Compare and contrast h2 and H2. Discuss the limitations of each in determining h

Broad-sense heritability (H) is defined as the part of the phenotypic variance that is due to the genetic differences among individuals in a population (H = Vg/Vx). It is termed “broad-sense” because it encompasses several different ways by which genes contribute to variation (ie. epistasis, gene interaction and the contribution of different genes). H measures the variation in a population on a scale of 0-1.0, if the variation in a population is due to environmental sources and there is no genetic variation, then H is 0.  When all of the variation is equal to genetics Vg is equal to Vx and H is 1.0.

   Narrow-sense heritability (h) is the proportion of the phenotypic variance that is attributed to additive effects (h = Va/Vx = Va/Va+Vd+Ve). Additive variance is the fraction of the genetic variation that is transmitted from parent to offspring. Narrow-sense heritability measures the extent to which variation among individuals in a population is predictably transmitted to their offspring.  The value of h can be estimated two different ways: (1) using the correlation between parents and offspring and (2) the ratio of the selection response to the selection differential. The value of h is an importand quality in plant and animal breeding since it provides a measure of how well a trait will respond to selective breeding.

   H is not useful in interpreting differences in trait means among populations.  With regard to analysis of narrow-sense heritability (h) in humans, results to improve would only be evident many years from now.  h is more appropriate for determining heritability in model organism with a short generation time.  Using h, there is a great chance of the experiment not being randomized. For example, if a parent re-creates the same environment he/she experienced as a child, there will be correlation between the environment sof the parent and the offspring.  Both H and h are is the property of the specific environment and population in which measured, one estimate may not be meaningful for another population or environment. Also, both involve the ratio of a covariance to a variance.