Statistical Genetics

This course is meant to prepare the students in applications of statistics in quantitative genetics and breeding. The students would be exposed to the physical basis of inheritance, detection and estimation of linkage, estimation of genetic parameters and development of selection indices.


  • Physical basis of inheritance. Analysis of segregation, detection and estimation of linkage for qualitative characters. Amount of information about linkage, Combined estimation, Disturbed segregation.
  • Gene and genotypic frequencies, Random mating and Hardy-Weinberg law, Application and extension of the equilibrium law, Fisher’s fundamental theorem of natural selection. Disequilibrium due to linkage for two pairs of genes, sex-linked genes
  • Forces affecting gene frequency - Selection, mutation and migration, Equilibrium between forces in large populations, Polymorphism.
  • Polygenic system for quantitative characters, Concepts of breeding value and dominance deviation. Genetic variance and its partitioning.
  • Correlations between relatives, Heritability, Repeatability and Genetic correlation. Response due to selection, Selection index and its applications in plants and animals improvement programmes, Correlated response to selection. Restricted selection index, Inbreeding and cross-breeding, Changes in mean and variance.


Test for the single factor segregation ratios, homogeneity of the families with regard to single factor segregation. Detection and estimation of linkage parameter by different procedures. Estimation of genotypic and gene frequency from a given data. Hardy-Weinberg law. Estimation of changes in gene frequency due to systematic forces, Inbreeding coefficient,  Genetic components of variation, Heritability and repeatability coefficient, Genetic correlation coefficient. Examination of effect of linkage, epistasis and inbreeding on mean and variance of metric traits. Construction of selection index including phenotypic index, restricted selection index. Correlated response to selection. Combined estimation, Disturbed segregation.