Embracing study heterogeneity for finding genetic interactions in large-scale research consortia

Genetic interactions have been recognized as a potentially important contributor to the heritability of complex diseases. Nevertheless, due to small effect sizes and stringent multiple-testing correction, identifying genetic interactions in complex diseases is particularly challenging. To address the above challenges, many genomic research initiatives collaborate to form large-scale consortia and develop open access to enable sharing of genome-wide association study (GWAS) data. Despite the perceived benefits of data sharing from large consortia, a number of practical issues have arisen, such as privacy concerns on individual genomic information and heterogeneous data sources from distributed GWAS databases. In the context of large consortia, we demonstrate that the heterogeneously appearing marginal effects over distributed GWAS databases can offer new insights into genetic interactions for which conventional methods have had limited success. In this paper, we develop a novel two-stage testing procedure, named phylogenY-based effect-size tests for interactions using first 2 moments (YETI2), to detect genetic interactions through both pooled marginal effects, in terms of averaging site-specific marginal effects, and heterogeneity in marginal effects across sites, using a meta-analytic framework. YETI2 can not only be applied to large consortia without shared personal information but also can be used to leverage underlying heterogeneity in marginal effects to prioritize potential genetic interactions. We investigate the performance of YETI2 through simulation studies and apply YETI2 to bladder cancer data from dbGaP.

RIMB-1/RIM-Binding Protein and UNC-10/RIM Redundantly Regulate Presynaptic Localization of the Voltage-Gated Calcium Channel in Caenorhabditis elegans

Presynaptic active zones (AZs) contain many molecules essential for neurotransmitter release and are assembled in a highly organized manner. A network of adaptor proteins known as cytomatrix at the AZ (CAZ) is important for shaping the structural characteristics of AZ. Rab3-interacting molecule (RIM)-binding protein (RBP) family are binding partners of the CAZ protein RIM and also bind the voltage-gated calcium channels (VGCCs) in mice and flies. Here, we investigated the physiological roles of RIMB-1, the homolog of RBPs in the nematode Caenorhabditis elegans RIMB-1 is expressed broadly in neurons and predominantly localized at presynaptic sites. Loss-of-function animals of rimb-1 displayed slight defects in motility and response to pharmacological inhibition of synaptic transmission, suggesting a modest involvement of rimb-1 in synapse function. We analyzed genetic interactions of rimb-1 by testing candidate genes and by an unbiased forward genetic screen for rimb-1 enhancer. Both analyses identified the RIM homolog UNC-10 that acts together with RIMB-1 to regulate presynaptic localization of the P/Q-type VGCC UNC-2/Ca_v2. We also find that the precise localization of RIMB-1 to presynaptic sites requires presynaptic UNC-2/Ca_v2. RIMB-1 has multiple FN3 and SH3 domains. Our transgenic rescue analysis with RIMB-1 deletion constructs revealed a functional requirement of a C-terminal SH3 in regulating UNC-2/Ca_v2 localization. Together, these findings suggest a redundant role of RIMB-1/RBP and UNC-10/RIM to regulate the abundance of UNC-2/Ca_v2 at the presynaptic AZ in C. elegans, depending on the bidirectional interplay between CAZ adaptor and channel proteins.SIGNIFICANCE STATEMENT Presynaptic active zones (AZs) are highly organized structures for synaptic transmission with characteristic networks of adaptor proteins called cytomatrix at the AZ (CAZ). In this study, we characterized a CAZ protein RIMB-1, named for RIM-binding protein (RBP), in the nematode Caenorhabditis elegans Through systematic analyses of genetic interactions and an unbiased genetic enhancer screen of rimb-1, we revealed a redundant role of two CAZ proteins RIMB-1/RBP and UNC-10/RIM in regulating presynaptic localization of UNC-2/Ca_v2, a voltage-gated calcium channel (VGCC) critical for proper neurotransmitter release. Additionally, the precise localization of RIMB-1/RBP requires presynaptic UNC-2/Ca_v2. These findings provide new mechanistic insight about how the interplay among multiple CAZ adaptor proteins and VGCC contributes to the organization of presynaptic AZ.

Functional genomic characterization of metallothioneins in brown trout (Salmo trutta L.). using synthetic genetic analysis

Metal pollution has made a significant impact on the earth's ecosystems and tolerance to metals in a wide variety of species has evolved. Metallothioneins, a group of cysteine-rich metal-ion binding proteins, are known to be a key physiological mechanism in regulating protection against metal toxicity. Many rivers across the southwest of England are detrimentally affected by metal pollution, but brown trout (Salmo trutta L.) populations are known to reside within them. In this body of work, two isoforms of metallothionein (MetA and MetB) isolated from trout occupying a polluted and a control river are examined. Using synthetic genetic array (SGA) analyses in the model yeast, Saccharomyces cerevisiae, functional genomics is used to explore the role of metallothionein isoforms in driving metal tolerance. By harnessing this experimental system, S. cerevisiae is used to (i) determine the genetic interaction maps of MetA and MetB isoforms; (ii) identify differences between the genetic interactions in both isoforms and (iii) demonstrate that pre-exposure to metals in metal-tolerant trout influences these interactions. By using a functional genomics approach leveraged from the model yeast Saccharomyces cerevisiae, we demonstrate how such approaches could be used in understanding the ecology and evolution of a non-model species.

Network dynamics of the yeast methyltransferome

Sulfur assimilation and the biosynthesis of methionine, cysteine and S-adenosylmethionine (SAM) are critical to life. As a cofactor, SAM is required for the activity of most methyltransferases (MTases) and as such has broad impact on diverse cellular processes. Assigning function to MTases remains a challenge however, as many MTases are partially redundant, they often have multiple cellular roles and these activities can be condition-dependent. To address these challenges, we performed a systematic synthetic genetic analysis of all pairwise MTase double mutations in normal and stress conditions (16°C, 37°C, and LiCl) resulting in an unbiased comprehensive overview of the complexity and plasticity of the methyltransferome. Based on this network, we performed biochemical analysis of members of the histone H3K4 COMPASS complex and the phospholipid methyltransferase OPI3 to reveal a new role for a phospholipid methyltransferase in mediating histone methylation (H3K4) which underscores a potential link between lipid homeostasis and histone methylation. Our findings provide a valuable resource to study methyltransferase function, the dynamics of the methyltransferome, genetic crosstalk between biological processes and the dynamics of the methyltransferome in response to cellular stress.

Genetic interaction between DNA repair factors PAXX, XLF, XRCC4 and DNA-PKcs in human cells

DNA double-strand breaks (DSBs) are highly cytotoxic lesions, and unrepaired or misrepaired DSBs can lead to various human diseases, including immunodeficiency, neurological abnormalities, growth retardation, and cancer. Nonhomologous end joining (NHEJ) is the major DSB repair pathway in mammals. Ku70 and Ku80 are DSB sensors that facilitate the recruitment of downstream factors, including protein kinase DNA-dependent protein kinase, catalytic subunit (DNA-PKcs), structural components [X-ray repair cross-complementing protein 4 (XRCC4), XRCC4-like factor (XLF), and paralogue of XRCC4 and XLF (PAXX)], and DNA ligase IV (LIG4), which complete DNA repair. DSBs also trigger the activation of the DNA damage response pathway, in which protein kinase ataxia-telangiectasia mutated (ATM) phosphorylates multiple substrates, including histone H2AX. Traditionally, research on NHEJ factors was performed using in vivo mouse models and murine cells. However, the current knowledge of the genetic interactions between NHEJ factors in human cells is incomplete. Here, we obtained genetically modified human HAP1 cell lines, which lacked one or two NHEJ factors, including LIG4, XRCC4, XLF, PAXX, DNA-PKcs, DNA-PKcs/XRCC4, and DNA-PKcs/PAXX. We examined the genomic instability of HAP1 cells, as well as their sensitivity to DSB-inducing agents. In addition, we determined the genetic interaction between XRCC4 paralogues (XRCC4, XLF, and PAXX) and DNA-PKcs. We found that in human cells, XLF, but not PAXX or XRCC4, genetically interacts with DNA-PKcs. Moreover, ATM possesses overlapping functions with DNA-PKcs, XLF, and XRCC4, but not with PAXX in response to DSBs. Finally, NHEJ-deficient HAP1 cells show increased chromosomal and chromatid breaks, when compared to the WT parental control. Overall, we found that HAP1 is a suitable model to study the genetic interactions in human cells.

Genetic Interaction of APOE and FGF1 is Associated with Memory Impairment and Hippocampal Atrophy in Alzheimer's Disease

The APOE and fibroblast growth factor 1 (FGF1) have both been associated with amyloid β accumulation and neurodegeneration. Investigation the effect of APOE-FGF1 interactions on episodic memory (EM) deficits and hippocampus atrophy (HA) might elucidate the complex clinical-pathological relationship in Alzheimer’s disease (AD). EM performance and hippocampal volume (HV) were characterized in patients with mild AD based on APOE-ε4 carrier status (APOE-ε4 carriers versus non-carriers) and FGF1 single nucleotide polymorphism (FGF1-rs34011-GG versus FGF1-rs34011-A-allele carriers). The clinical-pathological relationships within each genotypic group (ε4+/GG-carrier, ε4+/A-allele-carrier, ε4-/GG-carrier and ε4-/A-allele-carrier) were analyzed. There were no significant differences between the FGF1-rs34011-GG and FGF1-rs34011-A-allele carriers for the level of EM performance or HV (p> 0.05). The bilateral HV was significantly smaller and EM impairment was significantly worse in ε4+/GG-carrier than in ε4-/A-allele-carrier, and an interaction effect of APOE (APOE-ε4 carriers versus non-carriers) with FGF1 (FGF1-rs34011-GG versus FGF1-rs34011-A-allele carriers) predicted EM impairment (F4,92= 3.516, p= 0.018) and structural changes in voxel-based morphometry. Our data shows that concurrent consideration of APOE and FGF1 polymorphisms might be required to understand the clinical-pathological relationship in AD.

Robust genetic interaction analysis

For the risk, progression, and response to treatment of many complex diseases, it has been increasingly recognized that genetic interactions (including gene-gene and gene-environment interactions) play important roles beyond the main genetic and environmental effects. In practical genetic interaction analyses, model mis-specification and outliers/contaminations in response variables and covariates are not uncommon, and demand robust analysis methods. Compared with their nonrobust counterparts, robust genetic interaction analysis methods are significantly less popular but are gaining attention fast. In this article, we provide a comprehensive review of robust genetic interaction analysis methods, on their methodologies and applications, for both marginal and joint analysis, and for addressing model mis-specification as well as outliers/contaminations in response variables and covariates.

5-HTTLPR-brain-derived neurotrophic factor (BDNF) gene interactions and early adverse life events effect on impulsivity in suicide attempters

OBJECTIVES

An expanding body of research suggests that childhood adverse experiences can lead to different negative health outcomes, including attempted suicide. Serotonergic genes such as the promoter region of the serotonin transporter gene (5-HTTLPR) have been associated both with impulsivity in suicide attempts and reactivity to environmental stress exposure. BDNF gene may play an epigenetic role.

METHODS

We studied the influence of childhood stressful events and 5-HTTLPR genotype on impulsivity measured by Barratt Impulsivity Scale (BIS-10) in a multicentre sample of 1,655 suicide attempters (69.4% women, 30.6% men; mean age 40.13 years). A co-dominant additive genetic model was used for the statistical analyses. Interaction between 5-HTTLPR genotype and early trauma exposure was tested using moderated and multiple regression techniques. Interaction plots were used to explore BDNF genotype modulation.

RESULTS

Mildly higher impulsivity scores were found in men with SS compared with SL or LL genotypes, and men with childhood emotional and physical abuse. Interaction analyses showed that combination of 5-HTTLPR-SS genotype and early trauma exposure increase impulsivity scores independently. Impulsivity scores were not affected by the modulation of BDNF genes.

CONCLUSIONS

Childhood trauma and 5-HTTLPR genotype seem to be independently involved in suicide attempts, sharing a common pathway of increasing impulsivity.

Feature Learning of Virus Genome Evolution With the Nucleotide Skip-Gram Neural Network

Recent studies reveal that even the smallest genomes such as viruses evolve through complex and stochastic processes, and the assumption of independent alleles is not valid in most applications. Advances in sequencing technologies produce multiple time-point whole-genome data, which enable potential interactions between these alleles to be investigated empirically. To investigate these interactions, we represent alleles as distributed vectors that encode for relationships with other alleles in the course of evolution and apply artificial neural networks to time-sampled whole-genome datasets for feature learning. We build this platform using methods and algorithms derived from natural language processing (NLP), and we denote it as the nucleotide skip-gram neural network. We learn distributed vectors of alleles using the changes in allele frequency of echovirus 11 in the presence or absence of the disinfectant (ClO₂) from the experimental evolution data. Results from the training using a new open-source software TensorFlow show that the learned distributed vectors can be clustered using principal component analysis and hierarchical clustering to reveal a list of non-synonymous mutations that arise on the structural protein VP1 in connection to the candidate mutation for ClO₂ adaptation. Furthermore, this method can account for recombination rates by setting the extent of interactions as a biological hyper-parameter, and the results show that the most realistic scenario of mid-range interactions across the genome is most consistent with the previous studies.

Mutations in NCAPG2 Cause a Severe Neurodevelopmental Syndrome that Expands the Phenotypic Spectrum of Condensinopathies

The use of whole-exome and whole-genome sequencing has been a catalyst for a genotype-first approach to diagnostics. Under this paradigm, we have implemented systematic sequencing of neonates and young children with a suspected genetic disorder. Here, we report on two families with recessive mutations in NCAPG2 and overlapping clinical phenotypes that include severe neurodevelopmental defects, failure to thrive, ocular abnormalities, and defects in urogenital and limb morphogenesis. NCAPG2 encodes a member of the condensin II complex, necessary for the condensation of chromosomes prior to cell division. Consistent with a causal role for NCAPG2, we found abnormal chromosome condensation, augmented anaphase chromatin-bridge formation, and micronuclei in daughter cells of proband skin fibroblasts. To test the functional relevance of the discovered variants, we generated an ncapg2 zebrafish model. Morphants displayed clinically relevant phenotypes, such as renal anomalies, microcephaly, and concomitant increases in apoptosis and altered mitotic progression. These could be rescued by wild-type but not mutant human NCAPG2 mRNA and were recapitulated in CRISPR-Cas9 F0 mutants. Finally, we noted that the individual with a complex urogenital defect also harbored a heterozygous NPHP1 deletion, a common contributor to nephronophthisis. To test whether sensitization at the NPHP1 locus might contribute to a more severe renal phenotype, we co-suppressed nphp1 and ncapg2, which resulted in significantly more dysplastic renal tubules in zebrafish larvae. Together, our data suggest that impaired function of NCAPG2 results in a severe condensinopathy, and they highlight the potential utility of examining candidate pathogenic lesions beyond the primary disease locus.

Biochemical and Genetic Interactions of Phospholipase D Alpha 1 and Mitogen-Activated Protein Kinase 3 Affect Arabidopsis Stress Response

Phospholipase D alpha 1 (PLDα1, AT3G15730) and mitogen-activated protein kinases (MAPKs) participate on signaling-dependent events in plants. MAPKs are able to phosphorylate a wide range of substrates putatively including PLDs. Here we have focused on functional regulations of PLDα1 by interactions with MAPKs, their co-localization and impact on salt stress and abscisic acid (ABA) tolerance in Arabidopsis. Yeast two-hybrid and bimolecular fluorescent assays showed that PLDα1 interacts with MPK3. Immunoblotting analyses likewise confirmed connection between both these enzymes. Subcellularly we co-localized PLDα1 with MPK3 in the cortical cytoplasm close to the plasma membrane and in cytoplasmic strands. Moreover, genetic interaction studies revealed that pldα1mpk3 double mutant was resistant to a higher salinity and showed a higher tolerance to ABA during germination in comparison to single mutants and wild type. Thus, this study revealed importance of new biochemical and genetic interactions between PLDα1 and MPK3 for Arabidopsis stress (salt and ABA) response.

Genetic Interaction Between Two VNTRs in the SLC6A4 Gene Regulates Nicotine Dependence in Vietnamese Men

Nicotine dependence is an addiction to tobacco products and a global public health concern. Association between the SLC6A4 polymorphisms and nicotine dependence is controversial. Two variable number tandem repeat (VNTR) domains, termed HTTLPR and STin2, in the SLC6A4 gene are well characterized transcriptional regulatory elements. Their polymorphism in the copy number of the repeat correlates with the particular personality and psychiatric traits. We analyzed nicotine dependence in 1,804 participants from Central Vietnam. The Fagerström Test (FTND) was used to evaluate the nicotine dependence and PCR was used to determine the SLC6A4 HTTLPR and STin2 VNTRs. The HTTLPR VNTR was associated with difficulties to refrain from smoking in a prohibiting environment. The STIn2 10/10 genotype was associated with (1) years of smoking, (2) difficulties to quit the first cigarette, and (3) higher number of cigarettes smoked per day (CPD). Stratification analysis was used to find the genetic interaction between these two VNTRs in nicotine dependence as they may synergistically regulate the SLC6A4 expression. Smokers with the S/S HTTLPR genotypes showed a much stronger association between STin2 10/10 variant and CPD. This finding is consistent with the molecular evidence for the functional interaction between HTTLPR and STin2 in cell line models, where STin2 has described as a stronger expressional regulator. Similarly, we found that STin2 is a much stronger modifier of smoking with 10/10 genotype related to higher nicotine dependence. The present study supports genetic interaction between HTTLPR and STin2 VNTRs in the regulation of nicotine dependence with the dominance of the STin2 effects. This finding could be explained by their differential effect on the SLC6A4 expression.

CRISPR Activation Screens Systematically Identify Factors that Drive Neuronal Fate and Reprogramming

Comprehensive identification of factors that can specify neuronal fate could provide valuable insights into lineage specification and reprogramming, but systematic interrogation of transcription factors, and their interactions with each other, has proven technically challenging. We developed a CRISPR activation (CRISPRa) approach to systematically identify regulators of neuronal-fate specification. We activated expression of all endogenous transcription factors and other regulators via a pooled CRISPRa screen in embryonic stem cells, revealing genes including epigenetic regulators such as Ezh2 that can induce neuronal fate. Systematic CRISPR-based activation of factor pairs allowed us to generate a genetic interaction map for neuronal differentiation, with confirmation of top individual and combinatorial hits as bona fide inducers of neuronal fate. Several factor pairs could directly reprogram fibroblasts into neurons, which shared similar transcriptional programs with endogenous neurons. This study provides an unbiased discovery approach for systematic identification of genes that drive cell-fate acquisition.

Use of genetic and chemical synthetic lethality as probes of complexity in bacterial cell systems

Different conditions and genomic contexts are known to have an impact on gene essentiality and interactions. Synthetic lethal interactions occur when a combination of perturbations, either genetic or chemical, result in a more profound fitness defect than expected based on the effect of each perturbation alone. Synthetic lethality in bacterial systems has long been studied; however, during the past decade, the emerging fields of genomics and chemical genomics have led to an increase in the scale and throughput of these studies. Here, we review the concepts of genomics and chemical genomics in the context of synthetic lethality and their revolutionary roles in uncovering novel biology such as the characterization of genes of unknown function and in antibacterial drug discovery. We provide an overview of the methodologies, examples and challenges of both genetic and chemical synthetic lethal screening platforms. Finally, we discuss how to apply genetic and chemical synthetic lethal approaches to rationalize the synergies of drugs, screen for new and improved antibacterial therapies and predict drug mechanism of action.

Synthetic Lethal Networks for Precision Oncology: Promises and Pitfalls

Synthetic lethal interactions, in which the simultaneous loss of function of two genes produces a lethal phenotype, are being explored as a means to therapeutically exploit cancer-specific vulnerabilities and expand the scope of precision oncology. Currently, three Food and Drug Administration-approved drugs work by targeting the synthetic lethal interaction between BRCA1/2 and PARP. This review examines additional efforts to discover networks of synthetic lethal interactions and discusses both challenges and opportunities regarding the translation of new synthetic lethal interactions into the clinic.

Smoking and hypertension: Effect of adenosine deaminase polymorphism

Adenosine modulates cardiovascular functions reducing blood pressure and heart rate. Adenosine deaminase (ADA) by the irreversible deamination of adenosine to inosine contributes to the regulation of adenosine concentration in body fluids. We have studied the interaction between smoking and ADA genetic variability concerning their effects on blood pressure. We have studied 344 subjects admitted to the hospital for cardiovascular diseases. The genotypes of two polymorphic loci within the ADA gene were determined: ADA₁ and ADA₂. Both loci show two alleles: ADA₁*1 and ADA₁*2 in ADA₁ locus and ADA₂*1 and ADA₂*2 in ADA₂ locus. In the absence of smoking, the proportion of subjects with hypertension tends to be lower in carriers of the ADA₁*2 allele. In smoking subjects, the pattern is reversed and the proportion of those with hypertension tends to be higher in carriers of the ADA₁*2 allele. A similar pattern is observed for ADA₂ locus. Smoking increases the proportion of subjects showing hypertension: such effect is more marked in those carrying the ADA₁*2 allele as compared to subjects with ADA₁*1/*1 genotype. The same pattern of association is observed for ADA₂ locus. The two loci show an additive effect. The odds ratio for hypertension in smokers vs nonsmokers is 1.450 in subjects carrying ADA₁*1/*1 and ADA₂*1/*1 genotypes, while it is 11.200 in subjects carrying the *2 alleles in both loci. From a practical point, a view of our results suggest that smokers carrying both ADA₁*2 and ADA₂*2 alleles have a higher risk of hypertension.

A broadly conserved NERD genetically interacts with the exocyst to affect root growth and cell expansion

The exocyst, a conserved, octameric protein complex, helps mediate secretion at the plasma membrane, facilitating specific developmental processes that include control of root meristem size, cell elongation, and tip growth. A genetic screen for second-site enhancers in Arabidopsis identified NEW ENHANCER of ROOT DWARFISM1 (NERD1) as an exocyst interactor. Mutations in NERD1 combined with weak exocyst mutations in SEC8 and EXO70A1 result in a synergistic reduction in root growth. Alone, nerd1 alleles modestly reduce primary root growth, both by shortening the root meristem and by reducing cell elongation, but also result in a slight increase in root hair length, bulging, and rupture. NERD1 was identified molecularly as At3g51050, which encodes a transmembrane protein of unknown function that is broadly conserved throughout the Archaeplastida. A functional NERD1-GFP fusion localizes to the Golgi, in a pattern distinct from the plasma membrane-localized exocyst, arguing against a direct NERD1-exocyst interaction. Structural modeling suggests the majority of the protein is positioned in the lumen, in a β-propeller-like structure that has some similarity to proteins that bind polysaccharides. We suggest that NERD1 interacts with the exocyst indirectly, possibly affecting polysaccharides destined for the cell wall, and influencing cell wall characteristics in a developmentally distinct manner.

Genetic Network Complexity Shapes Background-Dependent Phenotypic Expression

The phenotypic consequences of a given mutation can vary across individuals. This so-called background effect is widely observed, from mutant fitness of loss-of-function variants in model organisms to variable disease penetrance and expressivity in humans; however, the underlying genetic basis often remains unclear. Taking insights gained from recent large-scale surveys of genetic interaction and suppression analyses in yeast, we propose that the genetic network context for a given mutation may shape its propensity of exhibiting background-dependent phenotypes. We argue that further efforts in systematically mapping the genetic interaction networks beyond yeast will provide not only key insights into the functional properties of genes, but also a better understanding of the background effects and the (un)predictability of traits in a broader context.

Analysis of the functions of TaGW2 homoeologs in wheat grain weight and protein content traits

GW2 is emerging as a key genetic determinant of grain weight in cereal crops; it has three homoeologs (TaGW2-A1, -B1 and -D1) in hexaploid common wheat (Triticum aestivum L.). Here, by analyzing the gene editing mutants that lack one (B1 or D1), two (B1 and D1) or all three (A1, B1 and D1) homoeologs of TaGW2, several insights are gained into the functions of TaGW2-B1 and -D1 in common wheat grain traits. First, both TaGW2-B1 and -D1 affect thousand-grain weight (TGW) by influencing grain width and length, but the effect conferred by TaGW2-B1 is stronger than that of TaGW2-D1. Second, there exists functional interaction between TaGW2 homoeologs because the TGW increase shown by a double mutant (lacking B1 and D1) was substantially larger than that of their single mutants. Third, both TaGW2-B1 and -D1 modulate cell number and length in the outer pericarp of developing grains, with TaGW2-B1 being more potent. Finally, TaGW2 homoeologs also affect grain protein content as this parameter was generally increased in the mutants, especially in the lines lacking two or three homoeologs. Consistent with this finding, two wheat end-use quality-related parameters, flour protein content and gluten strength, were considerably elevated in the mutants. Collectively, our data shed light on functional difference between and additive interaction of TaGW2 homoeologs in the genetic control of grain weight and protein content traits in common wheat, which may accelerate further research on this important gene and its application in wheat improvement.

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

Condition‐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 to detect 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 an increase in the activation of the checkpoint protein kinase Rad53.

The genetic landscape of a physical interaction

A key question in human genetics and evolutionary biology is how mutations in different genes combine to alter phenotypes. Efforts to systematically map genetic interactions have mostly made use of gene deletions. However, most genetic variation consists of point mutations of diverse and difficult to predict effects. Here, by developing a new sequencing-based protein interaction assay – deepPCA – we quantified the effects of >120,000 pairs of point mutations on the formation of the AP-1 transcription factor complex between the products of the FOS and JUN proto-oncogenes. Genetic interactions are abundant both in cis (within one protein) and trans (between the two molecules) and consist of two classes – interactions driven by thermodynamics that can be predicted using a three-parameter global model, and structural interactions between proximally located residues. These results reveal how physical interactions generate quantitatively predictable genetic interactions.

Proteins, the molecular workhorses of the cell, are made of small units called amino acids attached together like the links of a chain. Each protein is composed of a unique combination of amino acids, which is determined by a specific sequence of DNA called a gene. A change in a gene – a mutation – can create a variation in the protein it codes for, for instance by swapping a type of amino acid for another. Different mutations in the same gene can alter a protein in different ways. Some of these changes are harmless, but other can hinder how the protein performs its role. For example, a small change in the structure of a protein could affect how it will bind to other molecules.

It is possible for people to have identical mutations in the same genes, but experience different consequences. For instance, two persons could carry the same disease-inducing mutation, but one has a severe version of the condition and the other only mild symptoms. One reason is that changes in other genes cancel out or enhance the effect of a mutation. This phenomenon is known as a genetic interaction and it remains poorly understood, especially at the molecular level.

Here, Diss and Lehner developed a method, called deepPCA, to study the consequences of mutations in proteins in the laboratory. The experiments focused on two human genes which code for two proteins that normally attach to each other. Two mutations were artificially created, either one in each gene, or two in one of them. Diss and Lehner then examined how strongly the two mutated proteins could still attach to each other. By repeating this process with over 120,000 different pairs of mutations, it became possible to study how one mutation can have different effects depending on the presence of other mutations in the same protein or in the binding partner.

Overall, Diss and Lehner found that genetic interactions are the result of two mechanisms. In the first one, the two mutations together cause specific structural changes that modify how proteins bind to each other. In the second one, the changes solely depend on the magnitude of the initial, thermodynamic effects of individual mutations, but not on their specific physical and chemical properties. To predict the consequences of this second type of genetic interactions, knowing the identity or the exact effects of the two mutations is not necessary.

Understanding and predicting genetic interactions is important to develop personalized medicine, where treatments are tailored based on the genetic make up of an individual. This knowledge will also help to study how genes have evolved together.

Genetics and epigenetics of autism: A Review

Autism is a developmental disorder that starts before age 3 years, and children with autism have impairment in both social interaction and communication, and have restricted, repetitive, and stereotyped patterns of behavior, interests, and activities. There is a strong heritable component of autism and autism spectrum disorder (ASD) as studies have shown that parents who have a child with ASD have a 2-18% chance of having a second child with ASD. The prevalence of autism and ASD have been increasing during the last 3 decades and much research has been carried out to understand the etiology, so as to develop novel preventive and treatment strategies. This review aims at summarizing the latest research studies related to autism and ASD, focusing not only on the genetics but also some epigenetic findings of autism/ASD. Some promising areas of research using transgenic/knockout animals and some ideas related to potential novel treatment and prevention strategies will be discussed.

Targeting synthetic lethality between the SRC kinase and the EPHB6 receptor may benefit cancer treatment

Application of tumor genome sequencing has identified numerous loss-of-function alterations in cancer cells. While these alterations are difficult to target using direct interventions, they may be attacked with the help of the synthetic lethality (SL) approach. In this approach, inhibition of one gene causes lethality only when another gene is also completely or partially inactivated. The EPHB6 receptor tyrosine kinase has been shown to have anti-malignant properties and to be downregulated in multiple cancers, which makes it a very attractive target for SL applications. In our work, we used a genome-wide SL screen combined with expression and interaction network analyses, and identified the SRC kinase as a SL partner of EPHB6 in triple-negative breast cancer (TNBC) cells. Our experiments also reveal that this SL interaction can be targeted by small molecule SRC inhibitors, SU6656 and KX2-391, and can be used to improve elimination of human TNBC tumors in a xenograft model. Our observations are of potential practical importance, since TNBC is an aggressive heterogeneous malignancy with a very high rate of patient mortality due to the lack of targeted therapies, and our work indicates that FDA-approved SRC inhibitors may potentially be used in a personalized manner for treating patients with EPHB6-deficient TNBC. Our findings are also of a general interest, as EPHB6 is downregulated in multiple malignancies and our data serve as a proof of principle that EPHB6 deficiency may be targeted by small molecule inhibitors in the SL approach.

Hsp70-associated chaperones have a critical role in buffering protein production costs

Proteins are necessary for cellular growth. Concurrently, however, protein production has high energetic demands associated with transcription and translation. Here, we propose that activity of molecular chaperones shape protein burden, that is the fitness costs associated with expression of unneeded proteins. To test this hypothesis, we performed a genome-wide genetic interaction screen in baker's yeast. Impairment of transcription, translation, and protein folding rendered cells hypersensitive to protein burden. Specifically, deletion of specific regulators of the Hsp70-associated chaperone network increased protein burden. In agreement with expectation, temperature stress, increased mistranslation and a chemical misfolding agent all substantially enhanced protein burden. Finally, unneeded protein perturbed interactions between key components of the Hsp70-Hsp90 network involved in folding of native proteins. We conclude that specific chaperones contribute to protein burden. Our work indicates that by minimizing the damaging impact of gratuitous protein overproduction, chaperones enable tolerance to massive changes in genomic expression.

Systematic Genetic Screens Reveal the Dynamic Global Functional Organization of the Bacterial Translation Machinery

Bacterial protein synthesis is an essential, conserved, and environmentally responsive process. Yet, many of its components and dependencies remain unidentified. To address this gap, we used quantitative synthetic genetic arrays to map functional relationships among >48,000 gene pairs in Escherichia coli under four culture conditions differing in temperature and nutrient availability. The resulting data provide global functional insights into the roles and associations of genes, pathways, and processes important for efficient translation, growth, and environmental adaptation. We predict and independently verify the requirement of unannotated genes for normal translation, including a previously unappreciated role of YhbY in 30S biogenesis. Dynamic changes in the patterns of genetic dependencies across the four growth conditions and data projections onto other species reveal overarching functional and evolutionary pressures impacting the translation system and bacterial fitness, underscoring the utility of systematic screens for investigating protein synthesis, adaptation, and evolution.