scholarly journals Introduced populations of ragweed show as much evolutionary potential as native populations

2018 ◽  
Author(s):  
Brechann V. McGoey ◽  
John R. Stinchcombe
Keyword(s):  
Genetic Architecture ◽  
Genetic Variance ◽  
Additive Genetic Variance ◽  
Ambrosia Artemisiifolia ◽  
Empirical Literature ◽  
Ecological Problem ◽  
Adaptive Potential ◽  
Evolutionary Potential ◽  
Introduced Populations ◽  
Native Populations

AbstractInvasive species are a global economic and ecological problem. They also offer an opportunity to understand evolutionary processes in a colonizing context. The impacts of evolutionary factors, such as genetic variation, on the invasion process are increasingly appreciated but there remain gaps in the empirical literature. The adaptive potential of populations can be quantified using genetic variance-covariance matrices (G), which encapsulate the heritable genetic variance in a population. Here, we use a multivariate, Bayesian approach to assess the adaptive potential of introduced populations of ragweed, Ambrosia artemisiifolia, a serious allergen and agricultural weed. We compared several aspects of genetic architecture and the structure of G matrices between three native and three introduced populations, based on data collected in the field in a common garden experiment. We find moderate differences in the quantitative genetic architecture among populations, but we do not find that introduced populations suffer from a limited adaptive potential compared to native populations. Ragweed has an annual life history, is an obligate outcrosser, and produces billions of seeds and pollen grains per. These characteristics, combined with the significant additive genetic variance documented here, suggest ragweed will be able to respond quickly to selection pressures in both its native and introduced ranges.

scholarly journals Genetic variance in fitness and its cross-sex covariance predict adaptation during experimental evolution

2020 ◽  
Author(s):  
Eva L. Koch ◽  
Sonja H. Sbilordo ◽  
Frédéric Guillaume
Keyword(s):  
Experimental Evolution ◽  
Genetic Variance ◽  
Environmental Changes ◽  
Additive Genetic Variance ◽  
Relative Fitness ◽  
Male Fitness ◽  
Adaptive Potential ◽  
Genetic Covariance ◽  
Flour Beetles ◽  
Single Stress

AbstractIn presence of rapid environmental changes, it is of particular importance to assess the adaptive potential of populations, which is mostly determined by the additive genetic variation (VA) in fitness. In this study we used Tribolium castaneum (red flour beetles) to investigate its adaptive potential in three new environmental conditions (Dry, Hot, Hot-Dry). We tested for potential constraints that might limit adaptation, including negative genetic covariance between female and male fitness. Based on VA estimates for fitness, we expected the highest relative fitness increase in the most stressful condition Hot-Dry and similar increases in single stress conditions Dry and Hot. High adaptive potential in females in Hot was reduced by a negative covariance with male fitness. We tested adaptation to the three conditions after 20 generations of experimental evolution and found that observed adaptation mainly matched our predictions. Given that body size is commonly used as a proxy for fitness, we also tested how this trait and its genetic variance (including non-additive genetic variance) were impacted by environmental stress. In both traits, variances were sex and condition dependent, but they differed in their variance composition, cross-sex and cross-environment genetic covariances, as well as in the environmental impact on VA.

scholarly journals A guide to using a multiple-matrix animal model to disentangle genetic and nongenetic causes of phenotypic variance

2018 ◽  
Author(s):  
Caroline E. Thomson ◽  
Isabel S. Winney ◽  
Oceane C. Salles ◽  
Benoit Pujol
Keyword(s):  
Animal Model ◽  
Genetic Variance ◽  
Genetic Relatedness ◽  
Additive Genetic Variance ◽  
Phenotypic Traits ◽  
Phenotypic Variance ◽  
Data Types ◽  
Evolutionary Potential ◽  
Recent Developments

AbstractNon-genetic influences on phenotypic traits can affect our interpretation of genetic variance and the evolutionary potential of populations to respond to selection, with consequences for our ability to predict the outcomes of selection. Long-term population surveys and experiments have shown that quantitative genetic estimates are influenced by nongenetic effects, including shared environmental effects, epigenetic effects, and social interactions. Recent developments to the “animal model” of quantitative genetics can now allow us to calculate precise individual-based measures of non-genetic phenotypic variance. These models can be applied to a much broader range of contexts and data types than used previously, with the potential to greatly expand our understanding of nongenetic effects on evolutionary potential. Here, we provide the first practical guide for researchers interested in distinguishing between genetic and nongenetic causes of phenotypic variation in the animal model. The methods use matrices describing individual similarity in nongenetic effects, analogous to the additive genetic relatedness matrix. In a simulation of various phenotypic traits, accounting for environmental, epigenetic, or cultural resemblance between individuals reduced estimates of additive genetic variance, changing the interpretation of evolutionary potential. These variances were estimable for both direct and parental nongenetic variances. Our tutorial outlines an easy way to account for these effects in both wild and experimental populations. These models have the potential to add to our understanding of the effects of genetic and nongenetic effects on evolutionary potential. This should be of interest both to those studying heritability, and those who wish to understand nongenetic variance.

VERY LOW ADDITIVE GENETIC VARIANCE AND EVOLUTIONARY POTENTIAL IN MULTIPLE POPULATIONS OF TWO RAINFOREST DROSOPHILA SPECIES

Evolution ◽  
2006 ◽  
Vol 60 (5) ◽  
pp. 1104 ◽  
Author(s):  
Vanessa M. Kellermann ◽  
Belinda van Heerwaarden ◽  
Ary A. Hoffmann ◽  
Carla M. Sgrò
Keyword(s):  
Genetic Variance ◽  
Additive Genetic Variance ◽  
Drosophila Species ◽  
Evolutionary Potential ◽  
Multiple Populations

scholarly journals The genetic architecture of teosinte catalyzed and constrained maize domestication

2019 ◽  
Vol 116 (12) ◽  
pp. 5643-5652 ◽  
Author(s):  
Chin Jian Yang ◽  
Luis Fernando Samayoa ◽  
Peter J. Bradbury ◽  
Bode A. Olukolu ◽  
Wei Xue ◽  
...  
Keyword(s):  
Genetic Architecture ◽  
Genetic Variance ◽  
Additive Genetic Variance ◽  
Genetic Correlations ◽  
Reproductive Traits ◽  
Maize Landrace ◽  
Dominance Genetic Variance ◽  
Trait Locus ◽  
Maize Domestication ◽  
Selection Intensities

The process of evolution under domestication has been studied using phylogenetics, population genetics–genomics, quantitative trait locus (QTL) mapping, gene expression assays, and archaeology. Here, we apply an evolutionary quantitative genetic approach to understand the constraints imposed by the genetic architecture of trait variation in teosinte, the wild ancestor of maize, and the consequences of domestication on genetic architecture. Using modern teosinte and maize landrace populations as proxies for the ancestor and domesticate, respectively, we estimated heritabilities, additive and dominance genetic variances, genetic-by-environment variances, genetic correlations, and genetic covariances for 18 domestication-related traits using realized genomic relationships estimated from genome-wide markers. We found a reduction in heritabilities across most traits, and the reduction is stronger in reproductive traits (size and numbers of grains and ears) than vegetative traits. We observed larger depletion in additive genetic variance than dominance genetic variance. Selection intensities during domestication were weak for all traits, with reproductive traits showing the highest values. For 17 of 18 traits, neutral divergence is rejected, suggesting they were targets of selection during domestication. Yield (total grain weight) per plant is the sole trait that selection does not appear to have improved in maize relative to teosinte. From a multivariate evolution perspective, we identified a strong, nonneutral divergence between teosinte and maize landrace genetic variance–covariance matrices (G-matrices). While the structure of G-matrix in teosinte posed considerable genetic constraint on early domestication, the maize landrace G-matrix indicates that the degree of constraint is more unfavorable for further evolution along the same trajectory.

The Contemporary Evolution of Fitness

2018 ◽  
Vol 49 (1) ◽  
pp. 457-476 ◽  
Author(s):  
Andrew P. Hendry ◽  
Daniel J. Schoen ◽  
Matthew E. Wolak ◽  
Jane M. Reid
Keyword(s):  
Genetic Variance ◽  
Evolutionary Dynamics ◽  
Additive Genetic Variance ◽  
Deleterious Mutations ◽  
Contemporary Evolution ◽  
Evolutionary Potential ◽  
Empirical Estimates ◽  
Evolutionary Rescue ◽  
Proportional Change ◽  
Mean Fitness

The rate of evolution of population mean fitness informs how selection acting in contemporary populations can counteract environmental change and genetic degradation (mutation, gene flow, drift, recombination). This rate influences population increases (e.g., range expansion), population stability (e.g., cryptic eco-evolutionary dynamics), and population recovery (i.e., evolutionary rescue). We review approaches for estimating such rates, especially in wild populations. We then review empirical estimates derived from two approaches: mutation accumulation (MA) and additive genetic variance in fitness (IAw). MA studies inform how selection counters genetic degradation arising from deleterious mutations, typically generating estimates of <1% per generation. IAw studies provide an integrated prediction of proportional change per generation, nearly always generating estimates of <20% and, more typically, <10%. Overall, considerable, but not unlimited, evolutionary potential exists in populations facing detrimental environmental or genetic change. However, further studies with diverse methods and species are required for more robust and general insights.

scholarly journals Genomic and phenomic insights from an atlas of genetic effects on DNA methylation

2020 ◽  
Author(s):  
Josine L Min ◽  
Gibran Hemani ◽  
Eilis Hannon ◽  
Koen F Dekkers ◽  
Juan Castillo-Fernandez ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Genetic Variants ◽  
Complex Traits ◽  
Genetic Architecture ◽  
Genetic Variance ◽  
Genetic Factors ◽  
Additive Genetic Variance ◽  
Genetic Influences ◽  
Methylation Quantitative Trait Loci ◽  
Shared Genetic

Characterizing genetic influences on DNA methylation (DNAm) provides an opportunity to understand mechanisms underpinning gene regulation and disease. Here we describe results of DNA methylation-quantitative trait loci (mQTL) analyses on 32,851 participants, identifying genetic variants associated with DNAm at 420,509 DNAm sites in blood. We present a database of >270,000 independent mQTL of which 8.5% comprise long-range (trans) associations. Identified mQTL associations explain 15-17% of the additive genetic variance of DNAm. We reveal that the genetic architecture of DNAm levels is highly polygenic and DNAm exhibits signatures of negative and positive natural selection. Using shared genetic control between distal DNAm sites we construct networks, identifying 405 discrete genomic communities enriched for genomic annotations and complex traits. Shared genetic factors are associated with both blood DNAm levels and complex diseases but in most cases these associations do not reflect causal relationships from DNAm to trait or vice versa indicating a more complex genotype-phenotype map than has previously been hypothesised.

scholarly journals The Multi-allelic Genetic Architecture of a Variance-heterogeneity Locus for Molybdenum Accumulation Acts as a Source of Unexplained Additive Genetic Variance

2015 ◽  
Author(s):  
Simon K G Forsberg ◽  
Matthew E Andreatta ◽  
Xin-Yuan Huang ◽  
John Danku ◽  
David E Salt ◽  
...  
Keyword(s):  
Genetic Architecture ◽  
Genetic Variance ◽  
Phenotypic Diversity ◽  
Additive Genetic Variance ◽  
Genetic Regulation ◽  
Ion Homeostasis ◽  
Natural Populations ◽  
Biological Traits ◽  
Variance Heterogeneity ◽  
Copper Transporter

Most biological traits are regulated by both genetic and environmental factors. Individual loci contributing to the phenotypic diversity in a population are generally identified by their contributions to the trait mean. Genome-wide association (GWA) analyses can also detect loci based on variance differences between genotypes and several hypotheses have been proposed regarding the possible genetic mechanisms leading to such signals. Little is, however, known about what causes them and whether this genetic variance-heterogeneity reflects mechanisms of importance in natural populations. Previously, we identified a variance-heterogeneity GWA (vGWA) signal for leaf molybdenum concentrations in Arabidopsis thaliana. Here, fine-mapping of this association to a ~78 kb Linkage Disequilibrium (LD)-block reveals that it emerges from the independent effects of three genetic polymorphisms on the high-variance associated version of this LD-block. By revealing the genetic architecture underlying this vGWA signal, we uncovered the molecular source of a significant amount of hidden additive genetic variation (“missing heritability”). Two of the three polymorphisms on the high-variance LD-block are promoter variants for Molybdate transporter 1 (MOT1), and the third a variant located ~25 kb downstream of this gene. A fourth independent association was also detected ~600 kb upstream of the LD-block. Testing of T-DNA knockout alleles for genes in the associated regions suggest AT2G25660 (unknown function) and AT2G26975 (Copper Transporter 6; COPT6) as the strongest candidates for the associations outside MOT1. Our results show that multi-allelic genetic architectures within a single LD-block can lead to a variance-heterogeneity between genotypes in natural populations. Further they provide novel insights into the genetic regulation of ion homeostasis in A. thaliana, and empirically confirm that variance-heterogeneity based GWA methods are a valuable tool to detect novel associations of biological importance in natural populations.

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