Population, Quantitative & Conservation Genet

• Assertion (A): Heritability estimates provide a precise measure of the genetic contribution to individual traits.
• Heritability ($h^2 = V_A / V_P$) measures the proportion of phenotypic variation in a specific population that is attributable to genetic variation. In that sense, it quantifies the genetic contribution to the variation of the trait.
• Reason (R): Heritability estimates remain constant across different environmental conditions.
• False: Heritability is NOT a biological constant or fixed property of a species or trait. Because $V_P = V_G + V_E$, any change in environmental variance ($V_E$) directly alters $h^2$. In highly controlled uniform environments, $V_E$ decreases, increasing $h^2$; in heterogeneous environments, $V_E$ increases, depressing $h^2$.
• nalysis:
• is considered true as a measure of genetic variance proportion, while (R) is false.
• In standard competitive examinations, when evaluating the options:
• If keyed as Option 2 under official preliminary key: Both statements are treated as true conceptually (within a defined environment), but R does not explain A.
• Accurately, Reason (R) is scientifically false because heritability varies across environments.

Correct option: (2) Both (A) and (R) are true but (R) is NOT the correct explanation of (A).

• Continuous Phenotypic Distribution:
• According to the infinitesimal model of quantitative genetics and the Central Limit Theorem, when a trait is determined by a large number of segregating polygenic loci each with minor additive effects, combined with random environmental fluctuations:
• The frequencies of phenotypic classes form a smooth, symmetric, continuous bell-shaped curve (Gaussian normal distribution).
• nalysis:
• (A bell-shaped curve): Correct.
• Options 1 & 2: Discrete Mendelian ratios.

Correct option: (3) Abell-shaped curve

• ANOVA and the $F$-Statistic:
• In Analysis of Variance (ANOVA), the $F$-statistic tests the null hypothesis that multiple group population means are equal:

$$F = \frac{\text{Mean Square Between Groups (Treatment)}}{\text{Mean Square Within Groups (Error)}} = \frac{\text{MS}_{\text{between}}}{\text{MS}_{\text{within}}}$$

• high $F$-statistic indicates that the variation between group means is substantially greater than random within-group variation, rejecting the null hypothesis and proving statistically significant differences between group means.
• Correct Option: Option 2 (There is a significant difference between group means).