Genome dynamics during experimental evolution

Neutral null models for diversity in serial transfer evolution experiments

Evolution experiments with microorganisms coupled with genome-wide sequencing now allow for the systematic study of population genetic processes under a wide range of conditions. In learning about these processes in natural, sexual populations, neutral models that describe the behavior of diversity and divergence summaries have played a pivotal role. It is therefore natural to ask whether neutral models, suitably modified, could be useful in the context of evolution experiments. Here, we introduce coalescent models for polymorphism and divergence under the most common experimental evolution assay, a serial transfer experiment. This relatively simple setting allows us to address several issues that could affect diversity patterns in evolution experiments, whether selection is operating or not: the transient behavior of neutral polymorphism in an experiment beginning from a single clone, the effects of randomness in the timing of cell division and noisiness in population size in the dilution stage. In our analyses and discussion, we emphasize the implications for experiments aimed at measuring diversity patterns and making inferences about population genetic processes based on these measurements.

The dawn of evolutionary genome engineering

Genome engineering strategies--such as genome editing, reduction and shuffling, and de novo genome synthesis--enable the modification of specific genomic locations in a directed and combinatorial manner. These approaches offer an unprecedented opportunity to study central evolutionary issues in which natural genetic variation is limited or biased, which sheds light on the evolutionary forces driving complex and extremely slowly evolving traits; the selective constraints on genome architecture; and the reconstruction of ancestral states of cellular structures and networks.

The continuity of bacterial and physicochemical evolution: theory and experiments

The continuity of chemical and biological evolution, incorporating life's emergence, can be explored experimentally by energizing 'dead' bacterial biomacromolecules with nutrients under cycling physicochemical gradients. This approach arises from three evolutionary principles rooted in physical chemistry: (i) broken bacterial cells cannot spontaneously self-assemble into a living state without the supply of external energy - 2nd law of thermodynamics, (ii) the energy delivery must be cycling - the primary mechanism of chemical evolution at rotating planetary surfaces under solar irradiation, (iii) the cycling energy must act on chemical mixtures of high molecular diversity and crowding - provided by dead bacterial populations.

Modeling the evolution of molecular systems from a mechanistic perspective

Systems biology-inspired genotype-phenotype mapping models are increasingly being used to study the evolutionary properties of molecular biological systems, in particular the general emergent properties of evolving systems, such as modularity, robustness, and evolvability. However, the level of abstraction at which many of these models operate might not be sufficient to capture all relevant intricacies of biological evolution in sufficient detail. Here, we argue that in particular gene and genome duplications, both evolutionary mechanisms of potentially major importance for the evolution of molecular systems and of special relevance to plant evolution, are not adequately accounted for in most GPM modeling frameworks, and that more fine-grained mechanistic models may significantly advance understanding of how gen(om)e duplication impacts molecular systems evolution.

In vitro microbial culture models and their application in drug development

Drug development faces its nemesis in the form of drug resistance. The rate of bacterial resistance to antibiotics, or tumor resistance to chemotherapy decisively depends on the surrounding heterogeneous tissue. However, in vitro drug testing is almost exclusively done in well stirred, homogeneous environments. Recent advancements in microfluidics and microfabrication introduce opportunities to develop in vitro culture models that mimic the complex in vivo tissue environment. In this review, we will first discuss the design principles underlying such models. Then we will demonstrate two types of microfluidic devices that combine stressor gradients, cell motility, large population of competing/cooperative cells and time varying dosage of drugs. By incorporating ideas from how natural selection and evolution move drug resistance forward, we show that drug resistance can occur at much greater rates than in well-stirred environments. Finally, we will discuss the future direction of in vitro microbial culture models and how to extend the lessons learned from microbial systems to eukaryotic cells.

Characterizing the molecular basis of attenuation of Marek's disease virus via in vitro serial passage identifies de novo mutations in the helicase-primase subunit gene UL5 and other candidates associated with reduced virulence

Marek's disease (MD) is a lymphoproliferative disease of chickens caused by the oncogenic Gallid herpesvirus 2, commonly known as Marek's disease virus (MDV). MD vaccines, the primary control method, are often generated by repeated in vitro serial passage of this highly cell-associated virus to attenuate virulent MDV strains. To understand the genetic basis of attenuation, we used experimental evolution by serially passing three virulent MDV replicates generated from an infectious bacterial artificial chromosome (BAC) clone. All replicates became completely or highly attenuated, indicating that de novo mutation, and not selection among quasispecies existing in a strain, is the primary driving force for the reduction in virulence. Sequence analysis of the attenuated replicates revealed 41 to 95 single-nucleotide variants (SNVs) at 2% or higher frequency in each population and several candidate genes containing high-frequency, nonsynonymous mutations. Five candidate mutations were incorporated into recombinant viruses to determine their in vivo effect. SNVs within UL42 (DNA polymerase auxiliary subunit) and UL46 (tegument) had no measurable influence, while two independent mutations in LORF2 (a gene of unknown function) improved survival time of birds but did not alter disease incidence. A fifth SNV located within UL5 (helicase-primase subunit) greatly reduced in vivo viral replication, increased survival time of birds, and resulted in only 0 to 11% disease incidence. This study shows that multiple genes, often within pathways involving DNA replication and transcriptional regulation, are involved in de novo attenuation of MDV and provides targets for the rational design of future MD vaccines.

IMPORTANCE

Marek's disease virus (MDV) is a very important pathogen in chickens that costs the worldwide poultry industry $1 billion to $2 billion annually. Marek's disease (MD) vaccines, the primary control method, are often produced by passing virulent strains in cell culture until attenuated. To understand this process, we identified all the changes in the viral genome that occurred during repeated cell passage. We find that a single mutation in the UL5 gene, which encodes a viral protein necessary for DNA replication, reduces disease incidence by 90% or more. In addition, other candidate genes were identified. This information should lead to the development of more effective and rationally designed MD vaccines leading to improved animal health and welfare and lower costs to consumers.

A draft de novo genome assembly for the northern bobwhite (Colinus virginianus) reveals evidence for a rapid decline in effective population size beginning in the Late Pleistocene

Wild populations of northern bobwhites (Colinus virginianus; hereafter bobwhite) have declined across nearly all of their U.S. range, and despite their importance as an experimental wildlife model for ecotoxicology studies, no bobwhite draft genome assembly currently exists. Herein, we present a bobwhite draft de novo genome assembly with annotation, comparative analyses including genome-wide analyses of divergence with the chicken (Gallus gallus) and zebra finch (Taeniopygia guttata) genomes, and coalescent modeling to reconstruct the demographic history of the bobwhite for comparison to other birds currently in decline (i.e., scarlet macaw; Ara macao). More than 90% of the assembled bobwhite genome was captured within <40,000 final scaffolds (N50 = 45.4 Kb) despite evidence for approximately 3.22 heterozygous polymorphisms per Kb, and three annotation analyses produced evidence for >14,000 unique genes and proteins. Bobwhite analyses of divergence with the chicken and zebra finch genomes revealed many extremely conserved gene sequences, and evidence for lineage-specific divergence of noncoding regions. Coalescent models for reconstructing the demographic history of the bobwhite and the scarlet macaw provided evidence for population bottlenecks which were temporally coincident with human colonization of the New World, the late Pleistocene collapse of the megafauna, and the last glacial maximum. Demographic trends predicted for the bobwhite and the scarlet macaw also were concordant with how opposing natural selection strategies (i.e., skewness in the r-/K-selection continuum) would be expected to shape genome diversity and the effective population sizes in these species, which is directly relevant to future conservation efforts.

Engineering reduced evolutionary potential for synthetic biology

The field of synthetic biology seeks to engineer reliable and predictable behaviors in organisms from collections of standardized genetic parts. However, unlike other types of machines, genetically encoded biological systems are prone to changes in their designed sequences due to mutations in their DNA sequences after these devices are constructed and deployed. Thus, biological engineering efforts can be confounded by undesired evolution that rapidly breaks the functions of parts and systems, particularly when they are costly to the host cell to maintain. Here, we explain the fundamental properties that determine the evolvability of biological systems. Then, we use this framework to review current efforts to engineer the DNA sequences that encode synthetic biology devices and the genomes of their microbial hosts to reduce their ability to evolve and therefore increase their genetic reliability so that they maintain their intended functions over longer timescales.

The role of replicates for error mitigation in next-generation sequencing

Advances in next-generation sequencing (NGS) technologies have rapidly improved sequencing fidelity and substantially decreased sequencing error rates. However, given that there are billions of nucleotides in a human genome, even low experimental error rates yield many errors in variant calls. Erroneous variants can mimic true somatic and rare variants, thus requiring costly confirmatory experiments to minimize the number of false positives. Here, we discuss sources of experimental errors in NGS and how replicates can be used to abate such errors.