A global view of pleiotropy and phenotypically derived gene function in yeast

Most Pleiotropic Effects of Gene Knockouts Are Evolutionarily Transient in Yeasts

Pleiotropy, the phenomenon in which a single gene influences multiple traits, is a fundamental concept in genetics. However, the evolutionary mechanisms underlying pleiotropy require further investigation. In this study, we conducted parallel gene knockouts targeting 100 transcription factors in 2 strains of Saccharomyces cerevisiae. We systematically examined and quantified the pleiotropic effects of these knockouts on gene expression levels for each transcription factor. Our results showed that the knockout of a single gene generally affected the expression levels of multiple genes in both strains, indicating various degrees of pleiotropic effects. Strikingly, the pleiotropic effects of the knockouts change rapidly between strains in different genetic backgrounds, and ∼85% of them were nonconserved. Further analysis revealed that the conserved effects tended to be functionally associated with the deleted transcription factors, while the nonconserved effects appeared to be more ad hoc responses. In addition, we measured 184 yeast cell morphological traits in these knockouts and found consistent patterns. In order to investigate the evolutionary processes underlying pleiotropy, we examined the pleiotropic effects of standing genetic variations in a population consisting of ∼1,000 hybrid progenies of the 2 strains. We observed that newly evolved expression quantitative trait loci impacted the expression of a greater number of genes than did old expression quantitative trait loci, suggesting that natural selection is gradually eliminating maladaptive or slightly deleterious pleiotropic responses. Overall, our results show that, although being prevalent for new mutations, the majority of pleiotropic effects observed are evolutionarily transient, which explains how evolution proceeds despite complicated pleiotropic effects.

Experimental evolution of Saccharomyces cerevisiae for caffeine tolerance alters multidrug resistance and target of rapamycin signaling pathways

Caffeine is a natural compound that inhibits the major cellular signaling regulator target of rapamycin (TOR), leading to widespread effects including growth inhibition. Saccharomyces cerevisiae yeast can adapt to tolerate high concentrations of caffeine in coffee and cacao fermentations and in experimental systems. While many factors affecting caffeine tolerance and TOR signaling have been identified, further characterization of their interactions and regulation remain to be studied. We used experimental evolution of S. cerevisiae to study the genetic contributions to caffeine tolerance in yeast, through a collaboration between high school students evolving yeast populations coupled with further research exploration in university labs. We identified multiple evolved yeast populations with mutations in PDR1 and PDR5, which contribute to multidrug resistance, and showed that gain-of-function mutations in multidrug resistance family transcription factors Pdr1, Pdr3, and Yrr1 differentially contribute to caffeine tolerance. We also identified loss-of-function mutations in TOR effectors Sit4, Sky1, and Tip41 and showed that these mutations contribute to caffeine tolerance. These findings support the importance of both the multidrug resistance family and TOR signaling in caffeine tolerance and can inform future exploration of networks affected by caffeine and other TOR inhibitors in model systems and industrial applications.

Natural variation in yeast reveals multiple paths for acquiring higher stress resistance

BACKGROUND

Organisms frequently experience environmental stresses that occur in predictable patterns and combinations. For wild Saccharomyces cerevisiae yeast growing in natural environments, cells may experience high osmotic stress when they first enter broken fruit, followed by high ethanol levels during fermentation, and then finally high levels of oxidative stress resulting from respiration of ethanol. Yeast have adapted to these patterns by evolving sophisticated "cross protection" mechanisms, where mild 'primary' doses of one stress can enhance tolerance to severe doses of a different 'secondary' stress. For example, in many yeast strains, mild osmotic or mild ethanol stresses cross protect against severe oxidative stress, which likely reflects an anticipatory response important for high fitness in nature.

RESULTS

During the course of genetic mapping studies aimed at understanding the mechanisms underlying natural variation in ethanol-induced cross protection against H2O2, we found that a key H2O2 scavenging enzyme, cytosolic catalase T (Ctt1p), was absolutely essential for cross protection in a wild oak strain. This suggested the absence of other compensatory mechanisms for acquiring H2O2 resistance in that strain background under those conditions. In this study, we found surprising heterogeneity across diverse yeast strains in whether CTT1 function was fully necessary for acquired H2O2 resistance. Some strains exhibited partial dispensability of CTT1 when ethanol and/or salt were used as mild stressors, suggesting that compensatory peroxidases may play a role in acquired stress resistance in certain genetic backgrounds. We leveraged global transcriptional responses to ethanol and salt stresses in strains with different levels of CTT1 dispensability, allowing us to identify possible regulators of these alternative peroxidases and acquired stress resistance in general.

CONCLUSIONS

Ultimately, this study highlights how superficially similar traits can have different underlying molecular foundations and provides a framework for understanding the diversity and regulation of stress defense mechanisms.

From whole bodies to single cells: A guide to transcriptomic approaches for ecology and evolutionary biology

RNA sequencing (RNAseq) methodology has experienced a burst of technological developments in the last decade, which has opened up opportunities for studying the mechanisms of adaptation to environmental factors at both the organismal and cellular level. Selecting the most suitable experimental approach for specific research questions and model systems can, however, be a challenge and researchers in ecology and evolution are commonly faced with the choice of whether to study gene expression variation in whole bodies, specific tissues, and/or single cells. A wide range of sometimes polarised opinions exists over which approach is best. Here, we highlight the advantages and disadvantages of each of these approaches to provide a guide to help researchers make informed decisions and maximise the power of their study. Using illustrative examples of various ecological and evolutionary research questions, we guide the readers through the different RNAseq approaches and help them identify the most suitable design for their own projects.

The distribution of beneficial mutational effects between two sister yeast species poorly explains natural outcomes of vineyard adaptation

Domesticated strains of Saccharomyces cerevisiae have adapted to resist copper and sulfite, two chemical stressors commonly used in winemaking. S. paradoxus, has not adapted to these chemicals despite being consistently present in sympatry with S. cerevisiae in vineyards. This contrast represents a case of apparent evolutionary constraints favoring greater adaptive capacity in S. cerevisiae. In this study, we used a comparative mutagenesis approach to test whether S. paradoxus is mutationally constrained with respect to acquiring greater copper and sulfite resistance. For both species, we assayed the rate, effect size, and pleiotropic costs of resistance mutations and sequenced a subset of 150 mutants isolated from our screen. We found that the distributions of mutational effects displayed by the two species were very similar and poorly explained the natural pattern. We also found that chromosome VIII aneuploidy and loss of function mutations in PMA1 confer copper resistance in both species, whereas loss of function mutations in REG1 were only a viable route to copper resistance in S. cerevisiae. We also observed a single de novo duplication of the CUP1 gene in S. paradoxus but none in S. cerevisiae. For sulfite, loss of function mutations in RTS1 and KSP1 confer resistance in both species, but mutations in RTS1 have larger average effects in S. paradoxus. Our results show that even when the distributions of mutational effects are largely similar, species can differ in the adaptive paths available to them. They also demonstrate that assays of the distribution of mutational effects may lack predictive insight concerning adaptive outcomes.

Proline-directed yeast and human MAP kinases phosphorylate the Dot1p/DOT1L histone H3K79 methyltransferase

Disruptor of telomeric silencing 1 (Dot1p) is an exquisitely conserved histone methyltransferase and is the sole enzyme responsible for H3K79 methylation in the budding yeast Saccharomyces cerevisiae. It has been shown to be highly phosphorylated in vivo; however, the upstream kinases that act on Dot1p are almost entirely unknown in yeast and all other eukaryotes. Here, we used in vitro and in vivo kinase discovery approaches to show that mitogen-activated protein kinase HOG1 (Hog1p) is a bona fide kinase of the Dot1p methyltransferase. In vitro kinase assays showed that Hog1p phosphorylates Dot1p at multiple sites, including at several proline-adjacent sites that are consistent with known Hog1p substrate preferences. The activity of Hog1p was specifically enhanced at these proline-adjacent sites on Dot1p upon Hog1p activation by the osmostress-responsive MAP kinase kinase PBS2 (Pbs2p). Genomic deletion of HOG1 reduced phosphorylation at specific sites on Dot1p in vivo, providing further evidence for Hog1p kinase activity on Dot1p in budding yeast cells. Phenotypic analysis of knockout and phosphosite mutant yeast strains revealed the importance of Hog1p-catalysed phosphorylation of Dot1p for cellular responses to ultraviolet-induced DNA damage. In mammalian systems, this kinase-substrate relationship was found to be conserved: human DOT1L (the ortholog of yeast Dot1p) can be phosphorylated by the proline-directed kinase p38β (also known as MAPK11; the ortholog of yeast Hog1p) at multiple sites in vitro. Taken together, our findings establish Hog1p and p38β as newly identified upstream kinases of the Dot1p/DOT1L H3K79 methyltransferase enzymes in eukaryotes.

Genetic regulators of a resource polyphenism interact to couple predatory morphology and behaviour

Phenotypic plasticity often requires the coordinated response of multiple traits observed individually as morphological, physiological or behavioural. The integration, and hence functionality, of this response may be influenced by whether and how these component traits share a genetic basis. In the case of polyphenism, or discrete plasticity, at least part of the environmental response is categorical, offering a simple readout for determining whether and to what degree individual components of a plastic response can be decoupled. Here, we use the nematode Pristionchus pacificus, which has a resource polyphenism allowing it to be a facultative predator of other nematodes, to understand the genetic integration of polyphenism. The behavioural and morphological consequences of perturbations to the polyphenism's genetic regulatory network show that both predatory activity and ability are strongly influenced by morphology, different axes of morphological variation are associated with different aspects of predatory behaviour, and rearing environment can decouple predatory morphology from behaviour. Further, we found that interactions between some polyphenism-modifying genes synergistically affect predatory behaviour. Our results show that the component traits of an integrated polyphenic response can be decoupled and, in principle, selected upon individually, and they suggest that multiple routes to functionally comparable phenotypes are possible.

Current insight into the role of mRNA decay pathways in fungal pathogenesis

Pathogenic fungal species can cause superficial and mucosal infections, to potentially fatal systemic or invasive infections in humans. These infections are more common in immunocompromised or critically ill patients and have a significant morbidity and fatality rate. Fungal pathogens utilize several strategies to adapt the host environment resulting in efficient and comprehensive alterations in their cellular metabolism. Fungal virulence is regulated by several factors and post-transcriptional regulation mechanisms involving mRNA molecules are one of them. Post-transcriptional controls have emerged as critical regulatory mechanisms involved in the pathogenesis of fungal species. The untranslated upstream and downstream regions of the mRNA, as well as RNA-binding proteins, regulate morphogenesis and virulence by controlling mRNA degradation and stability. The limited number of available therapeutic drugs, the emergence of multidrug resistance, and high death rates associated with systemic fungal illnesses pose a serious risk to human health. Therefore, new antifungal treatments that specifically target mRNA pathway components can decrease fungal pathogenicity and when combined increase the effectiveness of currently available antifungal drugs. This review summarizes the mRNA degradation pathways and their role in fungal pathogenesis.

Convergent genetic adaptation of Escherichia coli in minimal media leads to pleiotropic divergence

Adaptation in an environment can either be beneficial, neutral or disadvantageous in another. To test the genetic basis of pleiotropic behaviour, we evolved six lines of E. coli independently in environments where glucose and galactose were the sole carbon sources, for 300 generations. All six lines in each environment exhibit convergent adaptation in the environment in which they were evolved. However, pleiotropic behaviour was observed in several environmental contexts, including other carbon environments. Genome sequencing reveals that mutations in global regulators rpoB and rpoC cause this pleiotropy. We report three new alleles of the rpoB gene, and one new allele of the rpoC gene. The novel rpoB alleles confer resistance to Rifampicin, and alter motility. Our results show how single nucleotide changes in the process of adaptation in minimal media can lead to wide-scale pleiotropy, resulting in changes in traits that are not under direct selection.

Thiolutin has complex effects in vivo but is a direct inhibitor of RNA polymerase II in vitro

Thiolutin is a natural product transcription inhibitor with an unresolved mode of action. Thiolutin and the related dithiolopyrrolone holomycin chelate Zn2+ and previous studies have concluded that RNA Polymerase II (Pol II) inhibition in vivo is indirect. Here, we present chemicogenetic and biochemical approaches to investigate thiolutin's mode of action in Saccharomyces cerevisiae. We identify mutants that alter sensitivity to thiolutin. We provide genetic evidence that thiolutin causes oxidation of thioredoxins in vivo and that thiolutin both induces oxidative stress and interacts functionally with multiple metals including Mn2+ and Cu2+, and not just Zn2+. Finally, we show direct inhibition of RNA polymerase II (Pol II) transcription initiation by thiolutin in vitro in support of classical studies that thiolutin can directly inhibit transcription in vitro. Inhibition requires both Mn2+ and appropriate reduction of thiolutin as excess DTT abrogates its effects. Pause prone, defective elongation can be observed in vitro if inhibition is bypassed. Thiolutin effects on Pol II occupancy in vivo are widespread but major effects are consistent with prior observations for Tor pathway inhibition and stress induction, suggesting that thiolutin use in vivo should be restricted to studies on its modes of action and not as an experimental tool.

Loss of mitochondrial DNA is associated with reduced DNA content variability in Saccharomyces cerevisiae

DNA content measurement by fluorescence-assisted cell sorting (FACS) provides information on cell cycle progression and DNA content variability. Saccharomyces cerevisiae mutants with DNA content variability that was reduced relative to wild-type strains had defects in mitochondrial DNA (mtDNA) maintenance and mitochondrial gene expression and were correlated with strains found to lack mtDNA ([ rho 0 ] cells) by genome sequencing and fluorescence microscopy. In contrast, mutants with increased variability had defects in cell cycle progression, which may indicate a loss of coordination between mtDNA and nuclear DNA replication. Thus, FACS measurement of DNA content variability can provide insight into cell-to-cell heterogeneity in mtDNA copy number.

Noncanonical usage of stop codons in ciliates expands proteins with structurally flexible Q-rich motifs

Serine(S)/threonine(T)-glutamine(Q) cluster domains (SCDs), polyglutamine (polyQ) tracts and polyglutamine/asparagine (polyQ/N) tracts are Q-rich motifs found in many proteins. SCDs often are intrinsically disordered regions that mediate protein phosphorylation and protein-protein interactions. PolyQ and polyQ/N tracts are structurally flexible sequences that trigger protein aggregation. We report that due to their high percentages of STQ or STQN amino acid content, four SCDs and three prion-causing Q/N-rich motifs of yeast proteins possess autonomous protein expression-enhancing activities. Since these Q-rich motifs can endow proteins with structural and functional plasticity, we suggest that they represent useful toolkits for evolutionary novelty. Comparative Gene Ontology (GO) analyses of the near-complete proteomes of 26 representative model eukaryotes reveal that Q-rich motifs prevail in proteins involved in specialized biological processes, including Saccharomyces cerevisiae RNA-mediated transposition and pseudohyphal growth, Candida albicans filamentous growth, ciliate peptidyl-glutamic acid modification and microtubule-based movement, Tetrahymena thermophila xylan catabolism and meiosis, Dictyostelium discoideum development and sexual cycles, Plasmodium falciparum infection, and the nervous systems of Drosophila melanogaster, Mus musculus and Homo sapiens. We also show that Q-rich-motif proteins are expanded massively in 10 ciliates with reassigned TAAQ and TAGQ codons. Notably, the usage frequency of CAGQ is much lower in ciliates with reassigned TAAQ and TAGQ codons than in organisms with expanded and unstable Q runs (e.g. D. melanogaster and H. sapiens), indicating that the use of noncanonical stop codons in ciliates may have coevolved with codon usage biases to avoid triplet repeat disorders mediated by CAG/GTC replication slippage.

Global analysis of the yeast knockout phenome

Genome-wide phenotypic screens in the budding yeast Saccharomyces cerevisiae, enabled by its knockout collection, have produced the largest, richest, and most systematic phenotypic description of any organism. However, integrative analyses of this rich data source have been virtually impossible because of the lack of a central data repository and consistent metadata annotations. Here, we describe the aggregation, harmonization, and analysis of ~14,500 yeast knockout screens, which we call Yeast Phenome. Using this unique dataset, we characterized two unknown genes (YHR045W and YGL117W) and showed that tryptophan starvation is a by-product of many chemical treatments. Furthermore, we uncovered an exponential relationship between phenotypic similarity and intergenic distance, which suggests that gene positions in both yeast and human genomes are optimized for function.

Caffeine-tolerant mutations selected through an at-home yeast experimental evolution teaching lab

yEvo is a curriculum for high school students centered around evolution experiments in S. cerevisiae . To adapt the curriculum for remote instruction, we created a new protocol to evolve non-engineered yeast in the presence of caffeine. Evolved strains had increased caffeine tolerance and distinct colony morphologies. Many possessed copy number variations, transposon insertions, and mutations affecting genes with known relationships to caffeine and TOR signaling - which is inhibited by caffeine - and in other genes not previously connected with caffeine. This demonstrates that our accessible, at-home protocol is sufficient to permit novel insights into caffeine tolerance.

Caffeine-tolerant mutations selected through an at-home yeast experimental evolution teaching lab

yEvo is a curriculum for high school students centered around evolution experiments in S. cerevisiae . To adapt the curriculum for remote instruction, we created a new protocol to evolve non-GMO yeast in the presence of caffeine. Evolved strains had increased caffeine tolerance and distinct colony morphologies. Many possessed copy number variations, transposon insertions, and mutations affecting genes with known relationships to caffeine and TOR signaling - which is inhibited by caffeine - and in other genes not previously connected with caffeine. This demonstrates that our accessible, at-home protocol is sufficient to permit novel insights into caffeine tolerance.

Metal ion availability and homeostasis as drivers of metabolic evolution and enzyme function

Metal ions are potent catalysts and have been available for cellular biochemistry at all stages of evolution. Growing evidence suggests that metal catalysis was critical for the origin of the very first metabolic reactions. With approximately 80% of modern metabolic pathways being dependent on metal ions, metallocatalysis and homeostasis continue to be essential for intracellular metabolic networks and physiology. However, the genetic network that controls metal ion homeostasis and the impact of metal availability on metabolism is poorly understood. Here, we review recent work on gene and protein evolution relevant for better understanding metal ion biology and its role in metabolism. We highlight the importance of analysing the origin and evolution of enzyme catalysis in the context of catalytically relevant metal ions, summarise unanswered questions essential for developing a comprehensive understanding of metal ion homeostasis and advocate for the consideration of metal ion properties and availability in the design and directed evolution of novel enzymes and pathways.

Loss of tolerance to multiple environmental stresses due to limitation of structural diversity of complex sphingolipids

Structural diversity of complex sphingolipids is important for maintenance of various cellular functions; however, the overall picture of the significance of this structural diversity remains largely unknown. To investigate the physiological importance of the structural diversity of complex sphingolipids, we here constructed a complex sphingolipid structural diversity disruption library in budding yeast, which comprises 11 mutants including with combinations of deletions of sphingolipid-metabolizing enzyme genes. The sensitivity of the mutants to various environmental stresses revealed that the more the structural variation of complex sphingolipids is limited, the more stress sensitivity tends to increase. Moreover, it was found that in mutant cells with only one subtype of complex sphingolipid, Slt2 MAP kinase and Msn2/4 transcriptional factors are essential for maintenance of a normal growth and compensation for reduced tolerance of multiple stresses caused by loss of complex sphingolipid diversity. Slt2 and Msn2/4 are involved in compensation for impaired integrity of cell walls and plasma membranes caused by loss of complex sphingolipid diversity, respectively. From these findings, it was suggested that loss of structural diversity of complex sphingolipids affects the environment of the cell surface, including both plasma membranes and cell walls, which could cause multiple environmental stress hypersensitivity.

In Silico Pleiotropy Analysis in KEGG Signaling Networks Using a Boolean Network Model

Pleiotropy, which refers to the ability of different mutations on the same gene to cause different pathological effects in human genetic diseases, is important in understanding system-level biological diseases. Although some biological experiments have been proposed, still little is known about pleiotropy on gene–gene dynamics, since most previous studies have been based on correlation analysis. Therefore, a new perspective is needed to investigate pleiotropy in terms of gene–gene dynamical characteristics. To quantify pleiotropy in terms of network dynamics, we propose a measure called in silico Pleiotropic Scores (sPS), which represents how much a gene is affected against a pair of different types of mutations on a Boolean network model. We found that our model can identify more candidate pleiotropic genes that are not known to be pleiotropic than the experimental database. In addition, we found that many types of functionally important genes tend to have higher sPS values than other genes; in other words, they are more pleiotropic. We investigated the relations of sPS with the structural properties in the signaling network and found that there are highly positive relations to degree, feedback loops, and centrality measures. This implies that the structural characteristics are principles to identify new pleiotropic genes. Finally, we found some biological evidence showing that sPS analysis is relevant to the real pleiotropic data and can be considered a novel candidate for pleiotropic gene research. Taken together, our results can be used to understand the dynamics pleiotropic characteristics in complex biological systems in terms of gene–phenotype relations.

Gene Coexpression Connectivity Predicts Gene Targets Underlying High Ionic-Liquid Tolerance in Yarrowia lipolytica

Microbial tolerance to organic solvents such as ionic liquids (ILs) is a robust phenotype beneficial for novel biotransformation. While most microbes become inhibited in 1% to 5% (vol/vol) IL (e.g., 1-ethyl-3-methylimidazolium acetate), we engineered a robust Yarrowia lipolytica strain (YlCW001) that tolerates a record high of 18% (vol/vol) IL via adaptive laboratory evolution. Yet, genotypes conferring high IL tolerance in YlCW001 remain to be discovered. In this study, we shed light on the underlying cellular processes that enable robust Y. lipolytica to thrive in inhibitory ILs. By using dynamic transcriptome sequencing (RNA-Seq) data, we introduced Gene Coexpression Connectivity (GeCCo) as a metric to discover genotypes conferring desirable phenotypes that might not be found by the conventional differential expression (DE) approaches. GeCCo selects genes based on their number of coexpressed genes in a subnetwork of upregulated genes by the target phenotype. We experimentally validated GeCCo by reverse engineering a high-IL-tolerance phenotype in wild-type Y. lipolytica. We found that gene targets selected by both DE and GeCCo exhibited the best statistical chance at increasing IL tolerance when individually overexpressed. Remarkably, the best combination of dual-overexpression genes was genes selected by GeCCo alone. This nonintuitive combination of genes, BRN1 and OYE2, is involved in guiding/regulating mitotic cell division, chromatin segregation/condensation, microtubule and cytoskeletal organization, and Golgi vesicle transport.

IMPORTANCE Cellular robustness to cope with stressors is an important phenotype. Y. lipolytica is an industrial robust oleaginous yeast that has recently been discovered to tolerate record high concentrations of ILs, beneficial for novel biotransformation in organic solvents. However, genotypes that link to IL tolerance in Y. lipolytica are largely unknown. Due to the complex IL-tolerant phenotype, conventional gene discovery and validation based on differential gene expression approaches are time-consuming due to a large search space and might encounter a high false-discovery rate. Here, using the developed Gene Coexpression Connectivity (GeCCo) method, we identified and validated a subset of most promising gene targets conferring the IL-tolerant phenotypes and shed light on their potential mechanisms. We anticipate GeCCo being a useful method to discover the genotype-to-phenotype link.

Sparse dictionary learning recovers pleiotropy from human cell fitness screens

In high-throughput functional genomic screens, each gene product is commonly assumed to exhibit a singular biological function within a defined protein complex or pathway. In practice, a single gene perturbation may induce multiple cascading functional outcomes, a genetic principle known as pleiotropy. Here, we model pleiotropy in fitness screen collections by representing each gene perturbation as the sum of multiple perturbations of biological functions, each harboring independent fitness effects inferred empirically from the data. Our approach (Webster) recovered pleiotropic functions for DNA damage proteins from genotoxic fitness screens, untangled distinct signaling pathways upstream of shared effector proteins from cancer cell fitness screens, and predicted the stoichiometry of an unknown protein complex subunit from fitness data alone. Modeling compound sensitivity profiles in terms of genetic functions recovered compound mechanisms of action. Our approach establishes a sparse approximation mechanism for unraveling complex genetic architectures underlying high-dimensional gene perturbation readouts.

High-value pleiotropic genes for developing multiple stress-tolerant biofortified crops for 21st-century challenges

The agriculture-based livelihood systems that are already vulnerable due to multiple challenges face immediate risk of increased crop failures due to weather vagaries. As breeders and biotechnologists, our strategy is to advance and innovate breeding for weather-proofing crops. Plant stress tolerance is a genetically complex trait. Additionally, crops rarely face a single type of stress in isolation, and it is difficult for plants to deal with multiple stresses simultaneously. One of the most helpful approaches to creating stress-resilient crops is genome editing and trans- or cis-genesis. Out of hundreds of stress-responsive genes, many have been used to impart tolerance against a particular stress factor, while a few used in combination for gene pyramiding against multiple stresses. However, a better approach would be to use multi-role pleiotropic genes that enable plants to adapt to numerous environmental stresses simultaneously. Herein we attempt to integrate and present the scattered information published in the past three decades about these pleiotropic genes for crop improvement and remodeling future cropping systems. Research articles validating functional roles of genes in transgenic plants were used to create groups of multi-role pleiotropic genes that could be candidate genes for developing weather-proof crop varieties. These biotech crop varieties will help create 'high-value farms' to meet the goal of a sustainable increase in global food productivity and stabilize food prices by ensuring a fluctuation-free assured food supply. It could also help create a gene repository through artificial gene synthesis for 'resilient high-value food production' for the 21st century.

The relative impact of evolving pleiotropy and mutational correlation on trait divergence

Both pleiotropic connectivity and mutational correlations can restrict the decoupling of traits under divergent selection, but it is unknown which is more important in trait evolution. To address this question, we create a model that permits within-population variation in both pleiotropic connectivity and mutational correlation, and compare their relative importance to trait evolution. Specifically, we developed an individual-based stochastic model where mutations can affect whether a locus affects a trait and the extent of mutational correlations in a population. We find that traits can decouple whether there is evolution in pleiotropic connectivity or mutational correlation, but when both can evolve, then evolution in pleiotropic connectivity is more likely to allow for decoupling to occur. The most common genotype found in this case is characterized by having one locus that maintains connectivity to all traits and another that loses connectivity to the traits under stabilizing selection (subfunctionalization). This genotype is favored because it allows the subfunctionalized locus to accumulate greater effect size alleles, contributing to increasingly divergent trait values in the traits under divergent selection without changing the trait values of the other traits (genetic modularization). These results provide evidence that partial subfunctionalization of pleiotropic loci may be a common mechanism of trait decoupling under regimes of corridor selection.

Gene by Environment Interactions reveal new regulatory aspects of signaling network plasticity

Phenotypes can change during exposure to different environments through the regulation of signaling pathways that operate in integrated networks. How signaling networks produce different phenotypes in different settings is not fully understood. Here, Gene by Environment Interactions (GEIs) were used to explore the regulatory network that controls filamentous/invasive growth in the yeast Saccharomyces cerevisiae. GEI analysis revealed that the regulation of invasive growth is decentralized and varies extensively across environments. Different regulatory pathways were critical or dispensable depending on the environment, microenvironment, or time point tested, and the pathway that made the strongest contribution changed depending on the environment. Some regulators even showed conditional role reversals. Ranking pathways' roles across environments revealed an under-appreciated pathway (OPI1) as the single strongest regulator among the major pathways tested (RAS, RIM101, and MAPK). One mechanism that may explain the high degree of regulatory plasticity observed was conditional pathway interactions, such as conditional redundancy and conditional cross-pathway regulation. Another mechanism was that different pathways conditionally and differentially regulated gene expression, such as target genes that control separate cell adhesion mechanisms (FLO11 and SFG1). An exception to decentralized regulation of invasive growth was that morphogenetic changes (cell elongation and budding pattern) were primarily regulated by one pathway (MAPK). GEI analysis also uncovered a round-cell invasion phenotype. Our work suggests that GEI analysis is a simple and powerful approach to define the regulatory basis of complex phenotypes and may be applicable to many systems.

Inactivating the mannose-ethanolamine phosphotransferase Gpi7 confers caspofungin resistance in the human fungal pathogen Candida albicans

Understanding the molecular mechanisms governing antifungal resistance is crucial for identifying new cellular targets for developing new antifungal therapeutics. In this study, we performed a transposon-mediated genome-wide genetic screen in haploid Candida albicans to identify mutants resistant to caspofungin, the first member of the echinocandin class of antifungal drugs. A mutant exhibiting the highest resistance possessed a transposon insertion that inactivates GPI7, a gene encoding the mannose-ethanolamine phosphotransferase. Deleting GPI7 in diploid C. albicans caused similar caspofungin resistance. gpi7Δ/Δ cells showed significantly elevated cell wall chitin content and enhanced phosphorylation of Mkc1, a core component of the PKC-MAPK cell-wall integrity pathway. Deleting MKC1 suppressed the chitin elevation and caspofungin resistance of gpi7Δ/Δ cells, but overexpressing the dominant inactive form of RHO1, an upstream activator of PKC-MAPK signaling, did not. Transcriptome analysis uncovered 406 differentially expressed genes in gpi7Δ/Δ cells, many related to cell wall construction. Our results suggest that GPI7 deletion impairs cell wall integrity, which triggers the cell-wall salvage mechanism via the PKC-MAPK pathway independently of Rho1, resulting in the compensatory chitin synthesis to confer caspofungin resistance.

A Multilayer Interactome Network Constructed in a Forest Poplar Population Mediates the Pleiotropic Control of Complex Traits

The effects of genes on physiological and biochemical processes are interrelated and interdependent; it is common for genes to express pleiotropic control of complex traits. However, the study of gene expression and participating pathways in vivo at the whole-genome level is challenging. Here, we develop a coupled regulatory interaction differential equation to assess overall and independent genetic effects on trait growth. Based on evolutionary game theory and developmental modularity theory, we constructed multilayer, omnigenic networks of bidirectional, weighted, and positive or negative epistatic interactions using a forest poplar tree mapping population, which were organized into metagalactic, intergalactic, and local interstellar networks that describe layers of structure between modules, submodules, and individual single nucleotide polymorphisms, respectively. These multilayer interactomes enable the exploration of complex interactions between genes, and the analysis of not only differential expression of quantitative trait loci but also previously uncharacterized determinant SNPs, which are negatively regulated by other SNPs, based on the deconstruction of genetic effects to their component parts. Our research framework provides a tool to comprehend the pleiotropic control of complex traits and explores the inherent directional connections between genes in the structure of omnigenic networks.

Dissecting the Fitness Costs of Complex Mutations

The fitness cost of complex pleiotropic mutations is generally difficult to assess. On the one hand, it is necessary to identify which molecular properties are directly altered by the mutation. On the other, this alteration modifies the activity of many genetic targets with uncertain consequences. Here, we examine the possibility of addressing these challenges by identifying unique predictors of these costs. To this aim, we consider mutations in the RNA polymerase (RNAP) in Escherichia coli as a model of complex mutations. Changes in RNAP modify the global program of transcriptional regulation, with many consequences. Among others is the difficulty to decouple the direct effect of the mutation from the response of the whole system to such mutation. A problem that we solve quantitatively with data of a set of constitutive genes, those on which the global program acts most directly. We provide a statistical framework that incorporates the direct effects and other molecular variables linked to this program as predictors, which leads to the identification that some genes are more suitable to determine costs than others. Therefore, we not only identified which molecular properties best anticipate fitness, but we also present the paradoxical result that, despite pleiotropy, specific genes serve as more solid predictors. These results have connotations for the understanding of the architecture of robustness in biological systems.

A prion accelerates proliferation at the expense of lifespan

In fluctuating environments, switching between different growth strategies, such as those affecting cell size and proliferation, can be advantageous to an organism. Trade-offs arise, however. Mechanisms that aberrantly increase cell size or proliferation-such as mutations or chemicals that interfere with growth regulatory pathways-can also shorten lifespan. Here we report a natural example of how the interplay between growth and lifespan can be epigenetically controlled. We find that a highly conserved RNA-modifying enzyme, the pseudouridine synthase Pus4/TruB, can act as a prion, endowing yeast with greater proliferation rates at the cost of a shortened lifespan. Cells harboring the prion grow larger and exhibit altered protein synthesis. This epigenetic state, [BIG+] (better in growth), allows cells to heritably yet reversibly alter their translational program, leading to the differential synthesis of dozens of proteins, including many that regulate proliferation and aging. Our data reveal a new role for prion-based control of an RNA-modifying enzyme in driving heritable epigenetic states that transform cell growth and survival.

Post-transcriptional and translational control of the morphology and virulence in human fungal pathogens

Host-pathogen interactions at the molecular level are the key to fungal pathogenesis. Fungal pathogens utilize several mechanisms such as adhesion, invasion, phenotype switching and metabolic adaptations, to survive in the host environment and respond. Post-transcriptional and translational regulations have emerged as key regulatory mechanisms ensuring the virulence and survival of fungal pathogens. Through these regulations, fungal pathogens effectively alter their protein pool, respond to various stress, and undergo morphogenesis, leading to efficient and comprehensive changes in fungal physiology. The regulation of virulence through post-transcriptional and translational regulatory mechanisms is mediated through mRNA elements (cis factors) or effector molecules (trans factors). The untranslated regions upstream and downstream of the mRNA, as well as various RNA-binding proteins involved in translation initiation or circularization of the mRNA, play pivotal roles in the regulation of morphology and virulence by influencing protein synthesis, protein isoforms, and mRNA stability. Therefore, post-transcriptional and translational mechanisms regulating the morphology, virulence and drug-resistance processes in fungal pathogens can be the target for new therapeutics. With improved "omics" technologies, these regulatory mechanisms are increasingly coming to the forefront of basic biology and drug discovery. This review aims to discuss various modes of post-transcriptional and translation regulations, and how these mechanisms exert influence in the virulence and morphogenesis of fungal pathogens.

Genetic interaction between F-box motif encoding YDR131C and retrograde signaling-related RTG1 regulates the stress response and apoptosis in Saccharomyces cerevisiae

The retrograde signaling pathway is well conserved from yeast to humans, which regulates cell adaptation during stress conditions and prevents cell death. One of its components, RTG1 encoded Rtg1p in association with Rtg3p communicates between mitochondria, nucleus, and peroxisome during stress for adaptation, by regulation of transcription. The F-box motif protein encoded by YDR131C  constitutes a part of SCF ^Ydr131c -E3 ligase complex, with unknown function; however, it is known that retrograde signaling is modulated by the E3 ligase complex. This study reports epistasis interaction between YDR131C and RTG1, which regulates cell growth, response to genotoxic stress, decreased apoptosis, resistance to petite mutation, and cell wall integrity. The cells of ydr131cΔrtg1Δ genetic background exhibits growth rate improvement however, sensitivity to hydroxyurea, itraconazole antifungal agent and synthetic indoloquinazoline-based alkaloid (8-fluorotryptanthrin, RK64), which disrupts the cell wall integrity in Saccharomyces cerevisiae. The epistatic interaction between YDR131C and RTG1 indicates a link between protein degradation and retrograde signaling pathways.

The impact of transcription factors Znf1, Sip4, Adr1, Tup1, and Hap4 on xylose alcoholic fermentation in the engineered yeast Saccharomyces cerevisiae

Lignocellulosic biomass is an attractive sustainable platform for fuel ethanol production. Xylose is a second after glucose most abounded sugar in lignocellulosic hydrolysates. Effective conversion of xylose to ethanol is one of key prerequisite for the development of an efficient conversion of biomass to ethanol. Engineered Saccharomyces cerevisiae strains are able to xylose fermentation. However, the yield and productivities of xylose fermentation remains lower in comparison with glucose fermentation. In this work, we studied impact of transcription factors Znf1, Sip4, Adr1, Tup1, and Hap4 on xylose catabolism. We have isolated znf1Δ, adr1Δ, tup1Δ and hap4Δ mutants, and strains overexpressing SIP4, ADR1 and HAP4 genes on the background of xylose-fermenting strain of S. cerevisiae aiming to explore involvement of these transcription factors in regulation of xylose growth and fermentation. It was shown that hap4Δ reveal 1.8-fold increase of ethanol production from xylose as compared to that of parental strain. The hap4Δ mutant accumulates 10.38 g l^-1 of ethanol with an overall ethanol yield reaching 0.41 g g^-1 of consumed xylose. While the other constructed strains revealed a decrease in ethanol production from this pentose.

Genome-wide identification and characterization of UBP gene family in wheat (Triticum aestivum L.)

Ubiquitination is essential for plant growth and development. Deubiquitination cooperates with ubiquitination to regulate the ubiquitination levels of target proteins. The ubiquitin-specific protease (UBP) family is the largest group of deubiquitinases (DUBs), which perform extensive and significant roles in eukaryotic organisms. However, the UBP genes in wheat (TaUBPs) are not identified, and the functions of TaUBPs are unknown. The present study identified 97 UBP genes in the whole genome of T. aestivum. These genes were divided into 15 groups and non-randomly distributed on chromosomes of T. aestivum. Analyses of evolutionary patterns revealed that TaUBPs mainly underwent purification selection. The studies of cis-acting regulatory elements indicated that they might be involved in response to hormones. Quantitative real-time PCR (qRT-PCR) results showed that TaUBPs were differentially expressed in different tissues. Besides, several TaUBPs were significantly up-regulated when plants were treated with salicylic acid (SA), implying that these DUBs may play a role in abiotic stress responses in plants and few TaUBPs displayed differential expression after viral infection. Furthermore, TaUBP1A.1 (TraesCS1A02G432600.1) silenced by virus-induced gene silencing (VIGS) facilitates Chinese wheat mosaic virus (CWMV) infection in wheat, indicating that TaUBP1A.1 may be involved in a defense mechanism against viruses. This study comprehensively analyzed the UBP gene family in wheat and provided a basis for further research of TaUBPs functions in wheat plant response to viral infection.

Reciprocal hemizygosity analysis reveals that the Saccharomyces cerevisiae CGI121 gene affects lag time duration in synthetic grape must

It is standard practice to ferment white wines at low temperatures (10–18°C). However, low temperatures increase fermentation duration and risk of problem ferments, leading to significant costs. The lag duration at fermentation initiation is heavily impacted by temperature; therefore, identification of Saccharomyces cerevisiae genes influencing fermentation kinetics is of interest for winemaking. We selected 28 S. cerevisiae BY4743 single deletants, from a prior list of open reading frames (ORFs) mapped to quantitative trait loci (QTLs) on Chr. VII and XIII, influencing the duration of fermentative lag time. Five BY4743 deletants, Δapt1, Δcgi121, Δclb6, Δrps17a, and Δvma21, differed significantly in their fermentative lag duration compared to BY4743 in synthetic grape must (SGM) at 15 °C, over 72 h. Fermentation at 12.5°C for 528 h confirmed the longer lag times of BY4743 Δcgi121, Δrps17a, and Δvma21. These three candidates ORFs were deleted in S. cerevisiae RM11-1a and S288C to perform single reciprocal hemizygosity analysis (RHA). RHA hybrids and single deletants of RM11-1a and S288C were fermented at 12.5°C in SGM and lag time measurements confirmed that the S288C allele of CGI121 on Chr. XIII, encoding a component of the EKC/KEOPS complex, increased fermentative lag phase duration. Nucleotide sequences of RM11-1a and S288C CGI121 alleles differed by only one synonymous nucleotide, suggesting that intron splicing, codon bias, or positional effects might be responsible for the impact on lag phase duration. This research demonstrates a new role of CGI121 and highlights the applicability of QTL analysis for investigating complex phenotypic traits in yeast.

CRISPRi screens reveal genes modulating yeast growth in lignocellulose hydrolysate

BACKGROUND

Baker's yeast is a widely used eukaryotic cell factory, producing a diverse range of compounds including biofuels and fine chemicals. The use of lignocellulose as feedstock offers the opportunity to run these processes in an environmentally sustainable way. However, the required hydrolysis pretreatment of lignocellulosic material releases toxic compounds that hamper yeast growth and consequently productivity.

RESULTS

Here, we employ CRISPR interference in S. cerevisiae to identify genes modulating fermentative growth in plant hydrolysate and in presence of lignocellulosic toxins. We find that at least one-third of hydrolysate-associated gene functions are explained by effects of known toxic compounds, such as the decreased growth of YAP1 or HAA1, or increased growth of DOT6 knock-down strains in hydrolysate.

CONCLUSION

Our study confirms previously known genetic elements and uncovers new targets towards designing more robust yeast strains for the utilization of lignocellulose hydrolysate as sustainable feedstock, and, more broadly, paves the way for applying CRISPRi screens to improve industrial fermentation processes.

FIREWORKS: a bottom-up approach to integrative coessentiality network analysis

Genetic coessentiality analysis, a computational approach which identifies genes sharing a common effect on cell fitness across large-scale screening datasets, has emerged as a powerful tool to identify functional relationships between human genes. However, widespread implementation of coessentiality to study individual genes and pathways is limited by systematic biases in existing coessentiality approaches and accessibility barriers for investigators without computational expertise. We created FIREWORKS, a method and interactive tool for the construction and statistical analysis of coessentiality networks centered around gene(s) provided by the user. FIREWORKS incorporates a novel bias reduction approach to reduce false discoveries, enables restriction of coessentiality analyses to custom subsets of cell lines, and integrates multiomic and drug-gene interaction datasets to investigate and target contextual gene essentiality. We demonstrate the broad utility of FIREWORKS through case vignettes investigating gene function and specialization, indirect therapeutic targeting of "undruggable" proteins, and context-specific rewiring of genetic networks.

Multi-metal tolerance of DHHC palmitoyl transferase-like protein isolated from metal contaminated soil

The microbiota inhabiting in metal polluted environment develops strong defense mechanisms to combat pollution and sustain life. Investigating the functional genes of the eukaryotic microbiota inhabiting in these environments by using metatranscriptomics approach was the focus of this study. Size fractionated eukaryotic cDNA libraries (library A, < 0.5 kb, library B, 0.5-1.0 kb, and library C, > 1.0 kb) were constructed from RNA isolated from the metal contaminated soil. The library C was screened for Cadmium (Cd) tolerant genes by using Cd sensitive yeast mutant ycf1^Δ by functional complementation assay, which yielded various clones capable of growing in Cd amended media. One of the Cd tolerant clones, PLCg39 was selected because of its ability to grow at high concentrations of Cd. Sequence analysis of PLCg39 showed homology with DHHC palmitoyl transferases, which are responsible for addition of palmitoyl groups to proteins and usually possess metal coordination domains. The cDNA PLCg39 was able to confer tolerance to Cd-sensitive (ycf1^Δ), Copper-sensitive (cup1^Δ) and Zn-sensitive (zrc1^Δ) yeast mutants when grown at different concentrations of Cd (40-100 μM), Cu (150-1000 μM) and Zn (10-13 mM), respectively. The DHHC mutant akr1^Δ transformed with PLCg39 rescued from the metal sensitivity indicating the role of DHHC palmitoyl transferase in metal tolerance. This study demonstrated that PLCg39 acts as a potential metal tolerant gene which could be used in bioremediation, biosensing and other biotechnological fields.

RS_CRZ1, a C2H2-Type Transcription Factor Is Required for Pathogenesis of Rhizoctonia solani AG1-IA in Tomato

Rhizoctonia solani is a necrotrophic fungal pathogen that causes disease in diverse plant species. In recent years, the genomic and transcriptomic studies have identified several candidate pathogenicity determinants of R. solani; however, most of them remain to be validated. In this study, we report a viral vector-based host-induced gene silencing (HIGS) as well as a dsRNA (double-stranded RNA)-based approach to effectively downregulate genes of R. solani AG1-IA (BRS1 strain) during pathogenesis in tomato. We tested a few of the in-planta upregulated R. solani genes and observed that silencing of one of them, i.e., RS_CRZ1 (a C2H2 type zinc finger transcription factor) significantly compromises the pathogenesis of R. solani in tomato. The RS_CRZ1-silenced plants not only exhibited significant reduction in disease symptoms, but the depth of pathogen colonization was also compromised. Furthermore, we identified the R. solani genes that were coregulated with RS_CRZ1 during the pathogenicity process. The HIGS-mediated silencing of a few of them [CL1756Contig1; subtilisin-like protease and CL1817Contig2; 2OG-Fe(II) oxygenase] compromised the pathogenesis of R. solani in tomato. The ectopic expression of RS_CRZ1 complemented the crz1 mutant of yeast and restored tolerance against various metal ion stress. Overall, our study reveals the importance of RS_CRZ1 in managing the hostile environment encountered during host colonization. Also, it emphasizes the relevance of the HIGS and dsRNA-based gene silencing approach toward functional characterization of pathogenicity determinants of R. solani.[Formula: see text] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

Extent and context dependence of pleiotropy revealed by high-throughput single-cell phenotyping

Pleiotropy-when a single mutation affects multiple traits-is a controversial topic with far-reaching implications. Pleiotropy plays a central role in debates about how complex traits evolve and whether biological systems are modular or are organized such that every gene has the potential to affect many traits. Pleiotropy is also critical to initiatives in evolutionary medicine that seek to trap infectious microbes or tumors by selecting for mutations that encourage growth in some conditions at the expense of others. Research in these fields, and others, would benefit from understanding the extent to which pleiotropy reflects inherent relationships among phenotypes that correlate no matter the perturbation (vertical pleiotropy). Alternatively, pleiotropy may result from genetic changes that impose correlations between otherwise independent traits (horizontal pleiotropy). We distinguish these possibilities by using clonal populations of yeast cells to quantify the inherent relationships between single-cell morphological features. Then, we demonstrate how often these relationships underlie vertical pleiotropy and how often these relationships are modified by genetic variants (quantitative trait loci [QTL]) acting via horizontal pleiotropy. Our comprehensive screen measures thousands of pairwise trait correlations across hundreds of thousands of yeast cells and reveals ample evidence of both vertical and horizontal pleiotropy. Additionally, we observe that the correlations between traits can change with the environment, genetic background, and cell-cycle position. These changing dependencies suggest a nuanced view of pleiotropy: biological systems demonstrate limited pleiotropy in any given context, but across contexts (e.g., across diverse environments and genetic backgrounds) each genetic change has the potential to influence a larger number of traits. Our method suggests that exploiting pleiotropy for applications in evolutionary medicine would benefit from focusing on traits with correlations that are less dependent on context.

Proper regulation of inositolphosphorylceramide levels is required for acquirement of low pH resistance in budding yeast

All organisms have stress response systems to protect themselves from various environmental stresses, and regulation of membrane lipids is thought to play an important role in acquirement of stress tolerance. Complex sphingolipids in the yeast Saccharomyces cerevisiae are classified into three types based on differences in the structure of the polar head group, and the compositions and quantities of complex sphingolipids in biomembranes are tightly regulated. In this study, we found that the accumulation of inositol phosphorylceramides (IPCs) due to a defect of mannosylinositol phosphorylceramide biosynthesis (sur1∆ csh1∆), i.e., disruption of the balance of the composition of complex sphingolipids, causes hypersensitivity to low pH conditions (pH 4.0–2.5). Furthermore, screening of suppressor mutations that confer low pH resistance to sur1∆ csh1∆ cells revealed that a change in ergosterol homeostasis at plasma membranes can rescue the hypersensitivity, suggesting the functional relationship between complex sphingolipids and ergosterol under low pH conditions. Under low pH conditions, wild-type yeast cells exhibited decreases in IPC levels, and forced enhancement of the biosynthesis of IPCs causes low pH hypersensitivity. Thus, it was suggested that the accumulation of IPCs is detrimental to yeast under low pH conditions, and downregulation of IPC levels is one of the adaptation mechanisms for low pH conditions.

Multiple Forms of Multifunctional Proteins in Health and Disease

Protein science has moved from a focus on individual molecules to an integrated perspective in which proteins emerge as dynamic players with multiple functions, rather than monofunctional specialists. Annotation of the full functional repertoire of proteins has impacted the fields of biochemistry and genetics, and will continue to influence basic and applied science questions - from the genotype-to-phenotype problem, to our understanding of human pathologies and drug design. In this review, we address the phenomena of pleiotropy, multidomain proteins, promiscuity, and protein moonlighting, providing examples of multitasking biomolecules that underlie specific mechanisms of human disease. In doing so, we place in context different types of multifunctional proteins, highlighting useful attributes for their systematic definition and classification in future research directions.

Trade-offs, Pleiotropy, and Shared Molecular Pathways: A Unified View of Constraints on Adaptation

The concept of trade-offs permeates our thinking about adaptive evolution because they are exhibited at every level of biological organization, from molecular and cellular processes to organismal and ecological functions. Trade-offs inevitably arise because different traits do not occur in isolation, but instead are imbedded within complex, integrated systems that make up whole organisms. The genetic and mechanistic underpinning of trade-offs can be found in the pleiotropic nodes that occur in the biological pathways shared between traits. Yet, often trade-offs are only understood as statistical correlations, limiting the ability to evaluate the interplay between how selection and constraint interact during adaptive evolution. Here, we first review the classic paradigms in which physiologists and evolutionary biologists have studied trade-offs and highlight the ways in which network and molecular pathway approaches unify these paradigms. We discuss how these approaches allow researchers to evaluate why trade-offs arise and how selection can act to overcome trait correlations and evolutionary constraints. We argue that understanding how the conserved molecular pathways are shared between different traits and functions provides a conceptual framework for evolutionary biologists, physiologists, and molecular biologists to meaningfully work together toward the goal of understanding why correlations and trade-offs occur between traits. We briefly highlight the melanocortin system and the hormonal control of osmoregulation as two case studies where an understanding of shared molecular pathways reveals why trade-offs occur between seemingly unrelated traits. While we recognize that applying such approaches poses challenges and limitations particularly in the context of natural populations, we advocate for the view that focusing on the biological pathways responsible for trade-offs provides a unified conceptual context accessible to a broad range of integrative biologists.

Transcriptome Analysis of Maternal Gene Transcripts in Unfertilized Eggs of Misgurnus anguillicaudatus and Identification of Immune-Related Maternal Genes

Maternal genes are important in directing early development and determining egg quality in fish. We here report the de novo transcriptome from four tissue libraries of the cyprinid loach, Misgurnus anguillicaudatus, and for the first time identified maternal gene transcripts in unfertilized eggs and suggest their immune system involvement. Expression profiles and functional enrichment revealed a total 24,116 transcripts were expressed as maternal transcripts in unfertilized eggs, which were involved in a wide range of biological functions and pathways. Comparison expression profiles and analysis of tissue specificity revealed that the large numbers of maternal transcripts were stored in unfertilized eggs near the late phase of ovarian maturation and before ovulation. Functional classification showed a total of 279 maternal immune-related transcripts classified with immune system process GO term and immune system KEGG pathway. qPCR analysis showed that transcript levels of identified maternal immune-related candidate genes were dynamically modulated during development and early ontogeny of M. anguillicaudatus. Taken together, this study could not only provide knowledge on the protective roles of maternal immune-related genes during early life stage of M. anguillicaudatus but could also be a valuable transcriptomic/genomic resource for further analysis of maternally provisioned genes in M. anguillicaudatus and other related teleost fishes.

Genetic interactions derived from high-throughput phenotyping of 6589 yeast cell cycle mutants

Over the last 30 years, computational biologists have developed increasingly realistic mathematical models of the regulatory networks controlling the division of eukaryotic cells. These models capture data resulting from two complementary experimental approaches: low-throughput experiments aimed at extensively characterizing the functions of small numbers of genes, and large-scale genetic interaction screens that provide a systems-level perspective on the cell division process. The former is insufficient to capture the interconnectivity of the genetic control network, while the latter is fraught with irreproducibility issues. Here, we describe a hybrid approach in which the 630 genetic interactions between 36 cell-cycle genes are quantitatively estimated by high-throughput phenotyping with an unprecedented number of biological replicates. Using this approach, we identify a subset of high-confidence genetic interactions, which we use to refine a previously published mathematical model of the cell cycle. We also present a quantitative dataset of the growth rate of these mutants under six different media conditions in order to inform future cell cycle models.

The deubiquitinating enzyme MoUbp8 is required for infection-related development, pathogenicity, and carbon catabolite repression in Magnaporthe oryzae

Deubiquitination is an essential regulatory step in the Ub-dependent pathway. Deubiquitinating enzymes (DUBs) mediate the removal of ubiquitin moieties from substrate proteins, which are involved in many regulatory mechanisms. As a component of the DUB module (Ubp8/Sgf11/Sus1/Sgf73) in the SAGA (Spt-Ada-Gcn5-acetyltransferase) complex, Ubp8 plays a crucial role in both Saccharomyces cerevisiae and humans. In S. cerevisiae, Ubp8-mediated deubiquitination regulates transcriptional activation processes. To investigate the contributions of Ubp8 to physiological and pathological development of filamentous fungi, we generated the deletion mutant of ortholog MoUBP8 (MGG-03527) in Magnaporthe oryzae (syn. Pyricularia oryzae). The ΔMoubp8 strain showed reduced sporulation, pathogenicity, and resistance to distinct stresses. Even though the conidia of the ΔMoubp8 mutant were delayed in appressorium formation, the normal and abnormal (none-septum or one-septum) conidia could finally form appressoria. Reduced melanin in the ΔMoubp8 mutant is highly responsible for the attenuated pathogenicity since the appressoria of the ΔMoubp8 mutant was much more fragile than those of the wild type, due to the defective turgidity. The weakened ability to detoxify or scavenge host-derived reactive oxygen species (ROS) further restricted the invasion of the pathogen. We also showed that carbon derepression, on the one hand, rendered the ΔMoubp8 strain highly sensitive to allyl alcohol, on the other hand, it enhances the resistance of the MoUBP8 defective strain to deoxyglucose. Overall, we suggest that MoUbp8 is not only required for sporulation, melanin formation, appressoria development, and pathogenicity but also involved in carbon catabolite repression of M. oryzae.

Genome-wide identification for genes involved in sodium dodecyl sulfate toxicity in Saccharomyces cerevisiae

Background

Sodium dodecyl sulfate (SDS) is one of the most widely used anionic alkyl sulfate surfactants. Toxicological information on SDS is accumulating, however, mechanisms of SDS toxicity regulation remain poorly understood. In this study, the relationship between the SDS-sensitive mutants and their intracellular ROS levels has been investigated.

Results

Through a genome-scale screen, we have identified 108 yeast single-gene deletion mutants that are sensitive to 0.03% SDS. These genes were predominantly related to the cellular processes of metabolism, cell cycle and DNA processing, cellular transport, transport facilities and transport routes, transcription and the protein with binding function or cofactor requirement (structural or catalytic). Measurement of the intracellular ROS (reactive oxygen species) levels of these SDS-sensitive mutants showed that about 79% of SDS-sensitive mutants accumulated significantly higher intracellular ROS levels than the wild-type cells under SDS stress. Moreover, SDS could generate oxidative damage and up-regulate several antioxidant defenses genes, and some of the SDS-sensitive genes were involved in this process.

Conclusion

This study provides insight on yeast genes involved in SDS tolerance and the elevated intracellular ROS caused by SDS stress, which is a potential way to understand the detoxification mechanisms of SDS by yeast cells.

Antagonistic pleiotropy conceals molecular adaptations in changing environments

The importance of positive selection in molecular evolution is debated. Evolution experiments under invariant laboratory conditions typically show a higher rate of nonsynonymous nucleotide changes than the rate of synonymous changes, demonstrating prevalent molecular adaptations. Natural evolution inferred from genomic comparisons, however, almost always exhibits the opposite pattern even among closely related conspecifics, which is indicative of a paucity of positive selection. Here we hypothesize that this apparent contradiction is at least in part attributable to ubiquitous and frequent environmental changes in nature, causing nonsynonymous mutations that are beneficial at one time to become deleterious soon after because of antagonistic pleiotropy and hindering their fixations relative to synonymous mutations despite continued population adaptations. To test this hypothesis, we performed yeast evolution experiments in changing and corresponding constant environments, followed by genome sequencing of the evolving populations. We observed a lower nonsynonymous to synonymous rate ratio in antagonistic changing environments than in the corresponding constant environments, and the population dynamics of mutations supports our hypothesis. These findings and the accompanying population genetic simulations suggest that molecular adaptation is consistently underestimated in nature due to the antagonistic fitness effects of mutations in changing environments.

Systematic genetics and single-cell imaging reveal widespread morphological pleiotropy and cell-to-cell variability

Our ability to understand the genotype-to-phenotype relationship is hindered by the lack of detailed understanding of phenotypes at a single-cell level. To systematically assess cell-to-cell phenotypic variability, we combined automated yeast genetics, high-content screening and neural network-based image analysis of single cells, focussing on genes that influence the architecture of four subcellular compartments of the endocytic pathway as a model system. Our unbiased assessment of the morphology of these compartments-endocytic patch, actin patch, late endosome and vacuole-identified 17 distinct mutant phenotypes associated with ~1,600 genes (~30% of all yeast genes). Approximately half of these mutants exhibited multiple phenotypes, highlighting the extent of morphological pleiotropy. Quantitative analysis also revealed that incomplete penetrance was prevalent, with the majority of mutants exhibiting substantial variability in phenotype at the single-cell level. Our single-cell analysis enabled exploration of factors that contribute to incomplete penetrance and cellular heterogeneity, including replicative age, organelle inheritance and response to stress.

Phenome-wide functional dissection of pleiotropic effects highlights key molecular pathways for human complex traits

Over the recent decades, genome-wide association studies (GWAS) have dramatically changed the understanding of human genetics. A recent genetic data release by UK Biobank (UKB) has allowed many researchers worldwide to have comprehensive look into the genetic architecture of thousands of human phenotypes. In this study, we used GWAS summary statistics derived from the UKB cohort to investigate functional mechanisms of pleiotropic effects across the human phenome. We find that highly pleiotropic variants often correspond to broadly expressed genes with ubiquitous functions, such as matrisome components and cell growth regulators; and tend to colocalize with tissue-shared eQTLs. At the same time, signaling pathway components are more prevalent among highly pleiotropic genes compared to regulatory proteins such as transcription factors. Our results suggest that protein-level pleiotropy mediated by ubiquitously expressed genes is the most prevalent mechanism of pleiotropic genetic effects across the human phenome.

Down-regulation of TUFM impairs host cell interaction and virulence by Paracoccidioides brasiliensis

The genus Paracoccidioides consist of dimorphic fungi geographically limited to the subtropical regions of Latin America, which are responsible for causing deep systemic mycosis in humans. However, the molecular mechanisms by which Paracoccidioides spp. causes the disease remain poorly understood. Paracoccidioides spp. harbor genes that encode proteins involved in host cell interaction and mitochondrial function, which together are required for pathogenicity and mediate virulence. Previously, we identified TufM (previously known as EF-Tu) in Paracoccidioides brasiliensis (PbTufM) and suggested that it may be involved in the pathogenicity of this fungus. In this study, we examined the effects of downregulating PbTUFM using a silenced strain with a 55% reduction in PbTUFM expression obtained by antisense-RNA (aRNA) technology. Silencing PbTUFM yielded phenotypic differences, such as altered translation elongation, respiratory defects, increased sensitivity of yeast cells to reactive oxygen stress, survival after macrophage phagocytosis, and reduced interaction with pneumocytes. These results were associated with reduced virulence in Galleria mellonella and murine infection models, emphasizing the importance of PbTufM in the full virulence of P. brasiliensis and its potential as a target for antifungal agents against paracoccidioidomycosis.