Degree Of Pleiotropy Research Articles

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.

Biallelic Loss of Function Mutation in Sodium Channel Gene SCN10A in an Autism Spectrum Disorder Trio from Pakistan.

The genetic dissection of autism spectrum disorders (ASD) has uncovered the contribution of de novo mutations in many single genes as well as de novo copy number variants. More recent work also suggests a strong contribution from recessively inherited variants, particularly in populations in which consanguineous marriages are common. What is also becoming more apparent is the degree of pleiotropy, whereby mutations in the same gene may have quite different phenotypic and clinical consequences. We performed whole exome sequencing in a group of 115 trios from countries with a high level of consanguineous marriages. In this paper we report genetic and clinical findings on a proband with ASD, who inherited a biallelic truncating pathogenic/likely pathogenic variant in the gene encoding voltage-gated sodium channel X alpha subunit, SCN10A (NM_006514.2:c.937G>T:(p.Gly313*)). The biallelic pathogenic/likely pathogenic variant in this study have different clinical features than heterozygous mutations in the same gene. The study of consanguineous families for autism spectrum disorder is highly valuable.

Highly pleiotropic variants of human traits are enriched in genomic regions with strong background selection

Recent studies have shown the ubiquity of pleiotropy for variants affecting human complex traits. These studies also show that rare variants tend to be less pleiotropic than common ones, suggesting that purifying natural selection acts against highly pleiotropic variants of large effect. Here, we investigate the mean frequency, effect size and recombination rate associated with pleiotropic variants, and focus particularly on whether highly pleiotropic variants are enriched in regions with putative strong background selection. We evaluate variants for 41 human traits using data from the NHGRI-EBI GWAS Catalog, as well as data from other three studies. Our results show that variants involving a higher degree of pleiotropy tend to be more common, have larger mean effect sizes, and contribute more to heritability than variants with a lower degree of pleiotropy. This is consistent with the fact that variants of large effect and frequency are more likely detected by GWAS. Using data from four different studies, we also show that more pleiotropic variants are enriched in genome regions with stronger background selection than less pleiotropic variants, suggesting that highly pleiotropic variants are subjected to strong purifying selection. From the above results, we hypothesized that a number of highly pleiotropic variants of low effect/frequency may pass undetected by GWAS.

A population genetic interpretation of GWAS findings for human quantitative traits.

Human genome-wide association studies (GWASs) are revealing the genetic architecture of anthropomorphic and biomedical traits, i.e., the frequencies and effect sizes of variants that contribute to heritable variation in a trait. To interpret these findings, we need to understand how genetic architecture is shaped by basic population genetics processes—notably, by mutation, natural selection, and genetic drift. Because many quantitative traits are subject to stabilizing selection and because genetic variation that affects one trait often affects many others, we model the genetic architecture of a focal trait that arises under stabilizing selection in a multidimensional trait space. We solve the model for the phenotypic distribution and allelic dynamics at steady state and derive robust, closed-form solutions for summary statistics of the genetic architecture. Our results provide a simple interpretation for missing heritability and why it varies among traits. They predict that the distribution of variances contributed by loci identified in GWASs is well approximated by a simple functional form that depends on a single parameter: the expected contribution to genetic variance of a strongly selected site affecting the trait. We test this prediction against the results of GWASs for height and body mass index (BMI) and find that it fits the data well, allowing us to make inferences about the degree of pleiotropy and mutational target size for these traits. Our findings help to explain why the GWAS for height explains more of the heritable variance than the similarly sized GWAS for BMI and to predict the increase in explained heritability with study sample size. Considering the demographic history of European populations, in which these GWASs were performed, we further find that most of the associations they identified likely involve mutations that arose shortly before or during the Out-of-Africa bottleneck at sites with selection coefficients around s = 10−3.

Evolution of the Genotype-to-Phenotype Map and the Cost of Pleiotropy in Mammals.

Evolutionary studies have long emphasized that the genetic architecture of traits holds important microevolutionary consequences. Yet, studies comparing the genetic architecture of traits across species are rare, and discussions of the evolution of genetic systems are made on theoretical arguments rather than on empirical evidence. Here, we compared the genetic architecture of cranial traits in two different mammalian model organisms: the gray short-tailed opossum, Monodelphis domestica, and the laboratory mouse, Mus musculus We show that both organisms share a highly polygenic genetic architecture for craniofacial traits, with many loci of small effect. However, these two model species differ significantly in the overall degree of pleiotropy, N, of the genotype-to-phenotype map, with opossums presenting a higher average N They also diverge in their degree of genetic modularity, with opossums presenting less modular patterns of genetic association among traits. We argue that such differences highlight the context dependency of gene effects, with developmental systems shaping the variational properties of genetic systems. Finally, we also demonstrate based on the opossum data that current measurements for the relationship between the mutational effect size and N need to be re-evaluated in relation to the importance of the cost of pleiotropy for mammals.

Factors influencing the effect size distribution of adaptive substitutions.

The distribution of effect sizes of adaptive substitutions has been central to evolutionary biology since the modern synthesis. Early theory proposed that because large-effect mutations have negative pleiotropic consequences, only small-effect mutations contribute to adaptation. More recent theory suggested instead that large-effect mutations could be favoured when populations are far from their adaptive peak. Here we suggest that the distributions of effect sizes are expected to differ among study systems, reflecting the wide variation in evolutionary forces and ecological conditions experienced in nature. These include selection, mutation, genetic drift, gene flow, and other factors such as the degree of pleiotropy, the distance to the phenotypic optimum, whether the optimum is stable or moving, and whether new mutation or standing genetic variation provides the source of adaptive alleles. Our goal is to review how these factors might affect the distribution of effect sizes and to identify new research directions. Until more theory and empirical work is available, we feel that it is premature to make broad generalizations about the effect size distribution of adaptive substitutions important in nature.

Positive Selection and Centrality in the Yeast and Fly Protein-Protein Interaction Networks.

Proteins within a molecular network are expected to be subject to different selective pressures depending on their relative hierarchical positions. However, it is not obvious what genes within a network should be more likely to evolve under positive selection. On one hand, only mutations at genes with a relatively high degree of control over adaptive phenotypes (such as those encoding highly connected proteins) are expected to be “seen” by natural selection. On the other hand, a high degree of pleiotropy at these genes is expected to hinder adaptation. Previous analyses of the human protein-protein interaction network have shown that genes under long-term, recurrent positive selection (as inferred from interspecific comparisons) tend to act at the periphery of the network. It is unknown, however, whether these trends apply to other organisms. Here, we show that long-term positive selection has preferentially targeted the periphery of the yeast interactome. Conversely, in flies, genes under positive selection encode significantly more connected and central proteins. These observations are not due to covariation of genes' adaptability and centrality with confounding factors. Therefore, the distribution of proteins encoded by genes under recurrent positive selection across protein-protein interaction networks varies from one species to another.

Multi-trait multi-environment quantitative trait loci mapping for a sugarcane commercial cross provides insights on the inheritance of important traits.

Breeding trials typically consist of phenotypic observations for various traits evaluated in multiple environments. For sugarcane in particular, repeated measures are obtained for plant crop and one or more ratoons, such that joint analysis through mixed models for modeling heterogeneous genetic (co)variances between traits, locations and harvests is appropriate. This modeling approach also enables us to include molecular marker information, aiding in understanding the genetic architecture of quantitative traits. Our work aims at detecting QTL and QTL by environment interactions by fitting mixed models with multiple QTLs, with appropriate modeling of multi-trait multi-environment data for outcrossing species. We evaluated 100 individuals from a biparental cross at two locations and three years for fiber content, sugar content (POL) and tonnes of cane per hectare (TCH). We detected 13 QTLs exhibiting QTL by location, QTL by harvest or the three-way interaction. Overall, 11 of the 13 effects presented some degree of pleiotropy, affecting at least two traits. Furthermore, these QTLs always affected fiber and TCH in the same direction, whereas POL was affected in the opposite way. There was no evidence in favor of the linked QTL over the pleiotropic QTL hypothesis for any detected genome position. These results provide valuable insights into the genetic basis of quantitative variation in sugarcane and the genetic relation between traits.Electronic supplementary materialThe online version of this article (doi:10.1007/s11032-015-0366-6) contains supplementary material, which is available to authorized users.

Appearance, flavor, and texture attributes of pig dry-cured hams have a complex polygenic genomic architecture1

The influence that the genetics of species used as food sources has on the human perception of sensory attributes has been rarely addressed in previous studies. Dry-cured hams are high-quality highly appreciated pork products obtained by salting, curing, drying, and aging processes. We performed a QTL scan for 17 sensory attributes (including appearance, taste, flavor, and texture) and the overall liking evaluated by a panel of trained tasters in both semimembranosus (SM) and biceps femoris (BF) muscles of dry-cured hams from pigs raised in identical nutrition and management conditions. The QTL scan yielded a large array of chromosome- and genomewide QTL, reflecting the complex polygenic architecture of these traits. Among them, 6 QTL affecting SM flavor attributes (aged, matured, sweetness, and umami), 7 QTL associated to SM texture defects (adhesiveness and pastiness), and a single QTL for appearance (BF color intensity) reached the genomewide significant threshold. Discrepancies were observed between the BF and SM QTL maps, probably due to the differential drying and ripening rates determined by the external (SM) vs. internal (BF) location of each muscle. Within muscle, a certain degree of pleiotropy is supported by QTL co-localization for flavor (aged, matured, and sweet) or texture (such as pastiness and adhesiveness defects caused by excessive proteolysis) attributes. On the whole, QTL for overall sensory liking tended to co-localize with aged and matured QTL. Several functional candidate genes involved in the biochemical processes that shape flavor and texture attributes, such as ANPEP, LIPE, LIPA, MEP1B, and MMP28, co-localized with QTL hotspots. These results demonstrate that genetic factors of the pig influence the perception of the sensory attributes generated during dry-cured ham processing and represent a first contribution to elucidate which genetic factors may modulate the sensory properties of dry-cured hams.

On the Pleiotropic Structure of the Genotype–Phenotype Map and the Evolvability of Complex Organisms

Analyses of effects of mutants on many traits have enabled estimates to be obtained of the magnitude of pleiotropy, and in reviews of such data others have concluded that the degree of pleiotropy is highly restricted, with implications on the evolvability of complex organisms. We show that these conclusions are highly dependent on statistical assumptions, for example significance levels. We analyze models with pleiotropic effects on all traits at all loci but by variable amounts, considering distributions of numbers of traits declared significant, overall pleiotropic effects, and extent of apparent modularity of effects. We demonstrate that these highly pleiotropic models can give results similar to those obtained in analyses of experimental data and that conclusions on limits to evolvability through pleiotropy are not robust.

FISHER'S MODEL AND THE GENOMICS OF ADAPTATION: RESTRICTED PLEIOTROPY, HETEROGENOUS MUTATION, AND PARALLEL EVOLUTION

Genetic theories of adaptation generally overlook the genes in which beneficial substitutions occur, and the likely variation in their mutational effects. We investigate the consequences of heterogeneous mutational effects among loci on the genetics of adaptation. We use a generalization of Fisher's geometrical model, which assumes multivariate Gaussian stabilizing selection on multiple characters. In our model, mutation has a distinct variance-covariance matrix of phenotypic effects for each locus. Consequently, the distribution of selection coefficients s varies across loci. We assume each locus can only affect a limited number of independent linear combinations of phenotypic traits (restricted pleiotropy), which differ among loci, an effect we term "orientation heterogeneity." Restricted pleiotropy can sharply reduce the overall proportion of beneficial mutations. Orientation heterogeneity has little impact on the shape of the genomic distribution, but can substantially increase the probability of parallel evolution (the repeated fixation of beneficial mutations at the same gene in independent populations), which is highest with low pleiotropy. We also consider variation in the degree of pleiotropy and in the mean s across loci. The latter impacts the genomic distribution of s, but has a much milder effect on parallel evolution. We discuss these results in the light of evolution experiments.

Pleiotropic Quantitative Trait Loci Contribute to Population Divergence in Traits Associated With Life-History Variation in Mimulus guttatus

Evolutionary biologists seek to understand the genetic basis for multivariate phenotypic divergence. We constructed an F2 mapping population (N = 539) between two distinct populations of Mimulus guttatus. We measured 20 floral, vegetative, and life-history characters on parents and F1 and F2 hybrids in a common garden experiment. We employed multitrait composite interval mapping to determine the number, effect, and degree of pleiotropy in quantitative trait loci (QTL) affecting divergence in floral, vegetative, and life-history characters. We detected 16 QTL affecting floral traits; 7 affecting vegetative traits; and 5 affecting selected floral, vegetative, and life-history traits. Floral and vegetative traits are clearly polygenic. We detected a few major QTL, with all remaining QTL of small effect. Most detected QTL are pleiotropic, implying that the evolutionary shift between these annual and perennial populations is constrained. We also compared the genetic architecture controlling floral trait divergence both within (our intraspecific study) and between species, on the basis of a previously published analysis of M. guttatus and M. nasutus. Eleven of our 16 floral QTL map to approximately the same location in the interspecific map based on shared, collinear markers, implying that there may be a shared genetic basis for floral divergence within and among species of Mimulus.

Theories of Optimization, Form and Function in Branching Architecture in Plants

Optimality models are used as a tool for studying design in the context of natural selection. It has often been pointed out (e.g. Parker & Maynard Smith 1990) that it is not necessary to assume that organisms are optimal for optimality theory to be relevant: it can be valuable in providing a null hypothesis in investigations of adaptation and design. Despite this parsimonious view point, optimality has grown up as a major paradigm in biology closely associated with evolution theory and is the source of a major debate within the study of evolution (e.g. see Dupre 1987). One of the difficulties with the hypothesis of optimality is the availability of observations to test it. It seems logical to suppose that the most likely candidates for nearoptimal design as a result of evolutionary processes are those which share the following features: evidence of evolutionary convergence, a relatively simple form-function relationship, evidence of steep gradients in the 'adaptive landscape' and of increasing fitness over evolutionary time. One example that may qualify and where optimality arguments have frequently been used is the branching design of biological structures whose function is to fill space with a conservative use of materials (Zamir 1976; Honda & Fisher 1978; leFevre 1983; Niklas & Kerchner 1984; Niklas 1986; Morgan & Cannell 1988b). The proposition of evolutionary optimization in these forms is by no means certain. In this paper, we aim to show that some ideas growing up in the medical and engineering literatures, combined with ideas present in botany could substantially advance the study of form-function relations of branched structures and subject the optimization hypothesis to more critical assessment. In plants, above-ground branching pattern directly affects light capture, water transport, mechanical support, reproduction, wind resistance and ultimately, the competitive advantage of trees (KUppers 1989). Branch design can influence the relative growth rate of a tree via its effect on the light-extinction coefficient through determining the spatial distribution of foliage (Cannell 1989). A wide variety of botanical branched forms exist in nature, classified by Halle, Olderman & Tomlinson (1978). That these have persisted through evolutionary time to the present indicates that they are all functional forms and comply with the principle of adequate design (Rashevsky 1960). The term 'functional form' is used throughout this work to mean a form which performs a clear functional role with sufficient success that the organism to which it belongs reproduces enough for a viable species (i.e. one that persists over evolutionary time). Theoretical studies have shown that it is relatively simple to simulate branched forms with a basic branch generating rule, manipulating the values of relatively few parameters. These parameters, though, are not necessarily those that are genetically coded (Niklas 1994). It is likely that more than one function (or design objective) has exerted an influence over each genetically coded parameter of form. There is also likely to be a degree of pleiotropy further confusing relations between form and function. Frequently there will be multiple strategies leading to different forms for any given objective function and these could be combined so that trade-offs between them produce a set of different functional forms for the one design objective [see the example of Campbell, Grime & Mackey (1991) below]. The objective space, which plots all possible forms against one or more objective functions, can be seen as having contours of indifference resulting from the combination of strategies and of different objective functions which may not be orthogonal, indeed they may be highly correlated. Consequently there is not just a single optimal point nor several but rather some subspace (e.g. a surface) in adaptive space where different solutions represent 'adequate design'. This may help to explain the wide variety of form in nature: even when forms occupy what appear to be very similar niches (Tomlinson 1983). Despite this, there have been a number of demonstrations of apparently optimal form in branch design (reviewed by Fisher 1992) but these have all concerned optimization against only one design objective at a time. Our interest is in the effect of multiple objectives on the hypothesis of optimization in branched structures in the context of constraints, especially ontological constraints.