The Majority of Animal Genes Are Required for Wild-Type Fitness

Molecular Mechanisms of Genotype-Dependent Lifespan Variation Mediated by Caloric Restriction: Insight from Wild Yeast Isolates

Caloric restriction (CR) is known to extend lifespan across different species and holds great promise for preventing human age-onset pathologies. However, two major challenges exist. First, despite extensive research, the mechanisms of lifespan extension in response to CR remain elusive. Second, genetic differences causing variations in response to CR and genetic factors contributing to variability of CR response on lifespan are largely unknown. Here, we took advantage of natural genetic variation across 46 diploid wild yeast isolates of Saccharomyces species and the lifespan variation under CR conditions to uncover the molecular factors associated with CR response types. We identified genes and metabolic pathways differentially regulated in CR-responsive versus non-responsive strains. Our analysis revealed that altered mitochondrial function and activation of GCN4-mediated environmental stress response are inevitably linked to lifespan variation in response to CR and a unique mitochondrial metabolite might be utilized as a predictive marker for CR response rate. In sum, our data suggests that the effects of CR on longevity may not be universal, even among the closely related species or strains of a single species. Since mitochondrial-mediated signaling pathways are evolutionarily conserved, the dissection of related genetic pathways will be relevant to understanding the mechanism by which CR elicits its longevity effect.

HAP1, a new revolutionary cell model for gene editing using CRISPR-Cas9

The use of next-generation sequencing (NGS) technologies has been instrumental in the characterization of the mutational landscape of complex human diseases like cancer. But despite the enormous rise in the identification of disease candidate genetic variants, their functionality is yet to be fully elucidated in order to have a clear implication in patient care. Haploid human cell models have become the tool of choice for functional gene studies, since they only contain one copy of the genome and can therefore show the unmasked phenotype of genetic variants. Over the past few years, the human near-haploid cell line HAP1 has widely been consolidated as one of the favorite cell line models for functional genetic studies. Its rapid turnover coupled with the fact that only one allele needs to be modified in order to express the subsequent desired phenotype has made this human cell line a valuable tool for gene editing by CRISPR-Cas9 technologies. This review examines the recent uses of the HAP1 cell line model in functional genetic studies and high-throughput genetic screens using the CRISPR-Cas9 system. It covers its use in an attempt to develop new and relevant disease models to further elucidate gene function, and create new ways to understand the genetic basis of human diseases. We will cover the advantages and potential of the use of CRISPR-Cas9 technology on HAP1 to easily and efficiently study the functional interpretation of gene function and human single-nucleotide genetic variants of unknown significance identified through NGS technologies, and its implications for changes in clinical practice and patient care.

Defect-buffering cellular plasticity increases robustness of metazoan embryogenesis

Developmental processes are intrinsically robust so as to preserve a normal-like state in response to genetic and environmental fluctuations. However, the robustness and potential phenotypic plasticity of individual developing cells under genetic perturbations remain to be systematically evaluated. Using large-scale gene perturbation, live imaging, lineage tracing, and single-cell phenomics, we quantified the phenotypic landscape of C. elegans embryogenesis in >2,000 embryos following individual knockdown of over 750 conserved genes. We observed that cellular genetic systems are not sufficiently robust to single-gene perturbations across all cells; rather, gene knockdowns frequently induced cellular defects. Dynamic phenotypic analyses revealed many cellular defects to be transient, with cells exhibiting phenotypic plasticity that serves to alleviate, correct, and accommodate the defects. Moreover, potential developmentally related cell modules may buffer the phenotypic effects of individual cell position changes. Our findings reveal non-negligible contributions of cellular plasticity and multicellularity as compensatory strategies to increase developmental robustness.

A pan-CRISPR analysis of mammalian cell specificity identifies ultra-compact sgRNA subsets for genome-scale experiments

A genetic knockout can be lethal to one human cell type while increasing growth rate in another. This context specificity confounds genetic analysis and prevents reproducible genome engineering. Genome-wide CRISPR compendia across most common human cell lines offer the largest opportunity to understand the biology of cell specificity. The prevailing viewpoint, synthetic lethality, occurs when a genetic alteration creates a unique CRISPR dependency. Here, we use machine learning for an unbiased investigation of cell type specificity. Quantifying model accuracy, we find that most cell type specific phenotypes are predicted by the function of related genes of wild-type sequence, not synthetic lethal relationships. These models then identify unexpected sets of 100-300 genes where reduced CRISPR measurements can produce genome-scale loss-of-function predictions across >18,000 genes. Thus, it is possible to reduce in vitro CRISPR libraries by orders of magnitude—with some information loss—when we remove redundant genes and not redundant sgRNAs.

Context specificity confounds genetic analysis and prevents reproducible genome engineering. Here, the authors report a pan-CRISPR analysis of specificity in mammalian cells and identify ultra-compact sgRNA subsets for genome-scale screens.

Identification of Essential Genes in Caenorhabditis elegans with Lethal Mutations Maintained by Genetic Balancers

Genetic balancer systems, which allow effective capture and maintenance of lethal mutations stably, play an important role in identifying essential genes. Whole-genome sequencing (WGS) followed by bioinformatics analysis, combined with genetic mapping data analysis, allows for an efficient and economical means of identifying genomic mutations in essential genes. Using this approach, we successfully identified 104 essential genes on ChrI, ChrIII, and ChrV in C. elegans. In this report, we described a protocol that sequences the genome of prebalanced Caenorhabditis elegans (C. elegans) strains to carry lethal mutations and identifies candidate causal mutations and candidate essential genes using a robust bioinformatics procedure.

Wisdom of the crowds: A suggested polygenic plan for small-RNA-mediated regulation in bacteria

The omnigenic/polygenic theory, which states that complex traits are not shaped by single/few genes, but by situation-specific large networks, offers an explanation for a major enigma in microbiology: deletion of specific small RNAs (sRNAs) playing key roles in various aspects of bacterial physiology, including virulence and antibiotic resistance, results in surprisingly subtle phenotypes. A recent study uncovered polar accumulation of most sRNAs upon osmotic stress, the majority not known to be involved in the applied stress. Here we show that cells deleted for a handful of pole-enriched sRNAs exhibit fitness defect in several stress conditions, as opposed to single, double, or triple sRNA-knockouts, implying that regulation by sRNA relies on sets of genes. Moreover, analysis of RNA-seq data of Escherichia coli and Salmonella typhimurium exposed to antibiotics and/or infection-relevant conditions reveals the involvement of multiple sRNAs in all cases, in line with the existence of a polygenic plan for sRNA-mediated regulation.

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.

PhenoMIP: High-Throughput Phenotyping of Diverse Caenorhabditis elegans Populations via Molecular Inversion Probes

Whether generated within a lab setting or isolated from the wild, variant alleles continue to be an important resource for decoding gene function in model organisms such as Caenorhabditis elegans. With advances in massively parallel sequencing, multiple whole-genome sequenced (WGS) strain collections are now available to the research community. The Million Mutation Project (MMP) for instance, analyzed 2007 N2-derived, mutagenized strains. Individually, each strain averages ∼400 single nucleotide variants amounting to ∼80 protein-coding variants. The effects of these variants, however, remain largely uncharacterized and querying the breadth of these strains for phenotypic changes requires a method amenable to rapid and sensitive high-throughput analysis. Here we present a pooled competitive fitness approach to quantitatively phenotype subpopulations of sequenced collections via molecular inversion probes (PhenoMIP). We phenotyped the relative fitness of 217 mutant strains on multiple food sources and classified these into five categories. We also demonstrate on a subset of these strains, that their fitness defects can be genetically mapped. Overall, our results suggest that approximately 80% of MMP mutant strains may have a decreased fitness relative to the lab reference, N2. The costs of generating this form of analysis through WGS methods would be prohibitive while PhenoMIP analysis in this manner is accomplished at less than one-tenth of projected WGS costs. We propose methods for applying PhenoMIP to a broad range of population selection experiments in a cost-efficient manner that would be useful to the community at large.

Multiplex enCas12a screens detect functional buffering among paralogs otherwise masked in monogenic Cas9 knockout screens

BACKGROUND

Pooled library CRISPR/Cas9 knockout screening across hundreds of cell lines has identified genes whose disruption leads to fitness defects, a critical step in identifying candidate cancer targets. However, the number of essential genes detected from these monogenic knockout screens is low compared to the number of constitutively expressed genes in a cell.

RESULTS

Through a systematic analysis of screen data in cancer cell lines generated by the Cancer Dependency Map, we observe that half of all constitutively expressed genes are never detected in any CRISPR screen and that these never-essentials are highly enriched for paralogs. We investigated functional buffering among approximately 400 candidate paralog pairs using CRISPR/enCas12a dual-gene knockout screening in three cell lines. We observe 24 synthetic lethal paralog pairs that have escaped detection by monogenic knockout screens at stringent thresholds. Nineteen of 24 (79%) synthetic lethal interactions are present in at least two out of three cell lines and 14 of 24 (58%) are present in all three cell lines tested, including alternate subunits of stable protein complexes as well as functionally redundant enzymes.

CONCLUSIONS

Together, these observations strongly suggest that functionally redundant paralogs represent a targetable set of genetic dependencies that are systematically under-represented among cell-essential genes in monogenic CRISPR-based loss of function screens.

Distributed phenomics with the unPAK project reveals the effects of mutations

Determining how genes are associated with traits in plants and other organisms is a major challenge in modern biology. The unPAK project - undergraduates phenotyping Arabidopsis knockouts - has generated phenotype data for thousands of non-lethal insertion mutation lines within a single Arabidopsis thaliana genomic background. The focal phenotypes examined by unPAK are complex macroscopic fitness-related traits, which have ecological, evolutionary and agricultural importance. These phenotypes are placed in the context of the wild-type and also natural accessions (phytometers), and standardized for environmental differences between assays. Data from the unPAK project are used to describe broad patterns in the phenotypic consequences of insertion mutation, and to identify individual mutant lines with distinct phenotypes as candidates for further study. Inclusion of undergraduate researchers is at the core of unPAK activities, and an important broader impact of the project is providing students an opportunity to obtain research experience.

Empirical mean-noise fitness landscapes reveal the fitness impact of gene expression noise

The effects of cell-to-cell variation (noise) in gene expression have proven difficult to quantify because of the mechanistic coupling of noise to mean expression. To independently quantify the effects of changes in mean expression and noise we determine the fitness landscapes in mean-noise expression space for 33 genes in yeast. For most genes, short-lived (noise) deviations away from the expression optimum are nearly as detrimental as sustained (mean) deviations. Fitness landscapes can be classified by a combination of each gene’s sensitivity to protein shortage or surplus. We use this classification to explore evolutionary scenarios for gene expression and find that certain landscape topologies can break the mechanistic coupling of mean and noise, thus promoting independent optimization of both properties. These results demonstrate that noise is detrimental for many genes and reveal non-trivial consequences of mean-noise-fitness topologies for the evolution of gene expression systems.

Quantifying the effects of noise in gene expression is difficult since noise and mean expression are coupled. Here the authors determine fitness landscapes in mean-noise expression space to uncouple these two parameters and show that changes in noise and mean expression are similarly detrimental to fitness.

A network of human functional gene interactions from knockout fitness screens in cancer cells

The function of human genes can be strongly inferred from their knockout fitness profiles across hundreds of CRISPR screens, illuminating the modular organization of the cell.

Genetic interactions mediate the emergence of phenotype from genotype. The systematic survey of genetic interactions in yeast showed that genes operating in the same biological process have highly correlated genetic interaction profiles, and this observation has been exploited to infer gene function in model organisms. Such assays of digenic perturbations in human cells are also highly informative, but are not scalable, even with CRISPR-mediated methods. As an alternative, we developed an indirect method of deriving functional interactions. We show that genes having correlated knockout fitness profiles across diverse, non-isogenic cell lines are analogous to genes having correlated genetic interaction profiles across isogenic query strains and similarly imply shared biological function. We constructed a network of genes with correlated fitness profiles across 276 high-quality CRISPR knockout screens in cancer cell lines into a “coessentiality network,” with up to 500-fold enrichment for co-functional gene pairs, enabling strong inference of gene function and highlighting the modular organization of the cell.

Genomic identification and functional analysis of essential genes in Caenorhabditis elegans

Background

Essential genes are required for an organism’s viability and their functions can vary greatly, spreading across many pathways. Due to the importance of essential genes, large scale efforts have been undertaken to identify the complete set of essential genes and to understand their function. Studies of genome architecture and organization have found that genes are not randomly disturbed in the genome.

Results

Using combined genetic mapping, Illumina sequencing, and bioinformatics analyses, we successfully identified 44 essential genes with 130 lethal mutations in genomic regions of C. elegans of around 7.3 Mb from Chromosome I (left). Of the 44 essential genes, six of which were genes not characterized previously by mutant alleles, let-633/let-638 (B0261.1), let-128 (C53H9.2), let-511 (W09C3.4), let-162 (Y47G6A.18), let-510 (Y47G6A.19), and let-131 (Y71G12B.6). Examine essential genes with Hi-C data shows that essential genes tend to cluster within TAD units rather near TAD boundaries. We have also shown that essential genes in the left half of chromosome I in C. elegans function in enzyme and nucleic acid binding activities during fundamental processes, such as DNA replication, transcription, and translation. From protein-protein interaction networks, essential genes exhibit more protein connectivity than non-essential genes in the genome. Also, many of the essential genes show strong expression in embryos or early larvae stages, indicating that they are important to early development.

Conclusions

Our results confirmed that this work provided a more comprehensive picture of the essential gene and their functional characterization. These genetic resources will offer important tools for further heath and disease research.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-5251-3) contains supplementary material, which is available to authorized users.

Next-generation metrics for monitoring genetic erosion within populations of conservation concern

Genetic erosion is a major threat to biodiversity because it can reduce fitness and ultimately contribute to the extinction of populations. Here, we explore the use of quantitative metrics to detect and monitor genetic erosion. Monitoring systems should not only characterize the mechanisms and drivers of genetic erosion (inbreeding, genetic drift, demographic instability, population fragmentation, introgressive hybridization, selection) but also its consequences (inbreeding and outbreeding depression, emergence of large-effect detrimental alleles, maladaptation and loss of adaptability). Technological advances in genomics now allow the production of data the can be measured by new metrics with improved precision, increased efficiency and the potential to discriminate between neutral diversity (shaped mainly by population size and gene flow) and functional/adaptive diversity (shaped mainly by selection), allowing the assessment of management-relevant genetic markers. The requirements of such studies in terms of sample size and marker density largely depend on the kind of population monitored, the questions to be answered and the metrics employed. We discuss prospects for the integration of this new information and metrics into conservation monitoring programmes.

Combined flow cytometry and high-throughput image analysis for the study of essential genes in Caenorhabditis elegans

Background

Advances in automated image-based microscopy platforms coupled with high-throughput liquid workflows have facilitated the design of large-scale screens utilising multicellular model organisms such as Caenorhabditis elegans to identify genetic interactions, therapeutic drugs or disease modifiers. However, the analysis of essential genes has lagged behind because lethal or sterile mutations pose a bottleneck for high-throughput approaches, and a systematic way to analyse genetic interactions of essential genes in multicellular organisms has been lacking.

Results

In C. elegans, non-conditional lethal mutations can be maintained in heterozygosity using chromosome balancers, commonly expressing green fluorescent protein (GFP) in the pharynx. However, gene expression or function is typically monitored by the use of fluorescent reporters marked with the same fluorophore, presenting a challenge to sort worm populations of interest, particularly at early larval stages. Here, we develop a sorting strategy capable of selecting homozygous mutants carrying a GFP stress reporter from GFP-balanced animals at the second larval stage. Because sorting is not completely error-free, we develop an automated high-throughput image analysis protocol that identifies and discards animals carrying the chromosome balancer. We demonstrate the experimental usefulness of combining sorting of homozygous lethal mutants and automated image analysis in a functional genomic RNA interference (RNAi) screen for genes that genetically interact with mitochondrial prohibitin (PHB). Lack of PHB results in embryonic lethality, while homozygous PHB deletion mutants develop into sterile adults due to maternal contribution and strongly induce the mitochondrial unfolded protein response (UPR^mt). In a chromosome-wide RNAi screen for C. elegans genes having human orthologues, we uncover both known and new PHB genetic interactors affecting the UPR^mt and growth.

Conclusions

The method presented here allows the study of balanced lethal mutations in a high-throughput manner. It can be easily adapted depending on the user’s requirements and should serve as a useful resource for the C. elegans community for probing new biological aspects of essential nematode genes as well as the generation of more comprehensive genetic networks.

Electronic supplementary material

The online version of this article (10.1186/s12915-018-0496-5) contains supplementary material, which is available to authorized users.

A High-Resolution Genome-Wide CRISPR/Cas9 Viability Screen Reveals Structural Features and Contextual Diversity of the Human Cell-Essential Proteome

To interrogate genes essential for cell growth, proliferation and survival in human cells, we carried out a genome-wide clustered regularly interspaced short palindromic repeat (CRISPR)/Cas9 screen in a B-cell lymphoma line using a custom extended-knockout (EKO) library of 278,754 single-guide RNAs (sgRNAs) that targeted 19,084 RefSeq genes, 20,852 alternatively spliced exons, and 3,872 hypothetical genes. A new statistical analysis tool called robust analytics and normalization for knockout screens (RANKS) identified 2,280 essential genes, 234 of which were unique. Individual essential genes were validated experimentally and linked to ribosome biogenesis and stress responses. Essential genes exhibited a bimodal distribution across 10 different cell lines, consistent with a continuous variation in essentiality as a function of cell type. Genes essential in more lines had more severe fitness defects and encoded the evolutionarily conserved structural cores of protein complexes, whereas genes essential in fewer lines formed context-specific modules and encoded subunits at the periphery of essential complexes. The essentiality of individual protein residues across the proteome correlated with evolutionary conservation, structural burial, modular domains, and protein interaction interfaces. Many alternatively spliced exons in essential genes were dispensable and were enriched for disordered regions. Fitness defects were observed for 44 newly evolved hypothetical reading frames. These results illuminate the contextual nature and evolution of essential gene functions in human cells.

The combinatorial control of alternative splicing in C. elegans

Normal development requires the right splice variants to be made in the right tissues at the right time. The core splicing machinery is engaged in all splicing events, but which precise splice variant is made requires the choice between alternative splice sites—for this to occur, a set of splicing factors (SFs) must recognize and bind to short RNA motifs in the pre-mRNA. In C. elegans, there is known to be extensive variation in splicing patterns across development, but little is known about the targets of each SF or how multiple SFs combine to regulate splicing. Here we combine RNA-seq with in vitro binding assays to study how 4 different C. elegans SFs, ASD-1, FOX-1, MEC-8, and EXC-7, regulate splicing. The 4 SFs chosen all have well-characterised biology and well-studied loss-of-function genetic alleles, and all contain RRM domains. Intriguingly, while the SFs we examined have varied roles in C. elegans development, they show an unexpectedly high overlap in their targets. We also find that binding sites for these SFs occur on the same pre-mRNAs more frequently than expected suggesting extensive combinatorial control of splicing. We confirm that regulation of splicing by multiple SFs is often combinatorial and show that this is functionally significant. We also find that SFs appear to combine to affect splicing in two modes—they either bind in close proximity within the same intron or they appear to bind to separate regions of the intron in a conserved order. Finally, we find that the genes whose splicing are regulated by multiple SFs are highly enriched for genes involved in the cytoskeleton and in ion channels that are key for neurotransmission. Together, this shows that specific classes of genes have complex combinatorial regulation of splicing and that this combinatorial regulation is critical for normal development to occur.

Alternative splicing (AS) is a highly regulated process that is crucial for normal development. It requires the core splicing machinery, but the specific choice of splice site during AS is controlled by splicing factors (SFs) such as ELAV or RBFOX proteins that bind to specific sequences in pre-mRNAs to regulate usage of different splice sites. AS varies across the C. elegans life cycle and here we study how diverse SFs combine to regulate AS during C. elegans development. We selected 4 RRM-containing SFs that are all well studied and that have well-characterised loss-of-function genetic alleles. We find that these SFs regulate many of the same targets, and that combinatorial interactions between these SFs affect both individual splicing events and organism-level phenotypes including specific effects on the neuromuscular system. We further show that SFs combine to regulate splicing of an individual pre-mRNA in two distinct modes—either by binding in close proximity or by binding in a defined order on the pre-mRNA. Finally, we find that the genes whose splicing are most likely to be regulated by multiple SFs are genes that are required for the proper function of the neuromuscular system. These genes are also most likely to have changing AS patterns across development, suggesting that their splicing regulation is highly complex and developmentally regulated. Taken together, our data show that the precise splice variant expressed at any point in development is often the outcome of regulation by multiple SFs.

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.

Taxonomically Restricted Genes with Essential Functions Frequently Play Roles in Chromosome Segregation in Caenorhabditis elegans and Saccharomyces cerevisiae

Genes encoding essential components of core cellular processes are typically highly conserved across eukaryotes. However, a small proportion of essential genes are highly taxonomically restricted; there appear to be no similar genes outside the genomes of highly related species. What are the functions of these poorly characterized taxonomically restricted genes (TRGs)? Systematic screens in Saccharomyces cerevisiae and Caenorhabditis elegans previously identified yeast or nematode TRGs that are essential for viability and we find that these genes share many molecular features, despite having no significant sequence similarity. Specifically, we find that those TRGs with essential phenotypes have an expression profile more similar to highly conserved genes, they have more protein–protein interactions and more protein disorder. Surprisingly, many TRGs play central roles in chromosome segregation; a core eukaryotic process. We thus find that genes that appear to be highly evolutionarily restricted do not necessarily play roles in species-specific biological functions but frequently play essential roles in core eukaryotic processes.

Functional Profiling of a Plasmodium Genome Reveals an Abundance of Essential Genes

The genomes of malaria parasites contain many genes of unknown function. To assist drug development through the identification of essential genes and pathways, we have measured competitive growth rates in mice of 2,578 barcoded Plasmodium berghei knockout mutants, representing >50% of the genome, and created a phenotype database. At a single stage of its complex life cycle, P. berghei requires two-thirds of genes for optimal growth, the highest proportion reported from any organism and a probable consequence of functional optimization necessitated by genomic reductions during the evolution of parasitism. In contrast, extreme functional redundancy has evolved among expanded gene families operating at the parasite-host interface. The level of genetic redundancy in a single-celled organism may thus reflect the degree of environmental variation it experiences. In the case of Plasmodium parasites, this helps rationalize both the relative successes of drugs and the greater difficulty of making an effective vaccine.

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Two-thirds of Plasmodium berghei genes contribute to normal blood stage growth

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The core genome of malaria parasites is highly optimized for rapid host colonization

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Essential parasite genes and pathways are identified for drug target prioritization

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Low functional redundancy reflects the constant environment encountered by a parasite

Fitness effects of mutation: testing genetic redundancy in Arabidopsis thaliana

Screens of organisms with disruptive mutations in a single gene often fail to detect phenotypic consequences for the majority of mutants. One explanation for this phenomenon is that the presence of paralogous loci provides genetic redundancy. However, it is also possible that the assayed traits are affected by few loci, that effects could be subtle or that phenotypic effects are restricted to certain environments. We assayed a set of T-DNA insertion mutant lines of Arabidopsis thaliana to determine the frequency with which mutation affected fitness-related phenotypes. We found that between 8% and 42% of the assayed lines had altered fitness from the wild type. Furthermore, many of these lines exhibited fitness greater than the wild type. In a second experiment, we grew a subset of the lines in multiple environments and found whether a T-DNA insert increased or decreased fitness traits depended on the assay environment. Overall, our evidence contradicts the hypothesis that genetic redundancy is a common phenomenon in A. thaliana for fitness traits. Evidence for redundancy from prior screens of knockout mutants may often be an artefact of the design of the phenotypic assays which have focused on less complex phenotypes than fitness and have used single environments. Finally, our study adds to evidence that beneficial mutations may represent a significant component of the mutational spectrum of A. thaliana.

Seed maturation: Simplification of control networks in plants

Networks controlling developmental or metabolic processes in plants are often complex as a consequence of the duplication and specialisation of the regulatory genes as well as the numerous levels of transcriptional and post-transcriptional controls added during evolution. Networks serve to accommodate multicellular complexity and increase robustness to environmental changes. Mathematical simplification by regrouping genes or pathways in a limited number of hubs has facilitated the construction of models for complex traits. In a complementary approach, a biological simplification can be achieved by using genetic modification to understand the core and singular ancestral function of the network, which is likely to be more prevalent within the plant kingdom rather than specific to a species. With this viewpoint, we review examples of simplification successfully undertaken in yeast and other organisms. A strategy of progressive complementation of single, double and triple mutants of seed maturation confirmed the fundamental role of the AFL sub-family of B3 transcription factors as master regulators of seed maturation, illustrating that biological simplification of complex networks could be more widely applied in plants. Defining minimal control networks will facilitate evolutionary comparisons of regulatory processes and the identification of an essential gene set for synthetic biology.

Novel Metrics to Characterize Embryonic Elongation of the Nematode Caenorhabditis elegans

Dissecting the signaling pathways that control the alteration of morphogenic processes during embryonic development requires robust and sensitive metrics. Embryonic elongation of the nematode Caenorhabditis elegans is a late developmental stage consisting of the elongation of the embryo along its longitudinal axis. This developmental stage is controlled by intercellular communication between hypodermal cells and underlying body-wall muscles. These signaling mechanisms control the morphology of hypodermal cells by remodeling the cytoskeleton and the cell-cell junctions. Measurement of embryonic lethality and developmental arrest at larval stages as well as alteration of cytoskeleton and cell-cell adhesion structures in hypodermal and muscle cells are classical phenotypes that have been used for more than 25 years to dissect these signaling pathways. Recent studies required the development of novel metrics specifically targeting either early or late elongation and characterizing morphogenic defects along the antero-posterior axis of the embryo. Here, we provide detailed protocols enabling the accurate measurement of the length and the width of the elongating embryos as well as the length of synchronized larvae. These methods constitute useful tools to identify genes controlling elongation, to assess whether these genes control both early and late phases of this stage and are required evenly along the antero-posterior axis of the embryo.

Towards a compendium of essential genes - From model organisms to synthetic lethality in cancer cells

Essential genes are defined by their requirement to sustain life in cells or whole organisms. The systematic identification of essential gene sets not only allows insights into the fundamental building blocks of life, but may also provide novel therapeutic targets in oncology. The discovery of essential genes has been tightly linked to the development and deployment of various screening technologies. Here, we describe how gene essentiality was addressed in different eukaryotic model organisms, covering a range of organisms from yeast to mouse. We describe how increasing knowledge of evolutionarily divergent genomes facilitate identification of gene essentiality across species. Finally, the impact of gene essentiality and synthetic lethality on cancer research and the clinical translation of screening results are highlighted.

High-Resolution CRISPR Screens Reveal Fitness Genes and Genotype-Specific Cancer Liabilities

The ability to perturb genes in human cells is crucial for elucidating gene function and holds great potential for finding therapeutic targets for diseases such as cancer. To extend the catalog of human core and context-dependent fitness genes, we have developed a high-complexity second-generation genome-scale CRISPR-Cas9 gRNA library and applied it to fitness screens in five human cell lines. Using an improved Bayesian analytical approach, we consistently discover 5-fold more fitness genes than were previously observed. We present a list of 1,580 human core fitness genes and describe their general properties. Moreover, we demonstrate that context-dependent fitness genes accurately recapitulate pathway-specific genetic vulnerabilities induced by known oncogenes and reveal cell-type-specific dependencies for specific receptor tyrosine kinases, even in oncogenic KRAS backgrounds. Thus, rigorous identification of human cell line fitness genes using a high-complexity CRISPR-Cas9 library affords a high-resolution view of the genetic vulnerabilities of a cell.

Multi-endpoint, high-throughput study of nanomaterial toxicity in Caenorhabditis elegans

The booming nanotechnology industry has raised public concerns about the environmental health and safety impact of engineered nanomaterials (ENMs). High-throughput assays are needed to obtain toxicity data for the rapidly increasing number of ENMs. Here we present a suite of high-throughput methods to study nanotoxicity in intact animals using Caenorhabditis elegans as a model. At the population level, our system measures food consumption of thousands of animals to evaluate population fitness. At the organism level, our automated system analyzes hundreds of individual animals for body length, locomotion speed, and lifespan. To demonstrate the utility of our system, we applied this technology to test the toxicity of 20 nanomaterials at four concentrations. Only fullerene nanoparticles (nC60), fullerol, TiO2, and CeO2 showed little or no toxicity. Various degrees of toxicity were detected from different forms of carbon nanotubes, graphene, carbon black, Ag, and fumed SiO2 nanoparticles. Aminofullerene and ultraviolet-irradiated nC60 also showed small but significant toxicity. We further investigated the effects of nanomaterial size, shape, surface chemistry, and exposure conditions on toxicity. Our data are publicly available at the open-access nanotoxicity database www.QuantWorm.org/nano.

Natural RNA interference directs a heritable response to the environment

RNA interference can induce heritable gene silencing, but it remains unexplored whether similar mechanisms play a general role in responses to cues that occur in the wild. We show that transient, mild heat stress in the nematode Caenorhabditis elegans results in changes in messenger RNA levels that last for more than one generation. The affected transcripts are enriched for genes targeted by germline siRNAs downstream of the piRNA pathway, and worms defective for germline RNAi are defective for these heritable effects. Our results demonstrate that a specific siRNA pathway transmits information about variable environmental conditions between generations.

Transvection-based gene regulation in Drosophila is a complex and plastic trait

Transvection, a chromosome pairing-dependent form of trans-based gene regulation, is potentially widespread in the Drosophila melanogaster genome and varies across cell types and within tissues in D. melanogaster, characteristics of a complex trait. Here, we demonstrate that the trans-interactions at the Malic enzyme (Men) locus are, in fact, transvection as classically defined and are plastic with respect to both genetic background and environment. Using chromosomal inversions, we show that trans-interactions at the Men locus are eliminated by changes in chromosomal architecture that presumably disrupt somatic pairing. We further show that the magnitude of transvection at the Men locus is modified by both genetic background and environment (temperature), demonstrating that transvection is a plastic phenotype. Our results suggest that transvection effects in D. melanogaster are shaped by a dynamic interplay between environment and genetic background. Interestingly, we find that cis-based regulation of the Men gene is more robust to genetic background and environment than trans-based. Finally, we begin to uncover the nonlocal factors that may contribute to variation in transvection overall, implicating Abd-B in the regulation of Men in cis and in trans in an allele-specific and tissue-specific manner, driven by differences in expression of the two genes across genetic backgrounds and environmental conditions.

The genotype-phenotype map of yeast complex traits: basic parameters and the role of natural selection

Most phenotypic traits are controlled by many genes, but a global picture of the genotype-phenotype map (GPM) is lacking. For example, in no species do we know generally how many genes affect a trait and how large these effects are. It is also unclear to what extent GPMs are shaped by natural selection. Here we address these fundamental questions using the reverse genetic data of 220 morphological traits in 4,718 budding yeast strains, each of which lacks a nonessential gene. We show that 1) the proportion of genes affecting a trait varies from <1% to >30%, averaging 6%, 2) most traits are impacted by many more small-effect genes than large-effect genes, and 3) the mean effect of all nonessential genes on a trait decreases precipitously as the estimated importance of the trait to fitness increases. An analysis of 3,116 yeast gene expression traits in 754 gene-deletion strains reveals a similar pattern. These findings illustrate the power of genome-wide reverse genetics in genotype-phenotype mapping, uncover an enormous range of genetic complexity of phenotypic traits, and suggest that the GPM of cellular organisms has been shaped by natural selection for mutational robustness.

High-throughput capturing and characterization of mutations in essential genes of Caenorhabditis elegans

BACKGROUND

Essential genes are critical for the development of all organisms and are associated with many human diseases. These genes have been a difficult category to study prior to the availability of balanced lethal strains. Despite the power of targeted mutagenesis, there are limitations in identifying mutations in essential genes. In this paper, we describe the identification of coding regions for essential genes mutated using forward genetic screens in Caenorhabditis elegans. The lethal mutations described here were isolated and maintained by a wild-type allele on a rescuing duplication.

RESULTS

We applied whole genome sequencing to identify the causative molecular lesion resulting in lethality in existing C. elegans mutant strains. These strains are balanced and can be easily maintained for subsequent characterization. Our method can be effectively used to analyze mutations in a large number of essential genes. We describe here the identification of 64 essential genes in a region of chromosome I covered by the duplication sDp2. Of these, 42 are nonsense mutations, six are splice signal mutations, one deletion, and 15 are non-synonymous mutations. Many of the essential genes in this region function in cell cycle, transcriptional regulation, and RNA processing.

CONCLUSIONS

The essential genes identified here are represented by mutant strains, many of which have more than one mutant allele. The genetic resource can be utilized to further our understanding of essential gene function and will be applicable to the study of C. elegans development, conserved cellular function, and ultimately lead to improved human health.

No gene in the genome makes sense except in the light of evolution

Evolutionary conservation has been an accurate predictor of functional elements across the first decade of metazoan genomics. More recently, there has been a move to define functional elements instead from biochemical annotations. Evolutionary methods are, however, more comprehensive than biochemical approaches can be and can assess quantitatively, especially for subtle effects, how biologically important--how injurious after mutation--different types of elements are. Evolutionary methods are thus critical for understanding the large fraction (up to 10%) of the human genome that does not encode proteins and yet might convey function. These methods can also capture the ephemeral nature of much noncoding functional sequence, with large numbers of functional elements having been gained and lost rapidly along each mammalian lineage. Here, we review how different strengths of purifying selection have impacted on protein-coding and non-protein-coding loci and on transcription factor binding sites in mammalian and fruit fly genomes.

Characterisation of Caenorhabditis elegans sperm transcriptome and proteome

BACKGROUND

Although sperm is transcriptionally and translationally quiescent, complex populations of RNAs, including mRNAs and non-coding RNAs, exist in sperm. Previous microarray analysis of germ cell mutants identified hundreds of sperm genes in Caenorhabditis elegans. To take a more comprehensive view on C. elegans sperm genes, here, we isolate highly pure sperm cells and employ high-throughput technologies to obtain sperm transcriptome and proteome.

RESULTS

First, sperm transcriptome consists of considerable amounts of non-coding RNAs, many of which have not been annotated and may play functional roles during spermatogenesis. Second, apart from kinases/phosphatases as previously reported, ion binding proteins are also enriched in sperm, underlying the crucial roles of intracellular ions in post-translational regulation in sperm. Third, while the majority of sperm genes/proteins have low abundance, a small number of sperm genes/proteins are hugely enriched in sperm, implying that sperm only rely on a small set of proteins for post-translational regulation. Lastly, by extensive RNAi screening of sperm enriched genes, we identified a few genes that control fertility. Our further analysis reveals a tight correlation between sperm transcriptome and sperm small RNAome, suggesting that the endogenous siRNAs strongly repress sperm genes. This leads to an idea that the inefficient RNAi screening of sperm genes, a phenomenon currently with unknown causes, might result from the competition between the endogenous RNAi pathway and the exogenous RNAi pathway.

CONCLUSIONS

Together, the obtained sperm transcriptome and proteome serve as valuable resources to systematically study spermatogenesis in C. elegans.

Mainstreaming Caenorhabditis elegans in experimental evolution

Experimental evolution provides a powerful manipulative tool for probing evolutionary process and mechanism. As this approach to hypothesis testing has taken purchase in biology, so too has the number of experimental systems that use it, each with its own unique strengths and weaknesses. The depth of biological knowledge about Caenorhabditis nematodes, combined with their laboratory tractability, positions them well for exploiting experimental evolution in animal systems to understand deep questions in evolution and ecology, as well as in molecular genetics and systems biology. To date, Caenorhabditis elegans and related species have proved themselves in experimental evolution studies of the process of mutation, host-pathogen coevolution, mating system evolution and life-history theory. Yet these organisms are not broadly recognized for their utility for evolution experiments and remain underexploited. Here, we outline this experimental evolution work undertaken so far in Caenorhabditis, detail simple methodological tricks that can be exploited and identify research areas that are ripe for future discovery.

Pleiotropic constraints, expression level, and the evolution of miRNA sequences

Post-transcriptional gene regulation mediated by microRNAs (miRNAs) plays critical roles during development by modulating gene expression and conferring robustness to stochastic errors. Phylogenetic analyses suggest that miRNA acquisition could play a role in phenotypic innovation. Moreover, miRNA-induced regulation strongly impacts genome evolution, increasing selective constraints on 3'UTRs, protein sequences, and expression level divergence. Thus, it is essential to understand the factors governing sequence evolution for this important class of regulatory molecules. Investigation of the patterns of molecular evolution at miRNA loci have been limited in Caenorhabditis elegans because of the lack of a close outgroup. Instead, I used Caenorhabditis briggsae as the focus point of this study because of its close relationship to Caenorhabditis sp. 9. I also corroborated the patterns of sequence evolution in Caenorhabditis using published orthologous relationships among miRNAs in Drosophila. In nematodes and in flies, miRNA sequence divergence is not influenced by the genomic neighborhood (i.e., intronic or intergenic) but is nevertheless affected by the genomic context because X-linked miRNAs evolve faster than autosomal miRNAs. However, this effect of chromosomal linkage can be explained by differential expression levels rather than a fast-X effect. The results presented here support a universal negative relationship between rates of molecular evolution and expression level, and suggest that mutations in highly expressed miRNAs are more likely to be deleterious because they potentially affect a larger number of target genes. Finally, I show that many single family member miRNAs evolve faster than miRNAs from multigene families and have limited functional scope, suggesting that they are not strongly integrated in gene regulatory networks.

A database of Caenorhabditis elegans behavioral phenotypes

Using low-cost automated tracking microscopes, we have generated a behavioral database for 305 Caenorhabditis elegans strains, including 76 mutants with no previously described phenotype. The growing database currently consists of 9,203 short videos segmented to extract behavior and morphology features, and these videos and feature data are available online for further analysis. The database also includes summary statistics for 702 measures with statistical comparisons to wild-type controls so that phenotypes can be identified and understood by users.

The details in the distributions: why and how to study phenotypic variability

Phenotypic variability is present even when genetic and environmental differences between cells are reduced to the greatest possible extent. For example, genetically identical bacteria display differing levels of resistance to antibiotics, clonal yeast populations demonstrate morphological and growth-rate heterogeneity, and mouse blastomeres from the same embryo have stochastic differences in gene expression. However, the distributions of phenotypes present among isogenic organisms are often overlooked; instead, many studies focus on population aggregates such as the mean. The details of these distributions are relevant to major questions in diverse fields, including the evolution of antimicrobial-drug and chemotherapy resistance. We review emerging experimental and statistical techniques that allow rigorous analysis of phenotypic variability and thereby may lead to advances across the biological sciences.

A versatile platform for creating a comprehensive UAS-ORFeome library in Drosophila

Overexpression screens are used to explore gene functions in Drosophila, but this strategy suffers from the lack of comprehensive and systematic fly strain collections and efficient methods for generating such collections. Here, we present a strategy that could be used efficiently to generate large numbers of transgenic Drosophila strains, and a collection of 1149 UAS-ORF fly lines that were created with the site-specific ΦC31 integrase method. For this collection, we used a set of 655 genes that were cloned as two variants, either as an open reading frame (ORF) with a native stop codon or with a C-terminal 3xHA tag. To streamline the procedure for transgenic fly generation, we demonstrate the utility of injecting pools of plasmids into embryos, each plasmid containing a randomised sequence (barcode) that serves as a unique identifier for plasmids and, subsequently, fly strains. We also developed a swapping technique that facilitates the rapid exchange of promoters and epitope tags in vivo, expanding the versatility of the ORF collection. The work described here serves as the basis of a systematic library of Gal4/UAS-regulated transgenes.