0:00
Welcome to the lecture
on Statistical Techniques
in Human Population Genetics,
part of the statistical
genetic series.
I'm Garrett Hellenthal,
a research fellow
at University College London
whose main work
is in statistical
and population genetics.
0:13
The main aims of this lecture
are to describe the biological
and demographic processes
that contribute
to genetic diversity,
describe
the statistical techniques
that use observed DNA patterns
to infer these past processes,
illustrate the types of data
used for inferring
human history,
and how we can learn
different aspects of history
using these different
types of data, and finally,
highlight some key findings
about human history
derived through the use
of these techniques.
0:39
We'll start with
some brief background.
While overall DNA patterns
among different human groups
are very similar,
nonetheless they are
clear genetic differences
among different
human groups today.
Several factors have contributed
to this observed
genetic diversity.
For example,
geographic isolation,
groups being separated
from each other
due to physical boundaries,
population size changes,
and intermixing or admixture
among genetically
different groups.
And underlying these factors
are the usual genetic processes
you will have learned about
by now,
that which we'll
briefly review here,
genetic drift, mutation,
recombination, and selection.
What the population geneticist
is trying to do then
is take the genetic differences
that we observed
and try to reverse this to learn
about the past processes
that have led
to these differences.
1:23
There are several sources of DNA
we use to do this.
One is the autosomes,
of which we have 22 pairs
with an each pair inheriting
one chromosome per parents.
There is also the X chromosome
of which males have
one from their mother,
and females have one
from each parents.
The Y chromosome only in males
passed from father to son.
And finally, mitochondrial DNA
or mtDNA
just passed from mother
to offspring.
Initially the Y and mtDNA
were used extensively
to study demographic
history of humans,
and are still very informative
about sex-biased intermixing
among groups in particular
as we'll later demonstrate.
However, with the advent
of new technology,
I can efficiently and cheaply
target large amounts of DNA.
The autosomes and X chromosome
are more prominently used now
in large scale studies.
The major advantage of these
chromosomes is that
because of their large amount
and method of inheritance,
they contain many
thousands of times
more information
than Y or mtDNA,
but with these same features
make them more challenging
to analyze.
There are many types
of genetic variation data
that population
geneticists study.
The most common type
of genetic variation
or changes or point mutations
at Single-Nucleotides
in our approximate
three billion long
genetic sequence,
these are called
Singe-Nucleotide-Polymorphisms
or SNPs.
And it will be
the type of variation data
used throughout the majority
of this lecture.
However, some analyses
we discussed
will make use of microsatellites
which are contiguous
repeated DNA sequences.
For example, "A T"
repeated several times,
I have illustrated here,
where
individuals can differ in the
number of such repeats
if they carry.
There are many
other types of variation
including copy-number-variants,
indels, and inversions,
which I will not discuss here.
