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Hearing difficulty (HD) is a major health burden in older adults. While ageing-related changes in the peripheral auditory system play an important role, genetic variation associated with brain structure and function could also be involved in HD predisposition. We analysed a large-scale HD genome-wide association study (GWAS; n total = 501 825, 56% females) and GWAS data related to 3935 brain imaging-derived phenotypes (IDPs) assessed in up to 33 224 individuals (52% females) using multiple MRI modalities. To investigate HD pleiotropy with brain structure and function, we conducted genetic correlation, latent causal variable, Mendelian randomization and multivariable generalized linear regression analyses. Additionally, we performed local genetic correlation and multi-trait co-localization analyses to identify genomic regions and loci implicated in the pleiotropic mechanisms shared between HD and brain IDPs. We observed a widespread genetic correlation of HD with 120 IDPs in females, 89 in males and 171 in the sex-combined analysis. The latent causal variable analysis showed that some of these genetic correlations could be due to cause-effect relationships. For seven of them, the causal effects were also confirmed by the Mendelian randomization approach: vessel volume→HD in the sex-combined analysis; hippocampus volume→HD, cerebellum grey matter volume→HD, primary visual cortex volume→HD and HD→fluctuation amplitudes of node 46 in resting-state functional MRI dimensionality 100 in females; global mean thickness→HD and HD→mean orientation dispersion index in superior corona radiata in males. The local genetic correlation analysis identified 13 pleiotropic regions between HD and these seven IDPs. We also observed a co-localization signal for the rs13026575 variant between HD, primary visual cortex volume and SPTBN1 transcriptomic regulation in females. Brain structure and function may have a role in the sex differences in HD predisposition via possible cause-effect relationships and shared regulatory mechanisms. [ABSTRACT FROM AUTHOR]

Observations of genetically repeated evolution (repeatability) in complex organisms are incongruent with the Fisher–Orr model, which implies that repeated use of the same gene should be rare when mutations are pleiotropic (i.e. affect multiple traits). When spatially divergent selection occurs in the presence of migration, mutations of large effect are more strongly favored, and hence, repeatability is more likely, but it is unclear whether this observation is limited by pleiotropy. Here, we explore this question using individual-based simulations of a two-patch model incorporating multiple quantitative traits governed by mutations with pleiotropic effects. We explore the relationship between fitness trade-offs and repeatability by varying the alignment between mutation effect and spatial variation in trait optima. While repeatability decreases with increasing trait dimensionality, trade-offs in mutation effects on traits do not strongly limit the contribution of a locus of large effect to repeated adaptation, particularly under increased migration. These results suggest that repeatability will be more pronounced for local rather than global adaptation. Whereas pleiotropy limits repeatability in a single-population model, when there is local adaptation with gene flow, repeatability can occur if some loci are able to produce alleles of large effect, even when there are pleiotropic trade-offs. [ABSTRACT FROM AUTHOR]

Advancing male age is often hypothesized to reduce both male fertility and offspring quality due to reproductive senescence. However, the effects of advancing male age on reproductive output and offspring quality are not always deleterious. For example, older fathers might buffer the effects of reproductive senescence by terminally investing in reproduction. Similarly, males that survive to reproduce at an old age might carry alleles that confer high viability (viability selection), which are then inherited by offspring, or might have high reproductive potential (selective disappearance). Differentiating these mechanisms requires an integrated experimental study of paternal survival and reproductive performance, as well as offspring quality, which is currently lacking. Using a cross-sectional study in Drosophila melanogaster , we test the effects of paternal age at conception (PAC) on paternal survival and reproductive success, and on the lifespans of sons. We discover that mating at an old age is linked with decreased future male survival, suggesting that mating-induced mortality is possibly due to old fathers being frail. We find no evidence for terminal investment and show that reproductive senescence in fathers does not onset until their late-adult life. Additionally, we find that as a father's lifespan increases, his probability of siring offspring increases for older PAC treatments only. Lastly, we show that sons born to older fathers live longer than those born to younger fathers due to viability selection. Collectively, our results suggest that advancing paternal age is not necessarily associated with deleterious effects for offspring and may even lead to older fathers producing longer-lived offspring. [ABSTRACT FROM AUTHOR]

Mendelian randomization (MR) addresses causal questions using genetic variants as instrumental variables. We propose a new MR method, G-Estimation under No Interaction with Unmeasured Selection (GENIUS)-MAny Weak Invalid IV, which simultaneously addresses the 2 salient challenges in MR: many weak instruments and widespread horizontal pleiotropy. Similar to MR-GENIUS, we use heteroscedasticity of the exposure to identify the treatment effect. We derive influence functions of the treatment effect, and then we construct a continuous updating estimator and establish its asymptotic properties under a many weak invalid instruments asymptotic regime by developing novel semiparametric theory. We also provide a measure of weak identification, an overidentification test, and a graphical diagnostic tool. [ABSTRACT FROM AUTHOR]

Background and Hypothesis Schizophrenia (SCZ) and anorexia nervosa (AN) are 2 severe and highly heterogeneous disorders showing substantial familial co-aggregation. Genetic factors play a significant role in both disorders, but the shared genetic etiology between them is yet to be investigated. Study Design Using summary statistics from recent large genome-wide association studies on SCZ (N cases = 53 386) and AN (N cases = 16 992), a 2-sample Mendelian randomization analysis was conducted to explore the causal relationship between SCZ and AN. MiXeR was employed to quantify their polygenic overlap. A conditional/conjunctional false discovery rate (condFDR/conjFDR) framework was adopted to identify loci jointly associated with both disorders. Functional annotation and enrichment analyses were performed on the shared loci. Study Results We observed a cross-trait genetic enrichment, a suggestive bidirectional causal relationship, and a considerable polygenic overlap (Dice coefficient = 62.2%) between SCZ and AN. The proportion of variants with concordant effect directions among all shared variants was 69.9%. Leveraging overlapping genetic associations, we identified 6 novel loci for AN and 33 novel loci for SCZ at condFDR <0.01. At conjFDR <0.05, we identified 10 loci jointly associated with both disorders, implicating multiple genes highly expressed in the cerebellum and pituitary and involved in synapse organization. Particularly, high expression of the shared genes was observed in the hippocampus in adolescence and orbitofrontal cortex during infancy. Conclusions This study provides novel insights into the relationship between SCZ and AN by revealing a shared genetic component and offers a window into their complex etiology. [ABSTRACT FROM AUTHOR]

After the loss of a trait, theory predicts that the molecular machinery underlying its phenotypic expression should decay. Yet, empirical evidence is contrasting. Here, we test the hypotheses that (i) the molecular ground plan of a lost trait could persist due to pleiotropic effects on other traits and (ii) that gene co-expression network architecture could constrain individual gene expression. Our testing ground has been the Bacillus stick insect species complex, which contains close relatives that are either bisexual or parthenogenetic. After the identification of genes expressed in male reproductive tissues in a bisexual species, we investigated their gene co-expression network structure in two parthenogenetic species. We found that gene co-expression within the male gonads was partially preserved in parthenogens. Furthermore, parthenogens did not show relaxed selection on genes upregulated in male gonads in the bisexual species. As these genes were mostly expressed in female gonads, this preservation could be driven by pleiotropic interactions and an ongoing role in female reproduction. Connectivity within the network also played a key role, with highly connected—and more pleiotropic—genes within male gonad also having a gonad-biased expression in parthenogens. Our findings provide novel insight into the mechanisms which could underlie the production of rare males in parthenogenetic lineages; more generally, they provide an example of the cryptic persistence of a lost trait molecular architecture, driven by gene pleiotropy on other traits and within their co-expression network. [ABSTRACT FROM AUTHOR]

Phenotypic plasticity is one way for organisms to deal with variable environments through generalism. However, plasticity is not found universally and its evolution may be constrained by costs and other limitations such as complexity: the need for multiple mutational steps before the adaptation is realized. Theory predicts that greater experienced heterogeneity, such as organisms may encounter when spatial heterogeneity is fine-grained relative to dispersal, should favor the evolution of a broader niche. Here we tested this prediction via simulation. We found that, contrary to classical predictions, coarse-grained landscapes can be the most favorable for the evolution of plasticity, but only when populations encounter those landscapes through range expansion. During these range expansions, coarse-grained landscapes select for each step in the complex mutational pathway to plastic generalism by blocking the dispersal of specialists. These circumstances provide ecological opportunities for innovative mutations that change the niche. Our results indicate a new mechanism by which range expansion and spatially structured landscapes interact to shape evolution and reveal that the environments in which a complex adaptation has the highest fitness may not be the most favorable for its evolution. [ABSTRACT FROM AUTHOR]

Female spiders and praying mantises are renowned for their cannibalism of male partners before, during, or after mating. While several hypotheses have been proposed to explain species-specific examples of sexual cannibalism, much variation remains unexplained, including why the timing of cannibalism varies across taxa. Here, I outline how sexually cannibalistic behavior could evolve via sexually antagonistic selection as a type of behavioral resistance to male-imposed mating costs, and how such a generalizable interpretation provides a framework for understanding the evolution of both sexual cannibalism in females and anti-cannibalistic traits in males. I discuss how differences between mating systems that physiologically constrain males to mate only once (monogyny) or twice (bigyny) and systems where the sexes can potentially mate multiply (polygyny and polyandry) are likely to influence how sexual conflict shapes cannibalistic behavior. I review key examples from the literature that suggest how sexually cannibalistic behavior might function as a female resistance trait and provide comprehensive predictions for testing this hypothesis empirically. [ABSTRACT FROM AUTHOR]

Large-scale comparative genomics studies offer valuable resources for understanding both functional and evolutionary rate constraints. It is suggested that constraint aligns with the topology of genomic networks, increasing toward the center, with intermediate nodes combining relaxed constraint with higher contributions to the phenotype due to pleiotropy. However, this pattern has yet to be demonstrated in vertebrates. This study shows that constraint intensifies toward the network's center in placental mammals. Genes with rate changes associated with emergence of hibernation cluster mostly toward intermediate positions, with higher constraint in faster-evolving genes, which is indicative of a "sweet spot" for adaptation. If this trend holds universally, network node metrics could predict high-constraint regions even in clades lacking empirical constraint data. [ABSTRACT FROM AUTHOR]

Microdeletion syndromes are genetic diseases caused by multilocus chromosomal deletions too small to be detected by karyotyping. They are typified by complex pleiotropic developmental phenotypes that depend both on the extent of the deletion and variations in genetic background. Microdeletion alleles cause a wide array of consequences involving multiple pathways. How simultaneous haploinsufficiency of numerous adjacent genes leads to complex and variable pleiotropic phenotypes is not well understood. CRISPR/Cas9 genome editing has been shown to induce microdeletion-like alleles at a meaningful rate. Here, we describe a microdeletion allele in Caenorhabditis elegans recovered during a CRISPR/Cas9 genome editing experiment. We mapped the allele to chromosome V, balanced it with a reciprocal translocation crossover suppressor, and precisely defined the breakpoint junction. The allele simultaneously removes 32 protein-coding genes, yet animals homozygous for this mutation are viable as adults. Homozygous animals display a complex phenotype including maternal effect lethality, producing polynucleated embryos that grow into uterine tumors, vulva morphogenesis defects, body wall distensions, uncoordinated movement, and a shortened life span typified by death by bursting. Our work provides an opportunity to explore the complexity and penetrance of microdeletion phenotypes in a simple genetic model system. [ABSTRACT FROM AUTHOR]

Quantitative genetics models have shown that long-term selection responses depend on initial variance and mutational influx. Understanding limits of selection requires quantifying the role of mutational variance. However, correlative responses to selection on nonfocal traits can perturb the selection response on the focal trait; and generations are often confounded with selection environments so that genotype by environment (G × E) interactions are ignored. The Saclay divergent selection experiments (DSEs) on maize flowering time were used to track the fate of individual mutations combining genotyping data and phenotyping data from yearly measurements (DSEYM) and common garden experiments (DSECG) with four objectives: (1) to quantify the relative contribution of standing and mutational variance to the selection response, (2) to estimate genotypic mutation effects, (3) to study the impact of G × E interactions in the selection response, and (4) to analyze how trait correlations modulate the exploration of the phenotypic space. We validated experimentally the expected enrichment of fixed beneficial mutations with an average effect of +0.278 and +0.299 days to flowering, depending on the genetic background. Fixation of unfavorable mutations reached up to 25% of incoming mutations, a genetic load possibly due to antagonistic pleiotropy, whereby mutations fixed in the selection environment (DSEYM) turned to be unfavorable in the evaluation environment (DSECG). Global patterns of trait correlations were conserved across genetic backgrounds but exhibited temporal patterns. Traits weakly or uncorrelated with flowering time triggered stochastic exploration of the phenotypic space, owing to microenvironment-specific fixation of standing variants and pleiotropic mutational input. [ABSTRACT FROM AUTHOR]

The genetic covariance between traits can affect the evolution of a population through selection, drift, and migration. Conversely, research has demonstrated the reciprocal effect of evolutionary processes on changing genetic covariances, in part through mutational covariance, correlational selection, and plasticity. In this article, we propose that correlated changes in selective optima over generations can cause the evolution of genetic covariance and the G-matrix in such a way that the population can, in the future, evolve faster. We use individual-based simulations of populations exposed to three types of changing environments that differ in the correlation of the change between selective pressures. Our simulation experiments demonstrate that selection pressures for different traits changing in a correlated pattern over generations can lead to stronger trait correlations compared to the case with independently changing selective optima. Our findings show that correlated selective pressures result in significantly higher genetic trait covariance and that pleiotropy accounts for the majority of the difference in covariance between treatments. We also observe that the mutational variance evolves according to the environment that the populations were exposed to. Moreover, we show that clustered patterns of changes in selection can allow the evolution of genetic modularity. We show that the pattern of change in the selective environment affects the pace at which fitness evolves, with populations experiencing correlated change in optima having on average higher mean fitness than those experiencing uncorrelated environment change. Lay Summary: Trait covariance describes the relationship between the variance of two or more traits. The genetic covariance is the heritable portion of the covariance, and it can influence how a biological population changes through time. Researchers have also shown how the reciprocal effect is true, that is, how the evolution of a population may also impact the genetic covariance of traits. Here we are proposing one way in which evolution, specifically evolution through natural selection, can change the genetic covariance of traits. We call the mechanism we are proposing "correlated environmental change" because it describes a changing environment where the amount and direction of change over different traits are the same. Our results show that when the environment changes in such a way, compared to a not correlated way, genetic covariance between traits increases. Additionally, most of the covariance we find is a result of a heritable element (i.e., gene) impacting multiple traits. We also show how the future change given by mutations that impact these traits are more likely to happen in the direction of the changing environment. Finally, according to our results, populations become adapted to the way the environment changes, and are able to reach higher fitness faster when reexposed to the same type of change they were originally exposed to compared to a new type of change. [ABSTRACT FROM AUTHOR]

When quantitative longitudinal traits are risk factors for disease progression and subject to random biological variation, joint model analysis of time-to-event and longitudinal traits can effectively identify direct and/or indirect genetic association of single nucleotide polymorphisms (SNPs) with time-to-event. We present a joint model that integrates: (1) a multivariate linear mixed model describing trajectories of multiple longitudinal traits as a function of time, SNP effects, and subject-specific random effects and (2) a frailty Cox survival model that depends on SNPs, longitudinal trajectory effects, and subject-specific frailty accounting for dependence among multiple time-to-event traits. Motivated by complex genetic architecture of type 1 diabetes complications (T1DC) observed in the Diabetes Control and Complications Trial (DCCT), we implement a 2-stage approach to inference with bootstrap joint covariance estimation and develop a hypothesis testing procedure to classify direct and/or indirect SNP association with each time-to-event trait. By realistic simulation study, we show that joint modeling of 2 time-to-T1DC (retinopathy and nephropathy) and 2 longitudinal risk factors (HbA1c and systolic blood pressure) reduces estimation bias in genetic effects and improves classification accuracy of direct and/or indirect SNP associations, compared to methods that ignore within-subject risk factor variability and dependence among longitudinal and time-to-event traits. Through DCCT data analysis, we demonstrate feasibility for candidate SNP modeling and quantify effects of sample size and Winner's curse bias on classification for 2 SNPs identified as having indirect associations with time-to-T1DC traits. Joint analysis of multiple longitudinal and multiple time-to-event traits provides insight into complex traits architecture. [ABSTRACT FROM AUTHOR]

The influence of pleiotropy on adaptive responses is a highly controversial topic, with limited empirical evidence available. Recognizing the pivotal role of the correlation of fitness effects, we designed an experiment to compare the adaptive gene expression evolution of natural and experimental populations. To test this, we studied the evolution of gene expression in response to temperature in two Drosophila species on a natural temperature cline in North America and replicated populations evolving in hot- and cold-temperature regimes. If fitness effects of affected traits are independent, pleiotropy is expected to constrain the adaptive response in both settings, laboratory and natural populations. However, when fitness effects are more correlated in natural populations, adaptation in the wild will be facilitated by pleiotropy. Remarkably, we find evidence for both predicted effects. In both settings, genes with strong pleiotropic effects contribute less to adaptation, indicating that the majority of fitness effects are not correlated. In addition, we discovered that genes involved in adaptation exhibited more pleiotropic effects in natural populations. We propose that this pattern can be explained by a stronger correlation of fitness effects in nature. More insights into the dual role of pleiotropy will be crucial for the understanding of polygenic adaptation. [ABSTRACT FROM AUTHOR]

Background Immune mechanisms are indicated in schizophrenia (SCZ). Recent genome-wide association studies (GWAS) have identified genetic variants associated with SCZ and immune-related phenotypes. Here, we use cutting edge statistical tools to identify shared genetic variants between SCZ and white blood cell (WBC) counts and further understand the role of the immune system in SCZ. Study Design GWAS results from SCZ (patients, n = 53 386; controls, n = 77 258) and WBC counts (n = 56 3085) were analyzed. We applied linkage disequilibrium score regression, the conditional false discovery rate method and the bivariate causal mixture model for analyses of genetic associations and overlap, and 2 sample Mendelian randomization to estimate causal effects. Study Results The polygenicity for SCZ was 7.5 times higher than for WBC count and constituted 32%–59% of WBC count genetic loci. While there was a significant but weak positive genetic correlation between SCZ and lymphocytes (r g = 0.05), the conditional false discovery rate method identified 383 shared genetic loci (53% concordant effect directions), with shared variants encompassing all investigated WBC subtypes: lymphocytes, n = 215 (56% concordant); neutrophils, n = 158 (49% concordant); monocytes, n = 146 (47% concordant); eosinophils, n = 135 (56% concordant); and basophils, n = 64 (53% concordant). A few causal effects were suggested, but consensus was lacking across different Mendelian randomization methods. Functional analyses indicated cellular functioning and regulation of translation as overlapping mechanisms. Conclusions Our results suggest that genetic factors involved in WBC counts are associated with the risk of SCZ, indicating a role of immune mechanisms in subgroups of SCZ with potential for stratification of patients for immune targeted treatment. [ABSTRACT FROM AUTHOR]

Psychiatric disorders and common epilepsies are heritable disorders with a high comorbidity and overlapping symptoms. However, the causative mechanisms underlying this relationship are poorly understood. Here we aimed to identify overlapping genetic loci between epilepsy and psychiatric disorders to gain a better understanding of their comorbidity and shared clinical features. We analysed genome-wide association study data for all epilepsies (n = 44 889), genetic generalized epilepsy (n = 33 446), focal epilepsy (n = 39 348), schizophrenia (n = 77 096), bipolar disorder (n = 406 405), depression (n = 500 199), attention deficit hyperactivity disorder (n = 53 293) and autism spectrum disorder (n = 46 350). First, we applied the MiXeR tool to estimate the total number of causal variants influencing the disorders. Next, we used the conjunctional false discovery rate statistical framework to improve power to discover shared genomic loci. Additionally, we assessed the validity of the findings in independent cohorts, and functionally characterized the identified loci. The epilepsy phenotypes were considerably less polygenic (1.0 K to 3.4 K causal variants) than the psychiatric disorders (5.6 K to 13.9 K causal variants), with focal epilepsy being the least polygenic (1.0 K variants), and depression having the highest polygenicity (13.9 K variants). We observed cross-trait genetic enrichment between genetic generalized epilepsy and all psychiatric disorders and between all epilepsies and schizophrenia and depression. Using conjunctional false discovery rate analysis, we identified 40 distinct loci jointly associated with epilepsies and psychiatric disorders at conjunctional false discovery rate <0.05, four of which were associated with all epilepsies and 39 with genetic generalized epilepsy. Most epilepsy risk loci were shared with schizophrenia (n = 31). Among the identified loci, 32 were novel for genetic generalized epilepsy, and two were novel for all epilepsies. There was a mixture of concordant and discordant allelic effects in the shared loci. The sign concordance of the identified variants was highly consistent between the discovery and independent datasets for all disorders, supporting the validity of the findings. Gene-set analysis for the shared loci between schizophrenia and genetic generalized epilepsy implicated biological processes related to cell cycle regulation, protein phosphatase activity, and membrane and vesicle function; the gene-set analyses for the other loci were underpowered. The extensive genetic overlap with mixed effect directions between psychiatric disorders and common epilepsies demonstrates a complex genetic relationship between these disorders, in line with their bi-directional relationship, and indicates that overlapping genetic risk may contribute to shared pathophysiological and clinical features between epilepsy and psychiatric disorders. [ABSTRACT FROM AUTHOR]

Pleiotropy occurs when a genetic variant influences more than one trait. This is a key property of the genomic architecture of psychiatric disorders and has been observed for rare and common genomic variants. It is reasonable to hypothesize that the microscale genetic overlap (pleiotropy) across psychiatric conditions and cognitive traits may lead to similar overlaps at the macroscale brain level such as large-scale brain functional networks. We took advantage of brain connectivity, measured by resting-state functional MRI to measure the effects of pleiotropy on large-scale brain networks, a putative step from genes to behaviour. We processed nine resting-state functional MRI datasets including 32 726 individuals and computed connectome-wide profiles of seven neuropsychiatric copy-number-variants, five polygenic scores, neuroticism and fluid intelligence as well as four idiopathic psychiatric conditions. Nine out of 19 pairs of conditions and traits showed significant functional connectivity correlations (r Functional connectivity), which could be explained by previously published levels of genomic (r Genetic) and transcriptomic (r Transcriptomic) correlations with moderate to high concordance: r Genetic— r Functional connectivity = 0.71 [0.40–0.87] and r Transcriptomic— r Functional connectivity = 0.83 [0.52; 0.94]. Extending this analysis to functional connectivity profiles associated with rare and common genetic risk showed that 30 out of 136 pairs of connectivity profiles were correlated above chance. These similarities between genetic risks and psychiatric disorders at the connectivity level were mainly driven by the overconnectivity of the thalamus and the somatomotor networks. Our findings suggest a substantial genetic component for shared connectivity profiles across conditions and traits, opening avenues to delineate general mechanisms—amenable to intervention—across psychiatric conditions and genetic risks. [ABSTRACT FROM AUTHOR]

The effects of within-generation plasticity vs. transgenerational plasticity on trait expression are poorly understood, but important for evaluating plasticity's evolutionary consequences. We tested how genetics, within-generation plasticity, and transgenerational plasticity jointly shape traits influencing rapid evolution in the field cricket Teleogryllus oceanicus. In Hawaiian populations attacked by acoustically orienting parasitoid flies, a protective, X-linked variant (" flatwing") eliminates male acoustic sexual signals. Silent males rapidly spread to fixation, dramatically changing the acoustic environment. First, we found evidence supporting flatwing- associated pleiotropy in juveniles: pure-breeding flatwing males and females exhibit greater locomotion than those with normal-wing genotypes. Second, within-generation plasticity caused homozygous- flatwing females developing in silence, which mimics all-flatwing populations, to attain lower adult body condition and reproductive investment than those experimentally exposed to song. Third, maternal song exposure caused transgenerational plasticity in offspring, affecting adult, but not juvenile, size, condition, and reproductive investment. This contrasted with behavioral traits, which were only influenced by within-generation plasticity. Fourth, we matched and mismatched maternal and offspring social environments and found that transgenerational plasticity sometimes interacted with within-generation plasticity and sometimes opposed it. Our findings stress the importance of evaluating plasticity of different traits and stages across generations when evaluating its fitness consequences and role in adaptation. [ABSTRACT FROM AUTHOR]

Insect odorant-binding proteins (OBPs) are members of a rapidly evolving multigene family traditionally thought to facilitate chemosensation. However, studies on Drosophila have shown that members of this family have evolved functions beyond chemosensation, as evident from their expression in reproductive tissues and the brain. Previous studies implicated diverse functions of Obp56h, a member of the largest gene cluster of the D. melanogaster Obp repertoire. Here, we examined the effect of CRISPR/Cas9-mediated deletion of Obp56h on 2 fitness phenotypes, on resistance to starvation stress and heat stress, and on locomotion and sleep phenotypes. Obp56h-/- mutants show a strong sexually dimorphic effect on starvation stress survival, with females being more resistant to starvation stress than the control. In contrast, Obp56h-/- females, but not males, are highly sensitive to heat stress. Both sexes show changes in locomotion and sleep patterns. Transcriptional profiling of RNA from heads of Obp56h-/- flies and the wildtype control reveals differentially expressed genes, including gene products associated with antimicrobial immune responses and members of the Turandot family of stress-induced secreted peptides. In addition, differentially expressed genes of unknown function were identified in both sexes. Genes encoding components of the mitochondrial electron transport chain, cuticular proteins, gene products associated with regulation of feeding behavior (Lst and CCHa2), ribosomal proteins, lncRNAs, snoRNAs, tRNAs, and snRNAs show changes in transcript abundances in Obp56h-/- females. These differentially expressed genes are likely to contribute to Obp56h-mediated effects on the diverse phenotypes that arise upon deletion of this OBP. [ABSTRACT FROM AUTHOR]

Single nucleotide polymorphisms are the most common type of genetic variation, but how these variants contribute to the adaptation of complex phenotypes is largely unknown. Experimental evolution and genome-wide association studies have demonstrated that variation in the PPARγ-homolog Eip75B has associated with longevity and life-history differences in the fruit fly Drosophila melanogaster. Using RNAi knockdown, we first demonstrate that reduced expression of Eip75B in adult flies affects lifespan, egg-laying rate, and egg volume. We then tested the effects of a naturally occurring SNP within a cis-regulatory domain of Eip75B by applying two complementary approaches: a Mendelian randomization approach using lines of the Drosophila Genetic Reference Panel, and allelic replacement using precise CRISPR/Cas9-induced genome editing. Our experiments reveal that this natural polymorphism has a significant pleiotropic effect on fecundity and egg-to-adult viability, but not on longevity or other life-history traits. Our results provide a rare functional validation at the nucleotide level and identify a natural allelic variant affecting fitness and life-history adaptation. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The persistence of intrapopulation phenotypic variation typically requires some form of balancing selection because drift and directional selection eventually erode genetic variation. Heterozygote advantage remains a classic explanation for the maintenance of genetic variation in the face of selection. However, examples of heterozygote advantage, other than those associated with disease resistance, are rather uncommon. Across most of its distribution, males of the aposematic moth Arctia plantaginis have two hindwing phenotypes determined by a heritable one locus‐two allele polymorphism (genotypes: WW/Wy = white morph, yy = yellow morph). Using genotyped moths, we show that the presence of one or two copies of the yellow allele affects several life‐history traits. Reproductive output of both males and females and female mating success are negatively affected by two copies of the yellow allele. Females carrying one yellow allele (i.e., Wy) have higher fertility, hatching success, and offspring survival than either homozygote, thus leading to strong heterozygote advantage. Our results indicate strong female contribution especially at the postcopulatory stage in maintaining the color polymorphism. The interplay between heterozygote advantage, yellow allele pleiotropic effect, and morph‐specific predation pressure may exert balancing selection on the color locus, suggesting that color polymorphism may be maintained through complex interactions between natural and sexual selection. [ABSTRACT FROM AUTHOR]

Appropriate flowering time is a crucial adaptation impacting fitness in natural plant populations. Although the genetic basis of flowering variation has been extensively studied, its mechanisms in nonmodel organisms and its adaptive value in the field are still poorly understood. Here, we report new insights into the genetic basis of flowering time and its effect on fitness in Panicum hallii , a native perennial grass. Genetic mapping in populations derived from inland and coastal ecotypes identified flowering time quantitative trait loci (QTL) and many exhibited extensive QTL-by-environment interactions. Patterns of segregation within recombinant hybrids provide strong support for directional selection driving ecotypic divergence in flowering time. A major QTL on chromosome 5 (q-FT5) was detected in all experiments. Fine-mapping and expression studies identified a gene with orthology to a rice FLOWERING LOCUS T-like 9 (PhFTL9) as the candidate underlying q-FT5. We used a reciprocal transplant experiment to test for local adaptation and the specific impact of q-FT5 on performance. We did not observe local adaptation in terms of fitness tradeoffs when contrasting ecotypes in home versus away habitats. However, we observed that the coastal allele of q-FT5 conferred a fitness advantage only in its local habitat but not at the inland site. Sequence analyses identified an excess of low-frequency polymorphisms at the PhFTL9 promoter in the inland lineage, suggesting a role for either selection or population expansion on promoter evolution. Together, our findings demonstrate the genetic basis of flowering variation in a perennial grass and provide evidence for conditional neutrality underlying flowering time divergence. [ABSTRACT FROM AUTHOR]

We define teleonometrics as the theoretical and empirical study of teleonomy. We propose three laws for teleonometrics. The first law describes the hierarchical organization of teleonomic functions across biological levels from genes to individuals. According to this law, the number of goal-directed functions increases from individuals (one goal, maximizing inclusive fitness) to intermediate levels and to genes and alleles (myriad time-, space- and context-dependent goals, depending upon degrees and patterns of pleiotropy). The second law describes the operation of teleonomic functions under trade-offs, coadaptations and negative and positive pleiotropies, which are universal in biological systems. According to this law, the functions of an allele, gene or trait are described and defined by patterns of antagonistic (trading off) and compatible (coadapted) functions. The third law of teleonometrics is that the major transitions in evolution are driven by the origins of novel, emergent goals associated with functional changes and by the breaking and reshaping of trade-offs, especially by mechanisms involving increases in resources or time, and new divisions of labour or function. We illustrate the application of these laws using data from three empirical vignettes, which help to show the usefulness of teleonometric viewpoints for understanding the interfaces between function, trade-offs and dysfunctions manifest as disease. [ABSTRACT FROM AUTHOR]

Hyperuricemia (serum urate >6.8mg/dl) is associated with several cardiometabolic and renal diseases, such as gout and chronic kidney disease. Previous studies have examined the shared genetic basis of chronic kidney disease and hyperuricemia in humans either using singlevariant tests or estimating whole-genome genetic correlations between the traits. Individual variants typically explain a small fraction of the genetic correlation between traits, thus the ability to map pleiotropic loci is lacking power for available sample sizes. Alternatively, wholegenome estimates of genetic correlation indicate a moderate correlation between these traits. While useful to explain the comorbidity of these traits, whole-genome genetic correlation estimates do not shed light on what regions may be implicated in the shared genetic basis of traits. Therefore, to fill the gap between these two approaches, we used local Bayesian multitrait models to estimate the genetic covariance between a marker for chronic kidney disease (estimated glomerular filtration rate) and serum urate in specific genomic regions. We identified 134 overlapping linkage disequilibrium windows with statistically significant covariance estimates, 49 of which had positive directionalities, and 85 negative directionalities, the latter being consistent with that of the overall genetic covariance. The 134 significant windows condensed to 64 genetically distinct shared loci which validate 17 previously identified shared loci with consistent directionality and revealed 22 novel pleiotropic genes. Finally, to examine potential biological mechanisms for these shared loci, we have identified a subset of the genomic windows that are associated with gene expression using colocalization analyses. The regions identified by our local Bayesian multitrait model approach may help explain the association between chronic kidney disease and hyperuricemia. [ABSTRACT FROM AUTHOR]

Bloodfeeding leeches have powerful anticoagulants that allow them to feed for extended periods. However, many leech species are predatory rather than bloodfeeding. It is not known whether they express these proteins and whether the proteins are co-opted for other purposes. Little is known about salivary secretions of the sister groups of leeches, where blood is not part of the diet. We screened the transcriptomes of four non-bloodfeeding leeches and four leech relatives to identify major lineages of anticoagulant genes, helping to determine their evolutionary origin and maintenance. We estimated selection regimes that are expected after a change in feeding behaviour. We found widespread presence of putative anticoagulants, although our results also indicate that several of these are members of multicopy gene families. Our analyses suggest that homologues to leech anticoagulants were already present before the origin of bloodfeeding in leeches and that negative selection is the major driver of evolutionary rates even in non-bloodfeeding taxa. These results point to the retention of the original function by these molecules in non-bloodfeeding species. Ultimately, the proteins might not be involved in bloodfeeding or it seems likely that their putative pleiotropic effects are of great importance. [ABSTRACT FROM AUTHOR]

Background and aims The petaline operculum that covers the inner whorls until anthesis and the woody capsule that develops after fertilization are reproductive structures of eucalypts that protect the flower and seeds. Although they are distinct organs, they both develop from flower buds and this common ontogeny suggests shared genetic control. In Eucalyptus globulus their morphology is variable and we aimed to identify the quantitative trait loci (QTL) underlying this variation and determine whether there is common genetic control of these ecologically and taxonomically important reproductive structures. Methods Samples of opercula and capsules were collected from 206 trees that belong to a large outcrossed F2 E. globulus mapping population. The morphological variation in these structures was characterized by measuring six operculum and five capsule traits. QTL analysis was performed using these data and a linkage map consisting of 480 markers. Key results A total of 27 QTL were detected for operculum traits and 28 for capsule traits, with the logarithm of odds ranging from 2.8 to 11.8. There were many co-located QTL associated with operculum or capsule traits, generally reflecting allometric relationships. A key finding was five genomic regions where co-located QTL affected both operculum and capsule morphology, and the overall trend for these QTL was to affect elongation of both organs. Some of these QTL appear to have a significant effect on the phenotype, with the strongest QTL explaining 26.4 % of the variation in operculum shape and 16.4 % in capsule shape. Flower bud measurements suggest the expression of these QTL starts during bud development. Several candidate genes were found associated with the QTL and their putative function is discussed. Conclusions Variation in both operculum and capsule traits in E. globulus is under strong genetic control. Our results suggest that these reproductive structures share a common genetic pathway during flower bud development. [ABSTRACT FROM AUTHOR]

Due to extensive pleiotropy, trans -acting elements are often thought to be evolutionarily constrained. While the impact of trans -acting elements on gene expression evolution has been extensively studied, relatively little is understood about the contribution of a single trans regulator to interspecific expression and phenotypic divergence. Here, we disentangle the effects of genomic context and miR-983, an adaptively evolving young microRNA, on expression divergence between Drosophila melanogaster and D. simulans. We show miR-983 effects promote interspecific expression divergence in testis despite its antagonism with the often-predominant context effects. Single-cyst RNA-seq reveals that distinct sets of genes gain and lose miR-983 influence under disruptive or diversifying selection at different stages of spermatogenesis, potentially helping minimize antagonistic pleiotropy. At the round spermatid stage, the effects of miR-983 are weak and distributed, coincident with the transcriptome undergoing drastic expression changes. Knocking out miR-983 causes reduced sperm length with increased within-individual variation in D. melanogaster but not in D. simulans, and the D. melanogaster knockout also exhibits compromised sperm defense ability. Our results provide empirical evidence for the resolution of antagonistic pleiotropy and also have broad implications for the function and evolution of new trans regulators. [ABSTRACT FROM AUTHOR]

Enhancers are regulatory elements of genomes that determine spatio-temporal patterns of gene expression. The human genome contains a vast number of enhancers, which largely outnumber protein-coding genes. Historically, enhancers have been regarded as highly tissue-specific. However, recent evidence has demonstrated that many enhancers are pleiotropic, with activity in multiple developmental contexts. Yet, the extent and impact of pleiotropy remain largely unexplored. In this study we analyzed active enhancers across human organs based on the analysis of both eRNA transcription (FANTOM5 consortium data sets) and chromatin architecture (ENCODE consortium data sets). We show that pleiotropic enhancers are pervasive in the human genome and that most enhancers active in a particular organ are also active in other organs. In addition, our analysis suggests that the proportion of context-specific enhancers of a given organ is explained, at least in part, by the proportion of context-specific genes in that same organ. The notion that such a high proportion of human enhancers can be pleiotropic suggests that small regions of regulatory DNA contain abundant regulatory information and that these regions evolve under important evolutionary constraints. [ABSTRACT FROM AUTHOR]

The impact of fitness landscape features on evolutionary outcomes has attracted considerable interest in recent decades. However, evolution often occurs under time‐dependent selection in so‐called fitness seascapes where the landscape is under flux. Fitness seascapes are an inherent feature of natural environments, where the landscape changes owing both to the intrinsic fitness consequences of previous adaptations and extrinsic changes in selected traits caused by new environments. The complexity of such seascapes may curb the predictability of evolution. However, empirical efforts to test this question using a comprehensive set of regimes are lacking. Here, we employed an in vitro microbial model system to investigate differences in evolutionary outcomes between time‐invariant and time‐dependent environments, including all possible temporal permutations, with three subinhibitory antimicrobials and a viral parasite (phage) as selective agents. Expectedly, time‐invariant environments caused stronger directional selection for resistances compared to time‐dependent environments. Intriguingly, however, multidrug resistance outcomes in both cases were largely driven by two strong selective agents (rifampicin and phage) out of four agents in total. These agents either caused cross‐resistance or obscured the phenotypic effect of other resistance mutations, modulating the evolutionary outcome overall in time‐invariant environments and as a function of exposure epoch in time‐dependent environments. This suggests that identifying strong selective agents and their pleiotropic effects is critical for predicting evolution in fitness seascapes, with ramifications for evolutionarily informed strategies to mitigate drug resistance evolution. [ABSTRACT FROM AUTHOR]

Valid estimation of a causal effect using instrumental variables requires that all of the instruments are independent of the outcome conditional on the risk factor of interest and any confounders. In Mendelian randomization studies with large numbers of genetic variants used as instruments, it is unlikely that this condition will be met. Any given genetic variant could be associated with a large number of traits, all of which represent potential pathways to the outcome which bypass the risk factor of interest. Such pleiotropy can be accounted for using standard multivariable Mendelian randomization with all possible pleiotropic traits included as covariates. However, the estimator obtained in this way will be inefficient if some of the covariates do not truly sit on pleiotropic pathways to the outcome. We present a method that uses regularization to identify which out of a set of potential covariates need to be accounted for in a Mendelian randomization analysis in order to produce an efficient and robust estimator of a causal effect. The method can be used in the case where individual-level data are not available and the analysis must rely on summary-level data only. It can be used where there are any number of potential pleiotropic covariates up to the number of genetic variants less one. We show the results of simulation studies that demonstrate the performance of the proposed regularization method in realistic settings. We also illustrate the method in an applied example which looks at the causal effect of urate plasma concentration on coronary heart disease. [ABSTRACT FROM AUTHOR]

Rheumatoid arthritis (RA) and low bone mineral density (BMD), an indicator of osteoporosis (OP), appear epidemiologically associated. Shared genetic factors may explain this association. This study aimed to investigate the presence of pleiotropy to clarify the potential genetic association between RA and OP. We examined BMDs at varying skeletal sites reported in UK Biobank as well as OP fracture acquired from the Genetic Factors for Osteoporosis (GEFOS) Consortium and the TwinsUK study. PRSice‐2 was used to assess the potential shared genetic overlap between RA and OP. The presence of pleiotropy was examined using colocalization analysis. PRSice‐2 revealed that RA was significantly associated with OP fracture (β = 351.6 ± 83.9, p value = 2.76E‐05), total BMD (β = −1763.5 ± 612.8, p = 4.00E‐03), spine BMD (β = −919.8 ± 264.6, p value = 5.09E‐04), and forearm BMD (β = −66.09 ± 31.40, p value = 3.53E‐02). Through colocalization analysis, the same causal genetic variants, associated with both RA and OP, were apparent in 12 genes: PLCL1, BOLL, AC011997.1, TNFAIP3, RP11‐158I9.1, CDK6, CHCHD4P2, RP11‐505C13.1, PHF19, TRAF1, C5, and C11orf49 with moderate posterior probabilities (>50%). Pleiotropy is involved in the association between RA and OP phenotypes. These findings contribute to the understanding of disease mechanisms and provide insight into possible therapeutic advancements and enhanced screening measures. © 2021 American Society for Bone and Mineral Research (ASBMR). [ABSTRACT FROM AUTHOR]

Both pleiotropic connectivity and mutational correlations can restrict the decoupling of traits under divergent selection, but it is unknown which is more important in trait evolution. To address this question, we create a model that permits within-population variation in both pleiotropic connectivity and mutational correlation, and compare their relative importance to trait evolution. Specifically, we developed an individual-based stochastic model where mutations can affect whether a locus affects a trait and the extent of mutational correlations in a population. We find that traits can decouple whether there is evolution in pleiotropic connectivity or mutational correlation, but when both can evolve, then evolution in pleiotropic connectivity is more likely to allow for decoupling to occur. The most common genotype found in this case is characterized by having one locus that maintains connectivity to all traits and another that loses connectivity to the traits under stabilizing selection (subfunctionalization). This genotype is favored because it allows the subfunctionalized locus to accumulate greater effect size alleles, contributing to increasingly divergent trait values in the traits under divergent selection without changing the trait values of the other traits (genetic modularization). These results provide evidence that partial subfunctionalization of pleiotropic loci may be a common mechanism of trait decoupling under regimes of corridor selection. [ABSTRACT FROM AUTHOR]

Pleiotropy has important implication on genetic connection among complex phenotypes and facilitates our understanding of disease etiology. Genome-wide association studies provide an unprecedented opportunity to detect pleiotropic associations; however, efficient pleiotropy test methods are still lacking. We here consider pleiotropy identification from a methodological perspective of high-dimensional composite null hypothesis and propose a powerful gene-based method called MAIUP. MAIUP is constructed based on the traditional intersection–union test with two sets of independent P -values as input and follows a novel idea that was originally proposed under the high-dimensional mediation analysis framework. The key improvement of MAIUP is that it takes the composite null nature of pleiotropy test into account by fitting a three-component mixture null distribution, which can ultimately generate well-calibrated P -values for effective control of family-wise error rate and false discover rate. Another attractive advantage of MAIUP is its ability to effectively address the issue of overlapping subjects commonly encountered in association studies. Simulation studies demonstrate that compared with other methods, only MAIUP can maintain correct type I error control and has higher power across a wide range of scenarios. We apply MAIUP to detect shared associated genes among 14 psychiatric disorders with summary statistics and discover many new pleiotropic genes that are otherwise not identified if failing to account for the issue of composite null hypothesis testing. Functional and enrichment analyses offer additional evidence supporting the validity of these identified pleiotropic genes associated with psychiatric disorders. Overall, MAIUP represents an efficient method for pleiotropy identification. [ABSTRACT FROM AUTHOR]

The fatty acid composition of seed oil is a major determinant of the flavor, shelf-life, and nutritional quality of peanuts. Major QTLs controlling high oil content, high oleic content, and low linoleic content have been characterized in several seed oil crop species. Here, we employ genome-wide association approaches on a recently genotyped collection of 787 plant introduction accessions in the USDA peanut core collection, plus selected improved cultivars, to discover markers associated with the natural variation in fatty acid composition, and to explain the genetic control of fatty acid composition in seed oils. Overall, 251 single nucleotide polymorphisms (SNPs) had significant trait associations with the measured fatty acid components. Twelve SNPs were associated with two or three different traits. Of these loci with apparent pleiotropic effects, 10 were associated with both oleic (C18:1) and linoleic acid (C18:2) content at different positions in the genome. In all 10 cases, the favorable allele had an opposite effect--increasing and lowering the concentration, respectively, of oleic and linoleic acid. The other traits with pleiotropic variant control were palmitic (C16:0), behenic (C22:0), lignoceric (C24:0), gadoleic (C20:1), total saturated, and total unsaturated fatty acid content. One hundred (100) of the significantly associated SNPs were located within 1000 kbp of 55 genes with fatty acid biosynthesis functional annotations. These genes encoded, among others: ACCase carboxyl transferase subunits, and several fatty acid synthase II enzymes. With the exception of gadoleic (C20:1) and lignoceric (C24:0) acid content, which occur at relatively low abundance in cultivated peanuts, all traits had significant SNP interactions exceeding a stringent Bonferroni threshold (α = 1%). We detected 7682 pairwise SNP interactions affecting the relative abundance of fatty acid components in the seed oil. Of these, 627 SNP pairs had at least one SNP within 1000 kbp of a gene with fatty acid biosynthesis functional annotation. We evaluated 168 candidate genes underlying these SNP interactions. Functional enrichment and protein-to-protein interactions supported significant interactions (Pvalue< 1.0Ex16) among the genes evaluated. These results show the complex nature of the biology and genes underlying the variation in seed oil fatty acid composition and contribute to an improved genotype-to-phenotype map for fatty acid variation in peanut seed oil. [ABSTRACT FROM AUTHOR]

Classical genetic studies have identified many cases of pleiotropy where mutations in individual genes alter many different phenotypes. Quantitative genetic studies of natural genetic variants frequently examine one or a few traits, limiting their potential to identify pleiotropic effects of natural genetic variants. Widely adopted community association panels have been employed by plant genetics communities to study the genetic basis of naturally occurring phenotypic variation in a wide range of traits. High-density genetic marker data—18M markers—from 2 partially overlapping maize association panels comprising 1,014 unique genotypes grown in field trials across at least 7 US states and scored for 162 distinct trait data sets enabled the identification of of 2,154 suggestive marker-trait associations and 697 confident associations in the maize genome using a resampling-based genome-wide association strategy. The precision of individual marker-trait associations was estimated to be 3 genes based on a reference set of genes with known phenotypes. Examples were observed of both genetic loci associated with variation in diverse traits (e.g. above-ground and below-ground traits), as well as individual loci associated with the same or similar traits across diverse environments. Many significant signals are located near genes whose functions were previously entirely unknown or estimated purely via functional data on homologs. This study demonstrates the potential of mining community association panel data using new higher-density genetic marker sets combined with resampling-based genome-wide association tests to develop testable hypotheses about gene functions, identify potential pleiotropic effects of natural genetic variants, and study genotype-by-environment interaction. [ABSTRACT FROM AUTHOR]

How new traits originate in evolution is a fundamental question of evolutionary biology. When such traits arise, they can either be immediately beneficial in their environment of origin, or they may become beneficial only in a future environment. Compared to immediately beneficial novel traits, novel traits without immediate benefits remain poorly studied. Here we use experimental evolution to study novel traits that are not immediately beneficial but that allow bacteria to survive in new environments. Specifically, we evolved multiple E. coli populations in five antibiotics with different mechanisms of action, and then determined their ability to grow in more than 200 environments that are different from the environment in which they evolved. Our populations evolved viability in multiple environments that contain not just clinically relevant antibiotics, but a broad range of antimicrobial molecules, such as surfactants, organic and inorganic salts, nucleotide analogues and pyridine derivatives. Genome sequencing of multiple evolved clones shows that pleiotropic mutations are important for the origin of these novel traits. Our experiments, which lasted fewer than 250 generations, demonstrate that evolution can readily create an enormous reservoir of latent traits in microbial populations. These traits can facilitate adaptive evolution in a changing world. [ABSTRACT FROM AUTHOR]

Over most of the 20th century, evolutionary biologists predominantly subscribed to a strong form of "micro‐mutationism," in which adaptive phenotypic divergence arises from allele frequency changes at many loci, each with a small effect on the phenotype. To be sure, there were well‐known examples of large‐effect alleles contributing to adaptation, yet such cases were generally regarded as atypical and unrepresentative of evolutionary change in general. In 1998, Allen Orr published a landmark theoretical paper in Evolution, which showed that both small‐ and large‐effect mutations are likely to contribute to "adaptive walks" of a population to an optimum. Coupled with a growing set of empirical examples of large‐effect alleles contributing to divergence (e.g., from QTL studies), Orr's paper provided a mathematical formalism that converted many evolutionary biologists from micro‐mutationism to a more pluralistic perspective on the genetic basis of evolutionary change. We revisit the theoretical insights emerging from Orr's paper within the historical context leading up to 1998, and track the influence of this paper on the field of evolutionary biology through an examination of its citations over the last two decades and an analysis of the extensive body of theoretical and empirical research that Orr's pioneering paper inspired. [ABSTRACT FROM AUTHOR]

Background and aims Genome size varies considerably across the diversity of plant life. Although genome size is, by definition, affected by genetic presence/absence variants, which are ubiquitous in population sequencing studies, genome size is often treated as an intrinsic property of a species. Here, we studied intra- and interspecific genome size variation in taxonomically complex British eyebrights (Euphrasia , Orobanchaceae). Our aim is to document genome size diversity and investigate underlying evolutionary processes shaping variation between individuals, populations and species. Methods We generated genome size data for 192 individuals of diploid and tetraploid Euphrasia and analysed genome size variation in relation to ploidy, taxonomy, population affiliation and geography. We further compared the genomic repeat content of 30 samples. Key results We found considerable intraspecific genome size variation, and observed isolation-by-distance for genome size in outcrossing diploids. Tetraploid Euphrasia showed contrasting patterns, with genome size increasing with latitude in outcrossing Euphrasia arctica , but with little genome size variation in the highly selfing Euphrasia micrantha. Interspecific differences in genome size and the genomic proportions of repeat sequences were small. Conclusions We show the utility of treating genome size as the outcome of polygenic variation. Like other types of genetic variation, such as single nucleotide polymorphisms, genome size variation may be affected by ongoing hybridization and the extent of population subdivision. In addition to selection on associated traits, genome size is predicted to be affected indirectly by selection due to pleiotropy of the underlying presence/absence variants. [ABSTRACT FROM AUTHOR]

There is tantalizing evidence that phenotypic plasticity can buffer novel, adaptive genetic variants long enough to permit their evolutionary spread, and this process is often invoked in explanations for rapid adaptive evolution. However, the strength and generality of evidence for it is controversial. We identify a conceptual problem affecting this debate: recombination, segregation, and independent assortment are expected to quickly sever associations between genes controlling novel adaptations and genes contributing to trait plasticity that facilitates the novel adaptations by reducing their indirect fitness costs. To make clearer predictions about this role of plasticity in facilitating genetic adaptation, we describe a testable genetic mechanism that resolves the problem: genetic covariance between new adaptive variants and trait plasticity that facilitates their persistence within populations. We identify genetic architectures that might lead to such a covariance, including genetic coupling via physical linkage and pleiotropy, and illustrate the consequences for adaptation rates using numerical simulations. Such genetic covariances may also arise from the social environment, and we suggest the indirect genetic effects that result could further accentuate the process of adaptation. We call the latter mechanism of adaptation social drive, and identify methods to test it. We suggest that genetic coupling of plasticity and adaptations could promote unusually rapid 'runaway' evolution of novel adaptations. The resultant dynamics could facilitate evolutionary rescue, adaptive radiations, the origin of novelties, and other commonly studied processes. [ABSTRACT FROM AUTHOR]

The fitness cost of complex pleiotropic mutations is generally difficult to assess. On the one hand, it is necessary to identify which molecular properties are directly altered by the mutation. On the other, this alteration modifies the activity of many genetic targets with uncertain consequences. Here, we examine the possibility of addressing these challenges by identifying unique predictors of these costs. To this aim, we consider mutations in the RNA polymerase (RNAP) in Escherichia coli as a model of complex mutations. Changes in RNAP modify the global program of transcriptional regulation, with many consequences. Among others is the difficulty to decouple the direct effect of the mutation from the response of the whole system to such mutation. A problem that we solve quantitatively with data of a set of constitutive genes, those on which the global program acts most directly. We provide a statistical framework that incorporates the direct effects and other molecular variables linked to this program as predictors, which leads to the identification that some genes are more suitable to determine costs than others. Therefore, we not only identified which molecular properties best anticipate fitness, but we also present the paradoxical result that, despite pleiotropy, specific genes serve as more solid predictors. These results have connotations for the understanding of the architecture of robustness in biological systems. [ABSTRACT FROM AUTHOR]

Understanding the organization and evolution of social complexity is a major task because it requires building an understanding of mechanisms operating at different levels of biological organization from genes to social interactions. I discuss here, a unique forward genetic approach spanning more than 30 years beginning with human-assisted colony-level selection for a single social trait, the amount of pollen honey bees (Apis mellifera L.) store. The goal was to understand a complex social trait from the social phenotype to genes responsible for observed trait variation. The approach combined the results of colony-level selection with detailed studies of individual behavior and physiology resulting in a mapped, integrated phenotypic architecture composed of correlative relationships between traits spanning anatomy, physiology, sensory response systems, and individual behavior that affect individual foraging decisions. Colony-level selection reverse engineered the architecture of an integrated phenotype of individuals resulting in changes in the social trait. Quantitative trait locus (QTL) studies combined with an exceptionally high recombination rate (60 kb/cM), and a phenotypic map, provided a genotype-phenotype map of high complexity demonstrating broad QTL pleiotropy, epistasis, and epistatic pleiotropy suggesting that gene pleiotropy or tight linkage of genes within QTL integrated the phenotype. Gene expression and knockdown of identified positional candidates revealed genes affecting foraging behavior and confirmed one pleiotropic gene, a tyramine receptor, as a target for colony-level selection that was under selection in two different tissues in two different life stages. The approach presented here has resulted in a comprehensive understanding of the structure and evolution of honey bee social organization. [ABSTRACT FROM AUTHOR]

Enhancers are often studied as noncoding regulatory elements that modulate the precise spatiotemporal expression of genes in a highly tissue-specific manner. This paradigm has been challenged by recent evidence of individual enhancers acting in multiple tissues or developmental contexts. However, the frequency of these enhancers with high degrees of "pleiotropy" out of all putative enhancers is not well understood. Consequently, it is unclear how the variation of enhancer pleiotropy corresponds to the variation in expression breadth of target genes. Here, we use multi-tissue chromatin maps from diverse human tissues to investigate the enhancer–gene interaction architecture while accounting for 1) the distribution of enhancer pleiotropy, 2) the variations of regulatory links from enhancers to target genes, and 3) the expression breadth of target genes. We show that most enhancers are tissue-specific and that highly pleiotropy enhancers account for <1% of all putative regulatory sequences in the human genome. Notably, several genomic features are indicative of increasing enhancer pleiotropy, including longer sequence length, greater number of links to genes, increasing abundance and diversity of encoded transcription factor motifs, and stronger evolutionary conservation. Intriguingly, the number of enhancers per gene remains remarkably consistent for all genes (∼14). However, enhancer pleiotropy does not directly translate to the expression breadth of target genes. We further present a series of Gaussian Mixture Models to represent this organization architecture. Consequently, we demonstrate that a modest trend of more pleiotropic enhancers targeting more broadly expressed genes can generate the observed diversity of expression breadths in the human genome. [ABSTRACT FROM AUTHOR]

Background: Epidemiological studies have demonstrated a positive association between chronic lymphocytic leukaemia (CLL) and non-melanoma skin cancer (NMSC). We hypothesized that shared genetic risk factors between CLL and NMSC could contribute to the association observed between these diseases.Methods: We examined the association between (i) established NMSC susceptibility loci and CLL risk in a meta-analysis including 3100 CLL cases and 7667 controls and (ii) established CLL loci and NMSC risk in a study of 4242 basal cell carcinoma (BCC) cases, 825 squamous cell carcinoma (SCC) cases and 12802 controls. Polygenic risk scores (PRS) for CLL, BCC and SCC were constructed using established loci. Logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs).Results: Higher CLL-PRS was associated with increased BCC risk (OR4th-quartile-vs-1st-quartile = 1.13, 95% CI: 1.02-1.24, Ptrend = 0.009), even after removing the shared 6p25.3 locus. No association was observed with BCC-PRS and CLL risk (Ptrend = 0.68). These findings support a contributory role for CLL in BCC risk, but not for BCC in CLL risk. Increased CLL risk was observed with higher SCC-PRS (OR4th-quartile-vs-1st-quartile = 1.22, 95% CI: 1.08-1.38, Ptrend = 1.36 × 10-5), which was driven by shared genetic susceptibility at the 6p25.3 locus.Conclusion: These findings highlight the role of pleiotropy regarding the pathogenesis of CLL and NMSC and shows that a single pleiotropic locus, 6p25.3, drives the observed association between genetic susceptibility to SCC and increased CLL risk. The study also provides evidence that genetic susceptibility for CLL increases BCC risk. [ABSTRACT FROM AUTHOR]

Sex‐biased gene expression, particularly sex‐biased expression in the gonad, has been linked to rates of protein sequence evolution (nonsynonymous to synonymous substitutions, dN/dS) in animals. However, in insects, sex‐biased expression studies remain centred on a few holometabolous species. Moreover, other major tissue types such as the brain remain underexplored. Here, we studied sex‐biased gene expression and protein evolution in a hemimetabolous insect, the cricket Gryllus bimaculatus. We generated novel male and female RNA‐seq data for two sexual tissue types, the gonad and somatic reproductive system, and for two core components of the nervous system, the brain and ventral nerve cord. From a genome‐wide analysis, we report several core findings. Firstly, testis‐biased genes had accelerated evolution, as compared to ovary‐biased and unbiased genes, which was associated with positive selection events. Secondly, although sex‐biased brain genes were much less common than for the gonad, they exhibited a striking tendency for rapid protein sequence evolution, an effect that was stronger for the female than male brain. Further, some sex‐biased brain genes were linked to sexual functions and mating behaviours, which we suggest may have accelerated their evolution via sexual selection. Thirdly, a tendency for narrow cross‐tissue expression breadth, suggesting low pleiotropy, was observed for sex‐biased brain genes, suggesting relaxed purifying selection, which we speculate may allow enhanced freedom to evolve adaptive protein functional changes. The findings of rapid evolution of testis‐biased genes and male and female‐biased brain genes are discussed with respect to pleiotropy, positive selection and the mating biology of this cricket. [ABSTRACT FROM AUTHOR]

Community association populations are composed of phenotypically and genetically diverse accessions. Once these populations are genotyped, the resulting marker data can be reused by different groups investigating the genetic basis of different traits. Because the same genotypes are observed and scored for a wide range of traits in different environments, these populations represent a unique resource to investigate pleiotropy. Here, we assembled a set of 234 separate trait datasets for the Sorghum Association Panel, a group of 406 sorghum genotypes widely employed by the sorghum genetics community. Comparison of genome-wide association studies (GWAS) conducted with two independently generated marker sets for this population demonstrate that existing genetic marker sets do not saturate the genome and likely capture only 35-43% of potentially detectable loci controlling variation for traits scored in this population. While limited evidence for pleiotropy was apparent in cross-GWAS comparisons, a multivariate adaptive shrinkage approach recovered both known pleiotropic effects of existing loci and new pleiotropic effects, particularly significant impacts of known dwarfing genes on root architecture. In addition, we identified new loci with pleiotropic effects consistent with known trade-offs in sorghum development. These results demonstrate the potential for mining existing trait datasets from widely used community association populations to enable new discoveries from existing trait datasets as new, denser genetic marker datasets are generated for existing community association populations. [ABSTRACT FROM AUTHOR]

In North American gray wolves, black coat color is dominantly inherited via a 3 base pair coding deletion in the canine beta defensin 3 (CBD103) gene. This 3 base pair deletion, called the K B allele, was introduced through hybridization with dogs and subsequently underwent a selective sweep that increased its frequency in wild wolves. Despite apparent positive selection, K BB wolves have lower fitness than wolves with the K yB genotype, even though the 2 genotypes show no observable differences in black coat color. Thus, the K B allele is thought to have pleiotropic effects on as-yet unknown phenotypes. Given the role of skin-expressed CBD103 in innate immunity, we hypothesized that the K B allele influences the keratinocyte gene expression response to TLR3 pathway stimulation and/or infection by canine distemper virus (CDV). To test this hypothesis, we developed a panel of primary epidermal keratinocyte cell cultures from 24 wild North American gray wolves of both K yy and K yB genotypes. In addition, we generated an immortalized K yy line and used CRISPR/Cas9 editing to produce a K yB line on the same genetic background. We assessed the transcriptome-wide responses of wolf keratinocytes to the TLR3 agonist polyinosinic:polycytidylic acid (polyI:C), and to live CDV. K locus genotype did not predict the transcriptional response to either challenge, suggesting that variation in the gene expression response does not explain pleiotropic effects of the K B allele on fitness. This study supports the feasibility of using cell culture methods to investigate the phenotypic effects of naturally occurring genetic variation in wild mammals. [ABSTRACT FROM AUTHOR]

Pyrethroid resistance in the redlegged earth mite, Halotydeus destructor (Tucker), is primarily attributed to a kdr (knockdown resistance) mutation in the parasodium channel gene. To assess fitness costs associated with this resistance, adult resistant and susceptible populations were mixed in different proportions in microcosm tubs and placed in a shade-house simulating field conditions. Three separate experiments were undertaken whereby parental mites were collected from the field and offspring were followed for two to three generations. The association between fitness costs and kdr -mediated resistance was investigated by examining differences in mite numbers and changes in resistant allele frequencies across generations. In two (of the three) experiments, the population fitness measure of mites was significantly lower in microcosms containing a higher proportion of resistant individuals compared with treatments containing susceptible mites. No differences in mite fitness were observed between treatments in the third experiment; in this instance, the starting proportion of individuals homozygous for the resistant mutation was much lower (~40%) than in the other experiments (>90%). In all three experiments, a decrease in the resistant allele frequency across mite generations was observed. These findings indicate a potential deleterious pleiotropic effect of the kdr mutation on the fitness of H. destructor and have implications for resistance management strategies aimed at this important agricultural pest. Further experiments investigating fitness costs directly in the field are warranted. [ABSTRACT FROM AUTHOR]

Attenuation of FXI activity inhibiting either FXI or FXIa leads to reduced thrombin formation and venous thromboemblism (light arrows), while the extrinsic pathway and the contact pathway remain unaffected (dark arrows). FXI can be activated via either of two enzymes, FXIIa in the contact activation pathway and thrombin, generated by the downstream intrinsic coagulation pathway. Keywords: Factor XI; Thrombosis; Anticoagulants; Prevention; Pleiotropy EN Factor XI Thrombosis Anticoagulants Prevention Pleiotropy e72 e74 3 08/09/22 20220615 NES 220615 With the landmark studies showing comparable efficacy and safety for direct oral anticoagulants (DOACs) and vitamin K antagonists (VKAs), the principle of antithrombotic therapy through targeting single coagulation proteases was demonstrated and clinically embraced.[1] DOACs are rapidly replacing VKA for many common indications, like atrial fibrillation (AF) and venous thromboembolism (VTE). [Extracted from the article]

We previously identified a cluster of yield-related quantitative trait loci (QTLs) including plant height in CR4379, a near-isogenic line from a cross between Oryza sativa spp. japonica cultivar 'Hwaseong' and the wild relative Oryza rufipogon. Map-based cloning and transgenic approaches revealed that APX9 , which encodes an l -ascorbate peroxidase 4, is associated with this cluster. A 3 bp InDel was observed leading to the addition of a valine in Hwaseong compared with O. rufipogon. APX9- overexpressing transgenic plants in the Hwaseong background were taller than Hwaseong. Consistent with these results, APX9 T-DNA insertion mutants in the japonica cultivar Dongjin were shorter. These results confirm that APX9 is the causal gene for the QTL cluster. Sequence analysis of APX9 from 303 rice accessions revealed that the 3 bp InDel clearly differentiates japonica (APX9 HS) and O. rufipogon (APX9 OR) alleles. indica accessions shared both alleles, suggesting that APX9 HS was introgressed into indica followed by crossing. The finding that O. rufipogon accessions with different origins carry APX9 OR suggests that the 3 bp insertion was specifically selected in japonica during its domestication. Our findings demonstrate that APX9 acts as a major regulator of plant development by controlling a valuable suite of agronomically important traits in rice. [ABSTRACT FROM AUTHOR]