Mapping DNA damage-dependent genetic interactions in yeast via party mating and barcode fusion genetics

AbstractCondition-dependent genetic interactions can reveal functional relationships between genes that are not evident under standard culture conditions. State-of-the-art yeast genetic interaction mapping, which relies on robotic manipulation of arrays of double mutant strains, does not scale readily to multi-condition studies. Here we describe Barcode Fusion Genetics to map Genetic Interactions (BFG-GI), by which double mutant strains generated via en masse ‘party’ mating can also be monitored en masse for growth and genetic interactions. By using site-specific recombination to fuse two DNA barcodes, each representing a specific gene deletion, BFG-GI enables multiplexed quantitative tracking of double mutants via next-generation sequencing. We applied BFG-GI to a matrix of DNA repair genes under nine different conditions, including methyl methanesulfonate (MMS), 4-nitroquinoline 1-oxide (4NQO), bleomycin, zeocin, and three other DNA-damaging environments. BFG-GI recapitulated known genetic interactions and yielded new condition-dependent genetic interactions. We validated and further explored a subnetwork of condition-dependent genetic interactions involving MAG1, SLX4, and genes encoding the Shu complex, and inferred that loss of the Shu complex leads to a decrease in the activation or activity of the checkpoint protein kinase Rad53.

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Predictability of Genetic Interactions from Functional Gene Modules

10.1101/049627 ◽

2016 ◽

Author(s):

Jonathan H. Young ◽

Edward M. Marcotte

Keyword(s):

Web Application ◽

Genetic Interaction ◽

Homo Sapiens ◽

Interaction Network ◽

Genetic Interactions ◽

Functional Relationships ◽

Therapy Targets ◽

Genetic Interaction Network ◽

Gene Level ◽

Interaction Partners

AbstractCharacterizing genetic interactions is crucial to understanding cellular and organismal response to gene-level perturbations. Such knowledge can inform the selection of candidate disease therapy targets. Yet experimentally determining whether genes interact is technically non-trivial and time-consuming. High-fidelity prediction of different classes of genetic interactions in multiple organisms would substantially alleviate this experimental burden. Under the hypothesis that functionally-related genes tend to share common genetic interaction partners, we evaluate a computational approach to predict genetic interactions in Homo sapiens, Drosophila melanogaster, and Saccharomyces cerevisiae. By leveraging knowledge of functional relationships between genes, we cross-validate predictions on known genetic interactions and observe high-predictive power of multiple classes of genetic interactions in all three organisms. Additionally, our method suggests high-confidence candidate interaction pairs that can be directly experimentally tested. A web application is provided for users to query genes for predicted novel genetic interaction partners. Finally, by subsampling the known yeast genetic interaction network, we found that novel genetic interactions are predictable even when knowledge of currently known interactions is minimal.

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Exploring a local genetic interaction network using evolutionary replay experiments

10.1101/2021.01.27.428500 ◽

2021 ◽

Author(s):

Ryan C. Vignogna ◽

Sean W. Buskirk ◽

Gregory I. Lang

Keyword(s):

Experimental Evolution ◽

Gene Deletion ◽

Genetic Interaction ◽

Interaction Network ◽

Genetic Interactions ◽

Loss Of Function ◽

Positive Allele ◽

Genetic Interaction Network ◽

Allele Specific ◽

Yeast Genetic

ABSTRACTUnderstanding how genes interact is a central challenge in biology. Experimental evolution provides a useful, but underutilized, tool for identifying genetic interactions, particularly those that involve non-loss-of-function mutations or mutations in essential genes. We previously identified a strong positive genetic interaction between specific mutations in KEL1 (P344T) and HSL7 (A695fs) that arose in an experimentally-evolved Saccharomyces cerevisiae population. Because this genetic interaction is not phenocopied by gene deletion, it was previously unknown. Using “evolutionary replay” experiments we identified additional mutations that have positive genetic interactions with the kel1-P344T mutation. We replayed the evolution of this population 672 times from six timepoints. We identified 30 populations where the kel1-P344T mutation reached high frequency. We performed whole-genome sequencing on these populations to identify genes in which mutations arose specifically in the kel1-P344T background. We reconstructed mutations in the ancestral and kel1-P344T backgrounds to validate positive genetic interactions. We identify several genetic interactors with KEL1, we validate these interactions by reconstruction experiments, and we show these interactions are not recapitulated by loss-of-function mutations. Our results demonstrate the power of experimental evolution to identify genetic interactions that are positive, allele specific, and not readily detected by other methods, and sheds light on a previously under-explored region of the yeast genetic interaction network.

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Differential Requirement of SAGA Subunits for Mot1p and Taf1p Recruitment in Gene Activation

Molecular and Cellular Biology ◽

10.1128/mcb.25.12.4863-4872.2005 ◽

2005 ◽

Vol 25 (12) ◽

pp. 4863-4872 ◽

Cited By ~ 16

Author(s):

Chris J. C. van Oevelen ◽

Hetty A. A. M. van Teeffelen ◽

H. T. Marc Timmers

Keyword(s):

Saccharomyces Cerevisiae ◽

Double Mutant ◽

Gene Activation ◽

Transcription Activation ◽

Tata Binding Protein ◽

Genetic Interactions ◽

Hexose Transporter ◽

Phenotypic Analysis ◽

Transcription Factor Complexes ◽

Mutant Strains

ABSTRACT Transcription activation in yeast (Saccharomyces cerevisiae) involves ordered recruitment of transcription factor complexes, such as TFIID, SAGA, and Mot1p. Previously, we showed that both Mot1p and Taf1p are recruited to the HXT2 and HXT4 genes, which encode hexose transporter proteins. Here, we show that SAGA also binds to the HXT2 and HXT4 promoters and plays a pivotal role in the recruitment of Mot1p and Taf1p. The deletion of either SPT3 or SPT8 reduces Mot1p binding to HXT2 and HXT4. Surprisingly, the deletion of GCN5 reduces Taf1p binding to both promoters. When GCN5 is deleted in spt3Δ or spt8Δ strains, neither Mot1p nor Taf1p binds, and this results in a diminished recruitment of TATA binding protein and polymerase II to the HXT4 but not the HXT2 promoter. This is reflected by the SAGA-dependent expression of HXT4. In contrast, SAGA-independent induction of HXT2 suggests a functional redundancy with other factors. A functional interplay of different SAGA subunits with Mot1p and Taf1p was supported by phenotypic analysis of MOT1 SAGA or TAF1/SAGA double mutant strains, which revealed novel genetic interactions between MOT1 and SPT8 and between TAF1 and GCN5. In conclusion, our data demonstrate functional links between SAGA, Mot1p, and TFIID in HXT gene regulation.

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Genetic Interactions Effects of Cardiovascular Disorder Using Computational Models: A Review

Current Biotechnology ◽

10.2174/2211550109999201008125800 ◽

2020 ◽

Vol 9 (3) ◽

pp. 177-191

Author(s):

Sridharan Priya ◽

Radha K. Manavalan

Keyword(s):

Coronary Artery Disease ◽

Coronary Artery ◽

Cardiovascular Diseases ◽

Computational Models ◽

Genetic Interaction ◽

Association Studies ◽

Genetic Interactions ◽

Computational Techniques ◽

Genome Wide Association Studies ◽

Artery Disease

Background: The diseases in the heart and blood vessels such as heart attack, Coronary Artery Disease, Myocardial Infarction (MI), High Blood Pressure, and Obesity, are generally referred to as Cardiovascular Diseases (CVD). The risk factors of CVD include gender, age, cholesterol/ LDL, family history, hypertension, smoking, and genetic and environmental factors. Genome- Wide Association Studies (GWAS) focus on identifying the genetic interactions and genetic architectures of CVD. Objective: Genetic interactions or Epistasis infer the interactions between two or more genes where one gene masks the traits of another gene and increases the susceptibility of CVD. To identify the Epistasis relationship through biological or laboratory methods needs an enormous workforce and more cost. Hence, this paper presents the review of various statistical and Machine learning approaches so far proposed to detect genetic interaction effects for the identification of various Cardiovascular diseases such as Coronary Artery Disease (CAD), MI, Hypertension, HDL and Lipid phenotypes data, and Body Mass Index dataset. Conclusion: This study reveals that various computational models identified the candidate genes such as AGT, PAI-1, ACE, PTPN22, MTHR, FAM107B, ZNF107, PON1, PON2, GTF2E1, ADGRB3, and FTO, which play a major role in genetic interactions for the causes of CVDs. The benefits, limitations, and issues of the various computational techniques for the evolution of epistasis responsible for cardiovascular diseases are exhibited.

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The genetics of catalase in Drosophila melanogaster: isolation and characterization of acatalasemic mutants.

Genetics ◽

10.1093/genetics/122.3.643 ◽

1989 ◽

Vol 122 (3) ◽

pp. 643-652 ◽

Cited By ~ 1

Author(s):

W J Mackay ◽

G C Bewley

Keyword(s):

Drosophila Melanogaster ◽

Free Radical ◽

Catalase Activity ◽

Oxygen Toxicity ◽

Threshold Effect ◽

Culture Conditions ◽

Free Radical Damage ◽

Isolation And Characterization ◽

Standard Culture ◽

Hypomorphic Alleles

Abstract Activated oxygen species have been demonstrated to be the important agents in oxygen toxicity by disrupting the structural and functional integrity of cells through lipid peroxidation events, DNA damage and protein inactivation. The biological consequences of free radical damage have long been hypothesized to be a causal agent in many aging-related diseases. Catalase (H2O2:H2O2 oxidoreductase; EC 1.15.1.1) is one of several enzymes involved in the scavenging of oxygen free radicals and free radical derivatives. The structural gene for catalase in Drosophila melanogaster has been localized to region 75D1-76A on chromosome 3L by dosage responses to segmental aneuploidy. This study reports the isolation of a stable deficiency, Df(3L)CatDH104(75C1-2;75F1), that uncovers the catalase locus and the subsequent isolation of six acatalasemic mutants. All catalase mutants are viable under standard culture conditions and recessive lethal mutations within the 75Cl-F1 interval have been shown not to affect catalase activity. Two catalase mutations are amorphic while four are hypomorphic alleles of the Cat+ locus. The lack of intergenic complementation between the six catalase mutations strongly suggests that there is only one functional gene in Drosophila. One acatalesemic mutation was mapped to position 3-47.0 which resides within the catalase dosage sensitive region. While complete loss of catalase activity confers a severe viability effect, residual levels are sufficient to restore viability to wild type levels. These results suggest a threshold effect for viability and offer an explanation for the general lack of phenotypic effects associated with the known mammalian acatalasemics.

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Stress Mediating Genes in Aging, Health, and Longevity Traits: Effects of Multiple Interactions

Innovation in Aging ◽

10.1093/geroni/igaa057.915 ◽

2020 ◽

Vol 4 (Supplement_1) ◽

pp. 286-286

Author(s):

Anatoliy Yashin ◽

Dequing Wu ◽

Konstantin Arbeev ◽

Arseniy Yashkin ◽

Galina Gorbunova ◽

...

Keyword(s):

Strong Interaction ◽

Genetic Interaction ◽

Interaction Effects ◽

Genetic Interactions ◽

Risk Scores ◽

Data Sets ◽

Interaction Patterns ◽

Polygenic Risk ◽

Drug Candidates ◽

Aging Health

Abstract Persistent stress of external or internal origin accelerates aging, increases risk of aging related health disorders, and shortens lifespan. Stressors activate stress response genes, and their products collectively influence traits. The variability of stressors and responses to them contribute to trait heterogeneity, which may cause the failure of clinical trials for drug candidates. The objectives of this paper are: to address the heterogeneity issue; to evaluate collective interaction effects of genetic factors on Alzheimer’s disease (AD) and longevity using HRS data; to identify differences and similarities in patterns of genetic interactions within two genders; and to compare AD related genetic interaction patterns in HRS and LOADFS data. To reach these objectives we: selected candidate genes from stress related pathways affecting AD/longevity; implemented logistic regression model with interaction term to evaluate effects of SNP-pairs on these traits for males and females; constructed the novel interaction polygenic risk scores for SNPs, which showed strong interaction potential, and evaluated effects of these scores on AD/longevity; and compared patterns of genetic interactions within the two genders and within two datasets. We found there were many genes involved in highly significant interactions that were the same and that were different within the two genders. The effects of interaction polygenic risk scores on AD were strong and highly statistically significant. These conclusions were confirmed in analyses of interaction effects on longevity trait using HRS data. Comparison of HRS to LOADFS data showed that many genes had strong interaction effects on AD in both data sets.

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ARID2 Chromatin Remodeler in Hepatocellular Carcinoma

Cells ◽

10.3390/cells9102152 ◽

2020 ◽

Vol 9 (10) ◽

pp. 2152

Author(s):

Robin Loesch ◽

Linda Chenane ◽

Sabine Colnot

Keyword(s):

Gene Expression ◽

Hepatocellular Carcinoma ◽

Associated Factors ◽

Regulation Of Gene Expression ◽

Specific Gene ◽

Chromatin Remodeler ◽

Chromatin Remodelers ◽

Genes Encoding ◽

Gene Alterations

Chromatin remodelers are found highly mutated in cancer including hepatocellular carcinoma. These mutations frequently occur in ARID (AT-rich Interactive Domain) genes, encoding subunits of the ATP-dependent SWI/SNF remodelers. The increasingly prevalent complexity that surrounds the functions and specificities of the highly modular BAF (BG1/BRM-associated factors) and PBAF (polybromo-associated BAF) complexes, including ARID1A/B or ARID2, is baffling. The involvement of the SWI/SNF complexes in diverse tissues and processes, and especially in the regulation of gene expression, multiplies the specific outcomes of specific gene alterations. A better understanding of the molecular consequences of specific mutations impairing chromatin remodelers is needed. In this review, we summarize what we know about the tumor-modulating properties of ARID2 in hepatocellular carcinoma.

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Phosphorylation of MgrA and Its Effect on Expression of the NorA and NorB Efflux Pumps of Staphylococcus aureus

Journal of Bacteriology ◽

10.1128/jb.00018-10 ◽

2010 ◽

Vol 192 (10) ◽

pp. 2525-2534 ◽

Cited By ~ 55

Author(s):

Que Chi Truong-Bolduc ◽

David C. Hooper

Keyword(s):

Staphylococcus Aureus ◽

Multidrug Resistance ◽

Virulence Factors ◽

Double Mutant ◽

Efflux Pumps ◽

Efflux Transporters ◽

Global Regulator ◽

Binding Assays ◽

Genes Encoding ◽

Gel Shift

ABSTRACT MgrA is a global regulator in Staphylococcus aureus that controls the expression of diverse genes encoding virulence factors and multidrug resistance (MDR) efflux transporters. We identified pknB, which encodes the (Ser/Thr) kinase PknB, in the S. aureus genome. PknB was able to autophosphorylate as well as phosphorylate purified MgrA. We demonstrated that rsbU, which encodes a Ser/Thr phosphatase and is involved in the activation of the SigB regulon, was able to dephosphorylate MgrA-P but not PknB-P. Serines 110 and 113 of MgrA were found to be phosphorylated, and Ala substitutions at these positions resulted in reductions in the level of phosphorylation of MgrA. DNA gel shift binding assays using norA and norB promoters showed that MgrA-P was able to bind the norB promoter but not the norA promoter, a pattern which was the reverse of that for unphosphorylated MgrA. The double mutant MgrAS110A-S113A bound to the norA promoter but not the norB promoter. The double mutant led to a 2-fold decrease in norA transcripts and a 2-fold decrease in the MICs of norfloxacin and ciprofloxacin in strain RN6390. Thus, phosphorylation of MgrA results in loss of binding to the norA promoter, but with a gain of the ability to bind the norB promoter. Loss of the ability to phosphorylate MgrA by Ala substitution resulted in increased repression of norA expression and in reductions in susceptibilities to NorA substrates.

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Aspergillus nidulans wetA activates spore-specific gene expression.

Molecular and Cellular Biology ◽

10.1128/mcb.11.1.55 ◽

1991 ◽

Vol 11 (1) ◽

pp. 55-62 ◽

Cited By ~ 109

Author(s):

M A Marshall ◽

W E Timberlake

Keyword(s):

Gene Expression ◽

Cell Wall ◽

Aspergillus Nidulans ◽

Gene Activation ◽

Regulatory Function ◽

Specific Gene ◽

Coding Region ◽

Vegetative Cells ◽

Mutant Strains ◽

Late Stages

The Aspergillus nidulans wetA gene is required for synthesis of cell wall layers that make asexual spores (conidia) impermeable. In wetA mutant strains, conidia take up water and autolyze rather than undergoing the final stages of maturation. wetA is activated during conidiogenesis by sequential expression of the brlA and abaA regulatory genes. To determine whether wetA regulates expression of other sporulation-specific genes, its coding region was fused to a nutritionally regulated promoter that permits gene activation in vegetative cells (hyphae) under conditions that suppress conidiation. Expression of wetA in hyphae inhibited growth and caused excessive branching. It did not lead to activation of brlA or abaA but did cause accumulation of transcripts from genes that are normally expressed specifically during the late stages of conidiation and whose mRNAs are stored in mature spores. Thus, wetA directly or indirectly regulates expression of some spore-specific genes. At least one gene (wA), whose mRNA does not occur in spores but rather accumulates in the sporogenous phialide cells, was activated by wetA, suggesting that wetA may have a regulatory function in these cells as well as in spores. We propose that wetA is responsible for activating a set of genes whose products make up the final two conidial wall layers or direct their assembly and through this activity is responsible for acquisition of spore dormancy.

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act Operon Control of Developmental Gene Expression in Myxococcus xanthus

Journal of Bacteriology ◽

10.1128/jb.184.4.1172-1179.2002 ◽

2002 ◽

Vol 184 (4) ◽

pp. 1172-1179 ◽

Cited By ~ 32

Author(s):

Thomas M. A. Gronewold ◽

Dale Kaiser

Keyword(s):

Fruiting Body ◽

Myxococcus Xanthus ◽

The Other ◽

Loss Of Function ◽

Wild Type ◽

Developmental Gene ◽

Developmental Gene Expression ◽

Mutant Strains ◽

Genes Encoding ◽

Signal Production

ABSTRACT Cell-bound C-signal guides the building of a fruiting body and triggers the differentiation of myxospores. Earlier work has shown that transcription of the csgA gene, which encodes the C-signal, is directed by four genes of the act operon. To see how expression of the genes encoding components of the aggregation and sporulation processes depends on C-signaling, mutants with loss-of-function mutations in each of the act genes were investigated. These mutations were found to have no effect on genes that are normally expressed up to 3 h into development and are C-signal independent. Neither the time of first expression nor the rate of expression increase was changed in actA, actB, actC, or actD mutant strains. Also, there was no effect on A-signal production, which normally starts before 3 h. By contrast, the null act mutants have striking defects in C-signal production. These mutations changed the expression of four gene reporters that are related to aggregation and sporulation and are expressed at 6 h or later in development. The actA and actB null mutations substantially decreased the expression of all these reporters. The other act null mutations caused either premature expression to wild-type levels (actC) or delayed expression (actD), which ultimately rose to wild-type levels. The pattern of effects on these reporters shows how the C-signal differentially regulates the steps that together build a fruiting body and differentiate spores within it.

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