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Meiotic recombination is both a fundamental biological process required for proper chromosomal segregation during meiosis and an important genomic parameter that shapes major features of the genomic landscape. However, despite the central importance of this phenotype, we lack a clear understanding of the selective pressures that shape its variation in natural populations, including humans. While there is strong evidence of fitness costs of low rates of recombination, the possible fitness costs of high rates of recombination are less defined. To determine whether a single lower fitness bound can explain the variation in recombination rates observed in human populations, we simulated the evolution of recombination rates as a sexually dimorphic quantitative trait. Under each scenario, we statistically compared the resulting trait distribution with the observed distribution of recombination rates from a published study of the Icelandic population. To capture the genetic architecture of recombination rates in humans, we modeled it as a moderately complex trait with modest heritability. For our fitness function, we implemented a hyperbolic tangent curve with several flexible parameters to capture a wide range of existing hypotheses. We found that costs of low rates of recombination alone are likely insufficient to explain the current variation in recombination rates in both males and females, supporting the existence of fitness costs of high rates of recombination in humans. With simulations using both upper and lower fitness boundaries, we describe a parameter space for the costs of high recombination rates that produces results consistent with empirical observations. 

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 The expression of genomically-encoded information is not error-free. Transcript-error rates are dramatically higher than DNA-level mutation rates, and despite their transient nature, the steady-state load of such errors must impose some burden on cellular performance. However, a broad perspective on the degree to which transcript-error rates are constrained by natural selection and diverge among lineages remains to be developed. Here, we present a genome-wide analysis of transcript-error rates across the Tree of Life using a modified rolling-circle sequencing method, revealing that the range in error rates is remarkably narrow across diverse species. Transcript errors tend to be randomly distributed, with little evidence supporting local control of error rates associated with gene-expression levels. A majority of transcript errors result in missense errors if translated, and as with a fraction of nonsense transcript errors, these are underrepresented relative to random expectations, suggesting the existence of mechanisms for purging some such errors. To quantitatively understand how natural selection and random genetic drift might shape transcript-error rates across species, we present a model based on cell biology and population genetics, incorporating information on cell volume, proteome size, average degree of exposure of individual errors, and effective population size. However, while this model provides a framework for understanding the evolution of this highly conserved trait, as currently structured it explains only 20% of the variation in the data, suggesting a need for further theoretical work in this area. 

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. 

To determine the error rate of transcription in human cells, we analyzed the transcriptome of H1 human embryonic stem cells with a circle-sequencing approach that allows for high-fidelity sequencing of the transcriptome. These experiments identified approximately 100,000 errors distributed over every major RNA species in human cells. Our results indicate that different RNA species display different error rates, suggesting that human cells prioritize the fidelity of some RNAs over others. Cross-referencing the errors that we detected with various genetic and epigenetic features of the human genome revealed that the in vivo error rate in human cells changes along the length of a transcript and is further modified by genetic context, repetitive elements, epigenetic markers, and the speed of transcription. Our experiments further suggest that BRCA1, a DNA repair protein implicated in breast cancer, has a previously unknown role in the suppression of transcription errors. Finally, we analyzed the distribution of transcription errors in multiple tissues of a new mouse model and found that they occur preferentially in neurons, compared to other cell types. These observations lend additional weight to the idea that transcription errors play a key role in the progression of various neurological disorders, including Alzheimer’s disease.