Updated Chapter 9

Chapter 9: Quantitative Traits

Introduction to Quantitative Traits

• PMR Yellow wash, Costate, Romanesco are examples of traits.

• Hybridization noted between PMR Yellow Squash and Costata Romanesco.

Mendelian vs. Quantitative Traits

Mendelian Traits

• Characteristics: Inherited as dominant and recessive.

• Phenotypes: Each genotype corresponds to one specific phenotype.

Quantitative Traits

• Characteristics:

  • Polygenic: Influenced by multiple genes.

  • Multifactorial: Affected by multiple factors including environment.

  • Continuous: Show a range of phenotypes, not limited to distinct categories.

• Each phenotype determined by many genes, often unknown.

Population Genetics vs. Quantitative Genetics

Population Genetics

• Focus: Examines discrete genotypes.

• Key Terms: Allele and genotype frequencies within populations.

Quantitative Genetics

• Focus: Analyzes continuously distributed phenotypes.

• Key Metrics: Mean and variance of populations, and individuals' phenotypic values.

Characteristics of Quantitative Traits

• Complexity: Traits influenced by many loci with discrete options.

• Influence of Environment: Environmental factors further shape phenotypes.

• Examples: Traits like human height, cheetah sprint speed, and flower size demonstrate quantitative traits.

• Distinction: Continuous variation indicates quantitative traits, unlike qualitative traits that present a binary phenotype.

Causes of Continuous Variation

• Genetic Influence: Multiple genes play a role in phenotype shaping.

• Environmental Influence: Interaction of genetics and environmental factors complicates the genotype-phenotype relationship.

Descriptive Statistics in Quantitative Traits

• Usage of descriptive statistics to examine population variation.

• Normal Distribution: Quantitative traits frequently exhibit a normal distribution pattern.

Types of Distributions

• Normal Distribution: Symmetric, bell-shaped.

• Skewed Distribution: Asymmetric, reflecting a trait like coat color in guinea pigs.

• Bimodal Distribution: Two peaks; example found in female rattlesnake size distribution.

Gene Action Types Affecting Quantitative Traits

• Dominance: One allele masks the effect of another.

• Additive: Alleles coalesce to influence phenotype; can show codominance.

• Epistasis: Interaction between separate loci creates a unique phenotype.

Quantitative Genetics Applications

• Loci Identification: Often, the alleles affecting quantitative traits remain unidentified.

• Uses:

  • Measurement of heritable variation.

  • Assessing fitness differences.

  • Predicting evolutionary responses to selection.

Quantitative Trait Loci (QTL)

• Definition: Statistical identification of genomic regions linked to specific traits.

• Mapping Objectives: Locate genes contributing to quantitative traits, focusing on identifying associations with neutral genetic markers.

Steps for Creating a Genetic Map

• Create Populations: Cross different inbred lines, resulting in F1 and F2 generations.

• Backcrossing: F1 crossed with a parent to create a backcross population.

• Tracking Markers: Monitor neutral marker allele frequencies in the F2/backcross groups.

Linkage Mapping

• Recombination Frequency: Utilized to gauge distance in the linkage map.

• Centimorgans: Units measuring distance between markers based on expected recombination occurrences.

Association Testing in QTL Mapping

• Objective: Assess connections between phenotypic values and neutral markers.

• Significance: High occurrences of markers indicate potential QTL affecting traits.

QTL Statistics and LOD Scores

• Assessment of Association: Calculation of LOD scores to evaluate likelihood of QTL linkages to markers.

• LOD Plot Interpretation: Visual representation to identify QTL locations based on statistical significance.

Implications of QTL Findings

• Allows testing of candidate genes in identified loci for trait influence via mutations or CRISPR-Cas9 techniques.

Reasons for QTL Mapping

Applications

• Agriculture: Improve crops, enhance pest resistance, assist marker-based selection.

• Biomedical Science: Examine complex diseases and potential tailored therapies.

• Evolutionary Biology: Inform on biological models, comparative genomics, and ecology-related genetics.

Heritability and Its Calculation

• Definitions:

  • Phenotypic Value (P): P = G (genetic value) + E (environmental value).

  • Heritability: Proportion of variation attributable to genetic factors.

  • VP = VG + VE (Phenotypic variation = Genetic variation + Environmental variation).

Estimating Heritability

• Maintain environmental consistency for accurate measures.

• Use family phenotypic data to enhance estimation reliability.

Fitness Measurement and Its Impact on Evolution

• Connection of heritability and fitness differences aids in predicting trait evolution over generations.

• Example study: Mice tail length influenced by skeletal traits.

Selection Differential and Its Importance

• Identifies variations and execution of selection processes within populations.

Evolutionary Response Predictions

• Applications of heritability and selection differential in forecasting evolutionary outcomes:

  • Equation: R = h²S (R = response, h² = heritability, S = selection differential).

Patterns of Selection in Quantitative Traits

• Types:

  • Directional: Shift in trait values, selecting for traits at a value.

  • Stabilizing: Intermediate trait values favored; extreme variants selected against.

  • Disruptive: Extremes favored while intermediates are selected out.

Summary of Selection Impacts

• Directional Selection: Alters mean trait values; e.g., increase in cliff swallow body size.

• Stabilizing Selection: Reduces trait variance; e.g., medium birthweights preferred.

• Disruptive Selection: Elevates trait variance; e.g., extreme beak sizes in seed-cracking birds.