Broad Sense Vs Narrow Sense Heritability

Heritability, a cornerstone concept in genetics and breeding, measures the proportion of phenotypic variation in a population attributable to genetic factors. This seemingly straightforward idea branches into two distinct, yet related, concepts: broad sense heritability and narrow sense heritability. Understanding the nuances between these two is crucial for researchers, breeders, and anyone interested in the genetic architecture of traits. This article delves into the definitions, differences, calculations, applications, and limitations of broad and narrow sense heritability, providing a comprehensive overview of these essential tools.

Broad Sense Heritability: Capturing the Total Genetic Influence

Broad sense heritability (H²) quantifies the proportion of total phenotypic variance that is due to total genetic variance. In simpler terms, it reflects the extent to which differences in traits among individuals in a population are due to any and all genetic differences. It provides an upper limit to the degree to which a trait can be improved through selection.

Formula and Calculation

The formula for broad sense heritability is:

H² = VG / VP

Where:

• H² = Broad sense heritability
• VG = Genetic variance
• VP = Phenotypic variance

VP, the total phenotypic variance, can be further broken down into:

VP = VG + VE + VGE

Where:

• VE = Environmental variance (variance due to environmental factors)
• VGE = Variance due to gene-environment interaction (variance due to the interaction between genes and environment)

VG, the genetic variance, encompasses all forms of genetic variation, including:

VG = VA + VD + VI

Where:

• VA = Additive genetic variance (variance due to the additive effects of genes)
• VD = Dominance genetic variance (variance due to dominance relationships between alleles at a locus)
• VI = Epistatic genetic variance (variance due to interactions between genes at different loci)

Therefore, the most expanded form of the broad sense heritability equation is:

H² = (VA + VD + VI) / (VA + VD + VI + VE + VGE)

Understanding the Components

• Genetic Variance (VG): This represents the total genetic contribution to phenotypic variance. It includes all the ways in which genes can influence a trait, whether through direct additive effects, dominance interactions, or complex epistatic interactions.
• Environmental Variance (VE): This captures the impact of all non-genetic factors on the trait. These can include things like nutrition, climate, exposure to pathogens, and random developmental events.
• Gene-Environment Interaction Variance (VGE): This accounts for situations where the effect of a gene depends on the environment, or vice versa. For example, a genotype might perform well in one environment but poorly in another.

Estimating Broad Sense Heritability

Several methods can be used to estimate broad sense heritability:

• Twin Studies: By comparing the similarity of traits in monozygotic (identical) twins, who share 100% of their genes, to that in dizygotic (fraternal) twins, who share approximately 50% of their genes, researchers can estimate the proportion of variance due to genetics. Higher similarity in identical twins compared to fraternal twins suggests a higher heritability.
• Clonal Studies: In plants or organisms that can be cloned, researchers can compare the variance within a clone (which reflects environmental variance) to the variance among different clones (which reflects both genetic and environmental variance).
• Parent-Offspring Regression: Although typically used to estimate narrow sense heritability, parent-offspring regression can provide an estimate of broad sense heritability if environmental effects are carefully controlled or assumed to be negligible.
• ANOVA (Analysis of Variance): In designed experiments, ANOVA can partition the total variance into components attributable to different sources, such as genotypes and environments. This allows for the estimation of genetic and environmental variance components, which can then be used to calculate heritability.

Applications of Broad Sense Heritability

Broad sense heritability is useful in several contexts:

• Understanding the Genetic Basis of Traits: It provides a general indication of the extent to which a trait is genetically determined.
• Predicting Response to Selection: Although narrow sense heritability is more directly relevant to predicting response to selection, broad sense heritability can provide an upper limit on the potential for improvement.
• Designing Breeding Programs: It can help breeders decide whether to focus on genetic improvement or environmental management.
• Guiding Research: It can inform researchers about the relative importance of genetic and environmental factors in influencing a trait, guiding future studies to investigate specific genes or environmental factors.

Limitations of Broad Sense Heritability

• Overestimation: Broad sense heritability can overestimate the degree to which a trait is heritable, as it includes non-additive genetic effects (dominance and epistasis) that are not reliably passed on from parents to offspring.
• Population-Specific: Heritability is a population-specific measure. It depends on the genetic and environmental variation present in the population at the time of measurement.
• Environment-Specific: Heritability can vary depending on the environment in which it is measured. A trait may be highly heritable in one environment but not in another.
• Does Not Imply Genetic Determinism: High heritability does not mean that a trait is entirely determined by genes. Environmental factors can still play a significant role.
• Difficult to Estimate Accurately: Estimating broad sense heritability can be challenging, especially for complex traits that are influenced by many genes and environmental factors.

Narrow Sense Heritability: Focusing on Additive Genetic Effects

Narrow sense heritability (h²) focuses specifically on the proportion of phenotypic variance that is due to additive genetic variance. Additive genetic variance refers to the variance caused by the average effect of each allele on the phenotype. It is this additive component that is most reliably passed on from parents to offspring, making narrow sense heritability the key parameter for predicting response to selection.

Formula and Calculation

The formula for narrow sense heritability is:

h² = VA / VP

Where:

• h² = Narrow sense heritability
• VA = Additive genetic variance
• VP = Phenotypic variance (VA + VD + VI + VE + VGE)

Why Additive Genetic Variance Matters

Additive genetic variance is crucial because it reflects the portion of genetic variance that is directly inherited from parents to offspring. This is because offspring inherit alleles, not genotypes. The additive effect of an allele is the average effect of that allele across all possible genetic backgrounds. This means that, on average, offspring will resemble their parents in proportion to the narrow sense heritability.

Estimating Narrow Sense Heritability

Several methods are used to estimate narrow sense heritability:

• Parent-Offspring Regression: This is the most common method. It involves plotting the average phenotype of offspring against the average phenotype of their parents. The slope of the regression line provides an estimate of narrow sense heritability. This method relies on the assumption that environmental effects are independent of genotype and that there is no assortative mating (i.e., that individuals with similar phenotypes do not tend to mate with each other).
• Selection Experiments: By measuring the response to selection (the change in the mean phenotype across generations) and the selection differential (the difference between the mean phenotype of the selected parents and the mean phenotype of the population), researchers can estimate realized heritability. Realized heritability is the ratio of the response to selection to the selection differential.
• ANOVA (Analysis of Variance) in Half-Sib Designs: In animal breeding, half-sib designs are often used to estimate heritability. Half-sibs share one parent in common. By partitioning the variance into components attributable to different sires, researchers can estimate the additive genetic variance and, therefore, the narrow sense heritability.
• Genomic Methods: With the advent of genome-wide association studies (GWAS) and genomic selection, it is now possible to estimate narrow sense heritability using genomic data. These methods involve estimating the additive effects of individual genetic markers (SNPs) and then summing these effects to estimate the total additive genetic variance.

Applications of Narrow Sense Heritability

Narrow sense heritability is widely used in:

• Predicting Response to Selection: This is its primary application. Breeders use narrow sense heritability to predict how much a trait will improve in response to selection. The higher the narrow sense heritability, the greater the expected response.
• Designing Breeding Programs: Narrow sense heritability helps breeders choose the most effective breeding strategies. For example, if a trait has high narrow sense heritability, mass selection (selecting individuals based on their own phenotype) may be effective. If a trait has low narrow sense heritability, more sophisticated breeding strategies, such as family selection or genomic selection, may be needed.
• Estimating Breeding Values: Breeding value is the estimate of an individual's genetic merit for a particular trait. Narrow sense heritability is used in the calculation of breeding values.
• Understanding Evolutionary Processes: Narrow sense heritability is a key parameter in evolutionary biology. It determines the rate at which a population can evolve in response to natural selection.

Limitations of Narrow Sense Heritability

• Underestimation: Narrow sense heritability underestimates the total genetic contribution to phenotypic variance, as it only considers additive genetic effects. Dominance and epistasis can also contribute to genetic variance, but these are not captured by narrow sense heritability.
• Population-Specific and Environment-Specific: Like broad sense heritability, narrow sense heritability is population-specific and environment-specific.
• Assumptions: Estimating narrow sense heritability requires certain assumptions, such as the absence of assortative mating and the independence of environmental effects and genotype. Violations of these assumptions can lead to biased estimates.
• Difficult to Estimate Accurately: Estimating narrow sense heritability can be challenging, especially for complex traits. Large sample sizes and careful experimental designs are needed to obtain accurate estimates.

Broad Sense vs. Narrow Sense Heritability: A Direct Comparison

Key Differences Summarized:

• Scope: Broad sense heritability considers all genetic effects (additive, dominance, and epistasis), while narrow sense heritability focuses only on additive genetic effects.
• Prediction: Narrow sense heritability is the key parameter for predicting response to selection, as it reflects the portion of genetic variance that is reliably passed on from parents to offspring.
• Magnitude: Broad sense heritability is always greater than or equal to narrow sense heritability.
• Interpretation: A high broad sense heritability indicates that genetic factors play a significant role in determining phenotypic variation, but it does not necessarily mean that the trait will respond well to selection. A high narrow sense heritability indicates that the trait is likely to respond well to selection.

Factors Affecting Heritability Estimates

Several factors can influence heritability estimates:

• Genetic Variation: The amount of genetic variation present in the population. Higher genetic variation generally leads to higher heritability.
• Environmental Variation: The amount of environmental variation present in the population. Higher environmental variation generally leads to lower heritability.
• Gene-Environment Interaction: The presence of gene-environment interaction. Gene-environment interaction can either increase or decrease heritability, depending on the nature of the interaction.
• Population Structure: The presence of population structure (e.g., subpopulations with different allele frequencies). Population structure can lead to biased heritability estimates.
• Measurement Error: Errors in measuring the phenotype can lead to underestimates of heritability.
• Sample Size: Small sample sizes can lead to unreliable heritability estimates.

The Interplay of Genes and Environment: Beyond Heritability

While heritability provides valuable insights into the relative contributions of genes and environment to phenotypic variation, it's important to remember that genes and environment do not act in isolation. They interact in complex ways to shape the phenotype.

• Gene-Environment Correlation: This refers to situations where individuals with certain genotypes are more likely to experience certain environments. For example, children with a genetic predisposition for high intelligence may be more likely to grow up in stimulating environments.
• Epigenetics: Epigenetic modifications (e.g., DNA methylation, histone modification) can alter gene expression without changing the underlying DNA sequence. These modifications can be influenced by environmental factors and can be passed on from parents to offspring, leading to transgenerational epigenetic inheritance.
• Developmental Plasticity: This refers to the ability of an organism to alter its phenotype in response to environmental cues during development. Developmental plasticity can allow organisms to adapt to changing environments, but it can also make it difficult to predict the phenotype based on genotype alone.

Real-World Examples: Illustrating Heritability in Action

Agriculture:

• Crop Breeding: Narrow sense heritability is extensively used in crop breeding to predict the response to selection for traits such as yield, disease resistance, and nutritional content. Breeders use heritability estimates to design breeding programs that maximize genetic gain.
• Livestock Breeding: Similarly, narrow sense heritability is used in livestock breeding to improve traits such as milk production in dairy cattle, growth rate in beef cattle, and egg production in chickens. Genomic selection, which uses genomic data to predict breeding values, is becoming increasingly important in livestock breeding.

Human Health:

• Disease Risk: Heritability studies have shown that many diseases, such as heart disease, diabetes, and cancer, have a genetic component. However, it's important to remember that these diseases are also influenced by environmental factors, such as diet, lifestyle, and exposure to toxins.
• Behavioral Traits: Behavioral traits, such as intelligence, personality, and mental health, also have a genetic component. However, these traits are also strongly influenced by environmental factors, such as upbringing, education, and social support.

Evolutionary Biology:

• Adaptation: Heritability is a key factor in the evolution of adaptation. Natural selection can only act on traits that have a heritable component. The higher the heritability of a trait, the faster it can evolve in response to selection.
• Speciation: Heritability can also play a role in speciation. If two populations of a species are exposed to different environments, they may evolve different traits through natural selection. If these traits have a heritable component, the two populations may eventually diverge to the point where they can no longer interbreed.

Conclusion: Embracing the Complexity of Heritability

Broad sense and narrow sense heritability are powerful tools for understanding the genetic architecture of traits and predicting response to selection. While broad sense heritability provides a general indication of the extent to which a trait is genetically determined, narrow sense heritability is the key parameter for predicting response to selection. Understanding the differences between these two concepts, as well as their limitations, is crucial for researchers, breeders, and anyone interested in the genetic basis of traits. It is also important to remember that genes and environment interact in complex ways to shape the phenotype, and that heritability is just one piece of the puzzle. By embracing the complexity of heritability and considering the interplay of genes and environment, we can gain a deeper understanding of the biological world.