An introduction to quantitative genetics

Transcription

1 An introduction to quantitative genetics 1. What is the genetic architecture and molecular basis of phenotypic variation in natural populations? 2. Why is there phenotypic variation in natural populations?

2 Types of traits Monogenic traits (rare) - discrete binary characters - but modified by genetic and environmental background Polygenic traits (common) - discrete (bristle number) or continuous (height) or binary (disease) - binary traits with a polygenic basis are often described by a threshold model

3 History and origins of quantitative genetics Finally, that from the uninterrupted concurrence of these causes or from these laws of nature, together with much time and with an almost inconceivable diversity of influential circumstance, organic beings of all the orders have been successively formed. Jean-Baptiste Lamarck 1802 in Recherches sur l'organisation des Corps Vivans

4 Pangenesis The hypothesis of Pangenesis, as applied to the several great classes of facts just discussed, no doubt is extremely complex, but so are the facts. The chief assumption is that all of the units of the body, besides having the universally admitted power of growing by selfdivision, throw off minute gemmules which are dispersed through the system. Nor can this assumption be considered as too bold, for we know from the cases of graft-hybridization that formative matter of some kind is present in the tissues of plants, which is capable of combining with that included in another individual, and of reproducing every unit of the whole organism. But we have further to assume that the gemmules grow, multiply, and aggregate themselves into buds and the sexual elements; their development depending on their union with other nascent cells or units. They are also believed to be capable of transmission in a dormant state, like seeds in the ground, to successive generations. Charles Darwin, 1868 in The Variation of Animals and Plants Under Domestication

5 Francis Galton 1869 Hereditary Genius: An Inquiry into its Laws and Consequences.

6 Galton 1886 Regression towards mediocrity in hereditary stature. Journal of the Anthropological Institute 15:

7 The Twins have a special claim upon our attention; it is, that their history affords means of distinguishing between the effects of tendencies received at birth, and of those that were imposed by the special circumstances of their after lives; in other words, between the effects of nature and nurture. Galton, 1876 The History of Twins, as a Criterion of the Relative Powers of Nature and Nurture. The Journal of the Anthropological Institute of Great Britain and Ireland 5:

8 The famous Galtonian law of regression and its corolaries elaborated by Pearson pretended to have established the laws of 'ancestral influences' in mathematical terms. Now, by the pure-line explanation of the well known action of selection in poly-genotypic populations, these laws of correlation have been put in their right place; such interesting products of mathematical genius may be social statistics in optima forma, but they have nothing at all to do with genetics or general biology! Their premises are inadequate for insight into the nature of heredity. Johannsen 1911 The Genotype Conception of Heredity. The American Naturalist 45:

9 The Mendelians versus the Biometricians Mendelian Theorists Discontinuous variation Macromutations Bateson De Vries Punnett Johannsen Biometricians Continuous variation Slight changes Weldon Pearson

10 Ronald Fisher 1918 The correlation between relatives on the supposition of Mendelian inheritance. Trans. R. Soc. Edinburgh 52:

11 Castle-Wright estimator n e = [ P 1 P 2 2 Var P 1 Var P 2 ] [8Var S ]

12 Heritability the proportion of phenotypic variation that is attributable to genotypic variation Penetrance - is the percentage of individuals with a specific genotype that possess an associated phenotype. Categorical, e.g. Huntington's disease. Expressivity - is the degree to which individuals with a specific genotype display the associated phenotype. Quantitative, e.g. psoriasis.

13 Heritability the proportion of phenotypic variation that is attributable to genotypic variation Phenotype (P) = Genotype (G) + Environment (E) Var(P) = Var(G) + Var(E) + Cov(G,E) Broad-sense Heritability (H 2 ) = Var(G) / Var(P) Broad-sense heritability includes additive, dominance, epistatic variance along with maternal and paternal effects. Genetic (G) = Additive (A) + Dominance (D) + Interactions (I) Var(G) = Var(A) + Var(D) + Var(I) Narrow-sense heritability (h 2 ) = Var(A) / Var(P)

14 Estimating Heritability Analysis of variance or regression (correlation) H 2 = Var(G) / Var(P) Var(G) = Var(P) Var(E) Var(E) = Var(F 1 ) Var(P) = Var(F 2 ) h 2 = r / b r = the correlation coefficient or Cov(X,Y) / Var(X) Var(Y) b = the coefficient of relatedness or the probability that at a random locus, the alleles there will be identical by descent. What is the heritability if the correlation between brothers is 50%? What if the correlation is >50%? The square of the sample correlation coefficient, the coefficient of determination, is the fraction of the variance in y that is accounted for by a linear fit of x to y.

15 Heritability from Twins For comparison of monozygotic (MZ) and dizygotic (DZ) twins: r mz = A + C r dz = 0.5 * A + C A = 2*(r mz - r dz ) C = r mz A E = 1 - r mz Where the components of variance are A for additive, C for common environment and E for unique environment

16 Estimating Heritability & Threshold Characters General Population A threshold character that depends on an underlying normal distribution. q = incidence G = mean liability of population A = mean liability of the affected individuals R = mean liability of relatives of affected individuals R G is the selection response A G is the selection differential The regression of incidence in the general population to relatives of affected (r) = (R G) / (A G) or r = bh 2 where b is the coefficient of relationship. After some math h 2 = q g (x g x r ) / rz z is obtained by assuming an underlying Normal distribution. Relatives of Affected

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18 What explains heritable variation in natural populations? Mutation and genetic drift Mutation-selection balance

19 What explains heritable variation in natural populations? Mutation and genetic drift Lynch and Hill (1986) 2NV(m) < Var(G) < 4NV(m) N = effective population size V(m) = the new variance from mutation added to the population every generation Mutation-selection balance

20 What explains heritable variation in natural populations? Mutation and genetic drift Lynch and Hill (1986) 2NV(m) < Var(G) < 4NV(m) N = effective population size V(m) = the new variance from mutation added to the population every generation Mutation-selection balance Mutation increases Var(G) Selection decreases Var(G) R = h 2 S S is the selection differential and R is the selection response. Var(G) = sqrt (2N Var(m) Var(s)) for mutations of small effect Var(G) = 4Nu Var(s) for mutations of large effect Var(s) = variance in the fitness function

21 Estimating the mutation rate for monogenic traits If x be the proportion of haemophilic males in the population, and f their effective fertility, that is to say their chance, compared with a normal male, of producing offspring, then in a large population of 2N, (1 f )xn haemophilia genes are effectively wiped out per generation. The same number must be replaced by mutation. But as each of the N females has two X- chromosomes per cell, and each of the N males one, the mean mutation rate per X-chromosome per generation is 1/3(1 f )x, or if f is small, a little less than 1/3(x). Hence we have only to determine the frequency of haemophilia in males to arrive at the approximate mutation rate. JBS Haldane 1935 The rate of spontaneous mutation of a human gene. J. Genet. 31: AA = 1, Aa = 1, aa = 1-s, u = mutation rate from A to a, then The equilibrium frequency: q = sqrt(u/s) If Aa = 1-hs: q = u/(hs)

22 Estimating the mutation rate for polygenic traits Mukai (1964) The genetic structure of natural populations of Drosophila melanogaster. I. Spontaneous mutation rate of polygenes controlling viability. Genetics 50: Mutation accumulation scheme

23 Cross Scheme 15/101 lines carried a recessive lethal Using the Poisson Rate of lethal mutations = per second chromosome Viability index (v) v = 100 x (+/+) / total total = (Cy/+) + (+/+)

24 Control viabilities

25 Mutation accumulation causes a decline in viability

26 Estimating mutational parameters Assuming a linear increase in the number of mutation over time and interactions between mutations are not large the rate of polygenic mutation for viability is: a p=v o v a 2 a 2 p= G 2 a = average effect size v = viability index sigma_g = among line genetic variance sigma_a = variance in effect size p = average number of mutations difference in viabilities per generations = increase in variance per generation = 0.113

27 A high mutation rate for small effects Conclusion: 1. Mutation rate is very high, 20x that of lethals supported by frequency of mutation free lines 2. Mutations are predominantly of small effect