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Adaptation is driven by the selection for beneficial mutations that provide a fitness advantage in the specific environment in which a population is evolving. However, environments are rarely constant or predictable. When an organism well adapted to one environment finds itself in another, pleiotropic effects of mutations that made it well adapted to its former environment will affect its success. To better understand such pleiotropic effects, we evolved both haploid and diploid barcoded budding yeast populations in multiple environments, isolated adaptive clones, and then determined the fitness effects of adaptive mutations in 'non-home' environments in which they were not selected. We find that pleiotropy is common, with most adaptive evolved lineages showing fitness effects in non-home environments. Consistent with other studies, we find that these pleiotropic effects are unpredictable: they are beneficial in some environments and deleterious in others. However, we do find that lineages with adaptive mutations in the same genes tend to show similar pleiotropic effects. We also find that ploidy influences the observed adaptive mutational spectra in a condition-specific fashion. In some conditions, haploids and diploids are selected with adaptive mutations in identical genes, while in others they accumulate mutations in almost completely disjoint sets of genes., Competing Interests: VC, MJ, LH, PH, DY, YL, AA, SH, DP, MD, GS No competing interests declared, (© 2023, Chen, Johnson, Hérissant et al.)

The environmental conditions of microorganisms' habitats may fluctuate in unpredictable ways, such as changes in temperature, carbon source, pH, and salinity to name a few. Environmental heterogeneity presents a challenge to microorganisms, as they have to adapt not only to be fit under a specific condition, but they must also be robust across many conditions and be able to deal with the switch between conditions itself. While experimental evolution has been used to gain insight into the adaptive process, this has largely been in either unvarying or consistently varying conditions. In cases where changing environments have been investigated, relatively little is known about how such environments influence the dynamics of the adaptive process itself, as well as the genetic and phenotypic outcomes. We designed a systematic series of evolution experiments where we used two growth conditions that have differing timescales of adaptation and varied the rate of switching between them. We used lineage tracking to follow adaptation, and whole genome sequenced adaptive clones from each of the experiments. We find that both the switch rate and the order of the conditions influences adaptation. We also find different adaptive outcomes, at both the genetic and phenotypic levels, even when populations spent the same amount of total time in the two different conditions, but the order and/or switch rate differed. Thus, in a variable environment adaptation depends not only on the nature of the conditions and phenotypes under selection, but also on the complexity of the manner in which those conditions are combined to result in a given dynamic environment., Competing Interests: The authors declare that they have no conflict of interest.

Adaptive evolution plays a large role in generating the phenotypic diversity observed in nature, yet current methods are impractical for characterizing the molecular basis and fitness effects of large numbers of individual adaptive mutations. Here, we used a DNA barcoding approach to generate the genotype-to-fitness map for adaptation-driving mutations from a Saccharomyces cerevisiae population experimentally evolved by serial transfer under limiting glucose. We isolated and measured the fitness of thousands of independent adaptive clones and sequenced the genomes of hundreds of clones. We found only two major classes of adaptive mutations: self-diploidization and mutations in the nutrient-responsive Ras/PKA and TOR/Sch9 pathways. Our large sample size and precision of measurement allowed us to determine that there are significant differences in fitness between mutations in different genes, between different paralogs, and even between different classes of mutations within the same gene., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Measuring the fitnesses of genetic variants is a fundamental objective in evolutionary biology. A standard approach for measuring microbial fitnesses in bulk involves labeling a library of genetic variants with unique sequence barcodes, competing the labeled strains in batch culture, and using deep sequencing to track changes in the barcode abundances over time. However, idiosyncratic properties of barcodes can induce nonuniform amplification or uneven sequencing coverage that causes some barcodes to be over- or under-represented in samples. This systematic bias can result in erroneous read count trajectories and misestimates of fitness. Here, we develop a computational method, named REBAR (Removing the Effects of Bias through Analysis of Residuals), for inferring the effects of barcode processing bias by leveraging the structure of systematic deviations in the data. We illustrate this approach by applying it to two independent data sets, and demonstrate that this method estimates and corrects for bias more accurately than standard proxies, such as GC-based corrections. REBAR mitigates bias and improves fitness estimates in high-throughput assays without introducing additional complexity to the experimental protocols, with potential applications in a range of experimental evolution and mutation screening contexts. [ABSTRACT FROM AUTHOR]

Previously a ring finger protein 20 (RNF20) is found to be essential for meiotic recombination and mediates H2B ubiquitination during spermatogenesis. However, its role in meiotic division is still unknown. Here, it is shown that RNF20 is localized at both centromeres and spindle poles, and it is required for oocyte acentrosomal spindle organization and female fertility. RNF20‐depleted oocytes exhibit severely abnormal spindle and chromosome misalignment caused by defective bipolar organization. Notably, it is found that the function of RNF20 in spindle assembly is not dependent on its E3 ligase activity. Instead, RNF20 regulates spindle assembly by recruiting tropomyosin3 (TPM3) to both centromeres and spindle poles with its coiled‐coil motif. The RNF20‐TPM3 interaction is essential for acentrosomal meiotic spindle assembly. Together, the studies uncover a novel function for RNF20 in mediating TPM3 recruitment to both centromeres and spindle poles during oocyte spindle assembly. [ABSTRACT FROM AUTHOR]

Evolutionary compromises are thought to be common under fluctuating selection because the mutations that best enable adaptation to one environmental context can often be detrimental to others. Yet, prior experimental work has shown that generalists can sometimes perform as well as specialists in their own environments. Here we use a highly replicated evolutionary experiment (N  = 448 asexual lineages of the brewer's yeast) to show that even though fluctuation between two environmental conditions often induces evolutionary compromises (at least early on), it can also help reveal difficult to reach adaptive outcomes that ultimately improve performance in both environments. Specifically, we begin by showing that yeast adaptation to chemical stress can involve fitness trade-offs with stress-free environments and that, accordingly, lineages that are repeatedly exposed to occasional stress tend to respond by trading performance for breadth of adaptation. We then show that on rare occasions, fluctuating selection leads to the evolution of no-cost generalists that can even outcompete constant selection specialists in their own environments. We propose that the discovery of these broader and more effective adaptive outcomes under fluctuating selection could be partially facilitated by changes in the adaptive landscape that result from having to deal with fitness trade-offs across different environmental conditions. Overall, our findings indicate that reconciling the short- and long-term evolutionary consequences of fluctuating selection could significantly improve our understanding of the evolution of specialization and generalism. [ABSTRACT FROM AUTHOR]

Nucleopore Complexes are intricate protein assemblies composed of diverse nucleoporins, which serve as crucial mediators for the bidirectional movement of molecules between the nucleus and cytosol. These nucleoporins share both structural and functional characteristics across yeast, mammals, and plants. This review highlights these shared architectural elements and further examines specific nucleoporins. A particular emphasis is placed on the putative homologs yeast NUP1, human NUP153, and plant NUP136, and their shared involvement in critical processes such as developmental coordination, gene regulation, and immune responses. Despite variations in their amino acid sequences, these proteins exhibit a notable degree of structural conservation, supporting a convergent evolution that would underlie their similar functionalities. [ABSTRACT FROM AUTHOR]

The discrete steps of transcriptional rewiring have been proposed to occur neutrally to ensure steady gene expression under stabilizing selection. A conflict‐free switch of a regulon between regulators may require an immediate compensatory evolution to minimize deleterious effects. Here, we perform an evolutionary repair experiment on the Lachancea kluyveri yeast sef1Δ mutant using a suppressor development strategy. Complete loss of SEF1 forces cells to initiate a compensatory process for the pleiotropic defects arising from misexpression of TCA cycle genes. Using different selective conditions, we identify two adaptive loss‐of‐function mutations of IRA1 and AZF1. Subsequent analyses show that Azf1 is a weak transcriptional activator regulated by the Ras1‐PKA pathway. Azf1 loss‐of‐function triggers extensive gene expression changes responsible for compensatory, beneficial, and trade‐off phenotypes. The trade‐offs can be alleviated by higher cell density. Our results not only indicate that secondary transcriptional perturbation provides rapid and adaptive mechanisms potentially stabilizing the initial stage of transcriptional rewiring but also suggest how genetic polymorphisms of pleiotropic mutations could be maintained in the population. Synopsis: Evolutionary repair in sef1Δ mutant cells of the yeast Lachancea kluyveri highlights the rapid adaptive strategies to handle growth defects and to compensate for gene misexpression. Adaptive clones evolve rapidly in populations of sef1Δ cells under different selective conditions.Loss‐of‐function or hypomorphic mutations pervasively hit two genes, IRA1 and AZF1, which are responsible for the adaptive phenotypes.The pleiotropy of loss‐of‐function azf1 mutations has beneficial fitness and compensatory effects under favorable conditions but results in growth trade‐offs when encountering unfavorable conditions.The growth trade‐offs of azf1 genotypes can be alleviated by increasing the cell density in unfavorable conditions. [ABSTRACT FROM AUTHOR]

Pooled sequencing-based fitness assays are a powerful and widely used approach to quantifying fitness of thousands of genetic variants in parallel. Despite the throughput of such assays, they are prone to biases in fitness estimates, and errors in measurements are typically larger for deleterious fitness effects, relative to neutral effects. In practice, designing pooled fitness assays involves tradeoffs between the number of timepoints, the sequencing depth, and other parameters to gain as much information as possible within a feasible experiment. Here, we combined simulations and reanalysis of an existing experimental dataset to explore how assay parameters impact measurements of near-neutral and deleterious fitness effects using a standard fitness estimator. We found that sequencing multiple timepoints at relatively modest depth improved estimates of near-neutral fitness effects, but systematically biased measurements of deleterious effects. We showed that a fixed total number of reads, deeper sequencing at fewer timepoints improved resolution of deleterious fitness effects. Our results highlight a tradeoff between measurement of deleterious and near-neutral effect sizes for a fixed amount of data and suggest that fitness assay design should be tuned for fitness effects that are relevant to the specific biological question. [ABSTRACT FROM AUTHOR]

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 FROM AUTHOR]

In recent years, evolutionary biologists have developed an increasing interest in the use of barcoding strategies to study eco-evolutionary dynamics of lineages within evolving populations and communities. Although barcoded populations can deliver unprecedented insight into evolutionary change, barcoding microbes presents specific technical challenges. Here, strategies are described for barcoding populations of the model bacterium Pseudomonas fluorescens SBW25, including the design and cloning of barcoded regions, preparation of libraries for amplicon sequencing, and quantification of resulting barcoded lineages. In so doing, we hope to aid the design and implementation of barcoding methodologies in a broad range of model and non-model organisms. [ABSTRACT FROM AUTHOR]

Random DNA barcodes are a versatile tool for tracking cell lineages, with applications ranging from development to cancer to evolution. Here, we review and critically evaluate barcode designs as well as methods of barcode sequencing and initial processing of barcode data. We first demonstrate how various barcode design decisions affect data quality and propose a new design that balances all considerations that we are currently aware of. We then discuss various options for the preparation of barcode sequencing libraries, including inline indices and Unique Molecular Identifiers (UMIs). Finally, we test the performance of several established and new bioinformatic pipelines for the extraction of barcodes from raw sequencing reads and for error correction. We find that both alignment and regular expression-based approaches work well for barcode extraction, and that error-correction pipelines designed specifically for barcode data are superior to generic ones. Overall, this review will help researchers to approach their barcoding experiments in a deliberate and systematic way. [ABSTRACT FROM AUTHOR]

Aging biomarkers are a combination of biological parameters to (i) assess age-related changes, (ii) track the physiological aging process, and (iii) predict the transition into a pathological status. Although a broad spectrum of aging biomarkers has been developed, their potential uses and limitations remain poorly characterized. An immediate goal of biomarkers is to help us answer the following three fundamental questions in aging research: How old are we? Why do we get old? And how can we age slower? This review aims to address this need. Here, we summarize our current knowledge of biomarkers developed for cellular, organ, and organismal levels of aging, comprising six pillars: physiological characteristics, medical imaging, histological features, cellular alterations, molecular changes, and secretory factors. To fulfill all these requisites, we propose that aging biomarkers should qualify for being specific, systemic, and clinically relevant. [ABSTRACT FROM AUTHOR]

We consider a general class of Markovian models describing the growth in a randomly fluctuating environment of a clonal biological population having several phenotypes related by stochastic switching. Phenotypes differ e.g. by the level of gene expression for a population of bacteria. The time-averaged growth rate of the population, Λ , is self-averaging in the limit of infinite time; it may be understood as the fitness of the population in a context of Darwinian evolution. The observation time T being however typically finite, the growth rate fluctuates. For T finite but large, we obtain the variance of the time-averaged growth rate as the maximum of a functional based on the stationary probability distribution for the phenotypes. This formula is general. In the case of two states, the stationary probability was computed by Hufton et al. (J Stat Mech 2018:23501, 2018), allowing for an explicit expression which can be checked numerically. Applications of our main formula to the study of survival strategies of biological populations, as developed in the companion article (Dinis et al. in ), are presented here briefly. [ABSTRACT FROM AUTHOR]

Microbes are constantly confronted with changes and challenges in their environment. A proper response to these environmental cues is needed for optimal cellular functioning and fitness. Interestingly, past exposure to environmental cues can accelerate or boost the response when this condition returns, even in daughter cells that have not directly encountered the initial cue. Moreover, this behavior is mostly epigenetic and often goes hand in hand with strong heterogeneity in the strength and speed of the response between isogenic cells of the same population, which might function as a bet-hedging strategy. In this review, we discuss examples of history-dependent behavior (HDB) or "memory," with a specific focus on HDB in fluctuating environments. In most examples discussed, the lag time before the response to an environmental change is used as an experimentally measurable proxy for HDB. We highlight different mechanisms already implicated in HDB, and by using HDB in fluctuating carbon conditions as a case study, we showcase how the metabolic state of a cell can be a key determining factor for HDB. Finally, we consider possible evolutionary causes and consequences of such HDB. [ABSTRACT FROM AUTHOR]

Covalent modification of histones is an important tool for gene transcriptional control in eukaryotes, which coordinates growth, development, and adaptation to environmental changes. In recent years, an important role for monoubiquitination of histone 2B (H2B) has emerged in plants, where it is associated with transcriptional activation. In this review, we discuss the dynamics of the H2B monoubiquitination system in plants and its role in regulating developmental processes including flowering, circadian rhythm, photomorphogenesis, and the response to abiotic and biotic stress including drought, salinity, and fungal, bacterial, and viral pathogens. Furthermore, we highlight the crosstalk between H2B monoubiquitination and other histone modifications which fine-tunes transcription and ensures developmental plasticity. Finally, we put into perspective how this versatile regulatory mechanism can be developed as a useful tool for crop improvement. [ABSTRACT FROM AUTHOR]

The relationship between transcription and aging is one that has been studied intensively and experimentally with diverse attempts. However, the impact of the nuclear mRNA export on the aging process following its transcription is still poorly understood, although the nuclear events after transcription are coupled closely with the transcription pathway because the essential factors required for mRNA transport, namely TREX, TREX-2, and nuclear pore complex (NPC), physically and functionally interact with various transcription factors, including the activator/repressor and pre-mRNA processing factors. Dysregulation of the mediating factors for mRNA export from the nucleus generally leads to the aberrant accumulation of nuclear mRNA and further impairment in the vegetative growth and normal lifespan and the pathogenesis of neurodegenerative diseases. The optimal stoichiometry and density of NPC are destroyed during the process of cellular aging, and their damage triggers a defect of function in the nuclear permeability barrier. This review describes recent findings regarding the role of the nuclear mRNA export in cellular aging and age-related neurodegenerative disorders. [ABSTRACT FROM AUTHOR]

In genetic programming, an evolutionary method for producing computer programs that solve specified computational problems, parent selection is ordinarily based on aggregate measures of performance across an entire training set. Lexicase selection, by contrast, selects on the basis of performance on random sequences of training cases; this has been shown to enhance problem-solving power in many circumstances. Lexicase selection can also be seen as better reflecting biological evolution, by modeling sequences of challenges that organisms face over their lifetimes. Recent work has demonstrated that the advantages of lexicase selection can be amplified by down-sampling, meaning that only a random subsample of the training cases is used each generation. This can be seen as modeling the fact that individual organisms encounter only subsets of the possible environments and that environments change over time. Here we provide the most extensive benchmarking of down-sampled lexicase selection to date, showing that its benefits hold up to increased scrutiny. The reasons that down-sampling helps, however, are not yet fully understood. Hypotheses include that down-sampling allows for more generations to be processed with the same budget of program evaluations; that the variation of training data across generations acts as a changing environment, encouraging adaptation; or that it reduces overfitting, leading to more general solutions. We systematically evaluate these hypotheses, finding evidence against all three, and instead draw the conclusion that down-sampled lexicase selection's main benefit stems from the fact that it allows the evolutionary process to examine more individuals within the same computational budget, even though each individual is examined less completely. [ABSTRACT FROM AUTHOR]

Most natural environments exhibit a substantial component of random variation, with a degree of temporal autocorrelation that defines the color of environmental noise. Such environmental fluctuations cause random fluctuations in natural selection, affecting the predictability of evolution. But despite long-standing theoretical interest in population genetics in stochastic environments, there is a dearth of empirical estimation of underlying parameters of this theory. More importantly, it is still an open question whether evolution in fluctuating environments can be predicted indirectly using simpler measures, which combine environmental time series with population estimates in constant environments. Here we address these questions by using an automated experimental evolution approach. We used a liquid-handling robot to expose over a hundred lines of the micro-alga Dunaliella salina to randomly fluctuating salinity over a continuous range, with controlled mean, variance, and autocorrelation. We then tracked the frequencies of two competing strains through amplicon sequencing of nuclear and choloroplastic barcode sequences. We show that the magnitude of environmental fluctuations (determined by their variance), but also their predictability (determined by their autocorrelation), had large impacts on the average selection coefficient. The variance in frequency change, which quantifies randomness in population genetics, was substantially higher in a fluctuating environment. The reaction norm of selection coefficients against constant salinity yielded accurate predictions for the mean selection coefficient in a fluctuating environment. This selection reaction norm was in turn well predicted by environmental tolerance curves, with population growth rate against salinity. However, both the selection reaction norm and tolerance curves underestimated the variance in selection caused by random environmental fluctuations. Overall, our results provide exceptional insights into the prospects for understanding and predicting genetic evolution in randomly fluctuating environments. Author summary: Being able to predict evolution under natural selection is important for many applied fields of biology, ranging from agriculture to medicine or conservation. However, this endeavor is complicated by factors that inherently limit our ability to predict the future, such as random fluctuations in the environment. Population genetic theory indicates that probabilistic predictions can still be made in this context, but the extent to which this holds empirically, and whether these predictions can be based on simple measurements, are still open questions. Making progress on answering these questions can be achieved by capitalizing on experiments where the environment is precisely controlled over many generations. Here, we used a pipetting robot to generate random time series of salinities with controlled patterns of fluctuations, which we imposed on a microalga, Dunaliella salina. Tracking the frequencies of two genotypes in a mixture by sequencing a short barcode sequence, we were able to show how patterns of fluctuating selection relate to the fluctuating environment. Interestingly, parts of these responses, but not all, could be predicted by simpler measurements in constant environments, allowing precise characterization the limits and prospects for predicting evolution in fluctuating environments. [ABSTRACT FROM AUTHOR]

The distribution of fitness effects (DFEs) of new mutations across different environments quantifies the potential for adaptation in a given environment and its cost in others. So far, results regarding the cost of adaptation across environments have been mixed, and most studies have sampled random mutations across different genes. Here, we quantify systematically how costs of adaptation vary along a large stretch of protein sequence by studying the distribution of fitness effects of the same ≈2,300 amino-acid changing mutations obtained from deep mutational scanning of 119 amino acids in the middle domain of the heat shock protein Hsp90 in five environments. This region is known to be important for client binding, stabilization of the Hsp90 dimer, stabilization of the N-terminal-Middle and Middle-C-terminal interdomains, and regulation of ATPase–chaperone activity. Interestingly, we find that fitness correlates well across diverse stressful environments, with the exception of one environment, diamide. Consistent with this result, we find little cost of adaptation; on average only one in seven beneficial mutations is deleterious in another environment. We identify a hotspot of beneficial mutations in a region of the protein that is located within an allosteric center. The identified protein regions that are enriched in beneficial, deleterious, and costly mutations coincide with residues that are involved in the stabilization of Hsp90 interdomains and stabilization of client-binding interfaces, or residues that are involved in ATPase–chaperone activity of Hsp90. Thus, our study yields information regarding the role and adaptive potential of a protein sequence that complements and extends known structural information. [ABSTRACT FROM AUTHOR]

Cell growth and quiescence in eukaryotic cells is controlled by an evolutionarily conserved network of signaling pathways. Signal transduction networks operate to modulate a wide range of cellular processes and physiological properties when cells exit proliferative growth and initiate a quiescent state. How signaling networks function to respond to diverse signals that result in cell cycle exit and establishment of a quiescent state is poorly understood. Here, we studied the function of signaling pathways in quiescent cells using global genetic interaction mapping in the model eukaryotic cell, Saccharomyces cerevisiae (budding yeast). We performed pooled analysis of genotypes using molecular barcode sequencing (Bar‐seq) to test the role of ~4,000 gene deletion mutants and ~12,000 pairwise interactions between all non‐essential genes and the protein kinase genes TOR1,RIM15, and PHO85 in three different nutrient‐restricted conditions in both proliferative and quiescent cells. We detect up to 10‐fold more genetic interactions in quiescent cells than proliferative cells. We find that both individual gene effects and genetic interaction profiles vary depending on the specific pro‐quiescence signal. The master regulator of quiescence, RIM15, shows distinct genetic interaction profiles in response to different starvation signals. However, vacuole‐related functions show consistent genetic interactions with RIM15 in response to different starvation signals, suggesting that RIM15 integrates diverse signals to maintain protein homeostasis in quiescent cells. Our study expands genome‐wide genetic interaction profiling to additional conditions, and phenotypes, and highlights the conditional dependence of epistasis. Synopsis: A pooled analysis of genotypes using Bar‐seq shows that the genetic and functional requirements of proliferative and quiescent cells differ between conditions. Quantitative genetic interaction mapping reveals condition‐dependent genetic interaction profiles for the core regulatory kinases. Genetic interactions in thousands of mutants are studied using pooled assays and time series analyses using Bar‐seq, enabling efficient study of additional phenotypes such as survival of nutrient starvation.The genetic interactions of the signaling kinase genes TOR1, RIM15, PHO85 vary between different environmental conditions and cellular states.RIM15 interacts with similar functional classes of genes in different starvation conditions consistent with its role as a master regulator of quiescence.Unique and cohesive positive genetic interactions between RIM15 and Endoplasmic‐reticulum‐associated protein degradation (ERAD) genes point to a new functional relationship when responding to nitrogen starvation. [ABSTRACT FROM AUTHOR]

HISTONE MONOUBIQUITINATION1 (HUB1) and its paralog HUB2 act in a conserved heterotetrameric complex in the chromatinmediated transcriptional modulation of developmental programs, such as flowering time, dormancy, and the circadian clock. The KHD1 and SPEN3 proteins were identified as interactors of the HUB1 and HUB2 proteins with in vitro RNA-binding activity. Mutants in SPEN3 and KHD1 had reduced rosette and leaf areas. Strikingly, in spen3 mutants, the flowering time was slightly, but significantly, delayed, as opposed to the early flowering time in the hub1-4 mutant. The mutant phenotypes in biomass and flowering time suggested a deregulation of their respective regulatory genes CIRCADIAN CLOCKASSOCIATED1 (CCA1) and FLOWERING LOCUS C (FLC) that are known targets of the HUB1-mediated histone H2B monoubiquitination (H2Bub). Indeed, in the spen3-1 and hub1-4 mutants, the circadian clock period was shortened as observed by luciferase reporter assays, the levels of the CCA1α and CCA1β splice forms were altered, and the CCA1 expression and H2Bub levels were reduced. In the spen3-1 mutant, the delay in flowering time was correlated with an enhanced FLC expression, possibly due to an increased distal versus proximal ratio of its antisense COOLAIR transcript. Together with transcriptomic and double-mutant analyses, our data revealed that the HUB1 interaction with SPEN3 links H2Bub during transcript elongation with pre-mRNA processing at CCA1. Furthermore, the presence of an intact HUB1 at the FLC is required for SPEN3 function in the formation of the FLC-derived antisense COOLAIR transcripts. [ABSTRACT FROM AUTHOR]

Pre-existing and de novo genetic variants can both drive adaptation to environmental changes, but their relative contributions and interplay remain poorly understood. Here we investigated the evolutionary dynamics in drug-treated yeast populations with different levels of pre-existing variation by experimental evolution coupled with time-resolved sequencing and phenotyping. We found a doubling of pre-existing variation alone boosts the adaptation by 64.1% and 51.5% in hydroxyurea and rapamycin, respectively. The causative pre-existing and de novo variants were selected on shared targets: RNR4 in hydroxyurea and TOR1, TOR2 in rapamycin. Interestingly, the pre-existing and de novo TOR variants map to different functional domains and act via distinct mechanisms. The pre-existing TOR variants from two domesticated strains exhibited opposite rapamycin resistance effects, reflecting lineage-specific functional divergence. This study provides a dynamic view on how pre-existing and de novo variants interactively drive adaptation and deepens our understanding of clonally evolving populations. [ABSTRACT FROM AUTHOR]

Pab1, the major poly (A) binding protein of the yeast Saccharomyces cerevisiae, is involved in many intracellular functions associated with mRNA metabolism, such as mRNA nuclear export, deadenylation, translation initiation and termination. Pab1 consists of four RNA recognition motifs (RRM), a proline‐rich domain (P) and a carboxy‐terminal (C) domain. Due to its modular structure, Pab1 can simultaneously interact with poly (A) tails and different proteins that regulate mRNA turnover and translation. Furthermore, Pab1 also influences cell physiology under stressful conditions by affecting the formation of quinary assemblies and stress granules, as well as by stabilizing specific mRNAs to allow translation re‐initiation after stress. The main goal of this review is to correlate the structural complexity of this protein with the multiplicity of its functions. [ABSTRACT FROM AUTHOR]

Background: Intraspecific variation in ploidy occurs in a wide range of species including pathogenic and nonpathogenic eukaryotes such as yeasts and oomycetes. Ploidy can be inferred indirectly - without measuring DNA content - from experiments using next-generation sequencing (NGS). We present nQuire, a statistical framework that distinguishes between diploids, triploids and tetraploids using NGS. The command-line tool models the distribution of base frequencies at variable sites using a Gaussian Mixture Model, and uses maximum likelihood to select the most plausible ploidy model. nQuire handles large genomes at high coverage efficiently and uses standard input file formats. Results: We demonstrate the utility of nQuire analyzing individual samples of the pathogenic oomycete Phytophthora infestans and the Baker's yeast Saccharomyces cerevisiae. Using these organisms we show the dependence between reliability of the ploidy assignment and sequencing depth. Additionally, we employ normalized maximized log- likelihoods generated by nQuire to ascertain ploidy level in a population of samples with ploidy heterogeneity. Using these normalized values we cluster samples in three dimensions using multivariate Gaussian mixtures. The cluster assignments retrieved from a S. cerevisiae population recovered the true ploidy level in over 96% of samples. Finally, we show that nQuire can be used regionally to identify chromosomal aneuploidies. Conclusions: nQuire provides a statistical framework to study organisms with intraspecific variation in ploidy. nQuire is likely to be useful in epidemiological studies of pathogens, artificial selection experiments, and for historical or ancient samples where intact nuclei are not preserved. It is implemented as a stand-alone Linux command line tool in the C programming language and is available at https://github.com/clwgg/nQuireunder the MIT license. [ABSTRACT FROM AUTHOR]

Oleaginous microorganisms are able to convert numerous agro-industrial and municipal wastes into storage lipids (single cell oil (SCO)) and are therefore considered as potential biofuel producers. While from an environmental and technological point of view the idea to convert waste materials into fuels is very attractive, the production cost of SCO is not currently competitive to that of conventional oils due to the low productivity of oleaginous microorganisms in combination with the high fermentation cost. Current strategies used to optimize the lipid-accumulating capacity of oleaginous microorganisms include the overexpression of genes encoding for key enzymes implicated in fatty acid and triacylglycerol synthesis, such as ATP-dependent citrate lyase, acetyl-CoA carboxylase, malic enzyme, proteins of the fatty acid synthase complex, glycerol 3-phosphate dehydrogenase and various acyltransferases, and/or the inactivation of genes encoding for enzymes implicated in storage lipid catabolism, such as lipases and acyl-CoA oxidases. Furthermore, blocking, even partially, pathways competitive to lipid biosynthesis (e.g., those involved in the accumulation of storage polysaccharide or organic acid and polyol excretion) can also increase lipid-accumulating ability in oleaginous microorganisms. Methodologies, such as adaptive laboratory evolution, can be included in existing workflows for the generation of strains with improved lipid accumulation capacity. In our opinion, efforts should be focused in the construction of strains with high carbon uptake rates and a reprogrammed coordination of the individual parts of the oleaginous machinery that maximizes carbon flux towards lipogenesis. [ABSTRACT FROM AUTHOR]

Living systems control cell growth dynamically by processing information from their environment. Although responses to a single environmental change have been intensively studied, little is known about how cells react to fluctuating conditions. Here, we address this question at the genomic scale by measuring the relative proliferation rate (fitness) of 3,568 yeast gene deletion mutants in out-of-equilibrium conditions: periodic oscillations between two environmental conditions. In periodic salt stress, fitness and its genetic variance largely depended on the oscillating period. Surprisingly, dozens of mutants displayed pronounced hyperproliferation under short stress periods, revealing unexpected controllers of growth under fast dynamics. We validated the implication of the high-affinity cAMP phosphodiesterase and of a regulator of protein translocation to mitochondria in this group. Periodic oscillations of extracellular methionine, a factor unrelated to salinity, also altered fitness but to a lesser extent and for different genes. The results illustrate how natural selection acts on mutations in a dynamic environment, highlighting unsuspected genetic vulnerabilities to periodic stress in molecular processes that are conserved across all eukaryotes. [ABSTRACT FROM AUTHOR]

Transcription, RNA processing, and chromatin-related factors all interact with RNA polymerase II (Pol II) to ensure proper timing and coordination of transcription and co-transcriptional processes. Many transcription elongation regulators must function simultaneously to coordinate these processes, yet few strategies exist to explore the complement of factors regulating specific stages of transcription. To this end, we developed a strategy to purify Pol II elongation complexes from subgenic regions of a single gene, namely the 5′ and 3′ regions, using sequences in the nascent RNA. Applying this strategy to Saccharomyces cerevisiae, we determined the specific set of factors that interact with Pol II at precise stages during transcription. We identify many known region-specific factors as well as determine unappreciated associations of regulatory factors during early and late stages of transcription. These data reveal a role for the transcription termination factor, Rai1, in regulating the early stages of transcription genome-wide and support the role of Bye1 as a negative regulator of early elongation. We also demonstrate a role for the ubiquitin ligase, Bre1, in regulating Pol II dynamics during the latter stages of transcription. These data and our approach to analyze subgenic transcription elongation complexes will shed new light on the myriad factors that regulate the different stages of transcription and coordinate co-transcriptional processes. [ABSTRACT FROM AUTHOR]

Rapid progress in the study on the association of histone modifications with chromatin remodeling factors has broadened our understanding of chromatin dynamics in DNA transactions. In DNA double-strand break (DSB) repair, the well-known mark of histones is the phosphorylation of the H2A variant, H2AX, which has been used as a surrogate marker of DSBs. The ubiquitylation of histone H2B by RNF20 E3 ligase was recently found to be a DNA damage-induced histone modification. This modification is required for DSB repair and regulated by a distinctive pathway from that of histone H2AX phosphorylation. Moreover, the connection between H2B ubiquitylation and the chromatin remodeling activity of SNF2H has been elucidated. In this review, we summarize the current knowledge of RNF20-mediated processes and the molecular link to H2AX-mediated processes during DSB repair. [ABSTRACT FROM AUTHOR]

The cell central metabolism has been shaped throughout evolutionary times when facing challenges from the availability of resources. In the budding yeast, Saccharomyces cerevisiae, a set of duplicated genes originating from an ancestral whole-genome and several coetaneous small-scale duplication events drive energy transfer through glucose metabolism as the main carbon source either by fermentation or respiration. These duplicates (~a third of the genome) have been dated back to approximately 100 MY, allowing for enough evolutionary time to diverge in both sequence and function. Gene duplication has been proposed as a molecular mechanism of biological innovation, maintaining balance between mutational robustness and evolvability of the system. However, some questions concerning the molecular mechanisms behind duplicated genes transcriptional plasticity and functional divergence remain unresolved. In this work we challenged S. cerevisiae to the use of lactic acid/lactate as the sole carbon source and performed a small adaptive laboratory evolution to this non-fermentative carbon source, determining phenotypic and transcriptomic changes. We observed growth adaptation to acidic stress, by reduction of growth rate and increase in biomass production, while the transcriptomic response was mainly driven by repression of the whole-genome duplicates, those implied in glycolysis and overexpression of ROS response. The contribution of several duplicated pairs to this carbon source switch and acidic stress is also discussed. [ABSTRACT FROM AUTHOR]

Nuclear export of messenger RNA (mRNA) through the nuclear pore complex (NPC) is an indispensable step to ensure protein translation in the cytoplasm of eukaryotic cells. mRNA is not translocated on its own, but it forms ribonuclear particles (mRNPs) in association with proteins that are crucial for its metabolism, some of which; like Mex67/MTR2-NXF1/NXT1; are key players for its translocation to the cytoplasm. In this review, I will summarize our current body of knowledge on the basic characteristics of mRNA export through the NPC. To be granted passage, the mRNP cargo needs to bind transport receptors, which facilitate the nuclear export. During NPC transport, mRNPs undergo compositional and conformational changes. The interactions between mRNP and the central channel of NPC are described; together with the multiple quality control steps that mRNPs undergo at the different rings of the NPC to ensure only proper export of mature transcripts to the cytoplasm. I conclude by mentioning new opportunities that arise from bottom up approaches for a mechanistic understanding of nuclear export. [ABSTRACT FROM AUTHOR]

Monoubiquitination of histone H2B (to H2Bub1) is required for downstream events including histone H3 methylation, transcription, and mRNA export. The mechanisms and players regulating these events have not yet been completely delineated. Here, we show that the conserved Ran‐binding protein Mog1 is required to sustain normal levels of H2Bub1 and H3K4me3 in Saccharomyces cerevisiae. Mog1 is needed for gene body recruitment of Rad6, Bre1, and Rtf1 that are involved in H2B ubiquitination and genetically interacts with these factors. We provide evidence that the absence of MOG1 impacts on cellular processes such as transcription, DNA replication, and mRNA export, which are linked to H2Bub1. Importantly, the mRNA export defect in mog1Δ strains is exacerbated by the absence of factors that decrease H2Bub1 levels. Consistent with a role in sustaining H2Bub and H3K4me3 levels, Mog1 co‐precipitates with components that participate in these modifications such as Bre1, Rtf1, and the COMPASS‐associated factors Shg1 and Sdc1. These results reveal a novel role for Mog1 in H2B ubiquitination, transcription, and mRNA biogenesis. Synopsis: The conserved Mog1 protein is important for H2Bub1, H3K4me3, transcription, and mRNA export. This novel role is distinct from its known ability to bind Ran‐GTP during protein transport. Mog1 is required to sustain normal levels of H2Bub1 and H3K4me3 and co‐precipitates with components that participate in these modifications in Saccharomyces cerevisiae.The absence of MOG1 impacts on cellular processes linked to H2Bub1, such as transcription and mRNA export.Mog1 binding to Ran is not required for its role in epigenetic modifications. The conserved Mog1 protein is important for H2Bub1, H3K4me3, transcription, and mRNA export. This novel role is distinct from its known ability to bind Ran‐GTP during protein transport. [ABSTRACT FROM AUTHOR]