situations can arise in which the expected distribution of the degree of matching between interacting partners is bimodal, even in the face of constant selection. Although biomolecules with larger numbers of interacting partners are subject to increased levels of evolutionary conservation, their more numerous partners need not converge on a single sequence motif or be increasingly constrained in more complex systems. These results suggest that most phylogenetic differences in the sequences of binding interfaces are not the result of adaptive fine tuning but a simple consequence of random genetic drift.

Evolutionary cell biology: two origins, one objective

All aspects of biological diversification ultimately trace to evolutionary modifications at the cellular level. This central role of cells frames the basic questions as to how cells work and how cells come to be the way they are. Although these two lines of inquiry lie respectively within the traditional provenance of cell biology and evolutionary biology, a comprehensive synthesis of evolutionary and cell-biological thinking is lacking. We define evolutionary cell biology as the fusion of these two eponymous fields with the theoretical and quantitative branches of biochemistry, biophysics, and population genetics. The key goals are to develop a mechanistic understanding of general evolutionary processes, while specifically infusing cell biology with an evolutionary perspective. The full development of this interdisciplinary field has the potential to solve numerous problems in diverse areas of biology, including the degree to which selection, effectively neutral processes, historical contingencies, and/or constraints at the chemical and biophysical levels dictate patterns of variation for intracellular features. These problems can now be examined at both the within- and among-species levels, with single-cell methodologies even allowing quantification of variation within genotypes. Some results from this emerging field have already had a substantial impact on cell biology, and future findings will significantly influence applications in agriculture, medicine, environmental science, and synthetic biology.

The characteristic trajectory of a fixing allele: a consequence of fictitious selection that arises from conditioning

This work is concerned with the historical progression, to fixation, of an allele in a finite population. This progression is characterized by the average frequency trajectory of alleles that achieve fixation before a given time, T. Under a diffusion analysis, the average trajectory, conditional on fixation by time T, is shown to be equivalent to the average trajectory in an unconditioned problem involving additional selection. We call this additional selection "fictitious selection"; it plays the role of a selective force in the unconditioned problem but does not exist in reality. It is a consequence of conditioning on fixation. The fictitious selection is frequency dependent and can be very large compared with any real selection that is acting. We derive an approximation for the characteristic trajectory of a fixing allele, when subject to real additive selection, from an unconditioned problem, where the total selection is a combination of real and fictitious selection. Trying to reproduce the characteristic trajectory from the action of additive selection, in an infinite population, can lead to estimates of the strength of the selection that deviate from the real selection by >1000% or have the opposite sign. Strong evolutionary forces may be invoked in problems where conditioning has been carried out, but these forces may largely be an outcome of the conditioning and hence may not have a real existence. The work presented here clarifies these issues and provides two useful tools for future analyses: the characteristic trajectory of a fixing allele and the force that primarily drives this, namely fictitious selection. These should prove useful in a number of areas of interest including coalescence with selection, experimental evolution, time series analyses of ancient DNA, game theory in finite populations, and the historical dynamics of selected alleles in wild populations.

Allowing for population stratification in association analysis

In genetic association studies, it is necessary to correct for population structure to avoid inference bias. During the past decade, prevailing corrections often only involved adjustments of global ancestry differences between sampled individuals. Nevertheless, population structure may vary across local genomic regions due to the variability of local ancestries associated with natural selection, migration, or random genetic drift. Adjusting for global ancestry alone may be inadequate when local population structure is an important confounding factor. In contrast, adjusting for local ancestry can more effectively prevent false-positives due to local population structure. To more accurately locate disease genes, we recommend adjusting for local ancestries by interrogating local structure. In practice, locus-specific ancestries are usually unknown and cannot be accurately inferred when ancestral population information is not available. For such scenarios, we propose employing local principal components (PC) to represent local ancestries and adjusting for local PCs when testing for genotype-phenotype association. With an acceptable computation burden, the proposed algorithm successfully eliminates the known spurious association between SNPs in the LCT gene and height due to the population structure in European Americans.