Variation_genetic+model+for+quantitative+traits

Page 1: Genetic Model for Quantitative Traits

Page 2: Simply Inherited and Polygenic Traits

  • Simply Inherited Traits: Traits influenced by one or few genes.

    • Examples: coat color, presence of horns, genetic defects . ; (e.g., spider syndrome in sheep).

    • Phenotypes categorized as qualitative or categorical traits.

    • Minimal environmental influence on these traits.

Page 3: Polygenic Traits

  • Polygenic Traits: Traits influenced by many genes; no single gene has overriding effect.

    • Examples: growth rate, milk production, birth weight.

    • Generally quantified by numerical values; described as quantitative or continuous.

    • Exception: Dystocia, influenced by many genes but described categorically.

    • Environmental factors significantly affect polygenic traits.

Page 4: Basic Model for Quantitative Traits

  • Model Equation: P = µ + G + E

    • P: phenotypic value of an animal for a given trait.

    • µ: population mean for the trait.

    • G: genotypic value of the animal for the trait.

    • E: environmental effects on the phenotype.

    • Note: G and E expressed as deviations from population mean; sum of G and E in population equals zero.

Page 5: Genotypic Value

  • Genotypic Value (G): Overall effect of all genes on the phenotype of an animal.

    • Not directly measurable; expressed as: G = BV + GCV.

    • BV: Breeding value; GCV: Gene Combination Value.

Page 6: Breeding Value

  • Breeding Value (BV): Additive genetic value transmitted from parents to offspring.

    • Sum of individual gene effects, independent of dominance and epistasis effects.

    • Parental value significant for contribution of genes in next generation.

    • Animals selected based on estimated breeding values.

Page 7: Example of Breeding Value Calculation

  • Assume a trait affected by 5 loci with independent effects:

    • Allele impacts categorized by locus;

    • Example:

      • Locus 1: Average effects +3.0, -0.6 (sum +2.4)

      • Locus 2: +0.2, +4.2 (sum +4.4)

      • Resulting Breeding Value: +5.8

Page 8: Progeny Difference and Transmitting Ability

  • Progeny cache half of parental genes; this half is random.

    • Progeny Difference (PD) or Transmitting Ability (TA) defined as:

      • PD = TA = ½ BV

    • PD and TA indicate expected performance of offspring relative to population mean.

Page 9: Prediction of Progeny Difference

  • PD and TA not directly measurable but can be estimated through performance data.

    • Predicted values termed EPD (Expected Progeny Difference) or PTA (Predicted Transmitting Ability).

    • EPD used in beef, swine, sheep breeding; PTA in dairy breeding.

Page 10: Breeding Value of Offspring

  • Breeding value of offspring determined by additive effects from both sire and dam:

    • Example: Sire BV +2.5 kg, Dam BV +1.5 kg leads to average expected offspring BV of +2.0 kg.

    • If population mean weaning weight: 18 kg, expected offspring weight = 20 kg.

Page 11: Gene Combination Value (GCV)

  • GCV: Effect of gene combinations (dominance and epistasis); not transmittable to offspring.

    • Not important for selection as it cannot be passed on.

Page 12: Example of Gene Combination Value

  • Locus affecting litter size in swine with alleles T (dominant) and t (recessive).

    • Independent effects result in different BV values for different genotypes:

      • TT, Tt, tt genotype effects summarized in table format.

Page 13: Producing Ability (PA)

  • Producing Ability: Performance potential for repeated traits over time.

    • Key for understanding how genetic and environmental factors permanently affect performance.

    • Consideration of genotypic value and permanent environmental effects together.

Page 14: Permanent vs. Temporary Environmental Effects

  • Permanent Environmental Effects (Ep): Long-lasting factors affecting performance.

    • Examples: early nutrition, permanent udder problems affecting milk production.

  • Temporary Environmental Effects (Et): Short-term factors, change over time.

    • Examples: forage quality, weather conditions affecting performance inconsistently.

Page 15: Model for Producing Ability

  • Producing Ability equation: PA = BV + GCV + Ep

    • Population mean of PA typically averages zero.

    • Overall model for repeated traits: P = µ + BV + GCV + Ep + Et

Page 16: Example: 305-d Milk Production Records

  • Example of performance records for two cows showing P, BV, GCV, Ep, Et contributions for each.

    • Calculated PA shows negative and positive values indicating different productive capacities.

Page 17: Importance of Producing Ability

  • Critical for commercial producers assessing productive capacity.

    • Dairy farmers adjust feed based on producing ability.

    • Predicted PA termed Most Probable Producing Ability (MPPA); formula given for predicting next record.