Introduction to Genetics and Evolution is a college-level class being offered simultaneously to new students at Duke University. The course gives interested people a very basic overview of some principles behind these very fundamental areas of biology. We often hear about new "genome sequences," commercial kits that can tell you about your ancestry (including pre-human) from your DNA or disease predispositions, debates about the truth of evolution, why animals behave the way they do, and how people found "genetic evidence for natural selection." This course provides the basic biology you need to understand all of these issues better, tries to clarify some misconceptions, and tries to prepare students for future, more advanced coursework in Biology (and especially evolutionary genetics). No prior coursework is assumed.
Contribution of Genes vs. Environment III (S)
Loading...
En provenance du cours de Duke University
Introduction to Genetics and Evolution
630 notes
À partir de la leçon
Heritability and Population Growth
This module begins the transition to evolutionary genetics by looking at the relative contributions of genetics and environment to traits, and also introduces how population growth is studied.
Rencontrer les enseignants
Dr. Mohamed NoorEarl D. McLean Professor and Chair,
Biology
Hello, and welcome back to Introductions to Genetics and Evolution.
Now what we've been trying to do in the last couple of videos
is quantify when we're looking at variation in some traits,
such as human height, how much of the variation you see is genetic, and
how much of the variation you see is environmental.
Now, in the previous video we estimated heritability, or that fraction
of the overall phenotypic variation that is genetic using an F2 cross.
Here's the formula by the way for heritability.
Again, that fraction of the overall phenotypic variation is genetic.
We estimate using an F2 cross.
And we start off with tall parents, that are genetically identical to each other,
so the genetic variance here is equal to 0.
We cross into short parents, they're all genetically identical to each other.
So within this box, Janet grants a zero.
We got intermediates, the offspring here from them.
The genetic variation in these is also zero,
they may be heterozygous for a lot of low sine, but they're all heterozygous for
the same low sine exactly the same way.
Okay, so this is the F1s.
From these, we got the F2s, from the F2s,
we see quite a bit more spread than we saw in the F1s or in the parents.
The reason we see more spread is because we've added this.
Instead of Vp just being Ve, Vp here is Ve plus Vg,
we've added genetic variance here.
From this, by comparing, assuming that this Ve is the same as this Ve,
comparing the two Vg's we can get an estimate of heritability, as you saw.
This is not very useful in the context of something like, for example, human height.
Because we don't have a bunch of people who are all genetically identical,
they are tall.
And we can cross to a bunch of people that are all genetically identical,
they were short, and look at the offspring and
their grandkids, and obviously it's not feasible.
Instead, another way to estimate heritability is to use what we refer to as
parent offspring correlation.
If we assume that all variation is genetic, and
let's assume there's no dominance in this case,
then any individual should have exact average phenotype of the two parents.
So, here's a picture of me.
Here's a picture of my wife.
If you put us together into some online form,
it predicted this is what our kid should look like.
This is some sort of intermediate between me and my wife.
In contrast, my actual son looks like this.
There's a picture of him.
Close to, but not exactly identical to this exact average.
Now oh yeah, he's not usually quite that tan but
he was out, out in the sun a little bit much that summer.
Now if we look at lots of individuals, we can assess how well
the average of the parents' traits predicts the average of the offsprings.
And then we can use that.
We can look at the strength of the correlation or in this case,
the slope of the line to estimate heritability.
So let's imagine a hypothetical thing.
Let's take an average height of two parents, and
let's say the average height of two parents was 6 foot 0.
So let's take another average height of parents and
say their average height was 5 foot 0.
If the kids on average have exactly the same height as the parents
the average of the kids matches the average of the parents.
That slope is one; therefore the heritability is one.
That is a strong genetic component.
In contrast let's imagine that you see something looking.
Be more like this.
So you do, you look at the correlation between these two,
between the height of the parents and the height of the kids, and
you see that in general, there's no particular prediction whatsoever.
The slope of this line is zero, therefore there is no prediction,
from the average of the parents, to the average height of the kids.
This would suggest there's no genetic.
We can use this to assess heritability.
So I have here four figures.
In Figure A, this is a case where heritability would be approximately zero.
Where you have short versus tall average for the parents,
short versus tall average for the offspring.
You can see the slope there is basically zero.
These you see some relationship.
This would be about a case with heritability is about .5.
See here you have a very strong relationship.
There the heritability is very very close to one.
In this case the height of parents, the average of the two parents,
very well predicts the average height of the offspring.
And here's some real data over here.
This is looking at students and their parents.
This is from the Evolutionary Analysis textbook.
You see the midparent height is very close to the mid offspring height.
The slope there is 0.84,
suggesting a very stong genetic component to human height in this case.
Now that's interesting, but I have to remind you why this matters.
Again, there is medical relevance to this.
Let's say your parents get gall stones.
Is it worth it for you to alter your diet?
Right? Or is this predominantly genetic?
Do you as a doctor want to tell somebody, no, give up eating meat completely?
When in fact giving up eating meat may have no effect whatsoever on their
likelihood of having some sort of disease.
No, you need to be able to identify something as having a strong genetic
component versus a very weak genetic component and
more of an environmental effect, so you can practice medicine properly.
Similarly, let's say you want to breed a friendlier guinea pig.
How much will selective breeding matter?
Or, is friendliness just how much you handle the guinea pig,
something along those lines.
Unfortunately, things aren't always as straightforward as I said.
Now everything we've been talking about, ignores the fact that parents and
offspring may share some environmental factors, as well as genetic factors.
There's probably a correlation in food availability and
other characteristics between parents and offspring.
And what this does is this biases upward the estimate of heritability.
We are assuming anything that's shared in this way is from genetics but, in fact,
there may be some environmental affect that's shared,
especially in this sort of parent offspring correlation that I talked about.
There are other assumptions as well.
First that we're assume the environment is constant, such as for
example that F1, F2 cross we looked at.
We assumed that Ve was exactly the same in the F1 as in the F2.
But in fact the environment is probably not constant.
Estimates of heritability may also be very different
if you go to different places because Ve may be very different.
This is also true at different time.
And finally, the amount of genetic variation is also not constant
in different families or populations.
So let's say for
example you study in Australia the heritability of human height.
That result may not apply if you went to India, if you went to Japan,
things like that, because the amount of genetic variation is going to be
different, the amount of environmental variation may also be different.
But, despite all this, it's not perfect but it's a starting point.
And it's still useful under particular circumstances.
So next class, we'll actually go into another means for
estimating heritability and that is what's referred to as the breeder's equation.
We'll also talk a fair bit about population growth,
that will be a little bit of a side.
Thank you and I hope you enjoyed this.
Explorer notre catalogue
Rejoignez-nous gratuitement et obtenez des recommendations, des mises à jour et des offres personnalisées.
Coursera propose un accès universel à la meilleure formation au monde,
en partenariat avec des universités et des organisations du plus haut niveau, pour proposer des cours en ligne.
© 2019 Coursera Inc. Tous droits réservés.
