On the definition and measurement of pleiotropy

Trade-off between local replication and long-distance dissemination during experimental evolution of a satellite RNA

Satellite RNAs (satRNAs) are molecular parasites that depend on their non-homologous helper viruses (HVs) for essential biological functions. While there are multiple molecular and phylogenetic studies on satRNAs, there is no experimental evolution study on how satRNAs may evolve in common infection conditions. In this study, we serially passaged the Bamboo mosaic virus (BaMV) associated-satRNA (satBaMV) under conditions in which satBaMV either coinfects an uninfected host plant, Nicotiana benthamiana, with BaMV or superinfects a transgenic N. benthamiana expressing the full-length BaMV genome. Single-nucleotide polymorphisms (SNPs) of satBaMV populations were analyzed by deep sequencing. Forty-eight SNPs were identified across four different experimental treatments. Most SNPs are treatment-specific, and some are also ephemeral. However, mutations at positions 30, 34, 63, and 82, all located at the 5' untranslated region (UTR), are universal in all treatments. These universal SNPs are configured into several haplotypes and follow different population dynamics. We constructed isogenic satBaMV strains only differing at positions 30 and 82 and conducted competition experiments in protoplasts and host plants. We found that the haplotype that reached high frequency in protoplasts and inoculation leaves also exhibited poor dissemination to systemic leaves and vice versa, thus suggesting an apparent trade-off between local replication and long-distance dissemination. We posit that the trade-off is likely caused by antagonistic pleiotropy at the 5' UTR. Our findings revealed a hitherto under-explored connection between satRNA genome replication and movement within a host plant. The significance of such a connection during satRNA evolution warrants a more thorough investigation.

Network Topology Can Explain Differences in Pleiotropy Between Cis- and Trans-regulatory Mutations

A mutation's degree of pleiotropy (i.e., the number of traits it alters) is predicted to impact the probability of the mutation being detrimental to fitness. For mutations that impact gene expression, mutations acting in cis have been hypothesized to generally be less pleiotropic than mutations affecting the same gene's expression in trans, suggesting that cis-regulatory mutations should be less deleterious and more likely to fix over evolutionary time. Here, we use expression and fitness data from Saccharomyces cerevisiae gene deletion strains to test these hypotheses. By treating deletion of each gene as a cis-regulatory mutation affecting its own expression and deletions of other genes affecting expression of this focal gene as trans-regulatory mutations, we find that cis-acting mutations do indeed tend to be less pleiotropic than trans-acting mutations affecting expression of the same gene. This pattern was observed for the vast majority of genes in the data set and could be explained by the topology of the regulatory network controlling gene expression. Comparing the fitness of cis- and trans-acting mutations affecting expression of the same gene also confirmed that trans-acting deletions tend to be more deleterious. These findings provide strong support for pleiotropy playing a role in the preferential fixation of cis-regulatory alleles over evolutionary time.

Pleiotropic effects of trans-regulatory mutations on fitness and gene expression

Variation in gene expression arises from cis- and trans-regulatory mutations, which contribute differentially to expression divergence. We compare the impacts on gene expression and fitness resulting from cis- and trans-regulatory mutations in Saccharomyces cerevisiae, with a focus on the TDH3 gene. We use the effects of cis-regulatory mutations to infer effects of trans-regulatory mutations attributable to impacts beyond the focal gene, revealing a distribution of pleiotropic effects. Cis- and trans-regulatory mutations had different effects on gene expression with pleiotropic effects of trans-regulatory mutants affecting expression of genes both in parallel to and downstream of the focal gene. The more widespread and deleterious effects of trans-regulatory mutations we observed are consistent with their decreasing relative contribution to expression differences over evolutionary time.

Total genetic contribution assessment across the human genome

Quantifying the overall magnitude of every single locus' genetic effect on the widely measured human phenome is of great challenge. We introduce a unified modelling technique that can consistently provide a total genetic contribution assessment (TGCA) of a gene or genetic variant without thresholding genetic association signals. Genome-wide TGCA in five UK Biobank phenotype domains highlights loci such as the HLA locus for medical conditions, the bone mineral density locus WNT16 for physical measures, and the skin tanning locus MC1R and smoking behaviour locus CHRNA3 for lifestyle. Tissue-specificity investigation reveals several tissues associated with total genetic contributions, including the brain tissues for mental health. Such associations are driven by tissue-specific gene expressions, which share genetic basis with the total genetic contributions. TGCA can provide a genome-wide atlas for the overall genetic contributions in each particular domain of human complex traits.

Extent and context dependence of pleiotropy revealed by high-throughput single-cell phenotyping

Pleiotropy-when a single mutation affects multiple traits-is a controversial topic with far-reaching implications. Pleiotropy plays a central role in debates about how complex traits evolve and whether biological systems are modular or are organized such that every gene has the potential to affect many traits. Pleiotropy is also critical to initiatives in evolutionary medicine that seek to trap infectious microbes or tumors by selecting for mutations that encourage growth in some conditions at the expense of others. Research in these fields, and others, would benefit from understanding the extent to which pleiotropy reflects inherent relationships among phenotypes that correlate no matter the perturbation (vertical pleiotropy). Alternatively, pleiotropy may result from genetic changes that impose correlations between otherwise independent traits (horizontal pleiotropy). We distinguish these possibilities by using clonal populations of yeast cells to quantify the inherent relationships between single-cell morphological features. Then, we demonstrate how often these relationships underlie vertical pleiotropy and how often these relationships are modified by genetic variants (quantitative trait loci [QTL]) acting via horizontal pleiotropy. Our comprehensive screen measures thousands of pairwise trait correlations across hundreds of thousands of yeast cells and reveals ample evidence of both vertical and horizontal pleiotropy. Additionally, we observe that the correlations between traits can change with the environment, genetic background, and cell-cycle position. These changing dependencies suggest a nuanced view of pleiotropy: biological systems demonstrate limited pleiotropy in any given context, but across contexts (e.g., across diverse environments and genetic backgrounds) each genetic change has the potential to influence a larger number of traits. Our method suggests that exploiting pleiotropy for applications in evolutionary medicine would benefit from focusing on traits with correlations that are less dependent on context.

Multiple Forms of Multifunctional Proteins in Health and Disease

Protein science has moved from a focus on individual molecules to an integrated perspective in which proteins emerge as dynamic players with multiple functions, rather than monofunctional specialists. Annotation of the full functional repertoire of proteins has impacted the fields of biochemistry and genetics, and will continue to influence basic and applied science questions - from the genotype-to-phenotype problem, to our understanding of human pathologies and drug design. In this review, we address the phenomena of pleiotropy, multidomain proteins, promiscuity, and protein moonlighting, providing examples of multitasking biomolecules that underlie specific mechanisms of human disease. In doing so, we place in context different types of multifunctional proteins, highlighting useful attributes for their systematic definition and classification in future research directions.

Alleles of a gene differ in pleiotropy, often mediated through currency metabolite production, in E. coli and yeast metabolic simulations

A major obstacle to the mapping of genotype-phenotype relationships is pleiotropy, the tendency of mutations to affect seemingly unrelated traits. Pleiotropy has major implications for evolution, development, ageing, and disease. Except for disease data, pleiotropy is almost exclusively estimated from full gene knockouts. However, most deleterious alleles segregating in natural populations do not fully abolish gene function, and the degree to which a polymorphism reduces protein function may influence the number of traits it affects. Utilizing genome-scale metabolic models for Escherichia coli and Saccharomyces cerevisiae, we show that most fitness-reducing full gene knockouts of metabolic genes in these fast-growing microbes have pleiotropic effects, i.e., they compromise the production of multiple biomass components. Alleles of the same metabolic enzyme-encoding gene with increasingly reduced enzymatic function typically affect an increasing number of biomass components. This increasing pleiotropy is often mediated through effects on the generation of currency metabolites such as ATP or NADPH. We conclude that the physiological effects observed in full gene knockouts of metabolic genes will in most cases not be representative for alleles with only partially reduced enzyme capacity or expression level.

Pleiotropy, constraint, and modularity in the evolution of life histories: insights from genomic analyses

Multicellular organisms display an enormous range of life history (LH) strategies and present an evolutionary conundrum; despite strong natural selection, LH traits are characterized by high levels of genetic variation. To understand the evolution of life histories and maintenance of this variation, the specific phenotypic effects of segregating alleles and the genetic networks in which they act need to be elucidated. In particular, the extent to which LH evolution is constrained by the pleiotropy of alleles contributing to LH variation is generally unknown. Here, we review recent empirical results that shed light on this question, with an emphasis on studies employing genomic analyses. While genome-scale analyses are increasingly practical and affordable, they face limitations of genetic resolution and statistical power. We describe new research approaches that we believe can produce new insights and evaluate their promise and applicability to different kinds of organisms. Two approaches seem particularly promising: experiments that manipulate selection in multiple dimensions and measure phenotypic and genomic response and analytical approaches that take into account genome-wide associations between markers and phenotypes, rather than applying a traditional marker-by-marker approach.

Pervasive, yet idiosyncratic, epistatic pleiotropy during adaptation in a behaviourally complex microbe

Understanding how multiple mutations interact to jointly impact multiple ecologically important traits is critical for creating a robust picture of organismal fitness and the process of adaptation. However, this is complicated by both environmental heterogeneity and the complexity of genotype-to-phenotype relationships generated by pleiotropy and epistasis. Moreover, little is known about how pleiotropic and epistatic relationships themselves change over evolutionary time. The soil bacterium Myxococcus xanthus employs several distinct social traits across a range of environments. Here, we use an experimental lineage of M. xanthus that evolved a novel form of social motility to address how interactions between epistasis and pleiotropy evolve. Specifically, we test how mutations accumulated during selection on soft agar pleiotropically affect several other social traits (hard agar motility, predation and spore production). Relationships between changes in swarming rate in the selective environment and the four other traits varied greatly over time in both direction and magnitude, both across timescales of the entire evolutionary lineage and individual evolutionary time steps. We also tested how a previously defined epistatic interaction is pleiotropically expressed across these traits. We found that phenotypic effects of this epistatic interaction were highly correlated between soft and hard agar motility, but were uncorrelated between soft agar motility and predation, and inversely correlated between soft agar motility and spore production. Our results show that 'epistatic pleiotropy' varied greatly in magnitude, and often even in sign, across traits and over time, highlighting the necessity of simultaneously considering the interacting complexities of pleiotropy and epistasis when studying the process of adaptation.

Cryptic Genetic Variation in Evolutionary Developmental Genetics

Evolutionary developmental genetics has traditionally been conducted by two groups: Molecular evolutionists who emphasize divergence between species or higher taxa, and quantitative geneticists who study variation within species. Neither approach really comes to grips with the complexities of evolutionary transitions, particularly in light of the realization from genome-wide association studies that most complex traits fit an infinitesimal architecture, being influenced by thousands of loci. This paper discusses robustness, plasticity and lability, phenomena that we argue potentiate major evolutionary changes and provide a bridge between the conceptual treatments of macro- and micro-evolution. We offer cryptic genetic variation and conditional neutrality as mechanisms by which standing genetic variation can lead to developmental system drift and, sheltered within canalized processes, may facilitate developmental transitions and the evolution of novelty. Synthesis of the two dominant perspectives will require recognition that adaptation, divergence, drift and stability all depend on similar underlying quantitative genetic processes-processes that cannot be fully observed in continuously varying visible traits.

Apolipoprotein E (ApoE) polymorphism is related to differences in potential fertility in women: a case of antagonistic pleiotropy?

The alleles that are detrimental to health, especially in older age, are thought to persist in populations because they also confer some benefits for individuals (through antagonistic pleiotropy). The ApoE4 allele at the ApoE locus, encoding apolipoprotein E (ApoE), significantly increases risk of poor health, and yet it is present in many populations at relatively high frequencies. Why has it not been replaced by natural selection with the health-beneficial ApoE3 allele? ApoE is a major supplier of cholesterol precursor for the production of ovarian oestrogen and progesterone, thus ApoE has been suggested as the potential candidate gene that may cause variation in reproductive performance. Our results support this hypothesis showing that in 117 regularly menstruating women those with genotypes with at least one ApoE4 allele had significantly higher levels of mean luteal progesterone (144.21 pmol l(-1)) than women with genotypes without ApoE4 (120.49 pmol l(-1)), which indicates higher potential fertility. The hormonal profiles were based on daily data for entire menstrual cycles. We suggest that the finding of higher progesterone in women with ApoE4 allele could provide first strong evidence for an evolutionary mechanism of maintaining the ancestral and health-worsening ApoE4 allele in human populations.

Pleiotropy as the Mechanism for Evolving Novelty: Same Signal, Different Result

In contrast to the probabilistic way of thinking about pleiotropy as the random expression of a single gene that generates two or more distinct phenotypic traits, it is actually a deterministic consequence of the evolution of complex physiology from the unicellular state. Pleiotropic novelties emerge through recombinations and permutations of cell-cell signaling exercised during reproduction based on both past and present physical and physiologic conditions, in service to the future needs of the organism for its continued survival. Functional homologies ranging from the lung to the kidney, skin, brain, thyroid and pituitary exemplify the evolutionary mechanistic strategy of pleiotropy. The power of this perspective is exemplified by the resolution of evolutionary gradualism and punctuated equilibrium in much the same way that Niels Bohr resolved the paradoxical duality of light as Complementarity.

The differential view of genotype-phenotype relationships

An integrative view of diversity and singularity in the living world requires a better understanding of the intricate link between genotypes and phenotypes. Here we re-emphasize the old standpoint that the genotype-phenotype (GP) relationship is best viewed as a connection between two differences, one at the genetic level and one at the phenotypic level. As of today, predominant thinking in biology research is that multiple genes interact with multiple environmental variables (such as abiotic factors, culture, or symbionts) to produce the phenotype. Often, the problem of linking genotypes and phenotypes is framed in terms of genotype and phenotype maps, and such graphical representations implicitly bring us away from the differential view of GP relationships. Here we show that the differential view of GP relationships is a useful explanatory framework in the context of pervasive pleiotropy, epistasis, and environmental effects. In such cases, it is relevant to view GP relationships as differences embedded into differences. Thinking in terms of differences clarifies the comparison between environmental and genetic effects on phenotypes and helps to further understand the connection between genotypes and phenotypes.