The nonessentiality of essential genes in yeast provides therapeutic insights into a human disease

Recent advances in the characterization of essential genes and development of a database of essential genes

Over the past few decades, there has been a significant interest in the study of essential genes, which are crucial for the survival of an organism under specific environmental conditions and thus have practical applications in the fields of synthetic biology and medicine. An increasing amount of experimental data on essential genes has been obtained with the continuous development of technological methods. Meanwhile, various computational prediction methods, related databases and web servers have emerged accordingly. To facilitate the study of essential genes, we have established a database of essential genes (DEG), which has become popular with continuous updates to facilitate essential gene feature analysis and prediction, drug and vaccine development, as well as artificial genome design and construction. In this article, we summarized the studies of essential genes, overviewed the relevant databases, and discussed their practical applications. Furthermore, we provided an overview of the main applications of DEG and conducted comprehensive analyses based on its latest version. However, it should be noted that the essential gene is a dynamic concept instead of a binary one, which presents both opportunities and challenges for their future development.

A Caenorhabditis elegans model of adenylosuccinate lyase deficiency reveals neuromuscular and reproductive phenotypes of distinct etiology

Inborn errors of purine metabolism are rare syndromes with an array of complex phenotypes in humans. One such disorder, adenylosuccinate lyase deficiency (ASLD), is caused by a decrease in the activity of the bi-functional purine biosynthetic enzyme adenylosuccinate lyase (ADSL). Mutations in human ADSL cause epilepsy, muscle ataxia, and autistic-like symptoms. Although the genetic basis of ASLD is known, the molecular mechanisms driving phenotypic outcome are not. Here, we characterize neuromuscular and reproductive phenotypes associated with a deficiency of adsl-1 in Caenorhabditis elegans. We demonstrate that adsl-1 function contributes to regulation of spontaneous locomotion, that adsl-1 functions acutely for proper mobility, and that aspects of adsl-1-related dysfunction are reversible. Using pharmacological supplementation, we correlate phenotypes with distinct metabolic perturbations. The neuromuscular defect correlates with accumulation of a purine biosynthetic intermediate whereas reproductive deficiencies can be ameliorated by purine supplementation, indicating differing molecular mechanisms behind the phenotypes. Because purine metabolism is highly conserved in metazoans, we suggest that similar separable metabolic perturbations result in the varied symptoms in the human disorder and that a dual-approach therapeutic strategy may be beneficial.

Adenylosuccinate lyase deficiency affects neurobehavior via perturbations to tyramine signaling in Caenorhabditis elegans

Adenylosuccinate lyase deficiency is an ultrarare congenital metabolic disorder associated with muscle weakness and neurobehavioral dysfunction. Adenylosuccinate lyase is required for de novo purine biosynthesis, acting twice in the pathway at non-sequential steps. Genetic models can contribute to our understanding of the etiology of disease phenotypes and pave the way for development of therapeutic treatments. Here, we establish the first model to specifically study neurobehavioral aspects of adenylosuccinate lyase deficiency. We show that reduction of adsl-1 function in C. elegans is associated with a novel learning phenotype in a gustatory plasticity assay. The animals maintain capacity for gustatory plasticity, evidenced by a change in their behavior in response to cue pairing. However, their behavioral output is distinct from that of control animals. We link substrate accumulation that occurs upon adsl-1 deficiency to an unexpected perturbation in tyrosine metabolism and show that a lack of tyramine mediates the behavioral changes through action on the metabotropic TYRA-2 tyramine receptor. Our studies reveal a potential for wider metabolic perturbations, beyond biosynthesis of purines, to impact behavior under conditions of adenylosuccinate lyase deficiency.

Multiple intermolecular interactions facilitate rapid evolution of essential genes

Essential genes are commonly assumed to function in basic cellular processes and to change slowly. However, it remains unclear whether all essential genes are similarly conserved or if their evolutionary rates can be accelerated by specific factors. To address these questions, we replaced 86 essential genes of Saccharomyces cerevisiae with orthologues from four other species that diverged from S. cerevisiae about 50, 100, 270 and 420 Myr ago. We identify a group of fast-evolving genes that often encode subunits of large protein complexes, including anaphase-promoting complex/cyclosome (APC/C). Incompatibility of fast-evolving genes is rescued by simultaneously replacing interacting components, suggesting it is caused by protein co-evolution. Detailed investigation of APC/C further revealed that co-evolution involves not only primary interacting proteins but also secondary ones, suggesting the evolutionary impact of epistasis. Multiple intermolecular interactions in protein complexes may provide a microenvironment facilitating rapid evolution of their subunits.

Suppressor mutations that make the essential transcription factor Spn1/Iws1 dispensable in Saccharomyces cerevisiae

Spn1/Iws1 is an essential eukaryotic transcription elongation factor that is conserved from yeast to humans as an integral member of the RNA polymerase II elongation complex. Several studies have shown that Spn1 functions as a histone chaperone to control transcription, RNA splicing, genome stability, and histone modifications. However, the precise role of Spn1 is not understood, and there is little understanding of why it is essential for viability. To address these issues, we have isolated 8 suppressor mutations that bypass the essential requirement for Spn1 in Saccharomyces cerevisiae. Unexpectedly, the suppressors identify several functionally distinct complexes and activities, including the histone chaperone FACT, the histone methyltransferase Set2, the Rpd3S histone deacetylase complex, the histone acetyltransferase Rtt109, the nucleosome remodeler Chd1, and a member of the SAGA coactivator complex, Sgf73. The identification of these distinct groups suggests that there are multiple ways in which Spn1 bypass can occur, including changes in histone acetylation and alterations in other histone chaperones. Thus, Spn1 may function to overcome repressive chromatin by multiple mechanisms during transcription. Our results suggest that bypassing a subset of these functions allows viability in the absence of Spn1.

Exploring conditional gene essentiality through systems genetics approaches in yeast

An essential gene encodes for a cellular function that is required for viability. Although viability is a straightforward phenotype to analyze in yeast, defining a gene as essential is not always trivial. Gene essentiality has generally been studied in specific laboratory strains and under standard growth conditions, however, essentiality can vary across species, strains, and environments. Recent systematic studies of gene essentiality revealed that two sets of essential genes exist: core essential genes that are always required for viability and conditional essential genes that vary in essentiality in different genetic and environmental contexts. Here, we review recent advances made in the systematic analysis of gene essentiality in yeast and discuss the properties that distinguish core from context-dependent essential genes.

Systematic Identification of Essential Genes Required for Yeast Cell Wall Integrity: Involvement of the RSC Remodelling Complex

Conditions altering the yeast cell wall lead to the activation of an adaptive transcriptional response mainly governed by the cell wall integrity (CWI) mitogen-activated protein kinase (MAPK) pathway. Two high-throughput screenings were developed using the yTHC collection of yeast conditional mutant strains to systematically identify essential genes related to cell wall integrity, and those required for the transcriptional program elicited by cell wall stress. Depleted expression of 52 essential genes resulted in hypersensitivity to the dye Calcofluor white, with chromatin organization, Golgi vesicle transport, rRNA processing, and protein glycosylation processes, as the most highly representative functional groups. Via a flow cytometry-based quantitative assay using a CWI reporter plasmid, 97 strains exhibiting reduced gene-reporter expression levels upon stress were uncovered, highlighting genes associated with RNA metabolism, transcription/translation, protein degradation, and chromatin organization. This screening also led to the discovery of 41 strains displaying a basal increase in CWI-associated gene expression, including mainly putative cell wall-related genes. Interestingly, several members of the RSC chromatin remodelling complex were uncovered in both screenings. Notably, Rsc9 was necessary to regulate the gene expression of CWI-related genes both under stress and non-stress conditions, suggesting distinct requirements of the RSC complex for remodelling particular genes.

Rapid intraspecies evolution of fitness effects of yeast genes

Organisms within species have numerous genetic and phenotypic variations. Growing evidences show intraspecies variation of mutant phenotypes may be more complicated than expected. Current studies on intraspecies variations of mutant phenotypes are limited to just a few strains. This study investigated the intraspecies variation of fitness effects of 5,630 gene mutants in ten Saccharomyces cerevisiae strains using CRISPR–Cas9 screening. We found that the variability of fitness effects induced by gene disruptions is very large across different strains. Over 75% of genes affected cell fitness in a strain-specific manner to varying degrees. The strain specificity of the fitness effect of a gene is related to its evolutionary and functional properties. Subsequent analysis revealed that younger genes, especially those newly acquired in S. cerevisiae species, are more likely to be strongly strain-specific. Intriguingly, there seems to exist a ceiling of fitness effect size for strong strain-specific genes, and among them, the newly acquired genes are still evolving and have yet to reach this ceiling. Additionally, for a large proportion of protein complexes, the strain specificity profile is inconsistent among genes encoding the same complex. Taken together, these results offer a genome-wide map of intraspecies variation for fitness effect as a mutant phenotype and provide an updated insight on intraspecies phenotypic evolution.

Transposon insertional mutagenesis of diverse yeast strains suggests coordinated gene essentiality polymorphisms

Due to epistasis, the same mutation can have drastically different phenotypic consequences in different individuals. This phenomenon is pertinent to precision medicine as well as antimicrobial drug development, but its general characteristics are largely unknown. We approach this question by genome-wide assessment of gene essentiality polymorphism in 16 Saccharomyces cerevisiae strains using transposon insertional mutagenesis. Essentiality polymorphism is observed for 9.8% of genes, most of which have had repeated essentiality switches in evolution. Genes exhibiting essentiality polymorphism lean toward having intermediate numbers of genetic and protein interactions. Gene essentiality changes tend to occur concordantly among components of the same protein complex or metabolic pathway and among a group of over 100 mitochondrial proteins, revealing molecular machines or functional modules as units of gene essentiality variation. Most essential genes tolerate transposon insertions consistently among strains in one or more coding segments, delineating nonessential regions within essential genes.

Predicting miRNA-disease associations via layer attention graph convolutional network model

BACKGROUND

MiRNA is a class of non-coding single-stranded RNA molecules with a length of approximately 22 nucleotides encoded by endogenous genes, which can regulate the expression of other genes. Therefore, it is very important to predict the associations between miRNA and disease. Predecessors developed a new prediction method of drug-disease association, and it achieved good results.

METHODS

In this paper, we introduced the method of LAGCN to identify potential miRNA-disease associations. First, we integrate three associations into a heterogeneous network, such as the known miRNA-disease association, miRNA-miRNA similarities and disease-disease similarities, next we apply graph convolution network to learn the embedding of miRNA and disease. We use an attention mechanism to combine embedding from multiple convolution layers. Unobserved miRNA-disease associations are scored based on integrated embedding.

RESULTS

After fivefold cross-validations, the value of AUC is reached 0.9091, which is higher than other prediction methods and baseline methods.

CONCLUSIONS

In this paper, we introduced the method of LAGCN to identify potential miRNA-disease associations. LAGCN has achieved good performance in predicting miRNA-disease associations, and it is superior to other association prediction methods and baseline methods.

Pathway-specific effects of ADSL deficiency on neurodevelopment

Adenylosuccinate lyase (ADSL) functions in de novo purine synthesis (DNPS) and the purine nucleotide cycle. ADSL deficiency (ADSLD) causes numerous neurodevelopmental pathologies, including microcephaly and autism spectrum disorder. ADSLD patients have normal serum purine nucleotide levels but exhibit accumulation of dephosphorylated ADSL substrates, S-Ado, and SAICAr, the latter being implicated in neurotoxic effects through unknown mechanisms. We examined the phenotypic effects of ADSL depletion in human cells and their relation to phenotypic outcomes. Using specific interventions to compensate for reduced purine levels or modulate SAICAr accumulation, we found that diminished AMP levels resulted in increased DNA damage signaling and cell cycle delays, while primary ciliogenesis was impaired specifically by loss of ADSL or administration of SAICAr. ADSL-deficient chicken and zebrafish embryos displayed impaired neurogenesis and microcephaly. Neuroprogenitor attrition in zebrafish embryos was rescued by pharmacological inhibition of DNPS, but not increased nucleotide concentration. Zebrafish also displayed phenotypes commonly linked to ciliopathies. Our results suggest that both reduced purine levels and impaired DNPS contribute to neurodevelopmental pathology in ADSLD and that defective ciliogenesis may influence the ADSLD phenotypic spectrum.

Mapping single-cell-resolution cell phylogeny reveals cell population dynamics during organ development

Mapping the cell phylogeny of a complex multicellular organism relies on somatic mutations accumulated from zygote to adult. Available cell barcoding methods can record about three mutations per barcode, enabling only low-resolution mapping of the cell phylogeny of complex organisms. Here we developed SMALT, a substitution mutation-aided lineage-tracing system that outperforms the available cell barcoding methods in mapping cell phylogeny. We applied SMALT to Drosophila melanogaster and obtained on average more than 20 mutations on a three-kilobase-pair barcoding sequence in early-adult cells. Using the barcoding mutations, we obtained high-quality cell phylogenetic trees, each comprising several thousand internal nodes with 84-93% median bootstrap support. The obtained cell phylogenies enabled a population genetic analysis that estimates the longitudinal dynamics of the number of actively dividing parental cells (Np) in each organ through development. The Np dynamics revealed the trajectory of cell births and provided insight into the balance of symmetric and asymmetric cell division.

Harnessing model organism genomics to underpin the machine learning-based prediction of essential genes in eukaryotes - Biotechnological implications

The availability of high-quality genomes and advances in functional genomics have enabled large-scale studies of essential genes in model eukaryotes, including the 'elegant worm' (Caenorhabditis elegans; Nematoda) and the 'vinegar fly' (Drosophila melanogaster; Arthropoda). However, this is not the case for other, much less-studied organisms, such as socioeconomically important parasites, for which functional genomic platforms usually do not exist. Thus, there is a need to develop innovative techniques or approaches for the prediction, identification and investigation of essential genes. A key approach that could enable the prediction of such genes is machine learning (ML). Here, we undertake an historical review of experimental and computational approaches employed for the characterisation of essential genes in eukaryotes, with a particular focus on model ecdysozoans (C. elegans and D. melanogaster), and discuss the possible applicability of ML-approaches to organisms such as socioeconomically important parasites. We highlight some recent results showing that high-performance ML, combined with feature engineering, allows a reliable prediction of essential genes from extensive, publicly available 'omic data sets, with major potential to prioritise such genes (with statistical confidence) for subsequent functional genomic validation. These findings could 'open the door' to fundamental and applied research areas. Evidence of some commonality in the essential gene-complement between these two organisms indicates that an ML-engineering approach could find broader applicability to ecdysozoans such as parasitic nematodes or arthropods, provided that suitably large and informative data sets become/are available for proper feature engineering, and for the robust training and validation of algorithms. This area warrants detailed exploration to, for example, facilitate the identification and characterisation of essential molecules as novel targets for drugs and vaccines against parasitic diseases. This focus is particularly important, given the substantial impact that such diseases have worldwide, and the current challenges associated with their prevention and control and with drug resistance in parasite populations.

Ancestry analysis indicates two different sets of essential genes in eukaryotic model species

Essential genes are so-called because they are crucial for organism perpetuation. Those genes are usually related to essential functions to cellular metabolism or multicellular homeostasis. Deleterious alterations on essential genes produce a spectrum of phenotypes in multicellular organisms. The effects range from the impairment of the fertilization process, disruption of fetal development, to loss of reproductive capacity. Essential genes are described as more evolutionarily conserved than non-essential genes. However, there is no consensus about the relationship between gene essentiality and gene age. Here, we identified essential genes in five model eukaryotic species (Saccharomyces cerevisiae, Schizosaccharomyces pombe, Drosophila melanogaster, Caenorhabditis elegans, and Mus musculus) and estimate their evolutionary ancestry and their network properties. We observed that essential genes, on average, are older than other genes in all species investigated. The relationship of network properties and gene essentiality convey with previous findings, showing essential genes as important nodes in biological networks. As expected, we also observed that essential orthologs shared by the five species evaluated here are old. However, all the species evaluated here have a specific set of young essential genes not shared among them. Additionally, these two groups of essential genes are involved with distinct biological functions, suggesting two sets of essential genes: (i) a set of old essential genes common to all the evaluated species, regulating basic cellular functions, and (ii) a set of young essential genes exclusive to each species, which perform specific essential functions in each species.

In vivo and in vitro human gene essentiality estimations capture contrasting functional constraints

Gene essentiality estimation is a popular empirical approach to link genotypes to phenotypes. In humans, essentiality is estimated based on loss-of-function (LoF) mutation intolerance, either from population exome sequencing (in vivo) data or CRISPR-based in vitro perturbation experiments. Both approaches identify genes presumed to have detrimental consequences on the organism upon mutation. Are these genes constrained by having key cellular/organismal roles? Do in vivo and in vitro estimations equally recover these constraints? Insights into these questions have important implications in generalizing observations from cell models and interpreting disease risk genes. To empirically address these questions, we integrate genome-scale datasets and compare structural, functional and evolutionary features of essential genes versus genes with extremely high mutational tolerance. We found that essentiality estimates do recover functional constraints. However, the organismal or cellular context of estimation leads to functionally contrasting properties underlying the constraint. Our results suggest that depletion of LoF mutations in human populations effectively captures organismal-level functional constraints not experimentally accessible through CRISPR-based screens. Finally, we identify a set of genes (OrgEssential), which are mutationally intolerant in vivo but highly tolerant in vitro. These genes drive observed functional constraint differences and have an unexpected preference for nervous system expression.

Moderate levels of 5-fluorocytosine cause the emergence of high frequency resistance in cryptococci

The antifungal agent 5-fluorocytosine (5-FC) is used for the treatment of several mycoses, but is unsuitable for monotherapy due to the rapid development of resistance. Here, we show that cryptococci develop resistance to 5-FC at a high frequency when exposed to concentrations several fold above the minimal inhibitory concentration. The genomes of resistant clones contain alterations in genes relevant as well as irrelevant for 5-FC resistance, suggesting that 5-FC may be mutagenic at moderate concentrations. Mutations in FCY2 (encoding a known permease for 5-FC uptake), FCY1, FUR1, UXS1 (encoding an enzyme that converts UDP-glucuronic acid to UDP-xylose) and URA6 contribute to 5-FC resistance. The uxs1 mutants accumulate UDP-glucuronic acid, which appears to down-regulate expression of permease FCY2 and reduce cellular uptake of the drug. Additional mutations in genes known to be required for UDP-glucuronic acid synthesis (UGD1) or a transcriptional factor NRG1 suppress UDP-glucuronic acid accumulation and 5-FC resistance in the uxs1 mutants.

Pathogenic fungi rapidly develop resistance to the antifungal agent 5-fluorocytosine (5-FC). Here, Chang et al. explore the mechanisms by which Cryptococcus develops 5-FC resistance at a high frequency, including mutations in several genes and altered levels of key metabolites.

Essential genes from genome-wide screenings as a resource for neuropsychiatric disorders gene discovery

Genome-wide screenings of "essential genes", i.e., genes required for an organism or cell survival, have been traditionally conducted in vitro in cancer cell lines, limiting the translation of results to other tissues and non-cancerous cells. Recently, an in vivo screening was conducted in adult mouse striatum tissue, providing the first genome-wide dataset of essential genes in neuronal cells. Here, we aim to investigate the role of essential genes in brain development and disease risk with a comprehensive set of bioinformatics tools, including integration with transcriptomic data from developing human brain, publicly available data from genome-wide association studies, de novo mutation datasets for different neuropsychiatric disorders, and case-control transcriptomic data from postmortem brain tissues. For the first time, we found that the expression of neuronal essential genes (NEGs) increases before birth during the early development of human brain and maintains a relatively high expression after birth. On the contrary, common essential genes from cancer cell line screenings (ACEGs) tend to be expressed at high levels during development but quickly drop after birth. Both gene sets were enriched in neurodevelopmental disorders, but only NEGs were robustly associated with neuropsychiatric disorders risk genes. Finally, NEGs were more likely to show differential expression in the brains of neuropsychiatric disorders patients than ACEGs. Overall, genome-wide central nervous system screening of essential genes can provide new insights into neuropsychiatric diseases.

Position preference of essential genes in prokaryotic operons

Essential genes, which form the basis of life activities, are crucial for the survival of organisms. Essential genes tend to be located in operons, but how they are distributed in operons is still unclear for most prokaryotes. In order to clarify the general rule of position preference of essential genes in operons, an index of the average position of genes in an operon was proposed, and the distributions of essential and non-essential genes in operons in 51 bacterial genomes and two archaeal genomes were analyzed based on this new index. Consequently, essential genes were found to preferentially occupy the front positions of the operons, which tend to be expressed at higher levels.

Genotype to Phenotype: CRISPR Gene Editing Reveals Genetic Compensation as a Mechanism for Phenotypic Disjunction of Morphants and Mutants

Forward genetic screens have shown the consequences of deleterious mutations; however, they are best suited for model organisms with fast reproductive rates and large broods. Furthermore, investigators must faithfully identify changes in phenotype, even if subtle, to realize the full benefit of the screen. Reverse genetic approaches also probe genotype to phenotype relationships, except that the genetic targets are predefined. Until recently, reverse genetic approaches relied on non-genomic gene silencing or the relatively inefficient, homology-dependent gene targeting for loss-of-function generation. Fortunately, the flexibility and simplicity of the clustered regularly interspaced short palindromic repeats (CRISPR)/Cas system has revolutionized reverse genetics, allowing for the precise mutagenesis of virtually any gene in any organism at will. The successful integration of insertions/deletions (INDELs) and nonsense mutations that would, at face value, produce the expected loss-of-function phenotype, have been shown to have little to no effect, even if other methods of gene silencing demonstrate robust loss-of-function consequences. The disjunction between outcomes has raised important questions about our understanding of genotype to phenotype and highlights the capacity for compensation in the central dogma. This review describes recent studies in which genomic compensation appears to be at play, discusses the possible compensation mechanisms, and considers elements important for robust gene loss-of-function studies.

Combined embedding model for MiRNA-disease association prediction

BACKGROUND

Cumulative evidence from biological experiments has confirmed that miRNAs have significant roles to diagnose and treat complex diseases. However, traditional medical experiments have limitations in time-consuming and high cost so that they fail to find the unconfirmed miRNA and disease interactions. Thus, discovering potential miRNA-disease associations will make a contribution to the decrease of the pathogenesis of diseases and benefit disease therapy. Although, existing methods using different computational algorithms have favorable performances to search for the potential miRNA-disease interactions. We still need to do some work to improve experimental results.

RESULTS

We present a novel combined embedding model to predict MiRNA-disease associations (CEMDA) in this article. The combined embedding information of miRNA and disease is composed of pair embedding and node embedding. Compared with the previous heterogeneous network methods that are merely node-centric to simply compute the similarity of miRNA and disease, our method fuses pair embedding to pay more attention to capturing the features behind the relative information, which models the fine-grained pairwise relationship better than the previous case when each node only has a single embedding. First, we construct the heterogeneous network from supported miRNA-disease pairs, disease semantic similarity and miRNA functional similarity. Given by the above heterogeneous network, we find all the associated context paths of each confirmed miRNA and disease. Meta-paths are linked by nodes and then input to the gate recurrent unit (GRU) to directly learn more accurate similarity measures between miRNA and disease. Here, the multi-head attention mechanism is used to weight the hidden state of each meta-path, and the similarity information transmission mechanism in a meta-path of miRNA and disease is obtained through multiple network layers. Second, pair embedding of miRNA and disease is fed to the multi-layer perceptron (MLP), which focuses on more important segments in pairwise relationship. Finally, we combine meta-path based node embedding and pair embedding with the cost function to learn and predict miRNA-disease association. The source code and data sets that verify the results of our research are shown at https://github.com/liubailong/CEMDA .

CONCLUSIONS

The performance of CEMDA in the leave-one-out cross validation and fivefold cross validation are 93.16% and 92.03%, respectively. It denotes that compared with other methods, CEMDA accomplishes superior performance. Three cases with lung cancers, breast cancers, prostate cancers and pancreatic cancers show that 48,50,50 and 50 out of the top 50 miRNAs, which are confirmed in HDMM V2.0. Thus, this further identifies the feasibility and effectiveness of our method.

Systematic analysis of bypass suppression of essential genes

Essential genes tend to be highly conserved across eukaryotes, but, in some cases, their critical roles can be bypassed through genetic rewiring. From a systematic analysis of 728 different essential yeast genes, we discovered that 124 (17%) were dispensable essential genes. Through whole-genome sequencing and detailed genetic analysis, we investigated the genetic interactions and genome alterations underlying bypass suppression. Dispensable essential genes often had paralogs, were enriched for genes encoding membrane-associated proteins, and were depleted for members of protein complexes. Functionally related genes frequently drove the bypass suppression interactions. These gene properties were predictive of essential gene dispensability and of specific suppressors among hundreds of genes on aneuploid chromosomes. Our findings identify yeast's core essential gene set and reveal that the properties of dispensable essential genes are conserved from yeast to human cells, correlating with human genes that display cell line-specific essentiality in the Cancer Dependency Map (DepMap) project.

Transcriptional adaptation: a mechanism underlying genetic robustness

Mutations play a crucial role in evolution as they provide the genetic variation that allows evolutionary change. Although some mutations in regulatory elements or coding regions can be beneficial, a large number of them disrupt gene function and reduce fitness. Organisms utilize several mechanisms to compensate for the damaging consequences of genetic perturbations. One such mechanism is the recently identified process of transcriptional adaptation (TA): during this event, mutations that cause mutant mRNA degradation trigger the transcriptional modulation of so-called adapting genes. In some cases, for example when one (or more) of the upregulated genes is functionally redundant with the mutated gene, this process compensates for the loss of the mutated gene's product. Notably, unlike other mechanisms underlying genetic robustness, TA is not triggered by the loss of protein function, an observation that has prompted studies into the machinery of TA and the contexts in which it functions. Here, we review the discovery and current understanding of TA, and discuss how its main features appear to be conserved across species. In light of these findings, we also speculate on the importance of TA in the context of human disease, and provide some recommendations for genome-editing strategies that should be more effective.

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.

Decoupling gene functions from knockout effects by evolutionary analyses

Genic functions have long been confounded by pleiotropic mutational effects. To understand such genetic effects, we examine HAP4, a well-studied transcription factor in Saccharomyces cerevisiae that functions by forming a tetramer with HAP2, HAP3 and HAP5. Deletion of HAP4 results in highly pleiotropic gene expression responses, some of which are clustered in related cellular processes (clustered effects) while most are distributed randomly across diverse cellular processes (distributed effects). Strikingly, the distributed effects that account for much of HAP4 pleiotropy tend to be non-heritable in a population, suggesting they have few evolutionary consequences. Indeed, these effects are poorly conserved in closely related yeasts. We further show substantial overlaps of clustered effects, but not distributed effects, among the four genes encoding the HAP2/3/4/5 tetramer. This pattern holds for other biochemically characterized yeast protein complexes or metabolic pathways. Examination of a set of cell morphological traits of the deletion lines yields consistent results. Hence, only some deletion effects of a gene support related biochemical understandings with the rest being often pleiotropic and evolutionarily decoupled from the gene's normal functions. This study suggests a new framework for reverse genetic analysis.

Genetic compensation in a stable slc25a46 mutant zebrafish: A case for using F0 CRISPR mutagenesis to study phenotypes caused by inherited disease

A phenomenon of genetic compensation is commonly observed when an organism with a disease-bearing mutation shows incomplete penetrance of the disease phenotype. Such incomplete phenotypic penetrance, or genetic compensation, is more commonly found in stable knockout models, rather than transient knockdown models. As such, these incidents present a challenge for the disease modeling field, although a deeper understanding of genetic compensation may also hold the key for novel therapeutic interventions. In our study we created a knockout model of slc25a46 gene, which is a recently discovered important player in mitochondrial dynamics, and deleterious mutations in which are known to cause peripheral neuropathy, optic atrophy and cerebellar ataxia. We report a case of genetic compensation in a stable slc25a46 homozygous zebrafish mutant (hereafter referred as “mutant”), in contrast to a penetrant disease phenotype in the first generation (F0) slc25a46 mosaic mutant (hereafter referred as “crispant”), generated with CRISPR/Cas-9 technology. We show that the crispant phenotype is specific and rescuable. By performing mRNA sequencing, we define significant changes in slc25a46 mutant’s gene expression profile, which are largely absent in crispants. We find that among the most significantly altered mRNAs, anxa6 gene stands out as a functionally relevant player in mitochondrial dynamics. We also find that our genetic compensation case does not arise from mechanisms driven by mutant mRNA decay. Our study contributes to the growing evidence of the genetic compensation phenomenon and presents novel insights about Slc25a46 function. Furthermore, our study provides the evidence for the efficiency of F0 CRISPR screens for disease candidate genes, which may be used to advance the field of functional genetics.

Comprehensive understanding of Saccharomyces cerevisiae phenotypes with whole-cell model WM_S288C

Biological network construction for Saccharomyces cerevisiae is a widely used approach for simulating phenotypes and designing cell factories. However, due to a complicated regulatory mechanism governing the translation of genotype to phenotype, precise prediction of phenotypes remains challenging. Here, we present WM_S288C, a computational whole-cell model that includes 15 cellular states and 26 cellular processes and which enables integrated analyses of physiological functions of Saccharomyces cerevisiae. Using WM_S288C to predict phenotypes of S. cerevisiae, the functions of 1140 essential genes were characterized and linked to phenotypes at five levels. During the cell cycle, the dynamic allocation of intracellular molecules could be tracked in real-time to simulate cell activities. Additionally, one-third of non-essential genes were identified to affect cell growth via regulating nucleotide concentrations. These results demonstrated the value of WM_S288C as a tool for understanding and investigating the phenotypes of S. cerevisiae.

The conditional nature of gene essentiality

Essential genes are classically defined as required for cellular viability and reproductive success. Despite this deceptively simple definition, several lines of evidence suggest that gene essentiality is instead a conditional trait. Indeed, gene essentiality has been shown to depend on the environmental and genetic context as well as the variable ability of cells to acquire adaptive mutations to survive inactivation of seemingly essential genes. Here, we will discuss these findings and highlight the mechanisms underlying the ability of cells to survive an essential gene deletion. Also, since essential genes are prioritized as targets for anticancer therapy, we discuss emergence of bypass resistance mechanisms toward targeted therapies as the result of the conditional nature of gene essentiality. To identify targets associated to a lower risk of relapse (i.e. the return of cancer following remission), we finally call for a coordinated effort to quantify the variable nature of gene essentiality across species, cell types, and growth conditions.

Systematic analysis reveals the prevalence and principles of bypassable gene essentiality

Gene essentiality is a variable phenotypic trait, but to what extent and how essential genes can become dispensable for viability remain unclear. Here, we investigate 'bypass of essentiality (BOE)' - an underexplored type of digenic genetic interaction that renders essential genes dispensable. Through analyzing essential genes on one of the six chromosome arms of the fission yeast Schizosaccharomyces pombe, we find that, remarkably, as many as 27% of them can be converted to non-essential genes by BOE interactions. Using this dataset we identify three principles of essentiality bypass: bypassable essential genes tend to have lower importance, tend to exhibit differential essentiality between species, and tend to act with other bypassable genes. In addition, we delineate mechanisms underlying bypassable essentiality, including the previously unappreciated mechanism of dormant redundancy between paralogs. The new insights gained on bypassable essentiality deepen our understanding of genotype-phenotype relationships and will facilitate drug development related to essential genes.

Emerging and evolving concepts in gene essentiality

Gene essentiality is a founding concept of genetics with important implications in both fundamental and applied research. Multiple screens have been performed over the years in bacteria, yeasts, animals and more recently in human cells to identify essential genes. A mounting body of evidence suggests that gene essentiality, rather than being a static and binary property, is both context dependent and evolvable in all kingdoms of life. This concept of a non-absolute nature of gene essentiality changes our fundamental understanding of essential biological processes and could directly affect future treatment strategies for cancer and infectious diseases.

Genetic compensation: A phenomenon in search of mechanisms

Several recent studies in a number of model systems including zebrafish, Arabidopsis, and mouse have revealed phenotypic differences between knockouts (i.e., mutants) and knockdowns (e.g., antisense-treated animals). These differences have been attributed to a number of reasons including off-target effects of the antisense reagents. An alternative explanation was recently proposed based on a zebrafish study reporting that genetic compensation was observed in egfl7 mutant but not knockdown animals. Dosage compensation was first reported in Drosophila in 1932, and genetic compensation in response to a gene knockout was first reported in yeast in 1969. Since then, genetic compensation has been documented many times in a number of model organisms; however, our understanding of the underlying molecular mechanisms remains limited. In this review, we revisit studies reporting genetic compensation in higher eukaryotes and outline possible molecular mechanisms, which may include both transcriptional and posttranscriptional processes.

Mechanisms of suppression: The wiring of genetic resilience

Recent analysis of genome sequences has identified individuals that are healthy despite carrying severe disease-associated mutations. A possible explanation is that these individuals carry a second genomic perturbation that can compensate for the detrimental effects of the disease allele, a phenomenon referred to as suppression. In model organisms, suppression interactions are generally divided into two classes: genomic suppressors which are secondary mutations in the genome that bypass a mutant phenotype, and dosage suppression interactions in which overexpression of a suppressor gene rescues a mutant phenotype. Here, we describe the general properties of genomic and dosage suppression, with an emphasis on the budding yeast. We propose that suppression interactions between genetic variants are likely relevant for determining the penetrance of human traits. Consequently, an understanding of suppression mechanisms may guide the discovery of protective variants in healthy individuals that carry disease alleles, which could direct the rational design of new therapeutics.