Systematic triple-mutant analysis uncovers functional connectivity between pathways involved in chromosome regulation

Glycosphingolipids are linked to elevated neurotransmission and neurodegeneration in a Drosophila model of Niemann Pick type C

The lipid storage disease Niemann Pick type C (NPC) causes neurodegeneration owing primarily to loss of NPC1. Here, we employed a Drosophila model to test links between glycosphingolipids, neurotransmission and neurodegeneration. We found that Npc1a nulls had elevated neurotransmission at the glutamatergic neuromuscular junction (NMJ), which was phenocopied in brainiac (brn) mutants, impairing mannosyl glucosylceramide (MacCer) glycosylation. Npc1a; brn double mutants had the same elevated synaptic transmission, suggesting that Npc1a and brn function within the same pathway. Glucosylceramide (GlcCer) synthase inhibition with miglustat prevented elevated neurotransmission in Npc1a and brn mutants, further suggesting epistasis. Synaptic MacCer did not accumulate in the NPC model, but GlcCer levels were increased, suggesting that GlcCer is responsible for the elevated synaptic transmission. Null Npc1a mutants had heightened neurodegeneration, but no significant motor neuron or glial cell death, indicating that dying cells are interneurons and that elevated neurotransmission precedes neurodegeneration. Glycosphingolipid synthesis mutants also had greatly heightened neurodegeneration, with similar neurodegeneration in Npc1a; brn double mutants, again suggesting that Npc1a and brn function in the same pathway. These findings indicate causal links between glycosphingolipid-dependent neurotransmission and neurodegeneration in this NPC disease model.

Chromatin assembly factor-1 preserves genome stability in ctf4Δ cells by promoting sister chromatid cohesion

Chromatin assembly and the establishment of sister chromatid cohesion are intimately connected to the progression of DNA replication forks. Here we examined the genetic interaction between the heterotrimeric chromatin assembly factor-1 (CAF-1), a central component of chromatin assembly during replication, and the core replisome component Ctf4. We find that CAF-1 deficient cells as well as cells affected in newly-synthesized H3-H4 histones deposition during DNA replication exhibit a severe negative growth with ctf4Δ mutant. We dissected the role of CAF-1 in the maintenance of genome stability in ctf4Δ yeast cells. In the absence of CTF4, CAF-1 is essential for viability in cells experiencing replication problems, in cells lacking functional S-phase checkpoint or functional spindle checkpoint, and in cells lacking DNA repair pathways involving homologous recombination. We present evidence that CAF-1 affects cohesin association to chromatin in a DNA-damage-dependent manner and is essential to maintain cohesion in the absence of CTF4. We also show that Eco1-catalyzed Smc3 acetylation is reduced in absence of CAF-1. Furthermore, we describe genetic interactions between CAF-1 and essential genes involved in cohesin loading, cohesin stabilization, and cohesin component indicating that CAF-1 is crucial for viability when sister chromatid cohesion is affected. Finally, our data indicate that the CAF-1-dependent pathway required for cohesion is functionally distinct from the Rtt101-Mms1-Mms22 pathway which functions in replicated chromatin assembly. Collectively, our results suggest that the deposition by CAF-1 of newly-synthesized H3-H4 histones during DNA replication creates a chromatin environment that favors sister chromatid cohesion and maintains genome integrity.

Phenomics approaches to understand genetic networks and gene function in yeast

Over the past decade, major efforts have been made to systematically survey the characteristics or phenotypes associated with genetic variation in a variety of model systems. These so-called phenomics projects involve the measurement of 'phenomes', or the set of phenotypic information that describes an organism or cell, in various genetic contexts or states, and in response to external factors, such as environmental signals. Our understanding of the phenome of an organism depends on the availability of reagents that enable systematic evaluation of the spectrum of possible phenotypic variation and the types of measurements that can be taken. Here, we highlight phenomics studies that use the budding yeast, a pioneer model organism for functional genomics research. We focus on genetic perturbation screens designed to explore genetic interactions, using a variety of phenotypic read-outs, from cell growth to subcellular morphology.

Retention of duplicated genes in evolution

Gene duplication is a prevalent phenomenon across the tree of life. The processes that lead to the retention of duplicated genes are not well understood. Functional genomics approaches in model organisms, such as yeast, provide useful tools to test the mechanisms underlying retention with functional redundancy and divergence of duplicated genes, including fates associated with neofunctionalization, subfunctionalization, back-up compensation, and dosage amplification. Duplicated genes may also be retained as a consequence of structural and functional entanglement. Advances in human gene editing have enabled the interrogation of duplicated genes in the human genome, providing new tools to evaluate the relative contributions of each of these factors to duplicate gene retention and the evolution of genome structure.

τ-SGA: synthetic genetic array analysis for systematically screening and quantifying trigenic interactions in yeast

Systematic complex genetic interaction studies have provided insight into high-order functional redundancies and genetic network wiring of the cell. Here, we describe a method for screening and quantifying trigenic interactions from ordered arrays of yeast strains grown on agar plates as individual colonies. The protocol instructs users on the trigenic synthetic genetic array analysis technique, τ-SGA, for high-throughput screens. The steps describe construction of the double-mutant query strains and the corresponding single-mutant control query strains, which are screened in parallel in two replicates. The screening experimental set-up consists of sequential replica-pinning steps that enable automated mating, meiotic recombination and successive haploid selection steps for the generation of triple mutants, which are scored for colony size as a proxy for fitness, which enables the calculation of trigenic interactions. The procedure described here was used to conduct 422 trigenic interaction screens, which generated ~460,000 yeast triple mutants for trigenic interaction analysis. Users should be familiar with robotic equipment required for high-throughput genetic interaction screens and be proficient at the command line to execute the scoring pipeline. Large-scale screen computational analysis is achieved by using MATLAB pipelines that score raw colony size data to produce τ-SGA interaction scores. Additional recommendations are included for optimizing experimental design and analysis of smaller-scale trigenic interaction screens by using a web-based analysis system, SGAtools. This protocol provides a resource for those who would like to gain a deeper, more practical understanding of trigenic interaction screening and quantification methodology.

Genetic interaction mapping informs integrative structure determination of protein complexes

Determining structures of protein complexes is crucial for understanding cellular functions. Here, we describe an integrative structure determination approach that relies on in vivo measurements of genetic interactions. We construct phenotypic profiles for point mutations crossed against gene deletions or exposed to environmental perturbations, followed by converting similarities between two profiles into an upper bound on the distance between the mutated residues. We determine the structure of the yeast histone H3-H4 complex based on ~500,000 genetic interactions of 350 mutants. We then apply the method to subunits Rpb1-Rpb2 of yeast RNA polymerase II and subunits RpoB-RpoC of bacterial RNA polymerase. The accuracy is comparable to that based on chemical cross-links; using restraints from both genetic interactions and cross-links further improves model accuracy and precision. The approach provides an efficient means to augment integrative structure determination with in vivo observations.

CAF-1 and Rtt101p function within the replication-coupled chromatin assembly network to promote H4 K16ac, preventing ectopic silencing

Replication-coupled chromatin assembly is achieved by a network of alternate pathways containing different chromatin assembly factors and histone-modifying enzymes that coordinate deposition of nucleosomes at the replication fork. Here we describe the organization of a CAF-1-dependent pathway in Saccharomyces cerevisiae that regulates acetylation of histone H4 K16. We demonstrate factors that function in this CAF-1-dependent pathway are important for preventing establishment of silenced states at inappropriate genomic sites using a crippled HMR locus as a model, while factors specific to other assembly pathways do not. This CAF-1-dependent pathway required the cullin Rtt101p, but was functionally distinct from an alternate pathway involving Rtt101p-dependent ubiquitination of histone H3 and the chromatin assembly factor Rtt106p. A major implication from this work is that cells have the inherent ability to create different chromatin modification patterns during DNA replication via differential processing and deposition of histones by distinct chromatin assembly pathways within the network.

Resurrection from lethal knockouts: Bypass of gene essentiality

Understanding genotype-phenotype relationships is a central pursuit in biology. Gene knockout generates a complete loss-of-function genotype and is a commonly used approach for probing gene functions. The most severe phenotypic consequence of gene knockout is lethality. Genes with a lethal knockout phenotype are called essential genes. Based on genome-wide knockout analyses in yeasts, up to approximately a quarter of genes in a genome can be essential. Like other genotype-phenotype relationships, gene essentiality is subject to background effects and can vary due to gene-gene interactions. In particular, for some essential genes, lethality caused by knockout can be rescued by extragenic suppressors. Such "bypass of essentiality" (BOE) gene-gene interactions have been an understudied type of genetic suppression. A recent systematic analysis revealed that, remarkably, the essentiality of nearly 30% of essential genes in the fission yeast Schizosaccharomyces pombe can be bypassed by BOE interactions. Here, I review the history and recent progress on uncovering and understanding the bypass of gene essentiality.

Synthetic ablations in the C. elegans nervous system

Synthetic lethality, the finding that the simultaneous knockout of two or more individually nonessential genes leads to cell or organism death, has offered a systematic framework to explore cellular function, and also offered therapeutic applications. Yet the concept lacks its parallel in neuroscience—a systematic knowledge base on the role of double or higher order ablations in the functioning of a neural system. Here, we use the framework of network control to systematically predict the effects of ablating neuron pairs and triplets on the gentle touch response. We find that surprisingly small sets of 58 pairs and 46 triplets can reduce muscle controllability in this context, and that these sets are localized in the nervous system in distinct groups. Further, they lead to highly specific experimentally testable predictions about mechanisms of loss of control, and which muscle cells are expected to experience this loss.

“Synthetic lethality” in cell biology is an extreme example of the effects of higher order genetic interactions: The simultaneous knockout of two or more individually nonessential genes leads to cell death. We define a neural analog to this concept in relation to the locomotor response to gentle touch in C. elegans. Two or more neurons are synthetic essential if individually they are not required for this behavior, yet their combination is. We employ a network control approach to systematically assess all pairs and triplets of neurons by their effect on body wall muscle controllability, and find that only surprisingly small sets of neurons are synthetic essential. They are highly localized in the nervous system and predicted to affect control over specific sets of muscles.

Highly Combinatorial Genetic Interaction Analysis Reveals a Multi-Drug Transporter Influence Network

Many traits are complex, depending non-additively on variant combinations. Even in model systems, such as the yeast S. cerevisiae, carrying out the high-order variant-combination testing needed to dissect complex traits remains a daunting challenge. Here, we describe “X-gene” genetic analysis (XGA), a strategy for engineering and profiling highly combinatorial gene perturbations. We demonstrate XGA on yeast ABC transporters by engineering 5,353 strains, each deleted for a random subset of 16 transporters, and profiling each strain’s resistance to 16 compounds. XGA yielded 85,648 genotype-to-resistance observations, revealing high-order genetic interactions for 13 of the 16 transporters studied. Neural networks yielded intuitive functional models and guided exploration of fluconazole resistance, which was influenced non-additively by five genes. Together, our results showed that highly combinatorial genetic perturbation can functionally dissect complex traits, supporting pursuit of analogous strategies in human cells and other model systems.

Celaj et al. introduce “X-gene” genetic analysis (XGA), a strategy for modeling complex systems by engineering and profiling highly combinatorial genetic perturbations. They apply XGA to 16 yeast ABC transporters, revealing many high-order genetic interactions. Neural network models yielded intuitive functional models and illuminated an ABC transporter influence network, supporting application of XGA to other organisms and processes.

Noise-precision tradeoff in predicting combinations of mutations and drugs

Many biological problems involve the response to multiple perturbations. Examples include response to combinations of many drugs, and the effects of combinations of many mutations. Such problems have an exponentially large space of combinations, which makes it infeasible to cover the entire space experimentally. To overcome this problem, several formulae that predict the effect of drug combinations or fitness landscape values have been proposed. These formulae use the effects of single perturbations and pairs of perturbations to predict triplets and higher order combinations. Interestingly, different formulae perform best on different datasets. Here we use Pareto optimality theory to quantitatively explain why no formula is optimal for all datasets, due to an inherent bias-variance (noise-precision) tradeoff. We calculate the Pareto front of log-linear formulae and find that the optimal formula depends on properties of the dataset: the typical interaction strength and the experimental noise. This study provides an approach to choose a suitable prediction formula for a given dataset, in order to best overcome the combinatorial explosion problem.

Sometimes a combination of drugs works much better than each drug alone. Finding such drug cocktails is a pressing challenge in order to combat drug resistance and to improve drug effects. However, it is impossible to test all combinations of multiple drug experimentally. Therefore, researchers are looking for computational rather than experimental approaches to overcome this problem. One approach is to measure the effect of few drugs and plug it into a formula that predicts the effect of many drugs together. Existing prediction formulae typically perform best on the dataset that they were developed on, but less well on other datasets. Here we explain this observation and give a guide for the choice of an optimal prediction formula for a given dataset. The optimal formula depends on two main properties of the dataset: 1) The interaction strength between the drugs and 2) The experimental noise in the data. This study may help researchers discover effective combinations of multiple drugs and multiple perturbations in general.

Yeast genetic interaction screens in the age of CRISPR/Cas

The ease of performing both forward and reverse genetics in Saccharomyces cerevisiae, along with its stable haploid state and short generation times, has made this budding yeast the consummate model eukaryote for genetics. The major advantage of using budding yeast for reverse genetics is this organism's highly efficient homology-directed repair, allowing for precise genome editing simply by introducing DNA with homology to the chromosomal target. Although plasmid- and PCR-based genome editing tools are quite efficient, they depend on rare spontaneous DNA breaks near the target sequence. Consequently, they can generate only one genomic edit at a time, and the edit must be associated with a selectable marker. However, CRISPR/Cas technology is efficient enough to permit markerless and multiplexed edits in a single step. These features have made CRISPR/Cas popular for yeast strain engineering in synthetic biology and metabolic engineering applications, but it has not been widely employed for genetic screens. In this review, we critically examine different methods to generate multi-mutant strains in systematic genetic interaction screens and discuss the potential of CRISPR/Cas to supplement or improve on these methods.

Global Genetic Networks and the Genotype-to-Phenotype Relationship

Genetic interactions identify combinations of genetic variants that impinge on phenotype. With whole-genome sequence information available for thousands of individuals within a species, a major outstanding issue concerns the interpretation of allelic combinations of genes underlying inherited traits. In this Review, we discuss how large-scale analyses in model systems have illuminated the general principles and phenotypic impact of genetic interactions. We focus on studies in budding yeast, including the mapping of a global genetic network. We emphasize how information gained from work in yeast translates to other systems, and how a global genetic network not only annotates gene function but also provides new insights into the genotype-to-phenotype relationship.

Genetic analysis reveals functions of atypical polyubiquitin chains

Although polyubiquitin chains linked through all lysines of ubiquitin exist, specific functions are well-established only for lysine-48 and lysine-63 linkages in Saccharomyces cerevisiae. To uncover pathways regulated by distinct linkages, genetic interactions between a gene deletion library and a panel of lysine-to-arginine ubiquitin mutants were systematically identified. The K11R mutant had strong genetic interactions with threonine biosynthetic genes. Consistently, we found that K11R mutants import threonine poorly. The K11R mutant also exhibited a strong genetic interaction with a subunit of the anaphase-promoting complex (APC), suggesting a role in cell cycle regulation. K11-linkages are important for vertebrate APC function, but this was not previously described in yeast. We show that the yeast APC also modifies substrates with K11-linkages in vitro, and that those chains contribute to normal APC-substrate turnover in vivo. This study reveals comprehensive genetic interactomes of polyubiquitin chains and characterizes the role of K11-chains in two biological pathways.

Synthetic Lethality and Cancer - Penetrance as the Major Barrier

Synthetic lethality has long been proposed as an approach for targeting genetic defects in tumours. Despite a decade of screening efforts, relatively few robust synthetic lethal targets have been identified. Improved genetic perturbation techniques, including CRISPR/Cas9 gene editing, have resulted in renewed enthusiasm for searching for synthetic lethal effects in cancer. An implicit assumption behind this enthusiasm is that the lack of reproducibly identified targets can be attributed to limitations of RNAi technologies. We argue here that a bigger hurdle is that most synthetic lethal interactions (SLIs) are not highly penetrant, in other words they are not robust to the extensive molecular heterogeneity seen in tumours. We outline strategies for identifying and prioritising SLIs that are most likely to be highly penetrant.

[Searching for essential genes in cancer genomes]

The concept of essential genes, whose loss of functionality leads to cell death, is one of the fundamental concepts of genetics and is important for fundamental and applied research. This field is particularly promising in relation to oncology, since the search for genetic vulnerabilities of cancer cells allows us to identify new potential targets for antitumor therapy. The modern biotechnology capacities allow carrying out large-scale projects for sequencing somatic mutations in tumors, as well as directly interfering the genetic apparatus of cancer cells. They provided accumulation of a considerable body of knowledge about genetic variants and corresponding phenotypic manifestations in tumors. In the near future this knowledge will find application in clinical practice. This review describes the main experimental and computational approaches to the search for essential genes, concentrating on the application of these methods in the field of molecular oncology.

Systematic analysis of complex genetic interactions

To systematically explore complex genetic interactions, we constructed ~200,000 yeast triple mutants and scored negative trigenic interactions. We selected double-mutant query genes across a broad spectrum of biological processes, spanning a range of quantitative features of the global digenic interaction network and tested for a genetic interaction with a third mutation. Trigenic interactions often occurred among functionally related genes, and essential genes were hubs on the trigenic network. Despite their functional enrichment, trigenic interactions tended to link genes in distant bioprocesses and displayed a weaker magnitude than digenic interactions. We estimate that the global trigenic interaction network is ~100 times as large as the global digenic network, highlighting the potential for complex genetic interactions to affect the biology of inheritance, including the genotype-to-phenotype relationship.

High-Throughput Quantitative Genetic Interaction Mapping in the Fission Yeast Schizosaccharomyces pombe

Epistasis mapping, in which the phenotype that emerges from combining pairs of mutations is measured quantitatively, is a powerful tool for unbiased study of gene function. When performed at a large scale, this approach has been used to assign function to previously uncharacterized genes, define functional modules and pathways, and study their cross talk. These experiments rely heavily on methods for rapid sampling of binary combinations of mutant alleles by systematic generation of a series of double mutants. Epistasis mapping technologies now exist in various model systems. Here we provide an overview of different epistasis mapping technologies, including the pombe epistasis mapper (PEM) system designed for the collection of quantitative genetic interaction data in fission yeast Schizosaccharomyces pombe Comprising a series of high-throughput selection steps for generation and characterization of double mutants, the PEM system has provided insight into a wide range of biological processes as well as facilitated evolutionary analysis of genetic interactomes across different species.

Mapping a diversity of genetic interactions in yeast

Genetic interactions occur when the combination of multiple mutations yields an unexpected phenotype, and they may confound our ability to fully understand the genetic mechanisms underlying complex diseases. Genetic interactions are challenging to study because there are millions of possible different variant combinations within a given genome. Consequently, they have primarily been systematically explored in unicellular model organisms, such as yeast, with a focus on pairwise genetic interactions between loss-of-function alleles. However, there are many different types of genetic interactions, such as those occurring between gain-of-function or heterozygous mutations. Here, we review recent advances made in the systematic analysis of such diverse genetic interactions in yeast, and briefly discuss how similar studies could be undertaken in human cells.

Synthetic lethality and cancer

A synthetic lethal interaction occurs between two genes when the perturbation of either gene alone is viable but the perturbation of both genes simultaneously results in the loss of viability. Key to exploiting synthetic lethality in cancer treatment are the identification and the mechanistic characterization of robust synthetic lethal genetic interactions. Advances in next-generation sequencing technologies are enabling the identification of hundreds of tumour-specific mutations and alterations in gene expression that could be targeted by a synthetic lethality approach. The translation of synthetic lethality to therapy will be assisted by the synthesis of genetic interaction data from model organisms, tumour genomes and human cell lines.

Genetic interactions and functional analyses of the fission yeast gsk3 and amk2 single and double mutants defective in TORC1-dependent processes

The Target of Rapamycin (TOR) signalling network plays important roles in aging and disease. The AMP-activated protein kinase (AMPK) and the Gsk3 kinase inhibit TOR during stress. We performed genetic interaction screens using synthetic genetic arrays (SGA) with gsk3 and amk2 as query mutants, the latter encoding the regulatory subunit of AMPK. We identified 69 negative and 82 positive common genetic interactors, with functions related to cellular growth and stress. The 120 gsk3-specific negative interactors included genes functioning in translation and ribosomes. The 215 amk2-specific negative interactors included genes functioning in chromatin silencing and DNA damage repair. Both amk2- and gsk3-specific interactors were enriched in phenotype categories related to abnormal cell size and shape. We also performed SGA screen with the amk2 gsk3 double mutant as a query. Mutants sensitive to 5-fluorouracil, an anticancer drug are under-represented within the 305 positive interactors specific for the amk2 gsk3 query. The triple-mutant SGA screen showed higher number of negative interactions than the double mutant SGA screens and uncovered additional genetic network information. These results reveal common and specialized roles of AMPK and Gsk3 in mediating TOR-dependent processes, indicating that AMPK and Gsk3 act in parallel to inhibit TOR function in fission yeast.

Asf1 facilitates dephosphorylation of Rad53 after DNA double-strand break repair

In this study, Tsabar et al. investigated how the DNA damage checkpoint is extinguished and found that dissociation of histone H3 from Asf1, a histone chaperone, is required for efficient recovery. They also show that Asf1 is required for complete dephosphorylation of Rad53 when the upstream DNA damage checkpoint signaling is turned off, providing new insights into the mechanisms regulating the response to DNA damage.

To allow for sufficient time to repair DNA double-stranded breaks (DSBs), eukaryotic cells activate the DNA damage checkpoint. In budding yeast, Rad53 (mammalian Chk2) phosphorylation parallels the persistence of the unrepaired DSB and is extinguished when repair is complete in a process termed recovery or when the cells adapt to the DNA damage checkpoint. A strain containing a slowly repaired DSB does not require the histone chaperone Asf1 to resume cell cycle progression after DSB repair. When a second, rapidly repairable DSB is added to this strain, Asf1 becomes required for recovery. Recovery from two repairable DSBs also depends on the histone acetyltransferase Rtt109 and the cullin subunit Rtt101, both of which modify histone H3 that is associated with Asf1. We show that dissociation of histone H3 from Asf1 is required for efficient recovery and that Asf1 is required for complete dephosphorylation of Rad53 when the upstream DNA damage checkpoint signaling is turned off. Our data suggest that the requirements for recovery from the DNA damage checkpoint become more stringent with increased levels of damage and that Asf1 plays a histone chaperone-independent role in facilitating complete Rad53 dephosphorylation following repair.

Perturb-Seq: Dissecting Molecular Circuits with Scalable Single-Cell RNA Profiling of Pooled Genetic Screens

Genetic screens help infer gene function in mammalian cells, but it has remained difficult to assay complex phenotypes-such as transcriptional profiles-at scale. Here, we develop Perturb-seq, combining single-cell RNA sequencing (RNA-seq) and clustered regularly interspaced short palindromic repeats (CRISPR)-based perturbations to perform many such assays in a pool. We demonstrate Perturb-seq by analyzing 200,000 cells in immune cells and cell lines, focusing on transcription factors regulating the response of dendritic cells to lipopolysaccharide (LPS). Perturb-seq accurately identifies individual gene targets, gene signatures, and cell states affected by individual perturbations and their genetic interactions. We posit new functions for regulators of differentiation, the anti-viral response, and mitochondrial function during immune activation. By decomposing many high content measurements into the effects of perturbations, their interactions, and diverse cell metadata, Perturb-seq dramatically increases the scope of pooled genomic assays.

Synthetic Genetic Arrays: Automation of Yeast Genetics

Genome-sequencing efforts have led to great strides in the annotation of protein-coding genes and other genomic elements. The current challenge is to understand the functional role of each gene and how genes work together to modulate cellular processes. Genetic interactions define phenotypic relationships between genes and reveal the functional organization of a cell. Synthetic genetic array (SGA) methodology automates yeast genetics and enables large-scale and systematic mapping of genetic interaction networks in the budding yeast,Saccharomyces cerevisiae SGA facilitates construction of an output array of double mutants from an input array of single mutants through a series of replica pinning steps. Subsequent analysis of genetic interactions from SGA-derived mutants relies on accurate quantification of colony size, which serves as a proxy for fitness. Since its development, SGA has given rise to a variety of other experimental approaches for functional profiling of the yeast genome and has been applied in a multitude of other contexts, such as genome-wide screens for synthetic dosage lethality and integration with high-content screening for systematic assessment of morphology defects. SGA-like strategies can also be implemented similarly in a number of other cell types and organisms, includingSchizosaccharomyces pombe,Escherichia coli, Caenorhabditis elegans, and human cancer cell lines. The genetic networks emerging from these studies not only generate functional wiring diagrams but may also play a key role in our understanding of the complex relationship between genotype and phenotype.

Translation of Genotype to Phenotype by a Hierarchy of Cell Subsystems

Accurately translating genotype to phenotype requires accounting for the functional impact of genetic variation at many biological scales. Here we present a strategy for genotype-phenotype reasoning based on existing knowledge of cellular subsystems. These subsystems and their hierarchical organization are defined by the Gene Ontology or a complementary ontology inferred directly from previously published datasets. Guided by the ontology's hierarchical structure, we organize genotype data into an "ontotype," that is, a hierarchy of perturbations representing the effects of genetic variation at multiple cellular scales. The ontotype is then interpreted using logical rules generated by machine learning to predict phenotype. This approach substantially outperforms previous, non-hierarchical methods for translating yeast genotype to cell growth phenotype, and it accurately predicts the growth outcomes of two new screens of 2,503 double gene knockouts impacting DNA repair or nuclear lumen. Ontotypes also generalize to larger knockout combinations, setting the stage for interpreting the complex genetics of disease.

Beyond Agar: Gel Substrates with Improved Optical Clarity and Drug Efficiency and Reduced Autofluorescence for Microbial Growth Experiments

Agar, a seaweed extract, has been the standard support matrix for microbial experiments for over a century. Recent developments in high-throughput genetic screens have created a need to reevaluate the suitability of agar for use as colony support, as modern robotic printing systems now routinely spot thousands of colonies within the area of a single microtiter plate. Identifying optimal biophysical, biochemical, and biological properties of the gel support matrix in these extreme experimental conditions is instrumental to achieving the best possible reproducibility and sensitivity. Here we systematically evaluate a range of gelling agents by using the yeast Saccharomyces cerevisiae as a model microbe. We find that carrageenan and Phytagel have superior optical clarity and reduced autofluorescence, crucial for high-resolution imaging and fluorescent reporter screens. Nutrient choice and use of refined Noble agar or pure agarose reduce the effective dose of numerous selective drugs by >50%, potentially enabling large cost savings in genetic screens. Using thousands of mutant yeast strains to compare colony growth between substrates, we found no evidence of significant growth or nutrient biases between gel substrates, indicating that researchers could freely pick and choose the optimal gel for their respective application and experimental condition.

The CAF-1 and Hir Histone Chaperones Associate with Sites of Meiotic Double-Strand Breaks in Budding Yeast

In the meiotic prophase, programmed DNA double-strand breaks (DSB) are introduced along chromosomes to promote homolog pairing and recombination. Although meiotic DSBs usually occur in nucleosome-depleted, accessible regions of chromatin, their repair by homologous recombination takes place in a nucleosomal environment. Nucleosomes may represent an obstacle for the recombination machinery and their timely eviction and reincorporation into chromatin may influence the outcome of recombination, for instance by stabilizing recombination intermediates. Here we show in budding yeast that nucleosomes flanking a meiotic DSB are transiently lost during recombination, and that specific histone H3 chaperones, CAF-1 and Hir, are mobilized at meiotic DSBs. However, the absence of these chaperones has no effect on meiotic recombination, suggesting that timely histone reincorporation following their eviction has no influence on the recombination outcome, or that redundant pathways are activated. This study is the first example of the involvement of histone H3 chaperones at naturally occurring, developmentally programmed DNA double-strand breaks.

Replisome function during replicative stress is modulated by histone h3 lysine 56 acetylation through Ctf4

Histone H3 lysine 56 acetylation in Saccharomyces cerevisiae is required for the maintenance of genome stability under normal conditions and upon DNA replication stress. Here we show that in the absence of H3 lysine 56 acetylation replisome components become deleterious when replication forks collapse at natural replication block sites. This lethality is not a direct consequence of chromatin assembly defects during replication fork progression. Rather, our genetic analyses suggest that in the presence of replicative stress H3 lysine 56 acetylation uncouples the Cdc45-Mcm2-7-GINS DNA helicase complex and DNA polymerases through the replisome component Ctf4. In addition, we discovered that the N-terminal domain of Ctf4, necessary for the interaction of Ctf4 with Mms22, an adaptor protein of the Rtt101-Mms1 E3 ubiquitin ligase, is required for the function of the H3 lysine 56 acetylation pathway, suggesting that replicative stress promotes the interaction between Ctf4 and Mms22. Taken together, our results indicate that Ctf4 is an essential member of the H3 lysine 56 acetylation pathway and provide novel mechanistic insights into understanding the role of H3 lysine 56 acetylation in maintaining genome stability upon replication stress.

Histone chaperones: assisting histone traffic and nucleosome dynamics

The functional organization of eukaryotic DNA into chromatin uses histones as components of its building block, the nucleosome. Histone chaperones, which are proteins that escort histones throughout their cellular life, are key actors in all facets of histone metabolism; they regulate the supply and dynamics of histones at chromatin for its assembly and disassembly. Histone chaperones can also participate in the distribution of histone variants, thereby defining distinct chromatin landscapes of importance for genome function, stability, and cell identity. Here, we discuss our current knowledge of the known histone chaperones and their histone partners, focusing on histone H3 and its variants. We then place them into an escort network that distributes these histones in various deposition pathways. Through their distinct interfaces, we show how they affect dynamics during DNA replication, DNA damage, and transcription, and how they maintain genome integrity. Finally, we discuss the importance of histone chaperones during development and describe how misregulation of the histone flow can link to disease.

Histone chaperone CAF-1: essential roles in multi-cellular organism development

More and more studies have shown chromatin remodelers and histone modifiers play essential roles in regulating developmental patterns by organizing specific chromosomal architecture to establish programmed transcriptional profiles, with implications that histone chaperones execute a coordinating role in these processes. Chromatin assembly factor-1 (CAF-1), an evolutionarily conserved three-subunit protein complex, was identified as a histone chaperone coupled with DNA replication and repair in cultured mammalian cells and yeasts. Interestingly, recent findings indicate CAF-1 may have important regulatory roles during development by interacting with specific transcription factors and epigenetic regulators. In this review, we focus on the essential roles of CAF-1 in regulating heterochromatin organization, asymmetric cell division, and specific signal transduction through epigenetic modulations of the chromatin. In the end, we aim at providing a current image of facets of CAF-1 as a histone chaperone to orchestrate cell proliferation and differentiation during multi-cellular organism development.

Quantitative analysis of triple-mutant genetic interactions

The quantitative analysis of genetic interactions between pairs of gene mutations has proven to be effective for characterizing cellular functions, but it can miss important interactions for functionally redundant genes. To address this limitation, we have developed an approach termed triple-mutant analysis (TMA). The procedure relies on a query strain that contains two deletions in a pair of redundant or otherwise related genes, which is crossed against a panel of candidate deletion strains to isolate triple mutants and measure their growth. A central feature of TMA is to interrogate mutants that are synthetically sick when two other genes are deleted but interact minimally with either single deletion. This approach has been valuable for discovering genes that restore critical functions when the principal actors are deleted. TMA has also uncovered double-mutant combinations that produce severe defects because a third protein becomes deregulated and acts in a deleterious fashion, and it has revealed functional differences between proteins presumed to act together. The protocol is optimized for Singer ROTOR pinning robots, takes 3 weeks to complete and measures interactions for up to 30 double mutants against a library of 1,536 single mutants.

DNA replication and spindle checkpoints cooperate during S phase to delay mitosis and preserve genome integrity

Deoxyribonucleic acid (DNA) replication and chromosome segregation must occur in ordered sequence to maintain genome integrity during cell proliferation. Checkpoint mechanisms delay mitosis when DNA is damaged or upon replication stress, but little is known on the coupling of S and M phases in unperturbed conditions. To address this issue, we postponed replication onset in budding yeast so that DNA synthesis is still underway when cells should enter mitosis. This delayed mitotic entry and progression by transient activation of the S phase, G2/M, and spindle assembly checkpoints. Disabling both Mec1/ATR- and Mad2-dependent controls caused lethality in cells with deferred S phase, accompanied by Rad52 foci and chromosome missegregation. Thus, in contrast to acute replication stress that triggers a sustained Mec1/ATR response, multiple pathways cooperate to restrain mitosis transiently when replication forks progress unhindered. We suggest that these surveillance mechanisms arose when both S and M phases were coincidently set into motion by a unique ancestral cyclin-Cdk1 complex.

High-resolution network biology: connecting sequence with function

Proteins are not monolithic entities; rather, they can contain multiple domains that mediate distinct interactions, and their functionality can be regulated through post-translational modifications at multiple distinct sites. Traditionally, network biology has ignored such properties of proteins and has instead examined either the physical interactions of whole proteins or the consequences of removing entire genes. In this Review, we discuss experimental and computational methods to increase the resolution of protein-protein, genetic and drug-gene interaction studies to the domain and residue levels. Such work will be crucial for using interaction networks to connect sequence and structural information, and to understand the biological consequences of disease-associated mutations, which will hopefully lead to more effective therapeutic strategies.