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Practical H:\ferreira\biometric\sgene.exe. Practical Aim Visualize graphically how allele frequencies, genetic effects, dominance, etc, influence trait.

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Presentation on theme: "Practical H:\ferreira\biometric\sgene.exe. Practical Aim Visualize graphically how allele frequencies, genetic effects, dominance, etc, influence trait."— Presentation transcript:

1 Practical H:\ferreira\biometric\sgene.exe

2 Practical Aim Visualize graphically how allele frequencies, genetic effects, dominance, etc, influence trait mean and variance Ex1 a=0, d=0, p=0.4, Residual Variance = 0.04, Scale = 2. Vary a from 0 to 1. Ex2 a=1, d=0, p=0.4, Residual Variance = 0.04, Scale = 2. Vary d from -1 to 1. Ex3 a=1, d=0, p=0.4, Residual Variance = 0.04, Scale = 2. Vary p from 0 to 1. Look at scatter-plot, histogram and variance components.

3 Some conclusions 1.Additive genetic variance depends on allele frequency p & additive genetic value a as well as dominance deviation d 2.Additive genetic variance typically greater than dominance variance

4 Biometrical model for single biallelic QTL 3. Contribution of the QTL to the Covariance (X,Y) 2. Contribution of the QTL to the Variance (X) 1. Contribution of the QTL to the Mean (X)

5 Biometrical model for single biallelic QTL AA Aa aa AA Aaaa (a-m)(a-m) (d-m)(d-m) (-a-m) (a-m)(a-m) (d-m)(d-m) (a-m)2(a-m)2 (a-m)(a-m) (d-m)(d-m) (a-m)(a-m) (d-m)2(d-m)2 (d-m)(d-m) (-a-m) 2 3. Contribution of the QTL to the Cov (X,Y)

6 Biometrical model for single biallelic QTL AA Aa aa AA Aaaa (a-m)(a-m) (d-m)(d-m) (-a-m) (a-m)(a-m) (d-m)(d-m) (a-m)2(a-m)2 (a-m)(a-m) (d-m)(d-m) (a-m)(a-m) (d-m)2(d-m)2 (d-m)(d-m) (-a-m) 2 p2p pq 0 q2q2 3A. Contribution of the QTL to the Cov (X,Y) – MZ twins = (a-m) 2 p 2 + (d-m) 2 2pq + (-a-m) 2 q 2 Cov(X,Y) = V A QTL + V D QTL = 2pq[a+(q-p)d] 2 + (2pqd) 2

7 Biometrical model for single biallelic QTL AA Aa aa AA Aaaa (a-m)(a-m) (d-m)(d-m) (-a-m) (a-m)(a-m) (d-m)(d-m) (a-m)2(a-m)2 (a-m)(a-m) (d-m)(d-m) (a-m)(a-m) (d-m)2(d-m)2 (d-m)(d-m) (-a-m) 2 p3p3 p2qp2q 0 pq pq 2 q3q3 3B. Contribution of the QTL to the Cov (X,Y) – Parent-Offspring

8 e.g. given an AA father, an AA offspring can come from either AA x AA or AA x Aa parental mating types AA x AA will occur p 2 × p 2 = p 4 and have AA offspring Prob()=1 AA x Aa will occur p 2 × 2pq = 2p 3 q and have AA offspring Prob()=0.5 and have Aa offspring Prob()=0.5 Therefore, P(AA father & AA offspring) = p 4 + p 3 q = p 3 (p+q) = p 3

9 Biometrical model for single biallelic QTL AA Aa aa AA Aaaa (a-m)(a-m) (d-m)(d-m) (-a-m) (a-m)(a-m) (d-m)(d-m) (a-m)2(a-m)2 (a-m)(a-m) (d-m)(d-m) (a-m)(a-m) (d-m)2(d-m)2 (d-m)(d-m) (-a-m) 2 p3p3 p2qp2q 0 pq pq 2 q3q3 = (a-m) 2 p 3 + … + (-a-m) 2 q 3 Cov (X,Y) = ½V A QTL = pq[a+(q-p)d] 2 3B. Contribution of the QTL to the Cov (X,Y) – Parent-Offspring

10 Biometrical model for single biallelic QTL AA Aa aa AA Aaaa (a-m)(a-m) (d-m)(d-m) (-a-m) (a-m)(a-m) (d-m)(d-m) (a-m)2(a-m)2 (a-m)(a-m) (d-m)(d-m) (a-m)(a-m) (d-m)2(d-m)2 (d-m)(d-m) (-a-m) 2 p4p4 2p 3 q p2q2p2q2 4p 2 q 2 2pq 3 q4q4 = (a-m) 2 p 4 + … + (-a-m) 2 q 4 Cov (X,Y) = 0 3C. Contribution of the QTL to the Cov (X,Y) – Unrelated individuals

11 Biometrical model for single biallelic QTL Cov (X,Y) 3D. Contribution of the QTL to the Cov (X,Y) – DZ twins and full sibs ¼ genome ¼ (2 alleles) + ½ (1 allele) + ¼ (0 alleles) MZ twins P-O Unrelateds ¼ genome # identical alleles inherited from parents 0 1 (mother) 1 (father) 2 = ¼ Cov(MZ) + ½ Cov(P-O) + ¼ Cov(Unrel) = ¼(V A QTL +V D QTL ) + ½ (½ V A QTL ) + ¼ (0) = ½ V A QTL + ¼V D QTL

12 Summary…

13 Biometrical model predicts contribution of a QTL to the mean, variance and covariances of a trait Var (X) = V A QTL + V D QTL Cov (MZ) = V A QTL + V D QTL Cov (DZ) = ½V A QTL + ¼V D QTL On average! 0 or 10, 1/2 or 1 IBD estimation / Linkage Mean (X) = a(p-q) + 2pqd Association analysis Linkage analysis For a sib-pair, do the two sibs have 0, 1 or 2 alleles in common?

14 Biometrical model for single biallelic QTL 2A. Average allelic effect (α) The deviation of the allelic mean from the population mean a(p-q) + 2pqd A a αaαa αAαA ? ? Mean (X) Allele a Allele APopulation AAAaaa ad-a Apq ap+dq q(a+d(q-p)) apq dp-aq -p(a+d(q-p)) Allelic meanAverage allelic effect (α) 1/3

15 Biometrical model for single biallelic QTL Denote the average allelic effects - α A = q(a+d(q-p)) - α a = -p(a+d(q-p)) If only two alleles exist, we can define the average effect of allele substitution - α = α A - α a - α = (q-(-p))(a+d(q-p)) = (a+d(q-p)) Therefore: - α A = qα - α a = -pα 2/3

16 Biometrical model for single biallelic QTL 2B. Additive genetic variance The variance of the average allelic effects 2αA2αA Additive effect 2A. Average allelic effect (α) Freq. AA Aa aa p2p2 2pq q2q2 α A + α a 2αa2αa = 2qα = (q-p)α = -2pα V A QTL = (2qα) 2 p 2 + ((q-p)α) 2 2pq + (-2pα) 2 q 2 = 2pqα 2 = 2pq[a+d(q-p)] 2 d = 0, V A QTL = 2pqa 2 p = q, V A QTL = ½a 2 3/3 α A = qα α a = -pα


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