Narrow Sense Heritability Vs Broad Sense Heritability

Heritability, a cornerstone concept in genetics and breeding, quantifies the proportion of phenotypic variation in a population attributable to genetic factors. Understanding heritability is crucial for predicting the response to selection, designing effective breeding programs, and dissecting the genetic basis of complex traits. While heritability provides valuable insights, it is not a fixed property of a trait. Instead, it's a population-specific and environment-dependent measure, reflecting the interplay between genes and environment.

Broad Sense Heritability: Capturing Total Genetic Variance

Broad sense heritability (H²) represents the proportion of phenotypic variance that is due to total genetic variance. It encompasses all genetic contributions to phenotypic differences, including additive, dominance, and epistatic effects.

• Formula: H² = VG / VP, where VG is the total genetic variance and VP is the total phenotypic variance.
• Components of Genetic Variance (VG):
  • Additive Genetic Variance (VA): The variance due to the additive effects of genes. It represents the contribution of each allele to the phenotype, independent of other alleles or genes.
  • Dominance Genetic Variance (VD): The variance due to interactions between alleles at the same locus (dominance effects).
  • Epistatic Genetic Variance (VI): The variance due to interactions between genes at different loci (epistatic effects).
• Phenotypic Variance (VP): The total variance observed in a population for a given trait. It can be partitioned into genetic variance (VG) and environmental variance (VE): VP = VG + VE.
• Interpretation: A broad sense heritability of 0.8 indicates that 80% of the phenotypic variation in the population is due to genetic factors, while the remaining 20% is due to environmental factors.

Narrow Sense Heritability: Focusing on Additive Genetic Variance

Narrow sense heritability (h²) is a more refined measure that focuses specifically on the proportion of phenotypic variance attributable to additive genetic variance. This is the most important component of genetic variance for breeders because it predicts the response to selection.

• Formula: h² = VA / VP, where VA is the additive genetic variance and VP is the total phenotypic variance. It can also be expressed as h² = VA / (VA + VD + VI + VE).
• Importance of Additive Genetic Variance: Additive genetic variance is the only component of genetic variance that can be reliably passed on from parents to offspring. This is because additive effects are independent and predictable, while dominance and epistatic effects are dependent on specific combinations of alleles.
• Prediction of Response to Selection: Narrow sense heritability is used to predict the response to selection (R), which is the difference between the mean phenotype of the selected parents and the mean phenotype of the population before selection. The response to selection is related to the selection differential (S), which is the difference between the mean phenotype of the selected parents and the mean phenotype of the entire population. The relationship is given by: R = h² S.

Key Differences Between Narrow Sense and Broad Sense Heritability

Feature	Broad Sense Heritability (H²)	Narrow Sense Heritability (h²)
Genetic Variance	Total genetic variance (VG)	Additive genetic variance (VA)
Components	VA, VD, VI	VA
Prediction	Potential for genetic improvement	Response to selection
Application	Initial assessment of genetic influence	Breeding programs, evolutionary studies
Value	Higher than or equal to h²	Lower than or equal to H²

Estimating Heritability

Estimating heritability is crucial for genetic research and breeding applications. Several methods are used to estimate both broad sense and narrow sense heritability.

1. Twin Studies (for Broad Sense Heritability):

Twin studies compare the phenotypic similarity of monozygotic (identical) twins, who share 100% of their genes, and dizygotic (fraternal) twins, who share approximately 50% of their genes. By comparing the variance within and between twin pairs, researchers can estimate the proportion of phenotypic variance due to genetic factors.

• Assumptions: Twin studies assume that monozygotic and dizygotic twins share similar environments. However, this assumption may not always hold true, as monozygotic twins often experience more similar environments than dizygotic twins.
• Formula: H² = 2(rMZ - rDZ), where rMZ is the correlation coefficient for monozygotic twins and rDZ is the correlation coefficient for dizygotic twins.

2. Parent-Offspring Regression (for Narrow Sense Heritability):

Parent-offspring regression examines the relationship between the phenotypes of parents and their offspring. By regressing the offspring phenotype on the average phenotype of their parents, researchers can estimate the narrow sense heritability.

• Assumptions: Parent-offspring regression assumes that there is no assortative mating (i.e., parents do not choose mates based on the trait of interest) and that there are no common environmental effects between parents and offspring.
• Formula: h² = 2 * b, where b is the regression coefficient of offspring phenotype on the average parental phenotype.

3. Variance Components Analysis (for both Broad and Narrow Sense Heritability):

Variance components analysis involves partitioning the total phenotypic variance into different components, such as genetic variance, environmental variance, and their interactions. This method typically involves using statistical models, such as analysis of variance (ANOVA) or mixed models, to estimate the variance components.

• Experimental Designs: Variance components analysis requires carefully designed experiments that allow for the estimation of different variance components. Common experimental designs include:
  • Full-sib designs: Involve measuring the phenotypes of full siblings (individuals sharing both parents).
  • Half-sib designs: Involve measuring the phenotypes of half siblings (individuals sharing only one parent).
  • Nested designs: Involve nesting individuals within families or families within locations.
• Formulas: The specific formulas for estimating heritability depend on the experimental design and the statistical model used. However, in general, broad sense heritability is estimated as the ratio of total genetic variance to total phenotypic variance, while narrow sense heritability is estimated as the ratio of additive genetic variance to total phenotypic variance.

4. Realized Heritability (for Narrow Sense Heritability):

Realized heritability is calculated after a selection experiment has been conducted. It is the ratio of the response to selection (R) to the selection differential (S):

h² = R / S

This method provides a direct estimate of the heritability based on the actual outcome of selection.

Factors Affecting Heritability Estimates

Heritability estimates are not fixed values but are specific to a particular population in a particular environment. Several factors can influence heritability estimates:

• Genetic Variation: Heritability estimates are influenced by the amount of genetic variation present in the population. If there is little genetic variation for a trait, the heritability will be low, even if the trait is highly heritable in other populations.
• Environmental Variation: Heritability estimates are also influenced by the amount of environmental variation present in the population. If there is a lot of environmental variation, the heritability will be low, as much of the phenotypic variation will be due to environmental factors.
• Population Structure: Population structure, such as the presence of subpopulations or inbreeding, can also affect heritability estimates.
• Measurement Error: Measurement error can inflate the estimate of environmental variance, leading to an underestimation of heritability.
• Gene-Environment Interaction: Gene-environment interaction occurs when the effect of a gene on the phenotype depends on the environment. Gene-environment interaction can complicate the estimation of heritability, as it can lead to different heritability estimates in different environments.
• Gene-Environment Correlation: Gene-environment correlation occurs when individuals with certain genotypes are more likely to experience certain environments. Gene-environment correlation can also complicate the estimation of heritability, as it can lead to an overestimation of the genetic contribution to the phenotype.

Applications of Heritability

Heritability estimates have a wide range of applications in genetics, breeding, and evolutionary biology.

• Prediction of Response to Selection: Narrow sense heritability is used to predict the response to selection in breeding programs. By knowing the narrow sense heritability of a trait, breeders can estimate how much the trait will improve in response to selection.
• Design of Breeding Programs: Heritability estimates can be used to design effective breeding programs. For example, if a trait has a high heritability, breeders can use mass selection, in which individuals with the best phenotypes are selected as parents. If a trait has a low heritability, breeders may need to use more sophisticated breeding methods, such as family selection or marker-assisted selection.
• Understanding the Genetic Basis of Complex Traits: Heritability estimates can provide insights into the genetic basis of complex traits. Traits with high heritability are likely to be influenced by a relatively small number of genes with large effects, while traits with low heritability are likely to be influenced by a large number of genes with small effects.
• Evolutionary Studies: Heritability estimates are used in evolutionary studies to understand how traits evolve in response to natural selection.

Examples of Heritability

• Height in Humans: Height is a classic example of a trait with high heritability. Twin studies have shown that the heritability of height in humans is typically around 0.8, indicating that 80% of the variation in height is due to genetic factors.
• Milk Production in Dairy Cattle: Milk production is an economically important trait in dairy cattle. The heritability of milk production is moderately high, typically around 0.3, indicating that selection for milk production can be effective.
• Disease Resistance in Plants: Disease resistance is an important trait in crop plants. The heritability of disease resistance can vary depending on the plant species, the disease, and the environment. In some cases, disease resistance can be highly heritable, while in other cases it can be lowly heritable.
• IQ in Humans: IQ is a controversial trait, and the heritability of IQ is a subject of much debate. Some studies have suggested that the heritability of IQ is high, while others have suggested that it is low. The heritability of IQ is likely to vary depending on the population and the environment.

Limitations of Heritability

While heritability is a useful concept, it is important to be aware of its limitations:

• Population-Specific: Heritability estimates are specific to a particular population in a particular environment. They cannot be generalized to other populations or other environments.
• Environment-Dependent: Heritability estimates are influenced by the amount of environmental variation present in the population.
• No Information about Specific Genes: Heritability estimates do not provide any information about the specific genes that influence a trait.
• Not a Measure of Genetic Determination: Heritability is not a measure of genetic determination. A trait with high heritability is not necessarily determined by genes. Environmental factors can still play an important role.
• Can Be Misinterpreted: Heritability estimates can be easily misinterpreted. For example, a high heritability estimate does not mean that a trait cannot be influenced by the environment.

Conclusion

Understanding the distinction between narrow sense and broad sense heritability is crucial for researchers and breeders alike. Broad sense heritability provides an initial assessment of the genetic influence on a trait, while narrow sense heritability is essential for predicting the response to selection and designing effective breeding programs. While heritability estimates provide valuable insights, it's essential to recognize their limitations and interpret them within the context of the specific population and environment under consideration. By carefully considering these factors, we can effectively utilize heritability to advance our understanding of genetics and improve breeding outcomes.