Global Genetic Networks and the Genotype-to-Phenotype Relationship
TL;DR: It is emphasized how information gained from work in yeast translates to other systems, and how a global genetic network not only annotates gene function but also provides new insights into the genotype-to-phenotype relationship.
About: This article is published in Cell.The article was published on 2019-03-21 and is currently open access. It has received 157 citations till now.
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TL;DR: A map of the DNA damage response provides a rich resource to study this fundamental cellular system and has implications for the development and use of genotoxic agents in cancer therapy.
241 citations
TL;DR: The recent applications of TIS to answer overarching biological questions are discussed and emerging and multidisciplinary methods that build on TIS are explored, with an eye towards future applications.
Abstract: It has been 10 years since the introduction of modern transposon-insertion sequencing (TIS) methods, which combine genome-wide transposon mutagenesis with high-throughput sequencing to estimate the fitness contribution or essentiality of each genetic component in a bacterial genome. Four TIS variations were published in 2009: transposon sequencing (Tn-Seq), transposon-directed insertion site sequencing (TraDIS), insertion sequencing (INSeq) and high-throughput insertion tracking by deep sequencing (HITS). TIS has since become an important tool for molecular microbiologists, being one of the few genome-wide techniques that directly links phenotype to genotype and ultimately can assign gene function. In this Review, we discuss the recent applications of TIS to answer overarching biological questions. We explore emerging and multidisciplinary methods that build on TIS, with an eye towards future applications.
177 citations
TL;DR: An analytical framework for interpreting high-dimensional landscapes of cell states (manifolds) constructed from transcriptional phenotypes is presented, and recommender system machine learning is applied to predict interactions, facilitating exploration of vastly larger GI manifolds.
Abstract: How cellular and organismal complexity emerges from combinatorial expression of genes is a central question in biology. High-content phenotyping approaches such as Perturb-seq (single-cell RNA-sequencing pooled CRISPR screens) present an opportunity for exploring such genetic interactions (GIs) at scale. Here, we present an analytical framework for interpreting high-dimensional landscapes of cell states (manifolds) constructed from transcriptional phenotypes. We applied this approach to Perturb-seq profiling of strong GIs mined from a growth-based, gain-of-function GI map. Exploration of this manifold enabled ordering of regulatory pathways, principled classification of GIs (e.g., identifying suppressors), and mechanistic elucidation of synergistic interactions, including an unexpected synergy between CBL and CNN1 driving erythroid differentiation. Finally, we applied recommender system machine learning to predict interactions, facilitating exploration of vastly larger GI manifolds.
126 citations
National Institute for Health Research1, University of Cambridge2, Maastricht University3, Medical University of Vienna4, Cambridge University Hospitals NHS Foundation Trust5, Imperial College London6, NHS Blood and Transplant7, Austrian Academy of Sciences8, Shaare Zedek Medical Center9, Queen Mary University of London10, Katholieke Universiteit Leuven11, University of Bristol12, Maastricht University Medical Centre13, University College London14, Royal Free Hospital15
TL;DR: A molecular diagnosis has been reported for 894 index patients providing evidence that introducing an HTS genetic test is a valuable addition to laboratory diagnostics in patients with a high likelihood of having an inherited BTPD.
112 citations
TL;DR: CHyMErA represents an effective screening approach for GI mapping and the functional analysis of sizable genomic regions, such as alternative exons, when combining Cas9 and Cas12a outperforms previous approaches for combinatorial screening in mammalian cells.
Abstract: Systematic mapping of genetic interactions (GIs) and interrogation of the functions of sizable genomic segments in mammalian cells represent important goals of biomedical research. To advance these goals, we present a CRISPR (clustered regularly interspaced short palindromic repeats)-based screening system for combinatorial genetic manipulation that employs coexpression of CRISPR-associated nucleases 9 and 12a (Cas9 and Cas12a) and machine-learning-optimized libraries of hybrid Cas9–Cas12a guide RNAs. This system, named Cas Hybrid for Multiplexed Editing and screening Applications (CHyMErA), outperforms genetic screens using Cas9 or Cas12a editing alone. Application of CHyMErA to the ablation of mammalian paralog gene pairs reveals extensive GIs and uncovers phenotypes normally masked by functional redundancy. Application of CHyMErA in a chemogenetic interaction screen identifies genes that impact cell growth in response to mTOR pathway inhibition. Moreover, by systematically targeting thousands of alternative splicing events, CHyMErA identifies exons underlying human cell line fitness. CHyMErA thus represents an effective screening approach for GI mapping and the functional analysis of sizable genomic regions, such as alternative exons. Combining Cas9 and Cas12a outperforms previous approaches for combinatorial screening in mammalian cells.
75 citations
References
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TL;DR: Version 2.8 introduces two powerful new features—Custom Node Graphics and Attribute Equations—which can be used jointly to greatly enhance Cytoscape's data integration and visualization capabilities.
Abstract: Summary: Cytoscape is a popular bioinformatics package for biological network visualization and data integration. Version 2.8 introduces two powerful new features—Custom Node Graphics and Attribute Equations—which can be used jointly to greatly enhance Cytoscape's data integration and visualization capabilities. Custom Node Graphics allow an image to be projected onto a node, including images generated dynamically or at remote locations. Attribute Equations provide Cytoscape with spreadsheet-like functionality in which the value of an attribute is computed dynamically as a function of other attributes and network properties.
Availability and implementation: Cytoscape is a desktop Java application released under the Library Gnu Public License (LGPL). Binary install bundles and source code for Cytoscape 2.8 are available for download from http://cytoscape.org.
Contact: [email protected]
4,186 citations
"Global Genetic Networks and the Gen..." refers methods in this paper
...2 were connected and graphed using a spring-embedded layout algorithm (Smoot et al., 2011)....
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Stanford University1, Merck & Co.2, Université libre de Bruxelles3, Yale University4, University of Salamanca5, Johns Hopkins University School of Medicine6, McGill University7, Johns Hopkins University8, University of Basel9, Université catholique de Louvain10, Thermo Fisher Scientific11, Washington University in St. Louis12, Katholieke Universiteit Leuven13
TL;DR: A total of 6925 Saccharomyces cerevisiae strains were constructed, by a high-throughput strategy, each with a precise deletion of one of 2026 ORFs (more than one-third of the ORFs in the genome), finding that 17 percent were essential for viability in rich medium.
Abstract: The functions of many open reading frames (ORFs) identified in genome-sequencing projects are unknown. New, whole-genome approaches are required to systematically determine their function. A total of 6925 Saccharomyces cerevisiae strains were constructed, by a high-throughput strategy, each with a precise deletion of one of 2026 ORFs (more than one-third of the ORFs in the genome). Of the deleted ORFs, 17 percent were essential for viability in rich medium. The phenotypes of more than 500 deletion strains were assayed in parallel. Of the deletion strains, 40 percent showed quantitative growth defects in either rich or minimal medium.
4,051 citations
"Global Genetic Networks and the Gen..." refers background in this paper
...Similar to the impact of the arrayed collection of yeast deletion mutants (Winzeler et al., 1999), development of high-complexity genome-scale CRISPR (clustered regularly interspaced short palindromic repeats) libraries promise unprecedented functional characterization of the human genome....
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...This systematic endeavor defined the set of 1,000 genes essential for viability in laboratory growth conditions and generated a set of 5,000 viable haploid deletion mutants (Winzeler et al., 1999)....
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...Thus, the essential gene set which generally comprises 20% of the eukaryotic genome (Blomen et al., 2015; Hart et al., 2015; Wang et al., 2015; Winzeler et al., 1999) is necessary, but not sufficient, to construct a viable organism with a minimal genome due to the phenotypic consequences of GIs on fitness....
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TL;DR: In this paper, it was shown that the variance of a human measurement from its mean follows the Normal Law of Errors, and that the variability may be measured by the standard deviation corresponding to the square root of the mean square error.
Abstract: Several attempts have already been made to interpret the well-established results of biometry in accordance with the Mendelian scheme of inheritance. It is here attempted to ascertain the biometrical properties of a population of a more general type than has hitherto been examined, inheritance in which follows this scheme. It is hoped that in this way it will be possible to make a more exact analysis of the causes of human variability. The great body of available statistics show us that the deviations of a human measurement from its mean follow very closely the Normal Law of Errors, and, therefore, that the variability may be uniformly measured by the standard deviation corresponding to the square root of the mean square error. When there are two independent causes of variability capable of producing in an otherwise uniform population distributions with standard deviations σ1 and σ2, it is found that the distribution, when both causes act together, has a standard deviation . It is therefore desirable in analysing the causes of variability to deal with the square of the standard deviation as the measure of variability. We shall term this quantity the Variance of the normal population to which it refers, and we may now ascribe to the constituent causes fractions or percentages of the total variance which they together produce. It is desirable on the one hand that the elementary ideas at the basis of the calculus of correlations should be clearly understood, and easily expressed in ordinary language, and on the other that loose phrases about the “percentage of causation,” which obscure the essential distinction between the individual and the population, should be carefully avoided.
3,800 citations
TL;DR: A network based on genetic interaction profiles reveals a functional map of the cell in which genes of similar biological processes cluster together in coherent subsets, and highly correlated profiles delineate specific pathways to define gene function.
Abstract: A genome-scale genetic interaction map was constructed by examining 5.4 million gene-gene pairs for synthetic genetic interactions, generating quantitative genetic interaction profiles for ~75% of all genes in the budding yeast, Saccharomyces cerevisiae. A network based on genetic interaction profiles reveals a functional map of the cell in which genes of similar biological processes cluster together in coherent subsets, and highly correlated profiles delineate specific pathways to define gene function. The global network identifies functional cross-connections between all bioprocesses, mapping a cellular wiring diagram of pleiotropy. Genetic interaction degree correlated with a number of different gene attributes, which may be informative about genetic network hubs in other organisms. We also demonstrate that extensive and unbiased mapping of the genetic landscape provides a key for interpretation of chemical-genetic interactions and drug target identification.
2,225 citations
"Global Genetic Networks and the Gen..." refers background in this paper
...Indeed, while the average nonessential gene shares a negative GI with 2% of other nonessential ORFs in the yeast genome, genes important for metabolic processes are statistically underrepresented in the GI network (Costanzo et al., 2010)....
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...However, this subclass of positive GIs accounts for only a small fraction of those observed for nonessential gene pairs (Costanzo et al., 2010; Costanzo et al., 2016)....
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...By similarity analysis, a global network of GI profiles provides a guide for interpreting chemical-genetic interaction profiles and thereby linking compounds to their target pathway (Costanzo et al., 2010; Piotrowski et al., 2017)....
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TL;DR: The sequence kernel association test (SKAT) is proposed, a supervised, flexible, computationally efficient regression method to test for association between genetic variants (common and rare) in a region and a continuous or dichotomous trait while easily adjusting for covariates.
Abstract: Sequencing studies are increasingly being conducted to identify rare variants associated with complex traits. The limited power of classical single-marker association analysis for rare variants poses a central challenge in such studies. We propose the sequence kernel association test (SKAT), a supervised, flexible, computationally efficient regression method to test for association between genetic variants (common and rare) in a region and a continuous or dichotomous trait while easily adjusting for covariates. As a score-based variance-component test, SKAT can quickly calculate p values analytically by fitting the null model containing only the covariates, and so can easily be applied to genome-wide data. Using SKAT to analyze a genome-wide sequencing study of 1000 individuals, by segmenting the whole genome into 30 kb regions, requires only 7 hr on a laptop. Through analysis of simulated data across a wide range of practical scenarios and triglyceride data from the Dallas Heart Study, we show that SKAT can substantially outperform several alternative rare-variant association tests. We also provide analytic power and sample-size calculations to help design candidate-gene, whole-exome, and whole-genome sequence association studies.
2,202 citations
"Global Genetic Networks and the Gen..." refers background in this paper
...Specifically, as discussed earlier, the yeast GI network has a highly organized structure in which genes are grouped together to form discrete network modules, and several studies have leveraged pathway or network enrichment analyses to identify single loci associated with specific human diseases (Califano et al., 2012; Wang et al., 2010; Wu et al., 2011; Zhang et al., 2014; Zuk et al., 2014)....
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