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The study was conducted with the objective of estimating genetic and phenotypic parameters for tick (CRM) and Babesia bigemina (IBBi), Babesia bovis (IBBo), and Anaplasma marginale (IAM) burden in Angus female breed in Brazil. The sample group was composed of Angus females raised in herds located in a region of endemic instability for cattle tick fever in the state of Rio Grande Sul (RS), Brazil. The variance components were estimated using Bayesian inference and Gibbs sampling algorithm, considering a multi-trait animal model. Heritability estimates showed values of low magnitude, ranging from 0.03 (IBBo) to 0.16 (CRM), while repeatability estimates ranged between 0.07 (IBBo) and 0.21 (CRM). Regarding the genetic correlation estimates, the values showed low (-0.01 for IBBo × IAM) to moderate (0.55 between IBBi × IAM) magnitudes. The results indicate that it is possible to use tick count and hemoparasite infection levels as selection criteria, with small genetic gains.

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Visceral leishmaniasis (VL) is a potentially fatal disease caused mainly by Leishmania infantum in South America and Leishmania donovani in Asia and Africa. Disease outcomes have been associated with patient genotype, nutrition, age, sex, comorbidities, and coinfections. In this study, we examine the effects of parasite genetic variation on VL disease severity in Brazil. We collected and sequenced the genomes of 109 L. infantum isolates from patients in northeastern Brazil and retrieved matching patient clinical data from medical records, including mortality, sex, HIV coinfection, and laboratory data (creatinine, hemoglobin, and leukocyte and platelet counts). We identified genetic differences between parasite isolates, including single nucleotide polymorphisms (SNPs), small insertions/deletions (indels), and variations in genic, intergenic, and chromosome copy numbers (copy number variants [CNVs]). To describe associations between the parasite genotypes and clinical outcomes, we applied quantitative genetics methods of heritability and genome-wide association studies (GWAS), treating clinical outcomes as traits that may be influenced by parasite genotype. Multiple aspects of the genetic analysis indicate that parasite genotype affects clinical outcomes. We estimate that parasite genotype explains 83% chance of mortality (narrow-sense heritability [h2] = 0.83 ± 0.17) and has a significant relationship with patient sex (h2 = 0.60 ± 0.27). Impacts of parasite genotype on other clinical traits are lower (h2 ≤ 0.34). GWAS analysis identified multiple parasite genetic loci that were significantly associated with clinical outcomes; 17 CNVs were significantly associated with mortality, two with creatinine, and one with bacterial coinfection, jaundice, and HIV coinfection, and two SNPs/indels and six CNVs were associated with age, jaundice, HIV and bacterial coinfections, creatinine, and/or bleeding sites. Parasite genotype is an important factor in VL disease severity in Brazil. Our analysis indicates that specific genetic differences between parasites act as virulence factors, enhancing risks of severe disease and mortality. More detailed understanding of these virulence factors could be exploited for novel therapies. IMPORTANCE Multiple factors contribute to the risk of mortality from visceral leishmaniasis (VL), including, patient genotype, comorbidities, and nutrition. Many of these factors are influenced by socioeconomic biases. Our work suggests that the virulence of the infecting parasite is an important risk factor for mortality. We pinpoint some specific genomic markers that are associated with mortality, which can lead to a greater understanding of the molecular mechanisms that cause severe VL disease, to the identification of genetic markers for virulent parasites, and to the development of drug and vaccine therapies.

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Anastrepha fraterculus (Wiedmann) is an important American pest species. Knowledge of its population dynamics is of particular interest for ecology, evolutionary biology, and management programs. In the present study, phenotypic, genotypic, and spatial data were combined, within the frame of landscape genetics, to uncover the spatial population genetic structure (SGS) and demographic processes of an Argentinian local population from the Yungas ecoregion. Eight simple sequence repeats (SSR) loci and six morphometric traits were analysed considering the hierarchical levels: tree/fruit/individual. Genetic variability estimates were high (HE = 0.72, RA = 4.39). Multivariate analyses of phenotypic data showed that in average 52.81% of variance is explained by the tree level, followed by between individuals 28.37%. Spatial analysis of morphological traits revealed a negative autocorrelation in all cases. SGS analysis and isolation by distance based on SSR showed no significant autocorrelation for molecular coancestry. The comparison between phenotypic (PST) and molecular (FST) differentiation identified positive selection in different fruits for all traits. Bayesian analysis revealed a cryptic structure within the population, with three clusters spatially separated. The results of this study showed a metapopulation dynamics. The genetic background of the components of this metapopulation is expected to change through time due to seasonality, repopulation activities, and high gene flow, with an estimated dispersal ability of at least 10 km. Effective population size (Ne) of the metapopulation was estimated in around 800 flies, and within subpopulations (clusters) Ne was associated with the levels of genetic drift experienced by the founding lineages.

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The detection of spatial variability in field trials has great potential for accelerating plant breeding progress due to the possibility of better controlling non-genetic variation. Therefore, we aimed to evaluate a digital soil mapping approach and a high-density soil sampling procedure for identifying and adjusting spatial dependence in the early sugarcane breeding stage. Two experiments were conducted in regions with different soil classifications. High-density sampling of soil physical and chemical properties was performed in a regular grid to investigate the structure of spatial variability. Soil apparent electrical conductivity (ECa) was measured in both experimental areas with an EM38-MK2® sensor. In addition, principal component analysis (PCA) was employed to reduce the dimensionality of the physical and chemical soil data sets. After conducting the PCA and obtaining different thematic maps, we determined each experimental plot's exact position within the field. Tons of cane per hectare (TCH) data for each experiment were obtained and analyzed using mixed linear models. When environmental covariates were considered, a previous forward model selection step was applied to incorporate the variables. The PCA based on high-density soil sampling data captured part of the total variability in the data for Experimental Area 1 and was suggested to be an efficient index to be incorporated as a covariate in the statistical model, reducing the experimental error (residual variation coefficient, CVe). When incorporated into the different statistical models, the ECa information increased the selection accuracy of the experimental genotypes. Therefore, we demonstrate that the genetic parameter increased when both approaches (spatial analysis and environmental covariates) were employed.

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Biddick & Burns (2021) proposed a null/neutral model that reproduces the island rule as a product of random drift. We agree that it is unnecessary to assume adaptive processes driving island dwarfing or gigantism, but several flaws make their approach unrealistic and thus unsuitable as a stochastic model for evolutionary size changes.

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Our objectives were to estimate genetic parameters for male and female reproductive traits and their genetic correlations with body weight and carcass traits, evaluate the genetic trends over the years, and verify the effect of inbreeding on the phenotypes of Brahman cattle. The traits evaluated were body weights at 120, 210, 365, and 450 days of age (W120, W210, W365, and W450); scrotal circumference at 365 and 450 days of age (SC365 and SC450), age at first calving (AFC), gestation length (GL), stayability (STAY), ribeye area (REA), backfat thickness (BFT), and rump fat thickness (RFT). Direct heritability estimates ranged from 0.10 ± 0.03 (AFC) to 0.43 ± 0.06 (GL). Maternal heritability estimates for body weights, scrotal circumferences, and GL ranged from 0.07 ± 0.02 to 0.15 ± 0.03. The proportion of the maternal permanent environment for W120 and W210 was equal to 0.11 ± 0.02. Genetic correlations varied between -0.60 ± 0.25 (STAY and BFT) to 0.97 ± 0.01 (W365 and W450). Except for AFC, all genetic trends were significant (p < 0.05) and presented favorable annual genetic gains. Unfavorable effects due to the increase of inbreeding coefficients were observed for body weights and AFC, suggesting greater attention be paid to the applied mating systems to control inbreeding. Reproductive traits, such as AFC and STAY, could be assisted indirectly by scrotal circumference selection. The emphasis applied to body weight selection, especially at W210, may assist REA. The BFT and RFT traits presented genetic variability and have responded to selection, although not included in the Brahman selection index.

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The data in this article includes 300 simulated two-way data tables with 200 genotypes in the rows and 12 environments in the columns each. The yield data was obtained from a genotype-to-phenotype crop growth model that was adapted for pepper. The genotypes were characterized by 237 markers covering all the 12 chromosomes, and the environments were obtained as a combination of: (i) two levels of radiation based on historical data; (ii) three levels of daily average temperatures, 15, 20 and 25 °C; and (iii) two countries, Spain and The Netherlands. 100 two-way data tables were obtained for each of the three levels of heritability in the environments, 0.3, 0.5 and 0.8. The data is available as supplementary material of this paper.

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Breeding for grain yield (GY) in bread wheat at the International Maize and Wheat Improvement Center (CIMMYT) involves three-stage testing at Obregon, Mexico in different selection environments (SEs). To understand the efficiency of selection in the SEs, we performed a large retrospective quantitative genetics study using CIMMYT's yield trials evaluated in the SEs (2013-2014 to 2017-2018), the South Asia Bread Wheat Genomic Prediction Yield Trials (SABWGPYTs) evaluated in India, Pakistan, and Bangladesh (2014-2015 to 2017-2018), and the Elite Spring Wheat Yield Trials (ESWYTs) evaluated in several sites globally (2003-2004 to 2016-2017). First, we compared the narrow-sense heritabilities in the Obregon SEs and target sites and observed that the mean heritability in the SEs was 44.2 and 92.3% higher than the mean heritabilities in the SABWGPYT and ESWYT sites, respectively. Second, we observed significant genetic correlations between a SE in Obregon and all the five SABWGPYT sites and 65.1% of the ESWYT sites. Third, we observed high ratios of response to indirect selection in the SEs of Obregon with a mean of 0.80 ± 0.21 and 2.6 ± 5.4 in the SABWGPYT and ESWYT sites, respectively. Furthermore, our results also indicated that for all the SABWGPYT sites and 82% of the ESWYT sites, a response greater than 0.5 can be achieved by indirect selection for GY in Obregon. We also performed genomic prediction for GY in the target sites using the performance of the same lines in the SEs of Obregon and observed moderate mean prediction accuracies of 0.24 ± 0.08 and 0.28 ± 0.08 in the SABWGPYT and ESWYT sites, respectively using the genotype x environment (GxE) model. However, we observed similar accuracies using the baseline model with environment and line effects and no advantage of modeling GxE interactions. Overall, this study provides important insights into the suitability of the Obregon SEs in breeding for GY, while the variable genomic predictabilities of GY and the high year-to-year GY fluctuations reported, highlight the importance of multi-environment testing across time and space to stave off GxE induced uncertainties in varietal yields.

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Changes in landscape structure can affect essential population ecological features, such as dispersal and recruitment, and thus genetic processes. Here, we analyze the effects of landscape metrics on adaptive quantitative traits variation, evolutionary potential, and on neutral genetic diversity in populations of the Neotropical savanna tree Tabebuia aurea. Using a multi-scale approach, we sampled five landscapes with two sites of savanna in each. To obtain neutral genetic variation, we genotyped 60 adult individuals from each site using 10 microsatellite loci. We measured seed size and mass. Seeds were grown in nursery in completely randomized experimental design and 17 traits were measured in seedlings to obtain the average, additive genetic variance (V a ) and coefficient of variation (CV a %), which measures evolvability, for each trait. We found that habitat loss increased genetic diversity (He) and allelic richness (AR), and decreased genetic differentiation among populations (F ST ), most likely due to longer dispersal distance of pollen in landscapes with lower density of flowering individuals. Habitat amount positively influenced seed size. Seeds of T. aurea are wind-dispersed and larger seeds may be dispersed to short distance, increasing genetic differentiation and decreasing genetic diversity and allelic richness. Evolvability (CV a %) in root length decreased with habitat amount. Savanna trees have higher root than shoot growth rate in the initial stages, allowing seedlings to obtain water from water tables. Landscapes with lower habitat amount may be more stressful for plant species, due to the lower plant density, edge effects and the negative impacts of agroecosystems. In these landscapes, larger roots may provide higher ability to obtain water, increasing survival and avoiding dying back because of fire. Despite the very recent agriculture expansion in Central Brazil, landscape changes are affecting neutral and adaptive variation in T. aurea. Several populations have low additive genetic variation for some traits and thus, may have limited evolvability, which may jeopardize species long-term persistence. The effect of habitat loss on highly variable neutral loci may only be detected after a certain threshold of population size is attained, that could become dangerously small masking important losses of heterozygosity endangering species conservation.

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Plants are one of the most vulnerable groups to fragmentation and habitat loss, that may affect community richness, abundance, functional traits, and genetic diversity. Here, we address the effects of landscape features on adaptive quantitative traits and evolutionary potential, and on neutral genetic diversity in populations of the Neotropical savanna tree Caryocar brasiliense. We sampled adults and juveniles in 10 savanna remnants within five landscapes. To obtain neutral genetic variation, we genotyped all individuals from each site using nine microsatellite loci. For adaptive traits we measured seed size and mass and grown seeds in nursery in completely randomized experimental design. We obtained mean, additive genetic variance (V a ) and coefficient of variation (CV a %), which measures evolvability, for 17 traits in seedlings. We found that landscapes with higher compositional heterogeneity (SHDI) had lower evolutionary potential (CV a %) in leaf length (LL) and lower aboveground dry mass (ADM) genetic differentiation (Q ST ). We also found that landscapes with higher SHDI had higher genetic diversity (He) and allelic richness (AR) in adults, and lower genetic differentiation (F ST ). In juveniles, SHDI was also positively related to AR. These results are most likely due to longer dispersal distance of pollen in landscapes with lower density of flowering individuals. Agricultural landscapes with low quality mosaic may be more stressful for plant species, due to the lower habitat cover (%), higher cover of monocropping (%) and other land covers, and edge effects. However, in landscapes with higher SHDI with high quality mosaic, forest nearby savanna habitat and the other environments may facilitate the movement or provide additional habitat and resources for seed disperses and pollinators, increasing gene flow and genetic diversity. Finally, despite the very recent agriculture expansion in Central Brazil, we found no time lag in response to habitat loss, because both adults and juveniles were affected by landscape changes.

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We explored the evolution of morphological integration in the most noteworthy example of adaptive radiation in mammals, the New World leaf-nosed bats, using a massive dataset and by combining phylogenetic comparative methods and quantitative genetic approaches. We demonstrated that the phenotypic covariance structure remained conserved on a broader phylogenetic scale but also showed a substantial divergence between interclade comparisons. Most of the phylogenetic structure in the integration space can be explained by splits at the beginning of the diversification of major clades. Our results provide evidence for a multiple peak adaptive landscape in the evolution of cranial covariance structure and morphological differentiation, based upon diet and roosting ecology. In this scenario, the successful radiation of phyllostomid bats was triggered by the diversification of dietary and roosting strategies, and the invasion of these new adaptive zones lead to changes in phenotypic covariance structure and average morphology. Our results suggest that intense natural selection preceded the invasion of these new adaptive zones and played a fundamental role in shaping cranial covariance structure and morphological differentiation in this hyperdiverse clade of mammals. Finally, our study demonstrates the power of combining comparative methods and quantitative genetic approaches when investigating the evolution of complex morphologies.

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Forest tree breeding has been successful at delivering genetically improved material for multiple traits based on recurrent cycles of selection, mating, and testing. However, long breeding cycles, late flowering, variable juvenile-mature correlations, emerging pests and diseases, climate, and market changes, all pose formidable challenges. Genetic dissection approaches such as quantitative trait mapping and association genetics have been fruitless to effectively drive operational marker-assisted selection (MAS) in forest trees, largely because of the complex multifactorial inheritance of most, if not all traits of interest. The convergence of high-throughput genomics and quantitative genetics has established two new paradigms that are changing contemporary tree breeding dogmas. Genomic selection (GS) uses large number of genome-wide markers to predict complex phenotypes. It has the potential to accelerate breeding cycles, increase selection intensity and improve the accuracy of breeding values. Realized genomic relationships matrices, on the other hand, provide innovations in genetic parameters' estimation and breeding approaches by tracking the variation arising from random Mendelian segregation in pedigrees. In light of a recent flow of promising experimental results, here we briefly review the main concepts, analytical tools and remaining challenges that currently underlie the application of genomics data to tree breeding. With easy and cost-effective genotyping, we are now at the brink of extensive adoption of GS in tree breeding. Areas for future GS research include optimizing strategies for updating prediction models, adding validated functional genomics data to improve prediction accuracy, and integrating genomic and multi-environment data for forecasting the performance of genetic material in untested sites or under changing climate scenarios. The buildup of phenotypic and genome-wide data across large-scale breeding populations and advances in computational prediction of discrete genomic features should also provide opportunities to enhance the application of genomics to tree breeding.

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La ley del equilibrio Hardy-Weinberg es la piedra angular de la genética de poblaciones y la genética cuantitativa; sin embargo, para su cálculo en autopoliploides hay que tener en cuenta que las frecuencias alélicas y gaméticas son diferentes, caso contrario que los diploides donde son iguales. Esto ocasiona que el cálculo de esta fórmula deba hacerse con las frecuencias alélicas o las gaméticas basadas en las alélicas, de otra forma se puede romper el equilibrio de la población y el sesgo que esto conlleva en cálculos de otras pruebas como los estadísticos F de Wright, la GST de Nei o modelos bayesianos que se basan en los desequilibrios que presentan las poblaciones. Por eso este ensayo desarrolla los modelos de un locus con dos alelos en genotipos autotetraploides y autooctoploides para poder realizar una generalización de la ley del equilibrio en poblaciones autopoliploides.

The law of equilibrium Hardy-Weinberg is the cornerstone of the population genetics and of the quantitative genetics; however, for its calculation in autopolyploids it is necessary take in account that the allelic and gametic frequencies are different, contrary to the diploids where they are the same. This causes that the calculations must be done with the allelic frequencies or gametic based on allelic frequencies. Otherwise the equilibrium is broken in the population and the bias that this entails in the calculation of other genetical test like Wright's F statistics, the Nei's GST or Bayesian models that are based on the disequilibrium that populations show. That is why in this work they developed models of one locus with two alleles in autotetraploid and autooctoploid genotypes to make a generalization of the law of equilibrium in autopolyploid populations.

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Both modern humans (MHs) and Neanderthals successfully settled across western Eurasian cold-climate landscapes. Among the many adaptations considered as essential to survival in such landscapes, changes in the nasal morphology and/or function aimed to humidify and warm the air before it reaches the lungs are of key importance. Unfortunately, the lack of soft-tissue evidence in the fossil record turns difficult any comparative study of respiratory performance. Here, we reconstruct the internal nasal cavity of a Neanderthal plus two representatives of climatically divergent MH populations (southwestern Europeans and northeastern Asians). The reconstruction includes mucosa distribution enabling a realistic simulation of the breathing cycle in different climatic conditions via computational fluid dynamics. Striking across-specimens differences in fluid residence times affecting humidification and warming performance at the anterior tract were found under cold/dry climate simulations. Specifically, the Asian model achieves a rapid air conditioning, followed by the Neanderthals, whereas the European model attains a proper conditioning only around the medium-posterior tract. In addition, quantitative-genetic evolutionary analyses of nasal morphology provided signals of stabilizing selection for MH populations, with the removal of Arctic populations turning covariation patterns compatible with evolution by genetic drift. Both results indicate that, departing from important craniofacial differences existing among Neanderthals and MHs, an advantageous species-specific respiratory performance in cold climates may have occurred in both species. Fluid dynamics and evolutionary biology independently provided evidence of nasal evolution, suggesting that adaptive explanations regarding complex functional phenotypes require interdisciplinary approaches aimed to quantify both performance and evolutionary signals on covariation patterns.

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The importance of the environment in shaping phenotypic evolution lies at the core of evolutionary biology. Chipmunks of the genus Tamias (subgenus Neotamias) are part of a very recent radiation, occupying a wide range of environments with marked niche partitioning among species. One open question is if and how those differences in environments affected phenotypic evolution in this lineage. Herein we examine the relative importance of genetic drift versus natural selection in the origin of cranial diversity exhibited by clade members. We also explore the degree to which variation in potential selective agents (environmental variables) are correlated with the patterns of morphological variation presented. We found that genetic drift cannot explain morphological diversification in the group, thus supporting the potential role of natural selection as the predominant evolutionary force during Neotamias cranial diversification, although the strength of selection varied greatly among species. This morphological diversification, in turn, was correlated with environmental conditions, suggesting a possible causal relationship. These results underscore that extant Neotamias represent a radiation in which aspects of the environment might have acted as the selective force driving species' divergence.

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There are two heuristic explanations proposed for the evolution of endothermy in vertebrates: a correlated response to selection for stable body temperatures, or as a correlated response to increased activity. Parental care has been suggested as a major driving force in this context given its impact on the parents' activity levels and energy budgets, and in the offspring's growth rates due to food provisioning and controlled incubation temperature. This results in a complex scenario involving multiple traits and transgenerational fitness benefits that can be hard to disentangle, quantify and ultimately test. Here we demonstrate how standard quantitative genetic models of maternal effects can be applied to study the evolution of endothermy, focusing on the interplay between daily energy expenditure (DEE) of the mother and growth rates of the offspring. Our model shows that maternal effects can dramatically exacerbate evolutionary responses to selection in comparison to regular univariate models (breeder's equation). This effect would emerge from indirect selection mediated by maternal effects concomitantly with a positive genetic covariance between DEE and growth rates. The multivariate nature of selection, which could favor a higher DEE, higher growth rates or both, might partly explain how high turnover rates were continuously favored in a self-reinforcing process. Overall, our quantitative genetic analysis provides support for the parental care hypothesis for the evolution of endothermy. We contend that much has to be gained from quantifying maternal and developmental effects on metabolic and thermoregulatory variation during adulthood.

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Phenotypic (co)variation is a prerequisite for evolutionary change, and understanding how (co)variation evolves is of crucial importance to the biological sciences. Theoretical models predict that under directional selection, phenotypic (co)variation should evolve in step with the underlying adaptive landscape, increasing the degree of correlation among co-selected traits as well as the amount of genetic variance in the direction of selection. Whether either of these outcomes occurs in natural populations is an open question and thus an important gap in evolutionary theory. Here, we documented changes in the phenotypic (co)variation structure in two separate natural populations in each of two chipmunk species (Tamias alpinus and T. speciosus) undergoing directional selection. In populations where selection was strongest (those of T. alpinus), we observed changes, at least for one population, in phenotypic (co)variation that matched theoretical expectations, namely an increase of both phenotypic integration and (co)variance in the direction of selection and a re-alignment of the major axis of variation with the selection gradient.

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The study of the cephalic shape of crocodilian is relevant in the fields of ecology, systematics, evolution, and conservation. Therefore, the integration of geometric analysis within quantitative genetics allows the evaluation of the inheritable shape components. In this study, the dorsal cephalic region of 210 Caiman latirostris hatchlings was analyzed from seven populations in Santa Fe, Argentina, to detect intra-, and inter-population phenotypic variability, and to determine the heritability of biological shape and size, using newly available geometric morphometric tools. The principal component analysis showed two configurations of cephalic shape that could be related to sexual dimorphism. In the canonical variate analysis, Procrustes distances between groups indicated that there are differences in shape among populations. Furthermore, the method of partial least squares indicated a covariation between cephalic shape and environmental variables. Regarding to CS of the skull we found significant differences among populations, moreover the partial least squares was also significant. Estimates of the heritability of shape and size were high, indicating that the components of these features are susceptible to the selection.

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Modularity is a central concept in modern biology, providing a powerful framework for the study of living organisms on many organizational levels. Two central and related questions can be posed in regard to modularity: How does modularity appear in the first place, and what forces are responsible for keeping and/or changing modular patterns? We approached these questions using a quantitative genetics simulation framework, building on previous results obtained with bivariate systems and extending them to multivariate systems. We developed an individual-based model capable of simulating many traits controlled by many loci with variable pleiotropic relations between them, expressed in populations subject to mutation, recombination, drift, and selection. We used this model to study the problem of the emergence of modularity, and hereby show that drift and stabilizing selection are inefficient at creating modular variational structures. We also demonstrate that directional selection can have marked effects on the modular structure between traits, actively promoting a restructuring of genetic variation in the selected population and potentially facilitating the response to selection. Furthermore, we give examples of complex covariation created by simple regimes of combined directional and stabilizing selection and show that stabilizing selection is important in the maintenance of established covariation patterns. Our results are in full agreement with previous results for two-trait systems and further extend them to include scenarios of greater complexity. Finally, we discuss the evolutionary consequences of modular patterns being molded by directional selection.

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