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Printable Handouts
Navigable Slide Index
- Introduction
- Infinite alleles model
- Infinite alleles model: nucleotide diversity
- Infinite alleles model: real data example
- Historical super-exponential population growth
- Recent super-exponential population growth
- Impact of population growth on population genetics
- The neutral coalescent
- The neutral coalescent: common ancestors
- Genealogy with population growth
- Allele frequency and age
- The neutral site frequency spectrum
- Small samples used to infer population growth
- Large samples skew SFS (1)
- Large samples skew SFS (2)
- Variant number in a large sample
- Pronounced excess of rare variants
- Explosive population growth & excess rare variants
- Excess rare variants: study examples
- Studies show massive excess of rare variation
- Rare alleles have less sharing across populations
- Less sharing of rare alleles
- Highlight of ultra-deep sequencing studies
- Population growth and large sample
- A simple generative model
- The coalescent as balls-in-boxes
- The neutral coalescent
- Multiple coalescence
- Violation of Kingsman coalescent: what now?
- Decoupling of population growth and mutation rate
- HHEX: mutation & growth rates estimates
- KCNJ11: mutation & growth rates estimates
- Estimates of per-locus mutation rates
- What if variants are not neutral?
- Motoo Kimura and Tomoko Ohta
- Neutral and nearly neutral variants
- Methods to predict deleteriousness
- Rare variants are more likely to be deleterious
- Complex disease studies: growth implications
- Allelic heterogeneity of PAH
- Conclusions
- Acknowledgements
Topics Covered
- Brief introduction to population genetics
- The neutral coalescent & its distortion by population growth
- The site frequency spectrum
- Growth results in excess of rare variants
- Mutation rate & its estimation from rapidly growing populations
- Growth results in allelic heterogeneity
- Different rare variants at disease-causing loci
Talk Citation
Clark, A. (2015, April 21). Human population growth and its impact on genetic variation [Video file]. In The Biomedical & Life Sciences Collection, Henry Stewart Talks. Retrieved December 25, 2024, from https://doi.org/10.69645/DSRE1092.Export Citation (RIS)
Publication History
Financial Disclosures
- Prof. Andrew Clark has not informed HSTalks of any commercial/financial relationship that it is appropriate to disclose.
Other Talks in the Series: Human Population Genetics II
Transcript
Please wait while the transcript is being prepared...
0:00
Hi, my name is Andy Clark, and I would like to tell you about the human population
growth and its impact on genetic variation.
0:10
We're going to begin with some simple
population genetics to get an idea
of what we expect to be the behavior
of genetic variation in a population of different sizes.
First we're going to start with a particular model called an infinite alleles model,
and this model describes the balance between the input of genetic variation
by mutation, and the loss of that variation by random genetic drift.
This model predicts that the amount of heterozygosity, H in the population
at equilibrium will be theta divided by theta plus one.
I'll spare you the derivation of that, but
this is an essential conclusion from this infinite alleles model.
Theta is the population mutation rate,
and theta is equal to four times the effective population size
times the mutation rate.
I'll be talking a little bit more about what that term "effective population size" is in just a moment.
As I mentioned, H is the heterozygosity of the population
or the probability that when you draw two copies of a gene,
they will be different from each other in a sample from that population.
1:20
If we're talking about DNA sequences, we don't want to replace that term H,
the heterozygocity, by a term that we very easily measure when we get
DNA sequences from individuals,
and that's this term pi.
Pi is also referred to as the nucleotide diversity, or the average probability that
any pair of nucleotides across two different copies of a gene
are going to be different than each other.
Now, you notice that I just replaced the H with pi,
and all that we're doing here is considering the value of theta
for the mutation rate per the nucleotide site in the genome.
Now if theta then is very small, which it will be
considering the mutation rate per single nucleotide in the genome,
that's again on the order of ten to the minus eighth or so,
then that denominator term theta plus one is going to be very close to
one itself, because theta is so small.
So we can just remove that denominator and say pi is approximately equal to theta.
And as we said before, theta is equal to four times any times new.
So in this equilibrium case, the model predicts that the nucleotide
diversity should simply equal four and new approximately.