General analysis of inbreeding

1. General analysis of inbreeding • Self-fertilization and sibling mating most extreme forms of inbreeding, but matings between more distant relatives (e.g. cousins) has same effect on frequency of homozygotes, but rate is slower.

2. General analysis of inbreeding • F = Coefficient of inbreeding: probability that two alleles in an individual are identical by descent (both alleles are copies of a particular ancestor’s allele in some previous generation). • F increases as relatedness increases.

4. General analysis of inbreeding • If we compare heterozygosity of inbred population Hf with that of a random mating population Ho relationship is • Hf = Ho (1-F) • Anytime F>0 frequency of heterozygotes is reduced and frequency of homozygotes naturally increases.

5. General analysis of inbreeding • Calculating F. Need to use pedigree diagrams. • Example: Female is daughter of two half-siblings. • Two ways female could receive alleles that are identical by descent.

6. Half-sibling mating Male Female Male Male Female Fig 6.27a

7. Fig 6.27b

8. General analysis of inbreeding • Total probability of scenario is 1/16 + 1/16 = 1/8.

9. Inbreeding depression • Inbreeding increases frequency of homozygotes and thus the probability that deleterious alleles are visible to selection. • In humans, children of first cousins have higher mortality rates than children of unrelated individuals.

10. Each dot on graph represents mortality rates for a human population. Mortality rate for children of cousins consistently about 4% higher than rate for children of non-relatives. Fig 6.28

11. Inbreeding effects on high blood pressure • In a study of 2760 individuals from 25 Croatian islands Rudan et al. found a strong positive relationship between high blood pressure and the inbreeding coefficent.

13. Inbreeding depression • Inbreeding depression also documented in studies of wild animals. • E.g. Great Tit. Two studies show that survival of inbred nestlings is lower than that of outbred individuals and that hatching success of inbred eggs is lower than that of outbred eggs.

14. Fig. 6.30

15. Migration • Migration: movement of alleles between populations. • Migration can cause allele and genotype frequencies to deviate from Hardy-Weinberg equilibrium.

16. Migration • Consider Continent-Island migration model. • Migration from island to continent will have no effect of continental allele frequencies. Continental population much larger than island. • However continent to island migration can greatly alter allele frequencies.

17. Empirical example of migration’s effects • Lake Erie water snakes. Snakes range in appearance from unbanded to strongly banded. • Banding caused by single locus: banded allele dominant over unbanded.

18. Lake Erie water snakes • Mainland: almost all snakes banded. • Islands many snakes unbanded. • Unbanded snakes have selective advantage: better camouflage on limestone rocks. Camouflage very valuable when snake is young.

19. Fig 6.6

20. Lake Erie water snakes • If selection favors unbanded snakes on islands why aren’t all snakes unbanded? • Migration introduces alleles for banding.

21. Fig 6.7 A unbanded, B+C some banding, D strongly banded

22. Lake Erie water snakes • Migration of snakes from mainland makes island populations more like mainland. • This is general effect of migration: Homogenizes populations (making them resemble each other).

23. Genetic Drift • Genetic drift results from the influence of chance. When population size is small, chance events more likely to have a strong effect. • Sampling errors are very likely when small samples are taken from populations.

24. Genetic Drift • Assume gene pool where frequency A1 = 0.6, A2 = 0.4. • Produce 10 zygotes by drawing from pool of alleles. • Repeat multiple times to generate distribution of expected allele frequencies in next generation.

25. Fig 6.11

26. Genetic Drift • Allele frequencies much more likely to change than stay the same. • If same experiment repeated but number of zygotes increased to 250 the frequency of A1 settles close to expected 0.6.

27. 6.12c

28. Empirical examples of sampling error: Founder Effect • Founder Effect: when population founded by only a few individuals allele frequencies likely to differ from that of source population. • Only a subset of alleles likely to be represented and rare alleles may be over-represented.

29. Founder effect in Silvereye populations. • Silvereyes colonized South Island of New Zealand from Tasmania in 1830. • Later spread to other islands.

30. http://photogallery.canberrabirds.org.au/silvereye.htm

31. 6.13b

32. Founder effect in Silvereyes • Analysis of microsatellite DNA from populations shows Founder effect on populations. • Progressive decline in allele diversity from one population to the next in sequence of colonizations.

33. Fig 6.13 c

34. Founder effect in Silvereyes • Norfolk island Silvereye population has only 60% of allelic diversity of Tasmanian population.

35. Founder effect in human populations • Founder effect common in isolated human populations. • E.g. Pingelapese people of Eastern Caroline Islands are descendants of 20 survivors of a typhoon and famine that occurred around 1775.

36. Founder effect in human populations • One survivor was heterozygous carrier of a recessive loss of function allele of CNGB3 gene. • Codes for protein in cone cells of retina. • 4 generations after typhoon homozygotes for allele began to be born.

37. Founder effect in human populations • Homozygotes have achromotopsia (complete color blindness, extreme light sensitivity, and poor visual acuity). • Achromotopsia rare in most populations (<1 in 20,000 people). Among the 3,000 Pingelapese frequency is 1 in 20.

38. Founder effect in human populations • High frequency of allele for achromotopsia not due to a selective advantage, just a result of chance. • Founder effect followed by further genetic drift resulted in current high frequency.

39. Effects of genetic drift over time • Effects of genetic drift can be very strong when compounded over many generations. • Simulations of drift. Change in allele frequencies over 100 generations. Initial frequencies A1 = 0.6, A2 = 0.4. Simulation run for different population sizes.

40. 6.15A

41. 6.15B

42. 6.15C

43. Conclusions from simulations • Populations follow unique paths • Genetic drift has strongest effects on small populations. • Given enough time even in large populations genetic drift can have an effect. • Genetic drift leads to fixation or loss of alleles, which increases homozygosity and reduces heterozygosity.

44. 6.15D

45. 6.15E

46. 6.15F

47. Conclusions from simulations • Genetic drift produces steady decline in heterozygosity. • Frequency of heterozygotes highest at intermediate allele frequencies. As one allele drifts to fixation number of heterozygotes inevitably declines.

48. Wright-Fisher model • The Hardy-Weinberg model provides an idealized picture of how allele frequencies and genotype frequencies are expected to change over time in a large population. • The Wright-Fisher model is a similar model but applies to small populations.

49. Wright-Fisher model • The W-F model retains the assumptions of the H-W model except for population size and in the model only a small sample of gametes are drawn at random from the gene pool. • The small sample drawn mimics the effects of drift because allele frequencies in the sample can differ a lot from the starting gene pool.

50. Loss of heterozygosity over time • We know that genetic drift leads to a loss of heterozygosity over time. • Alleles going to fixation naturally reduce the diversity of alleles in the population and without allelic diversity heterozygosity must decline.