biometrical genetics

55
Biometrical genetics Manuel Ferreira Shaun Purcell Pak Sham Boulder Introductory Course 2006

Upload: daphne

Post on 19-Jan-2016

31 views

Category:

Documents


0 download

DESCRIPTION

Biometrical genetics. Manuel Ferreira Shaun Purcell Pak Sham. Boulder Introductory Course 2006. Outline. 1. Aim of this talk. 2. Genetic concepts. 3. Very basic statistical concepts. 4. Biometrical model. 1. Aim of this talk. - PowerPoint PPT Presentation

TRANSCRIPT

Page 1: Biometrical genetics

Biometrical genetics

Manuel Ferreira

Shaun Purcell

Pak Sham

Boulder Introductory Course

2006

Page 2: Biometrical genetics

Outline

1. Aim of this talk

2. Genetic concepts

3. Very basic statistical concepts

4. Biometrical model

Page 3: Biometrical genetics

1. Aim of this talk

Page 4: Biometrical genetics

Revisit common genetic parameters - such as allele frequencies, genetic effects, dominance, variance components, etc

Use these parameters to construct a biometrical genetic model

Model that expresses the:

(1) Mean

(2) Variance

(3) Covariance between individuals

for a quantitative phenotype as a function of genetic parameters.

Page 5: Biometrical genetics

PT1

ADE

PT2

A D E

[0.25/1]

[0.5/1]

e ad eda

11 1 1 1 1

Page 6: Biometrical genetics

2. Genetic concepts

Page 7: Biometrical genetics

Population level

Transmission level

Phenotype level

G

G

G

G

G

G

G

G

G

GG

G

G

G

G

G

GG

G

G

G

G

GG

PP

Allele and genotype frequencies

Mendelian segregationGenetic relatedness

Biometrical modelAdditive and dominance components

Page 8: Biometrical genetics

Population level

1. Allele frequencies

A single locus, with two alleles - Biallelic / diallelic - Single nucleotide polymorphism, SNP

Alleles A and a - Frequency of A is p - Frequency of a is q = 1 – p

A a

A a

Every individual inherits two alleles - A genotype is the combination of the two alleles - e.g. AA, aa (the homozygotes) or Aa (the heterozygote)

Page 9: Biometrical genetics

Population level

2. Genotype frequencies (Random mating)

A (p) a (q)

A (p)

a (q)

Allele 1A

llele

2 AA (p2)

aA (qp)

Aa (pq)

aa (q2)

Hardy-Weinberg Equilibrium frequencies

P (AA) = p2

P (Aa) = 2pq

P (aa) = q2

p2 + 2pq + q2 = 1

Page 10: Biometrical genetics

Transmission

level

Pure Lines AA aa

F1 Aa Aa

AA Aa Aa aa

3:1 Segregation Ratio

Intercross

1. Mendel’s experiments

Page 11: Biometrical genetics

Aa aa

Aa aa

F1 Pure line

Back cross

1:1 Segregation ratio

Transmission

level

Page 12: Biometrical genetics

Pure Lines AA aa

F1 Aa Aa

AA Aa Aa aa

3:1 Segregation Ratio

Intercross

Transmission

level

Page 13: Biometrical genetics

Aa aa

Aa aa

F1 Pure line

Back cross

1:1 Segregation ratio

Transmission

level

Page 14: Biometrical genetics

Segregation, Meiosis

1. Mendel’s law of segregation

A3 (½) A4 (½)

A1 (½)

A2 (½)

Mother (A3A4)

A1A3 (¼)

A2A3 (¼)

A1A4 (¼)

A2A4 (¼)

Gametes

Father (A1A2)

Transmission

level

Page 15: Biometrical genetics

Phenotype level

1. Classical Mendelian traits

Dominant trait (D - presence, R - absence) - AA, Aa D - aa R

Recessive trait (D - absence, R - presence) - AA, Aa D - aa R

Codominant trait (X, Y, Z) - AA X - Aa Y - aa Z

Page 16: Biometrical genetics

2. Dominant Mendelian inheritance

D (½) d (½)

D (½)

d (½)

Mother (Dd)

DD (¼)

dD (¼)

Dd (¼)

dd (¼)

Father (Dd)

Phenotype level

Page 17: Biometrical genetics

3. Dominant Mendelian inheritance with incomplete penetrance and phenocopies

D (½) d (½)

D (½)

d (½)

Mother (Dd)

DD (¼)

dD (¼)

Dd (¼)

dd (¼)Father (Dd)

Phenocopies

Incomplete penetrance

Phenotype level

Page 18: Biometrical genetics

4. Recessive Mendelian inheritance

D (½) d (½)

D (½)

d (½)

Mother (Dd)

DD (¼)

dD (¼)

Dd (¼)

dd (¼)

Father (Dd)

Phenotype level

Page 19: Biometrical genetics

5. Quantitative traits

Fra

ctio

n

Histograms by gqt

g==-1

0

.128205

g==0

-3.90647 2.7156g==1

-3.90647 2.7156

0

.128205

Fra

ctio

n

Histograms by gqt

g==-1

0

.128205

g==0

-3.90647 2.7156g==1

-3.90647 2.7156

0

.128205

Fra

ctio

n

Histograms by gqt

g==-1

0

.128205

g==0

-3.90647 2.7156g==1

-3.90647 2.7156

0

.128205

AA

Aa

aa

Fra

ctio

n

qt-3.90647 2.7156

0

.072

Phenotype level

Page 20: Biometrical genetics

m

d +a

P(X)

X

AA

Aa

aa

m + a m + dm – a

– a

AAAaaa

Genotypic means

Biometric Model

Genotypic effect

Phenotype level

Page 21: Biometrical genetics

3. Very basic statistical

concepts

Page 22: Biometrical genetics

Mean, variance,

covariance

i

iii

i

xfxn

xXE )(

1. Mean (X)

Page 23: Biometrical genetics

Mean, variance,

covariance

2. Variance (X)

iii

ii

xfxn

xXEXVar 2

2

2

1)()(

Page 24: Biometrical genetics

Mean, variance,

covariance

3. Covariance (X,Y)

iiiYiXi

iYiXi

YX

yxfyxn

yxYXEYXCov

,1

),(

Page 25: Biometrical genetics

4. Biometrical model

Page 26: Biometrical genetics

Biometrical model for single biallelic

QTLBiallelic locus - Genotypes: AA, Aa, aa - Genotype frequencies: p2, 2pq, q2

Genotype frequencies

(Random mating)

A (p) a (q)

A (p)

a (q)

Allele 1

Alle

le 2 AA (p2)

aA (qp)

Aa (pq)

aa (q2)

Hardy-Weinberg Equilibrium frequencies

P (AA) = p2

P (Aa) = 2pq

P (aa) = q2

p2 + 2pq + q2 = 1

Page 27: Biometrical genetics

Biometrical model for single biallelic

QTLBiallelic locus - Genotypes: AA, Aa, aa - Genotype frequencies: p2, 2pq, q2

Alleles at this locus are transmitted from P-O according to Mendel’s law of segregation

Genotypes for this locus influence the expression of a quantitative trait X (i.e. locus is a QTL)

Biometrical genetic model that estimates the contribution of this QTL towards the (1) Mean, (2) Variance and (3) Covariance between individuals for this quantitative trait X

Page 28: Biometrical genetics

m

d +a

P(X)

X

AA

Aa

aa

m + a m + dm – a

– a

AAAaaa

Genotypic means

Biometric Model

Genotypic effect

Phenotype level

Page 29: Biometrical genetics

Biometrical model for single biallelic

QTL1. Contribution of the QTL to the Mean (X)

aaAaAAGenotypes

Frequencies, f(x)

Effect, x

p2 2pq q2

a d -a

i

ii xfx

= a(p2) + d(2pq) – a(q2)Mean (X) = a(p-q) + 2pqd

Page 30: Biometrical genetics

Biometrical model for single biallelic

QTL2. Contribution of the QTL to the Variance (X)

aaAaAAGenotypes

Frequencies, f(x)

Effect, x

p2 2pq q2

a d -a

= (a-m)2p2 + (d-m)22pq + (-a-m)2q2 Var (X)

i

ii xfxVar 2

= VQTL

Broad-sense heritability of X at this locus = VQTL / V Total

Broad-sense total heritability of X = ΣVQTL / V Total

Page 31: Biometrical genetics

Biometrical model for single biallelic

QTL = (a-m)2p2 + (d-m)22pq + (-a-m)2q2 Var (X)

= 2pq[a+(q-p)d]2 + (2pqd)2

= VAQTL + VDQTL

m

d +a– a

AAaa

Aa

Additive effects: the main effects of individual alleles

Dominance effects: represent the interaction between alleles

d = 0

Page 32: Biometrical genetics

Biometrical model for single biallelic

QTL = (a-m)2p2 + (d-m)22pq + (-a-m)2q2 Var (X)

= 2pq[a+(q-p)d]2 + (2pqd)2

= VAQTL + VDQTL

m

d +a– a

AAaa

Aa

Additive effects: the main effects of individual alleles

Dominance effects: represent the interaction between alleles

d > 0

Page 33: Biometrical genetics

Biometrical model for single biallelic

QTL = (a-m)2p2 + (d-m)22pq + (-a-m)2q2 Var (X)

= 2pq[a+(q-p)d]2 + (2pqd)2

= VAQTL + VDQTL

m

d +a– a

AAaa

Aa

Additive effects: the main effects of individual alleles

Dominance effects: represent the interaction between alleles

d < 0

Page 34: Biometrical genetics

Biometrical model for single biallelic

QTL

aa Aa AA

m

-a

ad

Var (X) = Regression Variance + Residual Variance= Additive Variance + Dominance Variance

Page 35: Biometrical genetics

PracticalH:\manuel\Biometric\sgene.exe

Page 36: Biometrical genetics

Practical

Aim Visualize graphically how allele frequencies, genetic effects, dominance, etc, influence trait mean and variance

Ex1a=0, d=0, p=0.4, Residual Variance = 0.04, Scale = 2.Vary a from 0 to 1.

Ex2a=1, d=0, p=0.4, Residual Variance = 0.04, Scale = 2.Vary d from -1 to 1.

Ex3a=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.

Page 37: Biometrical genetics

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

Page 38: Biometrical genetics

Biometrical model for single biallelic

QTLVar (X)= 2pq[a+(q-p)d]2 + (2pqd)2

VAQTL + VDQTL

Demonstrate

2A. Average allelic effect

2B. Additive genetic variance

Page 39: Biometrical genetics

Biometrical model for single biallelic

QTL

2B. Additive genetic variance 2A. Average allelic effect (α)

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)

Page 40: Biometrical genetics

Biometrical model for single biallelic

QTL

i

iiYiXi yxfyxYXCov ,),(

AA

Aa

aa

AA Aa aa(a-m) (d-m) (-a-m)

(a-m)

(d-m)

(-a-m)

(a-m)2

(a-m)

(-a-m)

(d-m)

(a-m)

(d-m)2

(d-m)(-a-m) (-a-m)2

3. Contribution of the QTL to the Cov (X,Y)

Page 41: Biometrical genetics

Biometrical model for single biallelic

QTL

i

iiYiXi yxfyxYXCov ,),(

AA

Aa

aa

AA Aa aa(a-m) (d-m) (-a-m)

(a-m)

(d-m)

(-a-m)

(a-m)2

(a-m)

(-a-m)

(d-m)

(a-m)

(d-m)2

(d-m)(-a-m) (-a-m)2

p2

0

0

2pq

0 q2

3A. Contribution of the QTL to the Cov (X,Y) – MZ twins

= (a-m)2p2 + (d-m)22pq + (-a-m)2q2 Covar (Xi,Xj)

= VAQTL + VDQTL

= 2pq[a+(q-p)d]2 + (2pqd)2

Page 42: Biometrical genetics

Biometrical model for single biallelic

QTL

AA

Aa

aa

AA Aa aa(a-m) (d-m) (-a-m)

(a-m)

(d-m)

(-a-m)

(a-m)2

(a-m)

(-a-m)

(d-m)

(a-m)

(d-m)2

(d-m)(-a-m) (-a-m)2

p3

p2q

0

pq

pq2 q3

3B. Contribution of the QTL to the Cov (X,Y) – Parent-Offspring

Page 43: Biometrical genetics

• 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 p2 × p2 = p4

and have AA offspring Prob()=1

AA x Aa will occur p2 × 2pq = 2p3q

and have AA offspring Prob()=0.5

and have Aa offspring Prob()=0.5

Therefore, P(AA father & AA offspring) = p4 + p3q

= p3(p+q)

= p3

Page 44: Biometrical genetics

Biometrical model for single biallelic

QTL

AA

Aa

aa

AA Aa aa(a-m) (d-m) (-a-m)

(a-m)

(d-m)

(-a-m)

(a-m)2

(a-m)

(-a-m)

(d-m)

(a-m)

(d-m)2

(d-m)(-a-m) (-a-m)2

p3

p2q

0

pq

pq2 q3

= (a-m)2p3 + … + (-a-m)2q3 Cov (Xi,Xj)

= ½VAQTL= pq[a+(q-p)d]2

3B. Contribution of the QTL to the Cov (X,Y) – Parent-Offspring

Page 45: Biometrical genetics

Biometrical model for single biallelic

QTL

AA

Aa

aa

AA Aa aa(a-m) (d-m) (-a-m)

(a-m)

(d-m)

(-a-m)

(a-m)2

(a-m)

(-a-m)

(d-m)

(a-m)

(d-m)2

(d-m)(-a-m) (-a-m)2

p4

2p3q

p2q2

4p2q2

2pq3 q4

= (a-m)2p4 + … + (-a-m)2q4 Cov (Xi,Xj)

= 0

3C. Contribution of the QTL to the Cov (X,Y) – Unrelated individuals

Page 46: Biometrical genetics

Biometrical model for single biallelic

QTL

Cov (Xi,Xj)

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 ¼ genome ¼ genome

# identical alleles inherited

from parents

01(mother)

1(father)

2

= ¼ Cov(MZ) + ½ Cov(P-O) + ¼ Cov(Unrel) = ¼(VAQTL

+VDQTL) + ½ (½ VAQTL

) + ¼

(0) = ½ VAQTL + ¼VDQTL

Page 47: Biometrical genetics

Summary

Page 48: Biometrical genetics

Biometrical model predicts contribution of a QTL to the mean, variance and covariances of a trait

Var (X) = VAQTL + VDQTL

1 QTL

Cov (MZ) = VAQTL + VDQTL

Cov (DZ) = ½VAQTL + ¼VDQTL

Var (X) = Σ(VAQTL) + Σ(VDQTL

) = VA + VDMultiple QTL

Cov (MZ)

Cov (DZ)

= Σ(VAQTL) + Σ(VDQTL

) = VA + VD

= Σ(½VAQTL) + Σ(¼VDQTL

) = ½VA +

¼VD

Page 49: Biometrical genetics

Biometrical model underlies the variance components estimation performed in Mx

Var (X) = VA + VD + VE

Cov (MZ)

Cov (DZ)

= VA + VD

= ½VA + ¼VD

Page 50: Biometrical genetics

Biometrical model for single biallelic

QTL2A. Average allelic effect (α)

The deviation of the allelic mean from the population mean

a(p-q) + 2pqd

Aaαa αA

? ?Mean (X)

Allele a Allele APopulation

AA Aa aaa d -a

A p q ap+dq q(a+d(q-p))

a p q dp-aq -p(a+d(q-p))

Allelic mean Average allelic effect (α)

1/3

Page 51: Biometrical genetics

Biometrical model for single biallelic

QTLDenote the average allelic effects - αA

= q(a+d(q-p)) - αa

= -p(a+d(q-p))

If only two alleles exist, we can define the average effect of allele substitution - α = αA - αa - α = (q-(-p))(a+d(q-p)) = (a+d(q-p))

Therefore: - αA

= qα - αa

= -pα

2/3

Page 52: Biometrical genetics

Biometrical model for single biallelic

QTL2B. Additive genetic variance

The variance of the average allelic effects

2αA

Additive effect

2A. Average allelic effect (α)

Freq.

AA

Aa

aa

p2

2pq

q2

αA + αa

2αa

= 2qα

= (q-p)α

= -2pα

VAQTL= (2qα)2p2 + ((q-p)α)22pq + (-2pα)2q2

= 2pqα2

= 2pq[a+d(q-p)]2 d = 0, VAQTL= 2pqa2

p = q, VAQTL= ½a2

3/3

αA = qα

αa = -pα

Page 53: Biometrical genetics

0

0.07

5

0.15

0.22

5

0.3

0.37

5

0.45

0.52

5

0.6

0.67

5

0.75

0.82

5

0.9

0.97

5

0

0.16

0.32

0.48

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

a

p

d = 0, VAQTL= 2pqa2

VAQTL

Page 54: Biometrical genetics

-1

-0.8

-0.6

-0.4

-0.2 0

0.2

0.4

0.6

0.8 1

-1

-0.5

0

0.5

1

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

-1

-0.8

-0.6

-0.4

-0.2 0

0.2

0.4

0.6

0.8 1

-1

-0.4

0.2

0.8

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

-1

-0.8

-0.6

-0.4

-0.2 0

0.2

0.4

0.6

0.8 1

-1

-0.5

0

0.5

1

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

-1

-0.8

-0.6

-0.4

-0.2 0

0.2

0.4

0.6

0.8 1

-1

-0.4

0.2

0.8

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1-1

-0.8

-0.6

-0.4

-0.2 0

0.2

0.4

0.6

0.8 1

-1

-0.5

0

0.5

1

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

-1

-0.8

-0.6

-0.4

-0.2 0

0.2

0.4

0.6

0.8 1

-1

-0.4

0.2

0.8

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0.01 0.05 0.1 0.2 0.3 0.5

-1

-0.8

-0.6

-0.4

-0.2 0

0.2

0.4

0.6

0.8 1

-1

-0.5

0

0.5

1

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

-1

-0.8

-0.6

-0.4

-0.2 0

0.2

0.4

0.6

0.8 1

-1

-0.4

0.2

0.8

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

-1

-0.8

-0.6

-0.4

-0.2 0

0.2

0.4

0.6

0.8 1

-1

-0.4

0.2

0.8

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

-1

-0.8

-0.6

-0.4

-0.2 0

0.2

0.4

0.6

0.8 1

-1

-0.5

0

0.5

1

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

-1

-0.8

-0.6

-0.4

-0.2 0

0.2

0.4

0.6

0.8 1

-1

-0.4

0.2

0.8

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Allele frequency

Additive genetic variance VA

Dominance genetic variance VD

ad

+1-1

+1

-1

Page 55: Biometrical genetics

a

d

-1 0 +1

-1

0

+1

AA Aa aa

-1

-0.8

-0.6

-0.4

-0.2 0

0.2

0.4

0.6

0.8 1

-1

-0.9-0.8

-0.7-0.6

-0.5

-0.4-0.3

-0.2-0.1

0

0.10.2

0.30.4

0.5

0.60.7

0.80.9

1

-1

-0.8

-0.6

-0.4

-0.2 0

0.2

0.4

0.6

0.8 1

-1

-0.9-0.8

-0.7-0.6

-0.5

-0.4-0.3

-0.2-0.1

0

0.10.2

0.30.4

0.5

0.60.7

0.80.9

1

-1

-0.8

-0.6

-0.4

-0.2 0

0.2

0.4

0.6

0.8 1

-1

-0.9-0.8

-0.7-0.6

-0.5

-0.4-0.3

-0.2-0.1

0

0.10.2

0.30.4

0.5

0.60.7

0.80.9

1

-1

-0.8

-0.6

-0.4

-0.2 0

0.2

0.4

0.6

0.8 1

-1

-0.9-0.8

-0.7-0.6

-0.5

-0.4-0.3

-0.2-0.1

0

0.10.2

0.30.4

0.5

0.60.7

0.80.9

1

-1

-0.8

-0.6

-0.4

-0.2 0

0.2

0.4

0.6

0.8 1

-1

-0.9-0.8

-0.7-0.6

-0.5

-0.4-0.3

-0.2-0.1

0

0.10.2

0.30.4

0.5

0.60.7

0.80.9

1

-1

-0.8

-0.6

-0.4

-0.2 0

0.2

0.4

0.6

0.8 1

-1

-0.9-0.8

-0.7-0.6

-0.5

-0.4-0.3

-0.2-0.1

0

0.10.2

0.30.4

0.5

0.60.7

0.80.9

1

0.01 0.05 0.1 0.2 0.3 0.5Allele frequency

VA > VD

VA < VD