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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. 

Abstract Human cytomegalovirus (HCMV) represents a major threat to human health, contributing to both birth defects in neonates as well as organ transplant failure and opportunistic infections in immunocompromised individuals. HCMV exhibits considerable interhost and intrahost diversity, which likely influences the pathogenicity of the virus. Therefore, understanding the relative contributions of various evolutionary forces in shaping patterns of variation is of critical importance both mechanistically and clinically. Herein, we present the individual components of an evolutionary baseline model for HCMV, with a particular focus on congenital infections for the sake of illustration—including mutation and recombination rates, the distribution of fitness effects, infection dynamics, and compartmentalization—and describe the current state of knowledge of each. By building this baseline model, researchers will be able to better describe the range of possible evolutionary scenarios contributing to observed variation as well as improve power and reduce false-positive rates when scanning for adaptive mutations in the HCMV genome. 

Abstract Whole-genome duplications (WGDs) have occurred in many eukaryotic lineages. However, the underlying evolutionary forces and molecular mechanisms responsible for the long-term retention of gene duplicates created by WGDs are not well understood. We employ a population-genomic approach to understand the selective forces acting on paralogs and investigate ongoing duplicate-gene loss in multiple species of Paramecium that share an ancient WGD. We show that mutations that abolish protein function are more likely to be segregating in retained WGD paralogs than in single-copy genes, most likely because of ongoing nonfunctionalization post-WGD. This relaxation of purifying selection occurs in only one WGD paralog, accompanied by the gradual fixation of nonsynonymous mutations and reduction in levels of expression, and occurs over a long period of evolutionary time, “marking” one locus for future loss. Concordantly, the fitness effects of new nonsynonymous mutations and frameshift-causing indels are significantly more deleterious in the highly expressed copy compared with their paralogs with lower expression. Our results provide a novel mechanistic model of gene duplicate loss following WGDs, wherein selection acts on the sum of functional activity of both duplicate genes, allowing the two to wander in expression and functional space, until one duplicate locus eventually degenerates enough in functional efficiency or expression that its contribution to total activity is too insignificant to be retained by purifying selection. Retention of duplicates by such mechanisms predicts long times to duplicate-gene loss, which should not be falsely attributed to retention due to gain/change in function. 

Abstract Whole-genome duplications (WGDs) have shaped the gene repertoire of many eukaryotic lineages. The redundancy created by WGDs typically results in a phase of massive gene loss. However, some WGD–derived paralogs are maintained over long evolutionary periods, and the relative contributions of different selective pressures to their maintenance are still debated. Previous studies have revealed a history of three successive WGDs in the lineage of the ciliate Paramecium tetraurelia and two of its sister species from the Paramecium aurelia complex. Here, we report the genome sequence and analysis of 10 additional P. aurelia species and 1 additional out group, revealing aspects of post-WGD evolution in 13 species sharing a common ancestral WGD. Contrary to the morphological radiation of vertebrates that putatively followed two WGD events, members of the cryptic P. aurelia complex have remained morphologically indistinguishable after hundreds of millions of years. Biases in gene retention compatible with dosage constraints appear to play a major role opposing post-WGD gene loss across all 13 species. In addition, post-WGD gene loss has been slower in Paramecium than in other species having experienced genome duplication, suggesting that the selective pressures against post-WGD gene loss are especially strong in Paramecium. A near complete lack of recent single-gene duplications in Paramecium provides additional evidence for strong selective pressures against gene dosage changes. This exceptional data set of 13 species sharing an ancestral WGD and 2 closely related out group species will be a useful resource for future studies on Paramecium as a major model organism in the evolutionary cell biology. 

Abstract It has previously been shown that, conditional on its fixation, the time to fixation of a semi-dominant deleterious autosomal mutation in a randomly mating population is the same as that of an advantageous mutation. This result implies that deleterious mutations could generate selective sweep-like effects. Although their fixation probabilities greatly differ, the much larger input of deleterious relative to beneficial mutations suggests that this phenomenon could be important. We here examine how the fixation of mildly deleterious mutations affects levels and patterns of polymorphism at linked sites—both in the presence and absence of interference amongst deleterious mutations—and how this class of sites may contribute to divergence between-populations and species. We find that, while deleterious fixations are unlikely to represent a significant proportion of outliers in polymorphism-based genomic scans within populations, minor shifts in the frequencies of deleterious mutations can influence the proportions of private variants and the value of FST after a recent population split. As sites subject to deleterious mutations are necessarily found in functional genomic regions, interpretations in terms of recurrent positive selection may require reconsideration. 

ThUe:fiPelledaosefcpoonpfiurlmattihoantagllehneoamdinicgslehvaeslsagrreorwepnrreaspenidtelydcinorrreescptloyn: se to the recent advent of affordable, large-scale sequencing technologies. As opposed to the situation during the majority of the 20th century, in which the development of theoretical and statistical population genetic insights outpaced the generation of data to which they could be applied, genomic data are now being produced at a far greater rate than they can be meaningfully analyzed and interpreted. With this wealth of data has come a tendency to focus on fitting specific (and often rather idiosyncratic) models to data, at the expense of a careful exploration of the range of possible underlying evolutionary processes. For example, the approach of directly investigating models of adaptive evolution in each newly sequenced population or species often neglects the fact that a thorough characterization of ubiquitous nonadaptive processes is a prerequisite for accurate inference. We here describe the perils of these tendencies, present our consensus views on current best practices in population genomic data analysis, and highlight areas of statistical inference and theory that are in need of further attention. Thereby, we argue for the importance of defining a biologically relevant baseline model tuned to the details of each new analysis, of skepticism and scrutiny in interpreting model fitting results, and of carefully defining addressable hypotheses and underlying uncertainties.