Week 10 Flashcards
forces of genetic variation
Variation arises by mutation
Distribution of variation occurs because of genetic drift, migration and natural selection (dependent on effective population size Ne)
In total, four forces
hardy-wienburg
Species is one randomly mating group
No evolutionary forces acting
Models relationship between allele and genotype frequencies
HW helps us identify:
Deviations from random mating
Finite population size (bottlenecks, genetic drift)
Inbreeding
It is a null model
three main properties of HW
Allele frequencies do not change from one generation to the next (no evolution)
Genotypes are 100% reliably predictable from allele frequencies
A single generation of random mating is sufficient to return genotype frequencies to H-W expectations
how do we test if data fits HW?
Chi-squared test - compares. The observed genotype counts with expected under HW
d.f is calculated with number of possible genotypes - number of alleles
Chi allows us to see if the difference between observed and expected is significant
f statistics
Measuring the amount and direction of deviation from HW proportions
Measures genetic variation at different levels in the hierarchy of biological organisation (individuals, subpopulations and populations)
what does Fis tell us?
Whether individuals in subpopulations mate approximately at random in their subpopulation
It measures inbreeding
Measures how the variation within individuals (heterozygosity) compares to that in their subpopulation (average heterozygosity in subpopulation)
If the levels of heterozygosity are the same, the subpopulation is panmictic (randomly mating)
It DOES NOT measure heterozygosity or homozygosity (that’s what heterozygosity is for)
Fis range
From -1 to +1
Excessively high proportion of heterozygotes compared to HW = negative (deficient homozygous proportion)
Excessively homozygous compared to HW = positive
0 = expected proportions by HW
when data differs from HW, what might be untrue?
Random mating
No natural selection
No mutation
Infinite population size
No immigration
HW vs the real world
HW assumes allele frequencies do not change between generations (no evolution)
This assumes random mating and none of the four evolutionary forces are acting
This is often untrue in the real world
drivers of negative Fis
non-random mating - disassortative mating (unlike types mate, active outbreeding)
Immigration
Small population size (chance deviations)
Selection (balancing selection)
drivers of positive fis
Non-random mating due to population genetic structure (Wahlund effect)
Non-random mating due to assortative mating (mating with like, inbreeding)
Immigration is too recent for random mating
Small population causing chance deviations
Selection is directional
types of mating systems
Random
Assortative/inbreeding/selfing/cloning
Disassortative/outbreeding/inbreeding avoidance
Polygyny/monogamy/promiscuity
dispersal that causes gene flow
Long-distance/short distance
Sex-biased
population genetic structure
How genetic similarity is distributed in space and time
Random mating, isolation by distance, fragmented, cline etc.
genotypic arrays
Individual and population signatures of genetic variation
Even though alleles at all loci are found in both places, Ireland and Hungary have different characteristics
Considering the combination of genetic variation over many loci is powerful
Information arrises from correlations of different alleles at different loci
Some combinations are more common and some are less common (not random)
Tells us about reproductive modes and heaps more!
linkage disequilibrium
Combinations of alleles at different loci are more likely to appear than other combinations
genetic parentage analysis
Helps understand mating systems
Mate choice
Allocation of parental care
Inbreeding avoidance
Reproductive function
Likelihood proposed that a relationship is true (can work out who true father is)
genetic clustering analysis
Structure does two main tasks: determines the number of demes and finds what extent an individual fits in each deme (cluster membership value called q values)
Show us gene flow and migration patterns
assignment tests
Estimate the population origin of an individual
Gives us a probability signal
More powerful with more loci
what does dispersal do? how can it be measured?
Drives demographic and genetic connectivity
Brings genetic variation
Critical but hard to estimate
Can be measured with collars, tags, GPS, radio trackers
Direct genetic estimates of dispersal and gene flow can be down with parentage and assignment tests
