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Abstract The mitochondria contain their own genome derived from an alphaproteobacterial endosymbiont. From thousands of protein-coding genes originally encoded by their ancestor, only between 1 and about 70 are encoded on extant mitochondrial genomes (mitogenomes). Thanks to a dramatically increasing number of sequenced and annotated mitogenomes a coherent picture of why some genes were lost, or relocated to the nucleus, is emerging. In this review, we describe the characteristics of mitochondria-to-nucleus gene transfer and the resulting varied content of mitogenomes across eukaryotes. We introduce a ‘burst-upon-drift’ model to best explain nuclear-mitochondrial population genetics with flares of transfer due to genetic drift. 

Abstract The article discusses the Crow-Kimura model in the context of random transitions between different fitness landscapes. The duration of epochs, during which the fitness landscape is constant over time, is modeled by an exponential distribution. To obtain an exact solution, a system of functional equations is required. However, to approximate the model, we consider the cases of slow or fast transitions and calculate the first-order corrections using either the transition rate or its inverse. Specifically, we focus on the case of slow transitions and find that the average fitness is equal to the average fitness for evolution on static fitness landscapes, but with the addition of a load term. We also investigate the model for a small number of genes and identify the exact transition points to the transient phase. 

Abstract Yeasts are naturally diverse, genetically tractable, and easy to grow such that researchers can investigate any number of genotypes, environments, or interactions thereof. However, studies of yeast transcriptomes have been limited by the processing capabilities of traditional RNA sequencing techniques. Here we optimize a powerful, high‐throughput single‐cell RNA sequencing (scRNAseq) platform, SPLiT‐seq (Split Pool Ligation‐based Transcriptome sequencing), for yeasts and apply it to 43,388 cells of multiple species and ploidies. This platform utilizes a combinatorial barcoding strategy to enable massively parallel RNA sequencing of hundreds of yeast genotypes or growth conditions at once. This method can be applied to most species or strains of yeast for a fraction of the cost of traditional scRNAseq approaches. Thus, our technology permits researchers to leverage “the awesome power of yeast” by allowing us to survey the transcriptome of hundreds of strains and environments in a short period of time and with no specialized equipment. The key to this method is that sequential barcodes are probabilistically appended to cDNA copies of RNA while the molecules remain trapped inside of each cell. Thus, the transcriptome of each cell is labeled with a unique combination of barcodes. Since SPLiT‐seq uses the cell membrane as a container for this reaction, many cells can be processed together without the need to physically isolate them from one another in separate wells or droplets. Further, the first barcode in the sequence can be chosen intentionally to identify samples from different environments or genetic backgrounds, enabling multiplexing of hundreds of unique perturbations in a single experiment. In addition to greater multiplexing capabilities, our method also facilitates a deeper investigation of biological heterogeneity, given its single‐cell nature. For example, in the data presented here, we detect transcriptionally distinct cell states related to cell cycle, ploidy, metabolic strategies, and so forth, all within clonal yeast populations grown in the same environment. Hence, our technology has two obvious and impactful applications for yeast research: the first is the general study of transcriptional phenotypes across many strains and environments, and the second is investigating cell‐to‐cell heterogeneity across the entire transcriptome. 

Abstract The phrase “survival of the fittest” has become an iconic descriptor of how natural selection works. And yet, precisely measuring fitness, even for single-celled microbial populations growing in controlled laboratory conditions, remains a challenge. While numerous methods exist to perform these measurements, including recently developed methods utilizing DNA barcodes, all methods are limited in their precision to differentiate strains with small fitness differences. In this study, we rule out some major sources of imprecision, but still find that fitness measurements vary substantially from replicate to replicate. Our data suggest that very subtle and difficult to avoid environmental differences between replicates create systematic variation across fitness measurements. We conclude by discussing how fitness measurements should be interpreted given their extreme environment dependence. This work was inspired by the scientific community who followed us and gave us tips as we live tweeted a high-replicate fitness measurement experiment at #1BigBatch. 

Abstract Owing to advances in genome sequencing, genome stability has become one of the most scrutinized cellular traits across the Tree of Life. Despite its centrality to all things biological, the mutation rate (per nucleotide site per generation) ranges over three orders of magnitude among species and several‐fold within individual phylogenetic lineages. Within all major organismal groups, mutation rates scale negatively with the effective population size of a species and with the amount of functional DNA in the genome. This relationship is most parsimoniously explained by the drift‐barrier hypothesis, which postulates that natural selection typically operates to reduce mutation rates until further improvement is thwarted by the power of random genetic drift. Despite this constraint, the molecular mechanisms underlying DNA replication fidelity and repair are free to wander, provided the performance of the entire system is maintained at the prevailing level. The evolutionary flexibility of the mutation rate bears on the resolution of several prior conundrums in phylogenetic and population‐genetic analysis and raises challenges for future applications in these areas. 

Abstract Understanding why various organisms evolve alternative ways of living requires information on both the fitness advantages of phenotypic modifications and the costs of constructing and operating cellular features. Although the former has been the subject of a myriad of ecological studies, almost no attention has been given to how organisms allocate resources to alternative structures and functions. We address these matters by capitalizing on an array of observations on diverse ciliate species and from the emerging field of evolutionary bioenergetics. A relatively robust and general estimator for the total cost of a cell per cell cycle (in units of ATP equivalents) is provided, and this is then used to understand how the magnitudes of various investments scale with cell size. Among other things, we examine the costs associated with the large macronuclear genomes of ciliates, as well as ribosomes, various internal membranes, osmoregulation, cilia, and swimming activities. Although a number of uncertainties remain, the general approach taken may serve as blueprint for expanding this line of work to additional traits and phylogenetic lineages. 

Abstract Larger animals studied during ontogeny, across populations, or across species, usually have lower mass-specific metabolic rates than smaller animals (hypometric scaling). This pattern is usually observed regardless of physiological state (e.g., basal, resting, field, and maximally active). The scaling of metabolism is usually highly correlated with the scaling of many life-history traits, behaviors, physiological variables, and cellular/molecular properties, making determination of the causation of this pattern challenging. For across-species comparisons of resting and locomoting animals (but less so for across populations or during ontogeny), the mechanisms at the physiological and cellular level are becoming clear. Lower mass-specific metabolic rates of larger species at rest are due to (a) lower contents of expensive tissues (brains, liver, and kidneys), and (b) slower ion leak across membranes at least partially due to membrane composition, with lower ion pump ATPase activities. Lower mass-specific costs of larger species during locomotion are due to lower costs for lower-frequency muscle activity, with slower myosin and Ca++ ATPase activities, and likely more elastic energy storage. The evolutionary explanation(s) for hypometric scaling remain(s) highly controversial. One subset of evolutionary hypotheses relies on constraints on larger animals due to changes in geometry with size; for example, lower surface-to-volume ratios of exchange surfaces may constrain nutrient or heat exchange, or lower cross-sectional areas of muscles and tendons relative to body mass ratios would make larger animals more fragile without compensation. Another subset of hypotheses suggests that hypometric scaling arises from biotic interactions and correlated selection, with larger animals experiencing less selection for mass-specific growth or neurolocomotor performance. An additional third type of explanation comes from population genetics. Larger animals with their lower effective population sizes and subsequent less effective selection relative to drift may have more deleterious mutations, reducing maximal performance and metabolic rates. Resolving the evolutionary explanation for the hypometric scaling of metabolism and associated variables is a major challenge for organismal and evolutionary biology. To aid progress, we identify some variation in terminology use that has impeded cross-field conversations on scaling. We also suggest that promising directions for the field to move forward include (1) studies examining the linkages between ontogenetic, population-level, and cross-species allometries; (2) studies linking scaling to ecological or phylogenetic context; (3) studies that consider multiple, possibly interacting hypotheses; and (4) obtaining better field data for metabolic rates and the life history correlates of metabolic rate such as lifespan, growth rate, and reproduction. 

The tubulin-containing cytoskeleton of the human parasite Toxoplasma gondii includes several distinct structures: the conoid, formed of 14 ribbon-like tubulin polymers, and the array of 22 cortical microtubules (MTs) rooted in the apical polar ring. Here we analyze the structure of developing daughter parasites using both 3D-SIM and expansion microscopy. Cortical MTs and the conoid start to develop almost simultaneously, but from distinct precursors near the centrioles. Cortical MTs are initiated in a fixed sequence, starting around the periphery of a short arc that extends to become a complete circle. The conoid also develops from an open arc into a full circle, with a fixed spatial relationship to the centrioles. The patterning of the MT array starts from a “blueprint” with ∼five-fold symmetry, switching to 22-fold rotational symmetry in the final product, revealing a major structural rearrangement during daughter growth. The number of MT is essentially invariant in the wild-type array, but is perturbed by the loss of some structural components of the apical polar ring. This study provides insights into the development of tubulin-containing structures that diverge from conventional models, insights that are critical for understanding the evolutionary paths leading to construction and divergence of cytoskeletal frameworks. 

The ciliate genus Paramecium served as one of the first model systems in microbial eukaryotic genetics, contributing much to the early understanding of phenomena as diverse as genome rearrangement, cryptic speciation, cytoplasmic inheritance, and endosymbiosis, as well as more recently to the evolution of mating types, introns, and roles of small RNAs in DNA processing. Substantial progress has recently been made in the area of comparative and population genomics. Paramecium species combine some of the lowest known mutation rates with some of the largest known effective populations, along with likely very high recombination rates, thereby harboring a population-genetic environment that promotes an exceptionally efficient capacity for selection. As a consequence, the genomes are extraordinarily streamlined, with very small intergenic regions combined with small numbers of tiny introns. The subject of the bulk of Paramecium research, the ancient Paramecium aurelia species complex, is descended from two whole-genome duplication events that retain high degrees of synteny, thereby providing an exceptional platform for studying the fates of duplicate genes. Despite having a common ancestor dating to several hundred million years ago, the known descendant species are morphologically indistinguishable, raising significant questions about the common view that gene duplications lead to the origins of evolutionary novelties.