scholarly journals Fisher’s quantitative genetic model and the molecular genetics of multifactorial traits

2018 ◽  
Vol 135 (6) ◽  
pp. 391-392
Author(s):  
Leif Andersson
Keyword(s):  
Molecular Genetics ◽  
Genetic Model ◽  
Quantitative Genetic ◽  
Quantitative Genetic Model

Perennial grain crops: A synthesis of ecology and plant breeding

2005 ◽  
Vol 20 (1) ◽  
pp. 5-14 ◽  
Author(s):  
L.R. DeHaan ◽  
D.L. Van Tassel ◽  
T.S. Cox
Keyword(s):  
Plant Breeding ◽  
Environmental Changes ◽  
Genetic Model ◽  
Nutrient Loss ◽  
Trade Off ◽  
Grain Crops ◽  
Herbaceous Perennials ◽  
Quantitative Genetic ◽  
Quantitative Genetic Model ◽  
Perennial Grain

AbstractPerennial grain crops would address many agricultural problems, including soil erosion, nutrient loss and pesticide contamination. Doubts about the possibility of perennial grain crops rest upon two assumptions: (1) that the relationship between yield and longevity is a fixed function that cannot be influenced by selection, mutation or environmental changes; and (2) that yield and longevity trade off in a bivariate manner to the exclusion of all other traits. These assumptions are consistent with the phenotypic trade-off model, but recent research suggests that a quantitative genetic model is a more appropriate approach to trade-offs. In the quantitative genetic model, environmental and genetic changes can result in increases in two traits simultaneously even when a trade-off, or negative correlation, exists between the two traits. Empirical evidence that the trade-off between perenniality and reproductive allocation is not fixed comes from wild, herbaceous perennials that can produce more than 2000 kg seed ha−1 in the temperate zone, and herbaceous perennial crops that produce on average 8900 kg fruit ha−1 in the tropics. Ecological literature suggests that most perennials produce small amounts of seed relative to their vegetative growth not as a physiological absolute, but rather as a result of natural selection in a stable, competitive environment favoring longevity. By selecting strongly for seed yield in a population of perennial plants, the plant breeder can likely achieve that which is rare in nature—a high seed-yielding perennial plant. The same general methodologies that have allowed annual grain breeders to increase grain yield and push many combinations of negatively correlated traits to levels of expression not seen in nature are available to the perennial grain breeder. Perennial grain breeders are integrating ecological principles and traditional plant breeding methods in their efforts to develop perennial grain wheat (Triticum spp.), sorghum (Sorghum spp.), sunflower (Helianthus spp.), Illinois bundleflower (Desmanthus illinoensis) and rice (Oryza spp.).

scholarly journals A General Quantitative Genetic Model for Haplotyping a Complex Trait in Humans

2007 ◽  
Vol 8 (5) ◽  
pp. 343-350 ◽  
Author(s):  
Song Wu ◽  
Jie Yang ◽  
Chenguang Wang ◽  
Rongling Wu
Keyword(s):  
Genetic Model ◽  
Complex Trait ◽  
Quantitative Genetic ◽  
Quantitative Genetic Model

scholarly journals Evolution of sexual cooperation from sexual conflict

2019 ◽  
Vol 116 (46) ◽  
pp. 23225-23231 ◽  
Author(s):  
Maria R. Servedio ◽  
John M. Powers ◽  
Russell Lande ◽  
Trevor D. Price
Keyword(s):  
Sexual Selection ◽  
Sexual Conflict ◽  
Population Genetic ◽  
Genetic Model ◽  
Pair Formation ◽  
Selection Pressures ◽  
Quantitative Genetic ◽  
Pair Bonds ◽  
Quantitative Genetic Model ◽  
Female Investment

In many species that form pair bonds, males display to their mate after pair formation. These displays elevate the female’s investment into the brood. This is a form of cooperation because without the display, female investment is reduced to levels that are suboptimal for both sexes. The presence of such displays is paradoxical as in their absence the male should be able to invest extra resources directly into offspring, to the benefit of both sexes. We consider that the origin of these displays lies in the exploitation of preexisting perceptual biases which increase female investment beyond that which is optimal for her, initially resulting in a sexual conflict. We use a combined population genetic and quantitative genetic model to show how this conflict becomes resolved into sexual cooperation. A cooperative outcome is most likely when perceptual biases are under selection pressures in other contexts (e.g., detection of predators, prey, or conspecifics), but this is not required. Cooperation between pair members can regularly evolve even when this provides no net advantage to the pair and when the display itself reduces a male’s contributions to raising the brood. The findings account for many interactions between the sexes that have been difficult to explain in the context of sexual selection.

scholarly journals The benefits of maternal effects in novel and in stable environments

2012 ◽  
Vol 9 (75) ◽  
pp. 2403-2413 ◽  
Author(s):  
Rebecca B. Hoyle ◽  
Thomas H. G. Ezard
Keyword(s):  
Maternal Effects ◽  
Genetic Model ◽  
Phenotypic Variance ◽  
Phenotypic Evolution ◽  
Oscillatory Dynamics ◽  
Changing Environments ◽  
Quantitative Genetic ◽  
Quantitative Genetic Model ◽  
Mean Fitness ◽  
The Relationship

Natural selection favours phenotypes that match prevailing ecological conditions. A rapid process of adaptation is therefore required in changing environments. Maternal effects can facilitate such responses, but it is currently poorly understood under which circumstances maternal effects may accelerate or slow down the rate of phenotypic evolution. Here, we use a quantitative genetic model, including phenotypic plasticity and maternal effects, to suggest that the relationship between fitness and phenotypic variance plays an important role. Intuitive expectations that positive maternal effects are beneficial are supported following an extreme environmental shift, but, if too strong, that shift can also generate oscillatory dynamics that overshoot the optimal phenotype. In a stable environment, negative maternal effects that slow phenotypic evolution actually minimize variance around the optimum phenotype and thus maximize population mean fitness.

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