selection plant breeding
Genetic Gain
Overview: Genetic gain refers to the increase in performance of a trait achieved through artificial genetic improvement programs, typically measured after one generation. It is crucial for enhancing yield and other desirable traits in both plant and animal breeding.
Genetic Improvement Programs:
Aim to enhance specific traits through selective breeding.
Utilize methods from quantitative genetics to predict changes.
Involve both natural and artificial selection processes.
Yield Estimation:
Calculated using selection differential, selection intensity, and heritability.
Example calculation shows how to estimate genetic gain for yield per plant.
Heritability:
Represents the proportion of phenotypic variance attributable to genetic variance.
Important for predicting response to selection and potential genetic gain.
Higher heritability indicates greater potential for genetic improvement.
Response to Selection:
Both natural and artificial selection lead to genetic change.
Natural selection favors genotypes that produce more offspring.
Artificial selection accelerates desired traits in species (e.g., domestic animals).
Selection Intensity and Genetic Advance:
Selection intensity affects the rate of genetic gain.
Different intensities correspond to varying expected genetic advances.
Example values provided for different selection percentages (1%, 5%, 10%, 20%).
Response to Selection
Overview: Response to selection refers to the change in phenotypes across generations due to natural or artificial selection. It is influenced by genetic variation, heritability, and the selection differential, which together determine the rate of evolutionary change in populations.
Natural Selection:
Mechanism where certain genotypes produce more offspring.
Leads to adaptive changes in populations over time.
Artificial Selection:
Human-driven selective breeding mimicking natural selection.
Used for rapid changes in traits (e.g., domestic animals).
Genetic Variation:
Essential for both natural and artificial selection.
Determines the potential for evolutionary change.
Quantifying genetic variation is crucial for predicting responses to selection.
Quantitative Genetics:
Utilizes statistical methods to predict genetic change.
Involves measuring traits and their inheritance patterns.
Estimating the Response to Selection:
Phenotypic changes occur if appropriate genes are present.
The selection response (R) measures this change.
Example: Body size in Drosophila melanogaster.
Selection differential (s) calculated from selected vs. unselected mean phenotypes.
Breeder’s equation: R = h²S relates response to heritability and selection differential.
Selection Intensity and Genetic Advance:
Higher selection intensity leads to greater genetic advance in progeny.
Example data shows varying genetic advances at different selection intensities.
Estimating Response to Selection
Overview: Estimating response to selection involves understanding how phenotypic traits change across generations due to genetic selection. The response, denoted as R, is influenced by narrow-sense heritability and the selection differential, which can be quantified using the breeder's equation.
Phenotypic Change:
Changes in phenotype occur from one generation to the next due to selection.
Example: Body size in Drosophila melanogaster demonstrates measurable changes through selective breeding.
Selection Response (R):
Defined as the difference in mean phenotype between selected offspring and the original population.
Dependent on:
Narrow-sense heritability (h²).
Selection differential (S), calculated as the difference between means of selected parents and unselected population.
Narrow-Sense Heritability (h²):
Represents the proportion of phenotypic variance attributable to additive genetic variance.
Calculated using the formula: h² = R/S.
Breeder's Equation:
Expresses the relationship between selection response, heritability, and selection differential: R = h²S.
Used to estimate heritability based on observed responses to selection.
Factors Influencing Response to Selection:
Genetic variation must be present for traits to respond to selection.
Examples include both positive and negative phototactic behavior in Drosophila pseudoobscura.
Potential decrease in response may occur due to lack of genetic variation or detrimental effects of selected traits on other characteristics.
Applications:
Relevant in both plant and animal breeding, as well as evolutionary biology.
Natural selection leads to adaptive changes; artificial selection accelerates these processes in domesticated species.
Selection Intensity (i):
Defined as the ratio of selection differential (S) to the phenotypic standard deviation (σp): i = S/σp.
Example Calculation of Genetic Gain:
Given data for cotton varieties:
Mean yield of selected top 5%: 570 g/plant.
Overall mean yield: 455 g/plant.
Standard deviation: 58.0 g/plant.
Heritability: 50%.
Steps to calculate genetic gain (G):
Calculate selection differential (S): S = 570 g - 455 g = 115 g.
Determine selection intensity (i) at 5%: i = 2.063.
Compute genetic gain: G = i × σp × h² = 2.063 × 58.0 × 0.5 = 59.74 g.
Expected mean yield of progeny: 455 g + 59.74 g = 514.74 g/plant.
Selection Differential
Overview: Selection differential (S) quantifies the difference in phenotype between selected individuals and the overall population. It is crucial for understanding genetic change through selection, influencing both natural and artificial breeding practices.
Selection Intensity:
Defined as the proportion of selection differential to phenotypic standard deviation.
Formula: ( i = \frac{S}{\sigma_p} )
Indicates how strongly a trait is being selected for in a population.
Genetic Advance:
Refers to the expected improvement in a trait due to selection over generations.
Dependent on selection intensity and heritability of the trait.
Phenotypic Standard Deviation:
A measure of variation within a population's traits.
Essential for calculating selection intensity and understanding the spread of phenotypes.
Estimating Response to Selection:
Phenotypic changes occur across generations based on the presence of appropriate genes.
Example: In Drosophila melanogaster, selecting larger flies leads to increased average weight in subsequent generations.
Key factors include narrow-sense heritability and selection differential.
Response to Selection:
Both natural and artificial selection drive genetic change in populations.
Genetic variation is critical for determining the rate and type of evolutionary change.
Quantifying genetic variation aids in predicting outcomes of selective breeding.
Example Calculation:
Given nectar uptake rates in bees:
Parental mean: 9.5 μl/s
Population mean: 5.0 μl/s
Selection differential (S): ( 9.5 - 5.0 = 4.5 ) μl/s
Offspring mean: 8.7 μl/s
Selection response (R): ( 8.7 - 5.0 = 3.7 ) μl/s