Methods to Estimate Heritability in Animal Genetics and Breeding
Explore various methods to estimate heritability in animal genetics and breeding, including regression and correlation methods. Learn how to calculate heritability using offspring-parent data and understand the importance of choosing the most effective method for accurate estimations.
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ANIMAL GENETICS & BREEDING UNIT II Principles of Animal & Population Genetics Lecture 10 Methods to Estimate Heritability Dr K G Mandal Department of Animal Genetics & Breeding Bihar Veterinary College, Patna Bihar Animal Sciences University, Patna
Methods to Estimate Heritability (A)Regression Method (i) Regression of offspring on one parent (ii) Regression of offspring on mid-Parent (iii) Intra-sire regression of daughter on dam (B) Correlation Method (i) Half-sib correlation (ii) Full-sib correlation
Regression Method Regression of offspring on parent: Data structure: I. i) Required pair no. of observations. ii) Data required on one parent or mean of both the parents (mid-parents) and mean of their offspring.
Sl. No. Dam s LMY (kg) (X) Av. LMY of daughters (kg) (Y) 2200 1900 2500 2400 2800 1. 2. 3. 4. 5. 2000 1800 2200 2300 2500
Body weight (kg) of Black Bengal goats at 12 months of age: Sl. No. Sire Dam Mid- Progeny av. (Y) 15 14 13 13 15 parent (X) 14 13 12 12 13 1. 2. 3. 4. 5. 15 14 13 12 14 13 12 11 12 12
Estimation of h2 through regression of offspring on parents: Relatives Degree of resemblance Cov OP / 2P Heritability (h2) bop = h2 or, h2 = 2bop bop = h2 Offspring & one parent CovOP/ 2P Offspring & mid- parent
bOP = CovOP / VP Regression of offspring on one parent: bOP = VA /VP = h2 i.e., h2 = 2bOP Regression of offspring on mid-parent: bOP = VA / VP = h2 i.e., h2 = bOP byx = CovXY / VX byx = [ xy - x y/N] / [ x2 - ( x)2 /N]
Conclusion: Regression of offspring on one parent is better than regression of offspring on mid-parent. Why? Then what is the solution?
As for example, h2 in male regression of sons on fathers & regression of daughters on fathers. Regression of daughters on fathers is to be adjusted. b = b(6Pm/6Pf) h2 in case of female, Regression of sons on mothers is to be adjusted. b = b(6P f/6P m)
Correlation method Correlation between Half-sibs: Data structure on LMY (kg) of half-sibs Sire S1 S2 S3 Dam D1 D2 D3 D4 D5 D6 D7 D8 D9 Daughter d1 d2 d3 d4 d5 d6 d7 d8 d9 LMY(kg) 2000 2200 2300 2300 2500 2800 2500 2700 2800
Skeleton of ANOVA for HS analysis: Source of variation Between sire s - 1 within progeny or error d.f. Means Squares MS S MSw Composition of Mean Square 62w + k62S 62W s(k 1) s = number of sires k = number of progeny per sire
MSS MSW = 62w + k62S 62W = k62S 62S = 1/k(MSS MSW) VP = 62T = 62S + 62W 62s = VA t = VA / VP or, 4xt = h2 t = 62S / (62S + 62W) h2 = 4x 62S / (62S + 62W)
Correlation method Correlation between Full-sibs: Data structure of half-sib & full-sib family No. of Sire S1 S2 S3 No. of Dam / sire D1 D2 D3 D4 D5 D6 D7 D8 D9 No. of daughters /dam k k k k k k k k k
Skeleton of ANOVA for HS & FS Family: Source of variation Squares d.f. Sum of Means Square s MS S Composition of MS Between sire Between dams within sires within progeny 62w + k62D + dk62S 62w + k62D s - 1 SSS s(d 1) SSD MSD s = number of sires d = number of dams per sire k = number of progeny per dam 62W sd(k 1) SSW MSw
MSW = 62w MSD MSW = [62w + k62D] - 62w = k62D 62 D = 1/k(MSD MSW) MSS MSD = [62w + k62D + dk62S] [62w + k62D] = dk62S 62S = 1/dk(MSS MSD)
Thus, 62w = MSW 62 D = 1/k(MSD MSW) 62S = 1/dk(MSS MSD) 62s = VA 62D = VA + VD + VEC 62W = VA + VD VP = 62T = 62S + 62D + 62W or, = 462S = VA
t = 62S / (62S + 62W) h2S = 4x 62S / (62S + 62D+ 62W) h2D = 4x 62D / (62S + 62D+ 62W) h2S + D = 2 (62S + 62D)/ (62S + 62D+ 62W)
Conclusion: Estimation of h2 through regression of offspring on one parent is superior over regression of offspring on mid-parent. Half-sib correlation method is superior over Full-sib correlation.
