The complex underpinnings of genetic background effects

Genetic Background Strongly Influences the Impact of Carrying the Thr92Ala-DIO2 Polymorphism in the Male Mouse

About half of the world population carries at least one allele of the Ala92-DIO2, which slows down the activity of the type 2 deiodinase (D2), the enzyme that activates T4 to T3. Carrying the Ala92-DIO2 allele has been associated with increased body mass index and insulin resistance, but this has not been reproduced in all populations. To test if the genetic background affects the impact of this polymorphism, here we studied the genetically distant C57Bl/6J (B6) and FVB/N (FVB) mice carrying the Ala92-Dio2 allele as compared to control mice carrying the Thr92-Dio2 allele. Whereas B6-Ala92-Dio2 and B6-Thr92-Dio2 mice-fed chow or high-fat diet-behaved metabolically similar in studies using indirect calorimetry, glucose- and insulin tolerance tests, and measuring white adipose tissue (WAT) weight and liver steatosis, major differences were observed between FVB-Ala92-Dio2 and FVB-Thr92-Dio2 mice: carrying the Ala92-Dio2 allele (on a chow diet) resulted in hypercholesterolemia, smaller WAT pads, hepatomegaly, steatosis, and transcriptome changes in the interscapular brown adipose tissue (iBAT) typical of ER stress and apoptosis. Acclimatization at thermoneutrality (30 °C) eliminated most of the metabolic phenotype, indicating that impaired adaptive (BAT) thermogenesis can be involved. In conclusion, the metabolic impact of carrying the Ala92-Dio2 allele depends greatly on the genetic background of the mouse, varying from no phenotype in B6 mice to a major phenotype in FVB mice. These results will help the planning of future clinical trials studying the Thr92Ala-DIO2 polymorphism and may explain why some clinical studies performed in different populations across the globe have obtained inconsistent results.

Genome-scale analysis of interactions between genetic perturbations and natural variation

Interactions between genetic perturbations and segregating loci can cause perturbations to show different phenotypic effects across genetically distinct individuals. To study these interactions on a genome scale in many individuals, we used combinatorial DNA barcode sequencing to measure the fitness effects of 8046 CRISPRi perturbations targeting 1721 distinct genes in 169 yeast cross progeny (or segregants). We identified 460 genes whose perturbation has different effects across segregants. Several factors caused perturbations to show variable effects, including baseline segregant fitness, the mean effect of a perturbation across segregants, and interacting loci. We mapped 234 interacting loci and found four hub loci that interact with many different perturbations. Perturbations that interact with a given hub exhibit similar epistatic relationships with the hub and show enrichment for cellular processes that may mediate these interactions. These results suggest that an individual's response to perturbations is shaped by a network of perturbation-locus interactions that cannot be measured by approaches that examine perturbations or natural variation alone.

Environment-independent distribution of mutational effects emerges from microscopic epistasis

Predicting how new mutations alter phenotypes is difficult because mutational effects vary across genotypes and environments. Recently discovered global epistasis, where the fitness effects of mutations scale with the fitness of the background genotype, can improve predictions, but how the environment modulates this scaling is unknown. We measured the fitness effects of ~100 insertion mutations in 42 strains of Saccharomyces cerevisiae in six laboratory environments and found that the global-epistasis scaling is nearly invariant across environments. Instead, the environment tunes one global parameter, the background fitness at which most mutations switch sign. As a consequence, the distribution of mutational effects is predictable across genotypes and environments. Our results suggest that the effective dimensionality of genotype-to-phenotype maps across environments is surprisingly low.

Gene polymorphisms and thyroid hormone signaling: implication for the treatment of hypothyroidism

INTRODUCTION

Mutations and single nucleotide polymorphisms (SNPs) in the genes encoding the network of proteins involved in thyroid hormone signaling (TH) may have implications for the effectiveness of the treatment of hypothyroidism with LT4. It is conceivable that loss-of-function mutations or SNPs impair the ability of LT4 to be activated to T3, reach its targets, and ultimately resolve symptoms of hypothyroidism. Some of these patients do benefit from therapy containing LT4 and LT3.

METHODS

Here, we reviewed the PubMed and examined gene mutations and SNPs in the TH cellular transporters, deiodinases, and TH receptors, along with their impact on TH signaling, and potential clinical implications.

RESULTS

In some mechanisms, such as the Thr92Ala-DIO2 SNP, there is a compelling rationale for reduced T4 to T3 activation that limits the effectiveness of LT4 to restore euthyroidism. In other mechanisms, a potential case can be made but more studies with a larger number of individuals are needed.

DISCUSSION/CONCLUSION

Understanding the clinical impact of the genetic makeup of LT4-treated patients may help in the preemptive identification of those individuals that would benefit from therapy containing LT3.

Genetically transitional disease: conceptual understanding and applicability to rheumatic disease

In genomic medicine, the concept of genetically transitional disease (GTD) refers to cases in which gene mutation is necessary but not sufficient to cause disease. In this Perspective, we apply this novel concept to rheumatic diseases, which have been linked to hundreds of genetic variants via association studies. These variants are in the 'grey zone' between monogenic variants with large effect sizes and common susceptibility alleles with small effect sizes. Among genes associated with rare autoinflammatory diseases, many low-frequency and/or low-penetrance variants are known to increase susceptibility to systemic inflammation. In autoimmune diseases, hundreds of HLA and non-HLA genetic variants have been revealed to be modest- to moderate-risk alleles. These diseases can be reclassified as GTDs. The same concept could apply to many other human diseases. GTD could improve the reporting of genetic testing results, diagnostic yields, genetic counselling and selection of therapy, as well as facilitating research using a novel approach to human genetic diseases.

Pleiotropy, epistasis and the genetic architecture of quantitative traits

Pleiotropy (whereby one genetic polymorphism affects multiple traits) and epistasis (whereby non-linear interactions between genetic polymorphisms affect the same trait) are fundamental aspects of the genetic architecture of quantitative traits. Recent advances in the ability to characterize the effects of polymorphic variants on molecular and organismal phenotypes in human and model organism populations have revealed the prevalence of pleiotropy and unexpected shared molecular genetic bases among quantitative traits, including diseases. By contrast, epistasis is common between polymorphic loci associated with quantitative traits in model organisms, such that alleles at one locus have different effects in different genetic backgrounds, but is rarely observed for human quantitative traits and common diseases. Here, we review the concepts and recent inferences about pleiotropy and epistasis, and discuss factors that contribute to similarities and differences between the genetic architecture of quantitative traits in model organisms and humans.

Strain background of Candida albicans interacts with SIR2 to alter phenotypic switching

The genetic background between strains of a single species and within a single strain lineage can significantly impact the expression of biological traits. This genetic variation may also reshape epigenetic mechanisms of cell identity and environmental responses that are controlled by interconnected transcriptional networks and chromatin-modifying enzymes. Histone deacetylases, including sirtuins, are critical regulators of chromatin state and have been directly implicated in governing the phenotypic transition between the 'sterile' white state and the mating-competent opaque state in Candida albicans, a common fungal commensal and pathogen of humans. Here, we found that a previously ambiguous role for the sirtuin SIR2 in C. albicans phenotypic switching is likely linked to the genetic background of mutant strains produced in the RM lineage of SC5314. SIR2 mutants in a specific lineage of BWP17 displayed increased frequencies of switching to the opaque state compared to the wild-type. Loss of SIR2 in other SC5314-derived backgrounds, including newly constructed BWP17 sir2Δ/Δ mutants, failed to recapitulate the increased white-opaque switching frequencies observed in the original BWP17 sir2Δ/Δ mutant background. Whole-genome sequencing revealed the presence of multiple imbalanced chromosomes and large loss of heterozygosity tracts that likely interact with SIR2 to increase phenotypic switching in this BWP17 sir2Δ/Δ mutant lineage. These genomic changes are not found in other SC5314-derived sir2Δ/Δ mutants that do not display increased opaque cell formation. Thus, complex karyotypes can emerge during strain construction that modify mutant phenotypes and highlight the importance of validating strain background when interpreting phenotypes.

Genome-scale analysis of interactions between genetic perturbations and natural variation

Interactions between genetic perturbations and segregating loci can cause perturbations to show different phenotypic effects across genetically distinct individuals. To study these interactions on a genome scale in many individuals, we used combinatorial DNA barcode sequencing to measure the fitness effects of 7,700 CRISPRi perturbations targeting 1,712 distinct genes in 169 yeast cross progeny (or segregants). We identified 460 genes whose perturbation has different effects across segregants. Several factors caused perturbations to show variable effects, including baseline segregant fitness, the mean effect of a perturbation across segregants, and interacting loci. We mapped 234 interacting loci and found four hub loci that interact with many different perturbations. Perturbations that interact with a given hub exhibit similar epistatic relationships with the hub and show enrichment for cellular processes that may mediate these interactions. These results suggest that an individual's response to perturbations is shaped by a network of perturbation-locus interactions that cannot be measured by approaches that examine perturbations or natural variation alone.

Genome-wide artificial introgressions of Gossypium barbadense into G. hirsutum reveal superior loci for simultaneous improvement of cotton fiber quality and yield traits

INTRODUCTION

The simultaneous improvement of fiber quality and yield for cotton is strongly limited by the narrow genetic backgrounds of Gossypium hirsutum (Gh) and the negative genetic correlations among traits. An effective way to overcome the bottlenecks is to introgress the favorable alleles of Gossypium barbadense (Gb) for fiber quality into Gh with high yield.

OBJECTIVES

This study was to identify superior loci for the improvement of fiber quality and yield.

METHODS

Two sets of chromosome segment substitution lines (CSSLs) were generated by crossing Hai1 (Gb, donor-parent) with cultivar CCRI36 (Gh) and CCRI45 (Gh) as genetic backgrounds, and cultivated in 6 and 8 environments, respectively. The kmer genotyping strategy was improved and applied to the population genetic analysis of 743 genomic sequencing data. A progeny segregating population was constructed to validate genetic effects of the candidate loci.

RESULTS

A total of 68,912 and 83,352 genome-wide introgressed kmers were identified in the CCRI36 and CCRI45 populations, respectively. Over 90 % introgressions were homologous exchanges and about 21 % were reverse insertions. In total, 291 major introgressed segments were identified with stable genetic effects, of which 66(22.98 %), 64(21.99 %), 35(12.03 %), 31(10.65 %) and 18(6.19 %) were beneficial for the improvement of fiber length (FL), strength (FS), micronaire, lint-percentage (LP) and boll-weight, respectively. Thirty-nine introgression segments were detected with stable favorable additive effects for simultaneous improvement of 2 or more traits in Gh genetic background, including 6 could increase FL/FS and LP. The pyramiding effects of 3 pleiotropic segments (A07:C45Clu-081, D06:C45Clu-218, D02:C45Clu-193) were further validated in the segregating population.

CONCLUSION

The combining of genome-wide introgressions and kmer genotyping strategy showed significant advantages in exploring genetic resources. Through the genome-wide comprehensive mining, a total of 11 clusters (segments) were discovered for the stable simultaneous improvement of FL/FS and LP, which should be paid more attention in the future.

Implications of combined NOD2 and other gene mutations in autoinflammatory diseases

NOD-like receptors (NLRs) are intracellular sensors associated with systemic autoinflammatory diseases (SAIDs). We investigated the largest monocentric cohort of patients with adult-onset SAIDs for coinheritance of low frequency and rare mutations in NOD2 and other autoinflammatory genes. Sixty-three patients underwent molecular testing for SAID gene panels after extensive clinical workups. Whole exome sequencing data from the large Atherosclerosis Risk in Communities (ARIC) study of individuals of European-American ancestry were used as control. Of 63 patients, 44 (69.8%) were found to carry combined gene variants in NOD2 and another gene (Group 1), and 19 (30.2%) were carriers only for NOD2 variants (Group 2). The genetic variant combinations in SAID patients were digenic in 66% (NOD2/MEFV, NOD2/NLRP12, NOD2/NLRP3, and NOD2/TNFRSF1A) and oligogenic in 34% of cases. These variant combinations were either absent or significantly less frequent in the control population. By phenotype-genotype correlation, approximately 40% of patients met diagnostic criteria for a specific SAID, and 60% had mixed diagnoses. There were no statistically significant differences in clinical manifestations between the two patient groups except for chest pain. Due to overlapping phenotypes and mixed genotypes, we have suggested a new term, "Mixed NLR-associated Autoinflammatory Disease ", to describe this disease scenario. Gene variant combinations are significant in patients with SAIDs primarily presenting with mixed clinical phenotypes. Our data support the proposition that immunological disease expression is modified by genetic background and environmental exposure. We provide a preliminary framework in diagnosis, management, and interpretation of the clinical scenario.

Mutational hotspots lead to robust but suboptimal adaptive outcomes in certain environments

The observed mutational spectrum of adaptive outcomes can be constrained by many factors. For example, mutational biases can narrow the observed spectrum by increasing the rate of mutation at isolated sites in the genome. In contrast, complex environments can shift the observed spectrum by defining fitness consequences of mutational routes. We investigate the impact of different nutrient environments on the evolution of motility in Pseudomonas fluorescens Pf0-2x (an engineered non-motile derivative of Pf0-1) in the presence and absence of a strong mutational hotspot. Previous work has shown that this mutational hotspot can be built and broken via six silent mutations, which provide rapid access to a mutation that rescues swimming motility and confers the strongest swimming phenotype in specific environments. Here, we evolved a hotspot and non-hotspot variant strain of Pf0-2x for motility under nutrient-rich (LB) and nutrient-limiting (M9) environmental conditions. We observed the hotspot strain consistently evolved faster across all environmental conditions and its mutational spectrum was robust to environmental differences. However, the non-hotspot strain had a distinct mutational spectrum that changed depending on the nutrient environment. Interestingly, while alternative adaptive mutations in nutrient-rich environments were equal to, or less effective than, the hotspot mutation, the majority of these mutations in nutrient-limited conditions produced superior swimmers. Our competition experiments mirrored these findings, underscoring the role of environment in defining both the mutational spectrum and the associated phenotype strength. This indicates that while mutational hotspots working in concert with natural selection can speed up access to robust adaptive mutations (which can provide a competitive advantage in evolving populations), they can limit exploration of the mutational landscape, restricting access to potentially stronger phenotypes in specific environments.

Role of genetic architecture in phenotypic plasticity

Phenotypic plasticity, the ability of an organism to display different phenotypes across environments, is widespread in nature. Plasticity aids survival in novel environments. Herein, we review studies from yeast that allow us to start uncovering the genetic architecture of phenotypic plasticity. Genetic variants and their interactions impact the phenotype in different environments, and distinct environments modulate the impact of genetic variants and their interactions on the phenotype. Because of this, certain hidden genetic variation is expressed in specific genetic and environmental backgrounds. A better understanding of the genetic mechanisms of phenotypic plasticity will help to determine short- and long-term responses to selection and how wide variation in disease manifestation occurs in human populations.

Disease in the Pld4thss/thss Model of Murine Lupus Requires TLR9

Phospholipase D4 (PLD4) is an endolysosomal exonuclease of ssRNA and ssDNA, rather than a phospholipase as its name suggests. Human polymorphisms in the PLD4 gene have been linked by genome-wide association studies to systemic sclerosis, rheumatoid arthritis, and systemic lupus erythematosus. However, B6.129 Pld4-/- mice develop features of a distinct disease, macrophage activation syndrome, which is reversed in mice mutated in TLR9. In this article, we compare a Pld4 null mutant identified on the BALB/c background, Pld4thss/thss, which has distinct phenotypes: short stature, thin hair, and features of systemic lupus erythematosus. All phenotypes analyzed were largely normalized in Pld4thss/thssTlr9-/- mice. Thus, Pld4thss/thss represents a rare model in which mouse lupus etiology is TLR9 dependent. Compared with PLD4-deficient B6 mice, Pld4thss/thss mice had elevated levels of serum IgG, IgG anti-dsDNA autoantibodies, BAFF, and IFN-γ and elevated B cell numbers. Overall, the data suggest that PLD4 deficiency can lead to a diverse array of rheumatological abnormalities depending upon background-modifying genes, and that these diseases of PLD4 deficiency are largely driven by TLR9 recognition of ssDNA.

Transient mutation bias increases the predictability of evolution on an empirical genotype-phenotype landscape

Predicting how a population will likely navigate a genotype-phenotype landscape requires consideration of selection in combination with mutation bias, which can skew the likelihood of following a particular trajectory. Strong and persistent directional selection can drive populations to ascend toward a peak. However, with a greater number of peaks and more routes to reach them, adaptation inevitably becomes less predictable. Transient mutation bias, which operates only on one mutational step, can influence landscape navigability by biasing the mutational trajectory early in the adaptive walk. This sets an evolving population upon a particular path, constraining the number of accessible routes and making certain peaks and routes more likely to be realized than others. In this work, we employ a model system to investigate whether such transient mutation bias can reliably and predictably place populations on a mutational trajectory to the strongest selective phenotype or usher populations to realize inferior phenotypic outcomes. For this we use motile mutants evolved from ancestrally non-motile variants of the microbe Pseudomonas fluorescens SBW25, of which one trajectory exhibits significant mutation bias. Using this system, we elucidate an empirical genotype-phenotype landscape, where the hill-climbing process represents increasing strength of the motility phenotype, to reveal that transient mutation bias can facilitate rapid and predictable ascension to the strongest observed phenotype in place of equivalent and inferior trajectories. This article is part of the theme issue 'Interdisciplinary approaches to predicting evolutionary biology'.

Widespread epistasis among beneficial genetic variants revealed by high-throughput genome editing

The phenotypic effect of any genetic variant can be altered by variation at other genomic loci. Known as epistasis, these genetic interactions shape the genotype-phenotype map of every species, yet their origins remain poorly understood. To investigate this, we employed high-throughput genome editing to measure the fitness effects of 1,826 naturally polymorphic variants in four strains of Saccharomyces cerevisiae. About 31% of variants affect fitness, of which 24% have strain-specific fitness effects indicative of epistasis. We found that beneficial variants are more likely to exhibit genetic interactions and that these interactions can be mediated by specific traits such as flocculation ability. This work suggests that adaptive evolution will often involve trade-offs where a variant is only beneficial in some genetic backgrounds, potentially explaining why many beneficial variants remain polymorphic. In sum, we provide a framework to understand the factors influencing epistasis with single-nucleotide resolution, revealing widespread epistasis among beneficial variants.

Allopatric divergence of cooperators confers cheating resistance and limits effects of a defector mutation

BACKGROUND

Social defectors may meet diverse cooperators. Genotype-by-genotype interactions may constrain the ranges of cooperators upon which particular defectors can cheat, limiting cheater spread. Upon starvation, the soil bacterium Myxococcus xanthus cooperatively develops into spore-bearing fruiting bodies, using a complex regulatory network and several intercellular signals. Some strains (cheaters) are unable to sporulate effectively in pure culture due to mutations that reduce signal production but can exploit and outcompete cooperators within mixed groups.

RESULTS

In this study, interactions between a cheater disrupted at the signaling gene csgA and allopatrically diversified cooperators reveal a very small cheating range. Expectedly, the cheater failed to cheat on all natural-isolate cooperators owing to non-cheater-specific antagonisms. Surprisingly, some lab-evolved cooperators had already exited the csgA mutant's cheating range after accumulating fewer than 20 mutations and without experiencing cheating during evolution. Cooperators might also diversify in the potential for a mutation to reduce expression of a cooperative trait or generate a cheating phenotype. A new csgA mutation constructed in several highly diverged cooperators generated diverse sporulation phenotypes, ranging from a complete defect to no defect, indicating that genetic backgrounds can limit the set of genomes in which a mutation creates a defector.

CONCLUSIONS

Our results demonstrate that natural populations may feature geographic mosaics of cooperators that have diversified in their susceptibility to particular cheaters, limiting defectors' cheating ranges and preventing them from spreading. This diversification may also lead to variation in the phenotypes generated by any given cooperation-gene mutation, further decreasing the chance of a cheater emerging which threatens the persistence of cooperation in the system.

Regulation at Drosophila's Malic Enzyme highlights the complexity of transvection and its sensitivity to genetic background

Transvection, a type of trans-regulation of gene expression in which regulatory elements on one chromosome influence elements on a paired homologous chromosome, is itself a complex biological phenotype subject to modification by genetic background effects. However, relatively few studies have explored how transvection is affected by distal genetic variation, perhaps because it is strongly influenced by local regulatory elements and chromosomal architecture. With the emergence of the "hub" model of transvection and a series of studies showing variation in transvection effects, it is becoming clear that genetic background plays an important role in how transvection influences gene transcription. We explored the effects of genetic background on transvection by performing two independent genome wide association studies (GWASs) using the Drosophila genetic reference panel (DGRP) and a suite of Malic enzyme (Men) excision alleles. We found substantial variation in the amount of transvection in the 149 DGRP lines used, with broad-sense heritability of 0.89 and 0.84, depending on the excision allele used. The specific genetic variation identified was dependent on the excision allele used, highlighting the complex genetic interactions influencing transvection. We focussed primarily on genes identified as significant using a relaxed P-value cutoff in both GWASs. The most strongly associated genetic variant mapped to an intergenic single nucleotide polymorphism (SNP), located upstream of Tiggrin (Tig), a gene that codes for an extracellular matrix protein. Variants in other genes, such transcription factors (CG7368 and Sima), RNA binding proteins (CG10418, Rbp6, and Rig), enzymes (AdamTS-A, CG9743, and Pgant8), proteins influencing cell cycle progression (Dally and Eip63E) and signaling proteins (Atg-1, Axo, Egfr, and Path) also associated with transvection in Men. Although not intuitively obvious how many of these genes may influence transvection, some have been previously identified as promoting or antagonizing somatic homolog pairing. These results identify several candidate genes to further explore in the understanding of transvection in Men and in other genes regulated by transvection. Overall, these findings highlight the complexity of the interactions involved in gene regulation, even in phenotypes, such as transvection, that were traditionally considered to be primarily influenced by local genetic variation.

Loss-of-function mutation survey revealed that genes with background-dependent fitness are rare and functionally related in yeast

In different individuals, the same mutation can lead to different phenotypes due to genetic background effects. This is commonly observed in various systems, including many human diseases. While isolated examples of such background effects have been observed, a systematic view across a large number of individuals is still lacking. Here, we surveyed genetic background effects associated with gene loss-of-function mutations across a population of natural isolates of the yeast Saccharomyces cerevisiae. We found that ∼15% of genes can display a background-dependent fitness change. Genes related to mitochondrial functions are significantly overrepresented, and showed reversed patterns of fitness gain or loss with genes involved in transcription and chromatin remodeling as well as in nuclear–cytoplasmic transport, suggesting a potential functional rewiring.

In natural populations, the same mutation can lead to different phenotypic outcomes due to the genetic variation that exists among individuals. Such genetic background effects are commonly observed, including in the context of many human diseases. However, systematic characterization of these effects at the species level is still lacking to date. Here, we sought to comprehensively survey background-dependent traits associated with gene loss-of-function (LoF) mutations in 39 natural isolates of Saccharomyces cerevisiae using a transposon saturation strategy. By analyzing the modeled fitness variability of a total of 4,469 genes, we found that 15% of them, when impacted by a LoF mutation, exhibited a significant gain- or loss-of-fitness phenotype in certain natural isolates compared with the reference strain S288C. Out of these 632 genes with predicted background-dependent fitness effects, around 2/3 impact multiple backgrounds with a gradient of predicted fitness change while 1/3 are specific to a single genetic background. Genes related to mitochondrial function are significantly overrepresented in the set of genes showing a continuous variation and display a potential functional rewiring with other genes involved in transcription and chromatin remodeling as well as in nuclear–cytoplasmic transport. Such rewiring effects are likely modulated by both the genetic background and the environment. While background-specific cases are rare and span diverse cellular processes, they can be functionally related at the individual level. All genes with background-dependent fitness effects tend to have an intermediate connectivity in the global genetic interaction network and have shown relaxed selection pressure at the population level, highlighting their potential evolutionary characteristics.

Exploring conditional gene essentiality through systems genetics approaches in yeast

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

Dps Is a Universally Conserved Dual-Action DNA-Binding and Ferritin Protein

The DNA-binding protein from starved cells, Dps, is a universally conserved prokaryotic ferritin that, in many species, also binds DNA. Dps homologs have been identified in the vast majority of bacterial species and several archaea. Dps also may play a role in the global regulation of gene expression, likely through chromatin reorganization. Dps has been shown to use both its ferritin and DNA-binding functions to respond to a variety of environmental pressures, including oxidative stress. One mechanism that allows Dps to achieve this is through a global nucleoid restructuring event during stationary phase, resulting in a compact, hexacrystalline nucleoprotein complex called the biocrystal that occludes damaging agents from DNA. Due to its small size, hollow spherical structure, and high stability, Dps is being developed for applications in biotechnology.

The interplay of additivity, dominance, and epistasis on fitness in a diploid yeast cross

In diploid species, genetic loci can show additive, dominance, and epistatic effects. To characterize the contributions of these different types of genetic effects to heritable traits, we use a double barcoding system to generate and phenotype a panel of ~200,000 diploid yeast strains that can be partitioned into hundreds of interrelated families. This experiment enables the detection of thousands of epistatic loci, many whose effects vary across families. Here, we show traits are largely specified by a small number of hub loci with major additive and dominance effects, and pervasive epistasis. Genetic background commonly influences both the additive and dominance effects of loci, with multiple modifiers typically involved. The most prominent dominance modifier in our data is the mating locus, which has no effect on its own. Our findings show that the interplay between additivity, dominance, and epistasis underlies a complex genotype-to-phenotype map in diploids.

Epistatic genetic interactions govern morphogenesis during sexual reproduction and infection in a global human fungal pathogen

Cellular development is orchestrated by evolutionarily conserved signaling pathways, which are often pleiotropic and involve intra- and interpathway epistatic interactions that form intricate, complex regulatory networks. Cryptococcus species are a group of closely related human fungal pathogens that grow as yeasts yet transition to hyphae during sexual reproduction. Additionally, during infection they can form large, polyploid titan cells that evade immunity and develop drug resistance. Multiple known signaling pathways regulate cellular development, yet how these are coordinated and interact with genetic variation is less well understood. Here, we conducted quantitative trait locus (QTL) analyses of a mapping population generated by sexual reproduction of two parents, only one of which is unisexually fertile. We observed transgressive segregation of the unisexual phenotype among progeny, as well as a large-cell phenotype under mating-inducing conditions. These large-cell progeny were found to produce titan cells both in vitro and in infected animals. Two major QTLs and corresponding quantitative trait genes (QTGs) were identified: RIC8 (encoding a guanine-exchange factor) and CNC06490 (encoding a putative Rho-GTPase activator), both involved in G protein signaling. The two QTGs interact epistatically with each other and with the mating-type locus in phenotypic determination. These findings provide insights into the complex genetics of morphogenesis during unisexual reproduction and pathogenic titan cell formation and illustrate how QTL analysis can be applied to identify epistasis between genes. This study shows that phenotypic outcomes are influenced by the genetic background upon which mutations arise, implicating dynamic, complex genotype-to-phenotype landscapes in fungal pathogens and beyond.

Higher order genetic interactions switch cancer genes from two-hit to one-hit drivers

The classic two-hit model posits that both alleles of a tumor suppressor gene (TSG) must be inactivated to cause cancer. In contrast, for some oncogenes and haploinsufficient TSGs, a single genetic alteration can suffice to increase tumor fitness. Here, by quantifying the interactions between mutations and copy number alterations (CNAs) across 10,000 tumors, we show that many cancer genes actually switch between acting as one-hit or two-hit drivers. Third order genetic interactions identify the causes of some of these switches in dominance and dosage sensitivity as mutations in other genes in the same biological pathway. The correct genetic model for a gene thus depends on the other mutations in a genome, with a second hit in the same gene or an alteration in a different gene in the same pathway sometimes representing alternative evolutionary paths to cancer.

Decoding 'Unnecessary Complexity': A Law of Complexity and a Concept of Hidden Variation Behind "Missing Heritability" in Precision Medicine

The high hopes for the Human Genome Project and personalized medicine were not met because the relationship between genotypes and phenotypes turned out to be more complex than expected. In a previous study we laid the foundation of a theory of complexity and showed that because of the blind nature of evolution, and molecular and historical contingency, cells have accumulated unnecessary complexity, complexity beyond what is necessary and sufficient to describe an organism. Here we provide empirical evidence and show that unnecessary complexity has become integrated into the genome in the form of redundancy and is relevant to molecular evolution of phenotypic complexity. Unnecessary complexity creates uncertainty between molecular and phenotypic complexity, such that phenotypic complexity (CP) is higher than molecular complexity (CM), which is higher than DNA complexity (CD). The qualitative inequality in complexity is based on the following hierarchy: CP > CM > CD. This law-like relationship holds true for all complex traits, including complex diseases. We present a hypothesis of two types of variation, namely open and closed (hidden) systems, show that hidden variation provides a hitherto undiscovered "third source" of phenotypic variation, beside genotype and environment, and argue that "missing heritability" for some complex diseases is likely to be a case of "diluted heritability". There is a need for radically new ways of thinking about the principles of genotype-phenotype relationship. Understanding how cells use hidden, pathway variation to respond to stress can shed light on why two individuals who share the same risk factors may not develop the same disease, or how cancer cells escape death.

Introducing Beneficial Alleles from Plant Genetic Resources into the Wheat Germplasm

Wheat (Triticum sp.) is one of the world's most important crops, and constantly increasing its productivity is crucial to the livelihoods of millions of people. However, more than a century of intensive breeding and selection processes have eroded genetic diversity in the elite genepool, making new genetic gains difficult. Therefore, the need to introduce novel genetic diversity into modern wheat has become increasingly important. This review provides an overview of the plant genetic resources (PGR) available for wheat. We describe the most important taxonomic and phylogenetic relationships of these PGR to guide their use in wheat breeding. In addition, we present the status of the use of some of these resources in wheat breeding programs. We propose several introgression schemes that allow the transfer of qualitative and quantitative alleles from PGR into elite germplasm. With this in mind, we propose the use of a stage-gate approach to align the pre-breeding with main breeding programs to meet the needs of breeders, farmers, and end-users. Overall, this review provides a clear starting point to guide the introgression of useful alleles over the next decade.

Bisphenol A, S, and F exposure, ESR1/2, CAT, and eNOS genetic polymorphisms, and the risk of hypertension

While bisphenol A (BPA) exposure was inconsistently associated with hypertension risk, little is known about whether its alternatives bisphenol S and F (BPS and BPF) have similar hypertensive effects. Furthermore, epidemiologic studies on the genetic susceptibility to the hypertensive effects of bisphenols are scarce. We conducted a case-control study in 439 pairs of hypertension cases and matched controls. Urinary bisphenols concentrations were measured to characterize the internal exposure levels. The genotyping of ESR1/2, CAT, and eNOS was performed by a multiplex fluorescent polymerase chain reaction. BPA exposure was positively associated with hypertension risk. Carriers of rs2234693 C allele in ESR1 were associated with increased hypertension risk. Significant associations of BPA exposure with increased hypertension risk were suggested in individuals with the major allele of rs1256049 in ESR2, rs769214 in CAT, and rs1799983 in eNOS. Besides, rs4755374 in CAT might modify the association of BPA exposure with hypertension risk. Individuals with specific genotypes in ESR1/2, CAT, and eNOS might be more susceptible to the hypertensive effects of BPA.

Random Penetrance of Mutations Among Individuals: A New Type of Genetic Drift in Molecular Evolution

The determinative view of mutation penetrance is a fundamental assumption for the building of molecular evolutionary theory: individuals in the population with the same genotype have the same fitness effect. Since this view has been constantly challenged by experimental evidence, it is desirable to examine to what extent violation of this view could affect our understanding of molecular evolution. To this end, the author formulated a new theory of molecular evolution under a random model of penetrance: for any individual with the same mutational genotype, the coefficient of selection is a random variable. It follows that, in addition to the conventional N _e-genetic drift (N _e is the effective population size), the variance of penetrance among individuals (ε ²) represents a new type of genetic drift, coined by the ε ²-genetic drift. It has been demonstrated that these two genetic drifts together provided new insights on the nearly neutral evolution: the evolutionary rate is inversely related to the log-of-N _e when the ε ²-genetic drift is nontrivial. This log-of-N _e feature of ε ²-genetic drift did explain well why the d _N /d _S ratio (the nonsynonymous rate to the synonymous rate) in humans is only as twofold as that in mice, while the effective population size (N _e) of mice is about two-magnitude larger than that of humans. It was estimated that, for the first time, the variance of random penetrance in mammalian genes was approximately ε ²≈ 5.89 × 10^-3.

Natural variants suppress mutations in hundreds of essential genes

The consequence of a mutation can be influenced by the context in which it operates. For example, loss of gene function may be tolerated in one genetic background, and lethal in another. The extent to which mutant phenotypes are malleable, the architecture of modifiers and the identities of causal genes remain largely unknown. Here, we measure the fitness effects of ~ 1,100 temperature‐sensitive alleles of yeast essential genes in the context of variation from ten different natural genetic backgrounds and map the modifiers for 19 combinations. Altogether, fitness defects for 149 of the 580 tested genes (26%) could be suppressed by genetic variation in at least one yeast strain. Suppression was generally driven by gain‐of‐function of a single, strong modifier gene, and involved both genes encoding complex or pathway partners suppressing specific temperature‐sensitive alleles, as well as general modifiers altering the effect of many alleles. The emerging frequency of suppression and range of possible mechanisms suggest that a substantial fraction of monogenic diseases could be managed by modulating other gene products.

Environmental robustness of the global yeast genetic interaction network

Phenotypes associated with genetic variants can be altered by interactions with other genetic variants (GxG), with the environment (GxE), or both (GxGxE). Yeast genetic interactions have been mapped on a global scale, but the environmental influence on the plasticity of genetic networks has not been examined systematically. To assess environmental rewiring of genetic networks, we examined 14 diverse conditions and scored 30,000 functionally representative yeast gene pairs for dynamic, differential interactions. Different conditions revealed novel differential interactions, which often uncovered functional connections between distantly related gene pairs. However, the majority of observed genetic interactions remained unchanged in different conditions, suggesting that the global yeast genetic interaction network is robust to environmental perturbation and captures the fundamental functional architecture of a eukaryotic cell.

The complex role of genetic background in shaping the effects of spontaneous and induced mutations

Spontaneous and induced mutations frequently show different phenotypic effects across genetically distinct individuals. It is generally appreciated that these background effects mainly result from genetic interactions between the mutations and segregating loci. However, the architectures and molecular bases of these genetic interactions are not well understood. Recent work in a number of model organisms has tried to advance knowledge of background effects both by using large‐scale screens to find mutations that exhibit this phenomenon and by identifying the specific loci that are involved. Here, we review this body of research, emphasizing in particular the insights it provides into both the prevalence of background effects across different mutations and the mechanisms that cause these background effects.

A large fraction of mutations show different effects in distinct individuals.

These background effects are mainly caused by epistasis with segregating loci.

Mapping studies show a diversity of genetic architectures can be involved.

Genetically complex changes in gene expression are often, but not always, causative.

Genetic background impacts the timing of synaptonemal complex breakdown in Drosophila melanogaster

Experiments performed in different genetic backgrounds occasionally exhibit failure in experimental reproducibility. This is a serious issue in Drosophila where there are no standard control stocks. Here, we illustrate the importance of controlling genetic background by showing that the timing of a major meiotic event, the breakdown of the synaptonemal complex (SC), varies in different genetic backgrounds. We assessed SC breakdown in three different control stocks and found that in one control stock, y w; sv^spa-pol, the SC broke down earlier than in Oregon-R and w¹¹¹⁸ stocks. We further examined SC breakdown in these three control backgrounds with flies heterozygous for a null mutation in c(3)G, which encodes a key structural component of the SC. Flies heterozygous for c(3)G displayed differences in the timing of SC breakdown in different control backgrounds, providing evidence of a sensitizing effect of this mutation. These observations suggest that SC maintenance is associated with the dosage of c(3)G in some backgrounds. Lastly, chromosome segregation was not affected by premature SC breakdown in mid-prophase, consistent with previous findings that chromosome segregation is not dependent on full-length SC in mid-prophase. Thus, genetic background is an important variable to consider with respect to SC behavior during Drosophila meiosis.

The Genetic Architecture of Emerging Fungicide Resistance in Populations of a Global Wheat Pathogen

Containing fungal diseases often depends on the application of fungicidal compounds. Fungicides can rapidly lose effectiveness due to the rise of resistant individuals in populations. However, the lack of knowledge about resistance mutations beyond known target genes challenges investigations into pathways to resistance. We used whole-genome sequencing data and association mapping to reveal the multilocus genetic architecture of fungicide resistance in a global panel of 159 isolates of Parastagonospora nodorum, an important fungal pathogen of wheat. We found significant differences in azole resistance among global field populations. The populations evolved distinctive combinations of resistance alleles which can interact when co-occurring in the same genetic background. We identified 34 significantly associated single nucleotide polymorphisms located in close proximity to genes associated with fungicide resistance in other fungi, including a major facilitator superfamily transporter. Using fungal colony growth rates and melanin production at different temperatures as fitness proxies, we found no evidence that resistance was constrained by genetic trade-offs. Our study demonstrates how genome-wide association studies of a global collection of pathogen strains can recapitulate the emergence of fungicide resistance. The distinct complement of resistance mutations found among populations illustrates how the evolutionary trajectory of fungicide adaptation can be complex and challenging to predict.

The impact of the genetic background on gene deletion phenotypes in Saccharomyces cerevisiae

Loss-of-function (LoF) mutations associated with disease do not manifest equally in different individuals. The impact of the genetic background on the consequences of LoF mutations remains poorly characterized. Here, we systematically assessed the changes in gene deletion phenotypes for 3,786 gene knockouts in four Saccharomyces cerevisiae strains and 38 conditions. We observed 18.5% of deletion phenotypes changing between pairs of strains on average with a small fraction conserved in all four strains. Conditions causing higher wild-type growth differences and the deletion of pleiotropic genes showed above-average changes in phenotypes. In addition, we performed a genome-wide association study (GWAS) for growth under the same conditions for a panel of 925 yeast isolates. Gene-condition associations derived from GWAS were not enriched for genes with deletion phenotypes under the same conditions. However, cases where the results were congruent indicate the most likely mechanism underlying the GWAS signal. Overall, these results show a high degree of genetic background dependencies for LoF phenotypes.

Different Clinical Phenotypes Caused by Three F8 Missense Mutations in Three Chinese Families with Moderate Hemophilia A

In families with a monogenic disorder, the causal mutation usually cosegregates with the disease phenotype. In rare cases, however, individuals carrying the same mutation within a family may show various phenotypes. This study aimed to analyze the discrepancy between genotype and phenotype in three families with moderate hemophilia A (HA) caused by missense mutation in the F8 gene. Among the 67 noninversion moderate HA families in our cohort, incomplete penetrance was found in three families. In these three families, the grandfathers were asymptomatic, whereas the probands had different clinical phenotypes. Apart from one mutation in the VWF gene (c.1330 G>A) found in one grandfather, only one missense mutation (c.5837A>T, c.6679G>A, and c.6506G>A, in the respective families) in the F8 gene was identified in each proband and their grandfathers. Subsequent Sanger sequencing results combined with bioinformatic analysis indicated that the three missense mutations in the F8 gene were the causative mutations. Our study demonstrated incomplete penetrance of missense mutation within HA families in China. Therefore, genetic counseling and management of such cases need to be reappraised.

Dynamic genetic architecture of yeast response to environmental perturbation shed light on origin of cryptic genetic variation

Cryptic genetic variation could arise from, for example, Gene-by-Gene (G-by-G) or Gene-by-Environment (G-by-E) interactions. The underlying molecular mechanisms and how they influence allelic effects and the genetic variance of complex traits is largely unclear. Here, we empirically explored the role of environmentally influenced epistasis on the suppression and release of cryptic variation by reanalysing a dataset of 4,390 haploid yeast segregants phenotyped on 20 different media. The focus was on 130 epistatic loci, each contributing to segregant growth in at least one environment and that together explained most (69–100%) of the narrow sense heritability of growth in the individual environments. We revealed that the epistatic growth network reorganised upon environmental changes to alter the estimated marginal (additive) effects of the individual loci, how multi-locus interactions contributed to individual segregant growth and the level of expressed genetic variance in growth. The estimated additive effects varied most across environments for loci that were highly interactive network hubs in some environments but had few or no interactors in other environments, resulting in changes in total genetic variance across environments. This environmentally dependent epistasis was thus an important mechanism for the suppression and release of cryptic variation in this population. Our findings increase the understanding of the complex genetic mechanisms leading to cryptic variation in populations, providing a basis for future studies on the genetic maintenance of trait robustness and development of genetic models for studying and predicting selection responses for quantitative traits in breeding and evolution.

Many biological traits are polygenic, with complex interplay between underlying genes and the surrounding environment. As a result, individuals with the same allele might have distinctive phenotypes due to differences in the polygenic background and/or the environment. Such differences often create additional genetic variation that is highly relevant to quantitative and evolutionary genetics by limiting our ability to accurately predict the phenotypes in medical or agricultural applications and providing opportunities for long term evolution. Previously, yeast growth regulating genes were found to be organised in large interacting networks. Here, we found that these networks were reorganised upon environmental changes, and that this resulted in altered effect sizes of individual genes, and how the whole network contributed to growth and the level of total genetic variance, providing a basis for future studies on the genetic maintenance of trait robustness and development of genetic models for studying and predicting selection responses for quantitative traits.

Sexual Selection Does Not Increase the Rate of Compensatory Adaptation to a Mutation Influencing a Secondary Sexual Trait in Drosophila melanogaster

Theoretical work predicts that sexual selection can enhance natural selection, increasing the rate of adaptation to new environments and helping purge harmful mutations. While some experiments support these predictions, remarkably little work has addressed the role of sexual selection on compensatory adaptation—populations’ ability to compensate for the costs of deleterious alleles that are already present. We tested whether sexual selection, as well as the degree of standing genetic variation, affect the rate of compensatory evolution via phenotypic suppression in experimental populations of Drosophila melanogaster. These populations were fixed for a spontaneous mutation causing mild abnormalities in the male sex comb, a structure important for mating success. We fine-mapped this mutation to an ∼85 kb region on the X chromosome containing three candidate genes, showed that the mutation is deleterious, and that its phenotypic expression and penetrance vary by genetic background. We then performed experimental evolution, including a treatment where opportunity for mate choice was limited by experimentally enforced monogamy. Although evolved populations did show some phenotypic suppression of the morphological abnormalities in the sex comb, the amount of suppression did not depend on the opportunity for sexual selection. Sexual selection, therefore, may not always enhance natural selection; instead, the interaction between these two forces may depend on additional factors.

Global Genetic Networks and the Genotype-to-Phenotype Relationship

Genetic interactions identify combinations of genetic variants that impinge on phenotype. With whole-genome sequence information available for thousands of individuals within a species, a major outstanding issue concerns the interpretation of allelic combinations of genes underlying inherited traits. In this Review, we discuss how large-scale analyses in model systems have illuminated the general principles and phenotypic impact of genetic interactions. We focus on studies in budding yeast, including the mapping of a global genetic network. We emphasize 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.

The Genetic Background Modulates the Evolution of Fluoroquinolone-Resistance in Mycobacterium tuberculosis

Fluoroquinolones (FQ) form the backbone in experimental treatment regimens against drug-susceptible tuberculosis. However, little is known on whether the genetic variation present in natural populations of Mycobacterium tuberculosis (Mtb) affects the evolution of FQ-resistance (FQ-R). To investigate this question, we used nine genetically distinct drug-susceptible clinical isolates of Mtb and measured their frequency of resistance to the FQ ofloxacin (OFX) in vitro. We found that the Mtb genetic background led to differences in the frequency of OFX-resistance (OFX-R) that spanned two orders of magnitude and substantially modulated the observed mutational profiles for OFX-R. Further, in vitro assays showed that the genetic background also influenced the minimum inhibitory concentration and the fitness effect conferred by a given OFX-R mutation. To test the clinical relevance of our in vitro work, we surveyed the mutational profile for FQ-R in publicly available genomic sequences from clinical Mtb isolates, and found substantial Mtb lineage-dependent variability. Comparison of the clinical and the in vitro mutational profiles for FQ-R showed that 51% and 39% of the variability in the clinical frequency of FQ-R gyrA mutation events in Lineage 2 and Lineage 4 strains, respectively, can be attributed to how Mtb evolves FQ-R in vitro. As the Mtb genetic background strongly influenced the evolution of FQ-R in vitro, we conclude that the genetic background of Mtb also impacts the evolution of FQ-R in the clinic.

Why and how to study genetic changes with context-dependent effects

The phenotypic impacts of a genetic change can depend on genetic background (e.g. epistasis), as well as other contexts including environment, developmental stage, cell type, disease state, and higher-order combinations thereof. Recent advances in high-throughput phenotyping are uncovering examples of context dependence faster than genotype-phenotype maps and other core concepts are changing to reflect the dynamic nature of biological systems. Here, we review several approaches to study context dependence and their findings. In our opinion, these findings encourage more studies that examine the spectrum of effects a genetic change may have, as opposed to studies that exclusively measure the impact of a genetic change in a particular context. Studies that elucidate the mechanisms that cause the effects of genetic change to vary with context are of special interest. Previous studies of the mechanisms underlying context dependence have improved predictions of phenotype from genotype and have provided insight about how biological systems function and evolve.

The Causes and Consequences of Genetic Interactions (Epistasis)

The same mutation can have different effects in different individuals. One important reason for this is that the outcome of a mutation can depend on the genetic context in which it occurs. This dependency is known as epistasis. In recent years, there has been a concerted effort to quantify the extent of pairwise and higher-order genetic interactions between mutations through deep mutagenesis of proteins and RNAs. This research has revealed two major components of epistasis: nonspecific genetic interactions caused by nonlinearities in genotype-to-phenotype maps, and specific interactions between particular mutations. Here, we provide an overview of our current understanding of the mechanisms causing epistasis at the molecular level, the consequences of genetic interactions for evolution and genetic prediction, and the applications of epistasis for understanding biology and determining macromolecular structures.

Mutations in RELT cause autosomal recessive amelogenesis imperfecta

Amelogenesis imperfecta (AI) is a collection of isolated (non-syndromic) inherited diseases affecting dental enamel formation or a clinical phenotype in syndromic conditions. We characterized three consanguineous AI families with generalized irregular hypoplastic enamel with rapid attrition that perfectly segregated with homozygous defects in a novel gene: RELT that is a member of the tumor necrosis factor receptor superfamily (TNFRSF). RNAscope in situ hybridization of wild-type mouse molars and incisors showed specific Relt mRNA expression by secretory stage ameloblasts and by odontoblasts. Relt-/- mice generated by CRISPR/Cas9 exhibited incisor and molar enamel malformations. Relt-/- enamel had a rough surface and underwent rapid attrition. Normally unmineralized spaces in the deep enamel near the dentino-enamel junction (DEJ) were as highly mineralized as the adjacent enamel, which likely altered the mechanical properties of the DEJ. Phylogenetic analyses showed the existence of selective pressure on RELT gene outside of tooth development, indicating that the human condition may be syndromic, which possibly explains the history of small stature and severe childhood infections in two of the probands. Knowing a TNFRSF member is critical during the secretory stage of enamel formation advances our understanding of amelogenesis and improves our ability to diagnose human conditions featuring enamel malformations.

Complex modifier landscape underlying genetic background effects

Genetic background impacts the phenotypic outcome of a mutation in different individuals; however, the underlying molecular mechanisms are often unclear. We characterized genes exhibiting conditional essentiality when mutated in two genetically distinct yeast strains. Hybrid crosses and whole-genome sequencing revealed that conditional essentiality can be associated with nonchromosomal elements or a single-modifier locus, but most involve a complex set of modifier loci. Detailed analysis of the cysteine biosynthesis pathway showed that independent, rare, single-gene modifiers, related to both up- and downstream pathway functions, can arise in multiple allelic forms from separate lineages. For several genes, we also resolved complex sets of modifying loci underlying conditional essentiality, revealing specific genetic interactions that drive an individual strain’s background effect.

The phenotypic consequence of a given mutation can be influenced by the genetic background. For example, conditional gene essentiality occurs when the loss of function of a gene causes lethality in one genetic background but not another. Between two individual Saccharomyces cerevisiae strains, S288c and Σ1278b, ∼1% of yeast genes were previously identified as “conditional essential.” Here, in addition to confirming that some conditional essential genes are modified by a nonchromosomal element, we show that most cases involve a complex set of genomic modifiers. From tetrad analysis of S288C/Σ1278b hybrid strains and whole-genome sequencing of viable hybrid spore progeny, we identified complex sets of multiple genomic regions underlying conditional essentiality. For a smaller subset of genes, including CYS3 and CYS4, each of which encodes components of the cysteine biosynthesis pathway, we observed a segregation pattern consistent with a single modifier associated with conditional essentiality. In natural yeast isolates, we found that the CYS3/CYS4 conditional essentiality can be caused by variation in two independent modifiers, MET1 and OPT1, each with roles associated with cellular cysteine physiology. Interestingly, the OPT1 allelic variation appears to have arisen independently from separate lineages, with rare allele frequencies below 0.5%. Thus, while conditional gene essentiality is usually driven by genetic interactions associated with complex modifier architectures, our analysis also highlights the role of functionally related, genetically independent, and rare variants.

Layers of Cryptic Genetic Variation Underlie a Yeast Complex Trait

To better understand cryptic genetic variation, Lee et al. comprehensively map the genetic basis of a trait that is typically suppressed in a yeast cross. By determining how three different genetic perturbations give rise...

Cryptic genetic variation may be an important contributor to heritable traits, but its extent and regulation are not fully understood. Here, we investigate the cryptic genetic variation underlying a Saccharomyces cerevisiae colony phenotype that is typically suppressed in a cross of the laboratory strain BY4716 (BY) and a derivative of the clinical isolate 322134S (3S). To do this, we comprehensively dissect the trait’s genetic basis in the BYx3S cross in the presence of three different genetic perturbations that enable its expression. This allows us to detect and compare the specific loci that interact with each perturbation to produce the trait. In total, we identify 21 loci, all but one of which interact with just a subset of the perturbations. Beyond impacting which loci contribute to the trait, the genetic perturbations also alter the extent of additivity, epistasis, and genotype–environment interaction among the detected loci. Additionally, we show that the single locus interacting with all three perturbations corresponds to the coding region of the cell surface gene FLO11. While nearly all of the other remaining loci influence FLO11 transcription in cis or trans, the perturbations tend to interact with loci in different pathways and subpathways. Our work shows how layers of cryptic genetic variation can influence complex traits. Here, these layers mainly represent different regulatory inputs into the transcription of a single key gene.