0:04
So now let's
turn towards some data.
And thus far we've only been
talking about classical models
of population structure and thinking
through, just conceptually, how
migration drift and
natural selection
might be impacting
allele frequencies.
That gives us some
intuition of how we might
be able to infer things from data.
But now let's really look
at that problem directly.
0:27
So let's begin by looking at gene
genealogies or gene trees that
are inferred from sequence data.
0:35
What I'm showing in this slide is
data from Australian grass finches
where there are two sub
species of long-tailed finch
and one species of
black throated finch.
And the long-tailed finches are
more closely related to each other
than the black throated finch.
When we actually look at gene
trees from these three species
and by gene tree I mean, a tree
that is inferred to represent
the relationship between
sequences that have been taken
from a single DNA
molecule in this case,
from each of the three sub species
the acuticauda, hecki, and cincta.
So I'm showing 30 different
gene trees from anonymous loci
from the genome.
The average sequence used
to construct this gene trees
is 553 base pairs.
And only three individuals
was needed, one
per species, to construct these.
What we see in A is that
a set of the gene trees
support a relationship where the
acuticauda and hecki are more
closely related than the cincta.
In B there were set of gene trees
in which acuticauda is more closely
related to cincta than to hecki.
And then finally, in C, we
have a set of gene trees
where hecki and cincta are more
closely related than acuticauda
and D is fourth and final
case where the sequence
data doesn't actually allow
resolution to the relationships.
So this is, on the
surface, a bit confusing.
Why do we have different
topologies of gene trees
when there's a single
underlying species tree
and what can we maybe
learn from this?
To answer those questions,
we need to think
about the coalescent process.
