How well do you know your mutation? Complex effects of genetic background on expressivity, complementation, and ordering of allelic 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.

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.

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.

Dominance and multi-locus interaction

Dominance is usually considered a constant value that describes the relative difference in fitness or phenotype between heterozygotes and the average of homozygotes at a focal polymorphic locus. However, the observed dominance can vary with the genetic background of the focal locus. Here, alleles at other loci modify the observed phenotype through position effects or dominance modifiers that are sometimes associated with pathogen resistance, lineage, sex, or mating type. Theoretical models have illustrated how variable dominance appears in the context of multi-locus interaction (epistasis). Here, we review empirical evidence for variable dominance and how the observed patterns may be captured by proposed epistatic models. We highlight how integrating epistasis and dominance is crucial for comprehensively understanding adaptation and speciation.

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 association in Drosophila identifies a role for Piezo and Proc-R in sleep latency

Sleep latency, the amount of time that it takes an individual to fall asleep, is a key indicator of sleep need. Sleep latency varies considerably both among and within species and is heritable, but lacks a comprehensive description of its underlying genetic network. Here we conduct a genome-wide association study of sleep latency. Using previously collected sleep and activity data on a wild-derived population of flies, we calculate sleep latency, confirming significant, heritable genetic variation for this complex trait. We identify 520 polymorphisms in 248 genes contributing to variability in sleep latency. Tests of mutations in 23 candidate genes and additional putative pan-neuronal knockdown of 9 of them implicated CG44153, Piezo, Proc-R and Rbp6 in sleep latency. Two large-effect mutations in the genes Proc-R and Piezo were further confirmed via genetic rescue. This work greatly enhances our understanding of the genetic factors that influence variation in sleep latency.

Higher-order epistasis shapes natural variation in germ stem cell niche activity

To study how natural allelic variation explains quantitative developmental system variation, we characterized natural differences in germ stem cell niche activity, measured as progenitor zone (PZ) size, between two Caenorhabditis elegans isolates. Linkage mapping yielded candidate loci on chromosomes II and V, and we found that the isolate with a smaller PZ size harbours a 148 bp promoter deletion in the Notch ligand, lag-2/Delta, a central signal promoting germ stem cell fate. As predicted, introducing this deletion into the isolate with a large PZ resulted in a smaller PZ size. Unexpectedly, restoring the deleted ancestral sequence in the isolate with a smaller PZ did not increase-but instead further reduced-PZ size. These seemingly contradictory phenotypic effects are explained by epistatic interactions between the lag-2/Delta promoter, the chromosome II locus, and additional background loci. These results provide first insights into the quantitative genetic architecture regulating an animal stem cell system.

The genetic basis of adaptation to copper pollution in Drosophila melanogaster

Introduction: Heavy metal pollutants can have long lasting negative impacts on ecosystem health and can shape the evolution of species. The persistent and ubiquitous nature of heavy metal pollution provides an opportunity to characterize the genetic mechanisms that contribute to metal resistance in natural populations. Methods: We examined variation in resistance to copper, a common heavy metal contaminant, using wild collections of the model organism Drosophila melanogaster. Flies were collected from multiple sites that varied in copper contamination risk. We characterized phenotypic variation in copper resistance within and among populations using bulked segregant analysis to identify regions of the genome that contribute to copper resistance. Results and Discussion: Copper resistance varied among wild populations with a clear correspondence between resistance level and historical exposure to copper. We identified 288 SNPs distributed across the genome associated with copper resistance. Many SNPs had population-specific effects, but some had consistent effects on copper resistance in all populations. Significant SNPs map to several novel candidate genes involved in refolding disrupted proteins, energy production, and mitochondrial function. We also identified one SNP with consistent effects on copper resistance in all populations near CG11825, a gene involved in copper homeostasis and copper resistance. We compared the genetic signatures of copper resistance in the wild-derived populations to genetic control of copper resistance in the Drosophila Synthetic Population Resource (DSPR) and the Drosophila Genetic Reference Panel (DGRP), two copper-naïve laboratory populations. In addition to CG11825, which was identified as a candidate gene in the wild-derived populations and previously in the DSPR, there was modest overlap of copper-associated SNPs between the wild-derived populations and laboratory populations. Thirty-one SNPs associated with copper resistance in wild-derived populations fell within regions of the genome that were associated with copper resistance in the DSPR in a prior study. Collectively, our results demonstrate that the genetic control of copper resistance is highly polygenic, and that several loci can be clearly linked to genes involved in heavy metal toxicity response. The mixture of parallel and population-specific SNPs points to a complex interplay between genetic background and the selection regime that modifies the effects of genetic variation on copper resistance.

Genomic selection and genome-wide association studies in tetraploid chipping potatoes

Potato is a major food crop in the United States and around the world. Most potatoes grown in the United States are destined for processing. Genomic selection can speed up breeding progress for important traits, including those with complex inheritance by guiding the identification of the best parents and guiding selection to advance clones in the breeding program. However, the application of genomic selection in polyploid species has been challenging. In this study, we obtained breeding values of 384 chipping clones evaluated in Texas between 2017 and 2020. The mean reliability of the genomic-estimated breeding values obtained were 0.77, 0.41, 0.61, 0.71, and 0.24 for chip color, chip quality, specific gravity, vine maturity, and total yield, respectively. Potato clones with good chip quality, high yield, high specific gravity, and light-color chips were identified using a multi-trait selection index based on weighted standardized genomic-estimated breeding values. Genome-wide association studies identified quantitative trait loci on chromosome 5 for vine maturity and chromosomes 1, 3, and 7 for chip color. This research has laid the groundwork for implementing genomic selection in tetraploid potato breeding and understanding the genetic basis of chip processing traits in potatoes.

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.

Genetic basis of a spontaneous mutation’s expressivity

Genetic background often influences the phenotypic consequences of mutations, resulting in variable expressivity. How standing genetic variants collectively cause this phenomenon is not fully understood. Here, we comprehensively identify loci in a budding yeast cross that impact the growth of individuals carrying a spontaneous missense mutation in the nuclear-encoded mitochondrial ribosomal gene MRP20. Initial results suggested that a single large effect locus influences the mutation’s expressivity, with one allele causing inviability in mutants. However, further experiments revealed this simplicity was an illusion. In fact, many additional loci shape the mutation’s expressivity, collectively leading to a wide spectrum of mutational responses. These results exemplify how complex combinations of alleles can produce a diversity of qualitative and quantitative responses to the same mutation.

Cryptic genetic variation in a heat shock protein modifies the outcome of a mutation affecting epidermal stem cell development in C. elegans

A fundamental question in medical genetics is how the genetic background modifies the phenotypic outcome of mutations. We address this question by focusing on the seam cells, which display stem cell properties in the epidermis of Caenorhabditis elegans. We demonstrate that a putative null mutation in the GATA transcription factor egl-18, which is involved in seam cell fate maintenance, is more tolerated in the CB4856 isolate from Hawaii than the lab reference strain N2 from Bristol. We identify multiple quantitative trait loci (QTLs) underlying the difference in phenotype expressivity between the two isolates. These QTLs reveal cryptic genetic variation that reinforces seam cell fate through potentiating Wnt signalling. Within one QTL region, a single amino acid deletion in the heat shock protein HSP-110 in CB4856 is sufficient to modify Wnt signalling and seam cell development, highlighting that natural variation in conserved heat shock proteins can shape phenotype expressivity.

How the genetic background modifies the expression of mutations is a key question that is addressed in this study in the context of seam cell development in Caenorhabditis elegans isolates. One amino acid deletion in a conserved heat shock protein is sufficient to shape phenotype expressivity upon mutation of a GATA transcription factor.

Hierarchical Modelling of Haplotype Effects on a Phylogeny

We introduce a hierarchical model to estimate haplotype effects based on phylogenetic relationships between haplotypes and their association with observed phenotypes. In a population there are many, but not all possible, distinct haplotypes and few observations per haplotype. Further, haplotype frequencies tend to vary substantially. Such data structure challenge estimation of haplotype effects. However, haplotypes often differ only due to few mutations, and leveraging similarities can improve the estimation of effects. We build on extensive literature and develop an autoregressive model of order one that models haplotype effects by leveraging phylogenetic relationships described with a directed acyclic graph. The phylogenetic relationships can be either in a form of a tree or a network, and we refer to the model as the haplotype network model. The model can be included as a component in a phenotype model to estimate associations between haplotypes and phenotypes. Our key contribution is that we obtain a sparse model, and by using hierarchical autoregression, the flow of information between similar haplotypes is estimated from the data. A simulation study shows that the hierarchical model can improve estimates of haplotype effects compared to an independent haplotype model, especially with few observations for a specific haplotype. We also compared it to a mutation model and observed comparable performance, though the haplotype model has the potential to capture background specific effects. We demonstrate the model with a study of mitochondrial haplotype effects on milk yield in cattle. We provide R code to fit the model with the INLA package.

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.

Identification of Genes Contributing to a Long Circadian Period in Drosophila Melanogaster

The endogenous circadian period of animals and humans is typically very close to 24 h. Individuals with much longer circadian periods have been observed, however, and in the case of humans, these deviations have health implications. Previously, we observed a line of Drosophila with a very long average period of 31.3 h for locomotor activity behavior. Preliminary mapping indicated that the long period did not map to known canonical clock genes but instead mapped to multiple chromosomes. Using RNA-Seq, we surveyed the whole transcriptome of fly heads from this line across time and compared it with a wild-type control. A three-way generalized linear model revealed that approximately two-thirds of the genes were expressed differentially among the two genotypes, while only one quarter of the genes varied across time. Using these results, we applied algorithms to search for genes that oscillated over 24 h, identifying genes not previously known to cycle. We identified 166 differentially expressed genes that overlapped with a previous Genome-wide Association Study (GWAS) of circadian behavior, strongly implicating them in the long-period phenotype. We tested mutations in 45 of these genes for their effect on the circadian period. Mutations in Alk, alph, CG10089, CG42540, CG6034, Kairos (CG6123), CG8768, klg, Lar, sick, and tinc had significant effects on the circadian period, with seven of these mutations increasing the circadian period of locomotor activity behavior. Genetic rescue of mutant Kairos restored the circadian period to wild-type levels, suggesting it has a critical role in determining period length in constant darkness.

Marker Selection in Multivariate Genomic Prediction Improves Accuracy of Low Heritability Traits

Multivariate analysis using mixed models allows for the exploration of genetic correlations between traits. Additionally, the transition to a genomic based approach is simplified by substituting classic pedigrees with a marker-based relationship matrix. It also enables the investigation of correlated responses to selection, trait integration and modularity in different kinds of populations. This study investigated a strategy for the construction of a marker-based relationship matrix that prioritized markers using Partial Least Squares. The efficiency of this strategy was found to depend on the correlation structure between investigated traits. In terms of accuracy, we found no benefit of this strategy compared with the all-marker-based multivariate model for the primary trait of diameter at breast height (DBH) in a radiata pine (Pinus radiata) population, possibly due to the presence of strong and well-estimated correlation with other highly heritable traits. Conversely, we did see benefit in a shining gum (Eucalyptus nitens) population, where the primary trait had low or only moderate genetic correlation with other low/moderately heritable traits. Marker selection in multivariate analysis can therefore be an efficient strategy to improve prediction accuracy for low heritability traits due to improved precision in poorly estimated low/moderate genetic correlations. Additionally, our study identified the genetic diversity as a factor contributing to the efficiency of marker selection in multivariate approaches due to higher precision of genetic correlation estimates.

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.

Drosophila R8 photoreceptor cell subtype specification requires hibris

Cell differentiation and cell fate determination in sensory systems are essential for stimulus discrimination and coding of environmental stimuli. Color vision is based on the differential color sensitivity of retinal photoreceptors, however the developmental programs that control photoreceptor cell differentiation and specify color sensitivity are poorly understood. In Drosophila melanogaster, there is evidence that the color sensitivity of different photoreceptors in the compound eye is regulated by inductive signals between cells, but the exact nature of these signals and how they are propagated remains unknown. We conducted a genetic screen to identify additional regulators of this process and identified a novel mutation in the hibris gene, which encodes an irre cell recognition module protein (IRM). These immunoglobulin super family cell adhesion molecules include human KIRREL and nephrin (NPHS1). hibris is expressed dynamically in the developing Drosophila melanogaster eye and loss-of-function mutations give rise to a diverse range of mutant phenotypes including disruption of the specification of R8 photoreceptor cell diversity. We demonstrate that hibris is required within the retina, and that hibris over-expression is sufficient to disrupt normal photoreceptor cell patterning. These findings suggest an additional layer of complexity in the signaling process that produces paired expression of opsin genes in adjacent R7 and R8 photoreceptor cells.

Canalization and Robustness in Human Genetics and Disease

Canalization refers to the evolution of populations such that the number of individuals who deviate from the optimum trait, or experience disease, is minimized. In the presence of rapid cultural, environmental, or genetic change, the reverse process of decanalization may contribute to observed increases in disease prevalence. This review starts by defining relevant concepts, drawing distinctions between the canalization of populations and robustness of individuals. It then considers evidence pertaining to three continuous traits and six domains of disease. In each case, existing genetic evidence for genotype-by-environment interactions is insufficient to support a strong inference of decanalization, but we argue that the advent of genome-wide polygenic risk assessment now makes an empirical evaluation of the role of canalization in preventing disease possible. Finally, the contributions of both rare and common variants to congenital abnormality and adult onset disease are considered in light of a new kerplunk model of genetic effects.

UDP-GLYCOSYLTRANSFERASE 72E3 Plays a Role in Lignification of Secondary Cell Walls in Arabidopsis

Lignin is present in plant secondary cell walls and is among the most abundant biological polymers on Earth. In this work we investigated the potential role of the UGT72E gene family in regulating lignification in Arabidopsis. Chemical determination of floral stem lignin contents in ugt72e1, ugt72e2, and ugt72e3 mutants revealed no significant differences compared to WT plants. In contrast, the use of a novel safranin O ratiometric imaging technique indicated a significant increase in the cell wall lignin content of both interfascicular fibers and xylem from young regions of ugt72e3 mutant floral stems. These results were globally confirmed in interfascicular fibers by Raman microspectroscopy. Subsequent investigation using a bioorthogonal triple labelling strategy suggested that the augmentation in lignification was associated with an increased capacity of mutant cell walls to incorporate H-, G-, and S-monolignol reporters. Expression analysis showed that this increase was associated with an up-regulation of LAC17 and PRX71, which play a key role in lignin polymerization. Altogether, these results suggest that UGT72E3 can influence the kinetics of lignin deposition by regulating monolignol flow to the cell wall as well as the potential of this compartment to incorporate monomers into the growing lignin polymer.

Decoupling gene functions from knockout effects by evolutionary analyses

Genic functions have long been confounded by pleiotropic mutational effects. To understand such genetic effects, we examine HAP4, a well-studied transcription factor in Saccharomyces cerevisiae that functions by forming a tetramer with HAP2, HAP3 and HAP5. Deletion of HAP4 results in highly pleiotropic gene expression responses, some of which are clustered in related cellular processes (clustered effects) while most are distributed randomly across diverse cellular processes (distributed effects). Strikingly, the distributed effects that account for much of HAP4 pleiotropy tend to be non-heritable in a population, suggesting they have few evolutionary consequences. Indeed, these effects are poorly conserved in closely related yeasts. We further show substantial overlaps of clustered effects, but not distributed effects, among the four genes encoding the HAP2/3/4/5 tetramer. This pattern holds for other biochemically characterized yeast protein complexes or metabolic pathways. Examination of a set of cell morphological traits of the deletion lines yields consistent results. Hence, only some deletion effects of a gene support related biochemical understandings with the rest being often pleiotropic and evolutionarily decoupled from the gene's normal functions. This study suggests a new framework for reverse genetic analysis.

Genetic and environmental canalization are not associated among altitudinally varying populations of Drosophila melanogaster

Organisms are exposed to environmental and mutational effects influencing both mean and variance of phenotypes. Potentially deleterious effects arising from this variation can be reduced by the evolution of buffering (canalizing) mechanisms, ultimately reducing phenotypic variability. There has been interest regarding the conditions enabling the evolution of canalization. Under some models, the circumstances under which genetic canalization evolves are limited despite apparent empirical evidence for it. It has been argued that genetic canalization evolves as a correlated response to environmental canalization (congruence model). Yet, empirical evidence has not consistently supported predictions of a correlation between genetic and environmental canalization. In a recent study, a population of Drosophila adapted to high altitude showed evidence of genetic decanalization relative to those from low altitudes. Using strains derived from these populations, we tested if they varied for multiple aspects of environmental canalization We observed the expected differences in wing size, shape, cell (trichome) density and mutational defects between high- and low-altitude populations. However, we observed little evidence for a relationship between measures of environmental canalization with population or with defect frequency. Our results do not support the predicted association between genetic and environmental canalization.

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.

Chromosomal Substitution Strategies to Localize Genomic Regions Related to Complex Traits

Chromosomal substitution strategies provide a powerful tool to anonymously reveal the relationship between DNA sequence variants and a normal or disease phenotype of interest. Even in this age of CRISPR-Cas9 genome engineering, the knockdown or overexpression of a gene provides relevant information to our understanding of complex disease only when a close association of an allelic variant with the phenotype has first been established. Limitations of genetic linkage approaches led to the development of more efficient breeding strategies to substitute chromosomal segments from one animal strain into the genetic background of a different strain, enabling a direct comparison of the phenotypes of the strains with variant(s) that differ only at a defined locus. This substitution can be a whole chromosome (consomic), a part of a chromosome (congenic), or as small as only a single or several alleles (subcongenics). In contrast to complete knockout of a specific candidate gene of interest, which simply studies the effects of complete elimination of the gene, the substitution of naturally occurring variants can provide special insights into the functional actions of wild-type alleles. Strategies for production of these inbred strains are reviewed, and a number of examples are used to illustrate the utility of these model systems. Consomic/congenic strains provide a number of experimental advantages in the study of functions of genes and their variants, which are emphasized in this article, such as replication of experimental studies; determination of temporal relationships throughout a life; rigorously controlled experiments in which relations between genotype and phenotype can be tested with the confounding effects of heterogeneous genetic backgrounds, both targeted and multilayered; and "omic" studies performed at many levels of functionality, from molecules to organelles, cells to organs, and organs to organismal behavior across the life span. The application of chromosomal substitution strategies and development of consomic/congenic rat and mouse strains have greatly expanded our knowledge of genomic variants and their phenotypic relationship to physiological functions and to complex diseases such as hypertension and cancer. © 2020 American Physiological Society. Compr Physiol 10:365-388, 2020.

Addressing variability in iPSC-derived models of human disease: guidelines to promote reproducibility

Induced pluripotent stem cell (iPSC) technologies have provided in vitro models of inaccessible human cell types, yielding new insights into disease mechanisms especially for neurological disorders. However, without due consideration, the thousands of new human iPSC lines generated in the past decade will inevitably affect the reproducibility of iPSC-based experiments. Differences between donor individuals, genetic stability and experimental variability contribute to iPSC model variation by impacting differentiation potency, cellular heterogeneity, morphology, and transcript and protein abundance. Such effects will confound reproducible disease modelling in the absence of appropriate strategies. In this Review, we explore the causes and effects of iPSC heterogeneity, and propose approaches to detect and account for experimental variation between studies, or even exploit it for deeper biological insight.

Micro-computed tomography as a platform for exploring Drosophila development

Understanding how events at the molecular and cellular scales contribute to tissue form and function is key to uncovering the mechanisms driving animal development, physiology and disease. Elucidating these mechanisms has been enhanced through the study of model organisms and the use of sophisticated genetic, biochemical and imaging tools. Here, we present an accessible method for non-invasive imaging of Drosophila melanogaster at high resolution using micro-computed tomography (µ-CT). We show how rapid processing of intact animals, at any developmental stage, provides precise quantitative assessment of tissue size and morphology, and permits analysis of inter-organ relationships. We then use µ-CT imaging to study growth defects in the Drosophila brain through the characterization of a bnormal spindle (asp) and WD repeat domain 62 (W dr62), orthologs of the two most commonly mutated genes in human microcephaly patients. Our work demonstrates the power of combining µ-CT with traditional genetic, cellular and developmental biology tools available in model organisms to address novel biological mechanisms that control animal development and disease.

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.

Effects of stable ectopic expression of the primary sex determination gene Yob in the mosquito Anopheles gambiae

BACKGROUND

Mosquito-borne diseases, such as malaria, are controlled primarily by suppressing mosquito vector populations using insecticides. The current control programmes are seriously threatened by the emergence and rapid spread of resistance to approved insecticides. Genetic approaches proposed to complement the existing control efforts may be a more sustainable solution to mosquito control. All such approaches would rely on releases of modified male mosquitoes, because released females would contribute to biting and pathogen transmission. However, no sufficiently large-scale methods for sex separation in mosquitoes exist.

RESULTS

Here we exploited the female embryo-killing property of the sex determining gene Yob from the African malaria mosquito, Anopheles gambiae, to evaluate the feasibility of creating transgenic An. gambiae sexing strains with a male-only phenotype. We generated An. gambiae lines with Yob expression, in both sexes, controlled by the vas2 promoter. Penetrance of the female-lethal phenotype was highly dependent on the location of the transgenic construct within the genome. A strong male bias was observed in one of the lines. All the females that survived to adulthood in that line possessed masculinized head appendages and terminal abdominal segments. They did not feed on blood, lacked host-seeking behavior, and thus were effectively sterile. Males, however, were not affected by Yob overexpression.

CONCLUSIONS

Our study demonstrates that ectopic expression of Yob results in a recovery of viable, fertile males, and in death, or otherwise strongly deleterious effects, in females. This result shows potential for generation of transgenic sexing strains of Anopheles gambiae with a conditional male-only phenotype.

Analysis of Epistasis in Natural Traits Using Model Organisms

The ability to detect and understand epistasis in natural populations is important for understanding how biological traits are influenced by genetic variation. However, identification and characterization of epistasis in natural populations remains difficult due to statistical issues that arise as a result of multiple comparisons, and the fact that most genetic variants segregate at low allele frequencies. In this review, we discuss how model organisms may be used to manipulate genotypic combinations to power the detection of epistasis as well as test interactions between specific genes. Findings from a number of species indicate that statistical epistasis is pervasive between natural genetic variants. However, the properties of experimental systems that enable analysis of epistasis also constrain extrapolation of these results back into natural populations.

Genome-Wide Association Study of Circadian Behavior in Drosophila melanogaster

Circadian rhythms influence physiological processes from sleep–wake cycles to body temperature and are controlled by highly conserved cycling molecules. Although the mechanistic basis of the circadian clock has been known for decades, the extent to which circadian rhythms vary in nature and the underlying genetic basis for that variation is not well understood. We measured circadian period (Ʈ) and rhythmicity index in the Drosophila Genetic Reference Panel (DGRP) and observed extensive genetic variation in both. Seven DGRP lines had sexually dimorphic arrhythmicity and one line had an exceptionally long Ʈ. Genome-wide analyses identified 584 polymorphisms in 268 genes. We observed differences among transcripts for nine genes predicted to interact among themselves and canonical clock genes in the long period line and a control. Mutations/RNAi knockdown targeting these genes also affected circadian behavior. Our observations reveal that complex genetic interactions influence high levels of variation in circadian phenotypes.

Role of the Genetic Background in Resistance to Plant Viruses

In view of major economic problems caused by viruses, the development of genetically resistant crops is critical for breeders but remains limited by the evolution of resistance-breaking virus mutants. During the plant breeding process, the introgression of traits from Crop Wild Relatives results in a dramatic change of the genetic background that can alter the resistance efficiency or durability. Here, we conducted a meta-analysis on 19 Quantitative Trait Locus (QTL) studies of resistance to viruses in plants. Frequent epistatic effects between resistance genes indicate that a large part of the resistance phenotype, conferred by a given QTL, depends on the genetic background. We next reviewed the different resistance mechanisms in plants to survey at which stage the genetic background could impact resistance or durability. We propose that the genetic background may impair effector-triggered dominant resistances at several stages by tinkering the NB-LRR (Nucleotide Binding-Leucine-Rich Repeats) response pathway. In contrast, effects on recessive resistances by loss-of-susceptibility-such as eIF4E-based resistances-are more likely to rely on gene redundancy among the multigene family of host susceptibility factors. Finally, we show how the genetic background is likely to shape the evolution of resistance-breaking isolates and propose how to take this into account in order to breed plants with increased resistance durability to viruses.

The complex underpinnings of genetic background effects

Genetic interactions between mutations and standing polymorphisms can cause mutations to show distinct phenotypic effects in different individuals. To characterize the genetic architecture of these so-called background effects, we genotype 1411 wild-type and mutant yeast cross progeny and measure their growth in 10 environments. Using these data, we map 1086 interactions between segregating loci and 7 different gene knockouts. Each knockout exhibits between 73 and 543 interactions, with 89% of all interactions involving higher-order epistasis between a knockout and multiple loci. Identified loci interact with as few as one knockout and as many as all seven knockouts. In mutants, loci interacting with fewer and more knockouts tend to show enhanced and reduced phenotypic effects, respectively. Cross–environment analysis reveals that most interactions between the knockouts and segregating loci also involve the environment. These results illustrate the complicated interactions between mutations, standing polymorphisms, and the environment that cause background effects.

Mutations often show distinct phenotypic effects across different genetic backgrounds. Here the authors describe the genetic basis of these so-called background effects using data on genotype and growth in 10 environments from 1411 segregants from a cross of two strains of budding yeast.

The Sleep Inbred Panel, a Collection of Inbred Drosophila melanogaster with Extreme Long and Short Sleep Duration

Understanding how genomic variation causes differences in observable phenotypes remains a major challenge in biology. It is difficult to trace the sequence of events originating from genomic variants to changes in transcriptional responses or protein modifications. Ideally, one would conduct experiments with individuals that are at either extreme of the trait of interest, but such resources are often not available. Further, advances in genome editing will enable testing of candidate polymorphisms individually and in combination. Here we have created a resource for the study of sleep with 39 inbred lines of Drosophila-the Sleep Inbred Panel (SIP). SIP lines have stable long- and short-sleeping phenotypes developed from naturally occurring polymorphisms. These lines are fully sequenced, enabling more accurate targeting for genome editing and transgenic constructs. This panel facilitates the study of intermediate transcriptional and proteomic correlates of sleep, and supports genome editing studies to verify polymorphisms associated with sleep duration.

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.

Linkage mapping of yeast cross protection connects gene expression variation to a higher-order organismal trait

Gene expression variation is extensive in nature, and is hypothesized to play a major role in shaping phenotypic diversity. However, connecting differences in gene expression across individuals to higher-order organismal traits is not trivial. In many cases, gene expression variation may be evolutionarily neutral, and in other cases expression variation may only affect phenotype under specific conditions. To understand connections between gene expression variation and stress defense phenotypes, we have been leveraging extensive natural variation in the gene expression response to acute ethanol in laboratory and wild Saccharomyces cerevisiae strains. Previous work found that the genetic architecture underlying these expression differences included dozens of “hotspot” loci that affected many transcripts in trans. In the present study, we provide new evidence that one of these expression QTL hotspot loci affects natural variation in one particular stress defense phenotype—ethanol-induced cross protection against severe doses of H₂O₂. A major causative polymorphism is in the heme-activated transcription factor Hap1p, which we show directly impacts cross protection, but not the basal H₂O₂ resistance of unstressed cells. This provides further support that distinct cellular mechanisms underlie basal and acquired stress resistance. We also show that Hap1p-dependent cross protection relies on novel regulation of cytosolic catalase T (Ctt1p) during ethanol stress in a wild oak strain. Because ethanol accumulation precedes aerobic respiration and accompanying reactive oxygen species formation, wild strains with the ability to anticipate impending oxidative stress would likely be at an advantage. This study highlights how strategically chosen traits that better correlate with gene expression changes can improve our power to identify novel connections between gene expression variation and higher-order organismal phenotypes.

A major goal in genetics is to understand how individuals with different genetic makeups respond to their environment. Understanding these “gene-environment interactions” is important for the development of personalized medicine. For example, gene-environment interactions can explain why some people are more sensitive to certain drugs or are more likely to get certain cancers. While the underlying causes of gene-environment interactions are unclear, one possibility is that differences in gene expression across individuals are responsible. In this study, we examined that possibility using baker’s yeast as a model. We were interested in a phenomenon called acquired stress resistance, where cells exposed to a mild dose of one stress can become resistant to an otherwise lethal dose of severe stress. This response is observed in diverse organisms ranging from bacteria to humans, though the specific mechanisms governing acquisition of higher stress resistance are poorly understood. To understand the differences between yeast strains with and without the ability to acquire further stress resistance, we employed genetic mapping. We found that part of the variation in acquired stress resistance was due to sequence differences in a key regulatory protein, thus providing new insight into how different individuals respond to acute environmental change.

Complex genetic interactions of novel Suppressor of Hairless alleles deficient in co-repressor binding

Throughout the animal kingdom, the Notch signalling pathway allows cells to acquire diversified cell fates. Notch signals are translated into activation of Notch target genes by CSL transcription factors. In the absence of Notch signals, CSL together with co-repressors functions as a transcriptional repressor. In Drosophila, repression of Notch target genes involves the CSL homologue Suppressor of Hairless (Su(H)) and the Notch (N) antagonist Hairless (H) that together form a repressor complex. Guided by crystal structure, three mutations Su(H)LL, Su(H)LLF and Su(H)LLL were generated that specifically affect interactions with the repressor H, and were introduced into the endogenous Su(H) locus by gene engineering. In contrast to the wild type isoform, these Su(H) mutants are incapable of repressor complex formation. Accordingly, Notch signalling activity is dramatically elevated in the homozygotes, resembling complete absence of H activity. It was noted, however, that heterozygotes do not display a dominant H loss of function phenotype. In this work we addressed genetic interactions the three H-binding deficient Su(H) mutants display in combination with H and N null alleles. We included a null mutant of Delta (Dl), encoding the ligand of the Notch receptor, as well as of Su(H) itself in our genetic analyses. H, N or Dl mutations cause dominant wing phenotypes that are sensitive to gene dose of the others. Moreover, H heterozygotes lack bristle organs and develop bristle sockets instead of shafts. The latter phenotype is suppressed by Su(H) null alleles but not by H-binding deficient Su(H) alleles which we attribute to the socket cell specific activity of Su(H). Modification of the dominant wing phenotypes of either H, N or Dl, however, suggested some lack of repressor activity in the Su(H) null allele and likewise in the H-binding deficient Su(H) alleles. Overall, Su(H) mutants are recessive perhaps reflecting self-adjusting availability of Su(H) protein.