DNA

WEBVTT
Kind: captions
Language: en

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I'm sure many of y'all have
already heard of the molecule

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DNA, and it stands for
deoxyribonucleic acid.

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I wrote it out ahead of time
to spare you the pain of

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watching me spell this
in real time.

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But it is-- and I think you
already have an idea.

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This is the basic unit of
heredity, or it's what codes

00:00:21.170 --> 00:00:23.790
all of our genetic
information.

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And what I want to do in this
video-- because I think that's

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kind of common knowledge.

00:00:26.910 --> 00:00:30.240
That's popular knowledge that,
oh, everything that makes my

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hair black or my eyes blue or
whatever, that's all somehow

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encoded in our DNA.

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But what I want to do in this
video is give you an idea of

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how something like DNA, a
molecule, can actually code

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for what we are.

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How does the information, one,
get stored in this type of a

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molecule, then how does that
actually turn into the

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proteins that make up our
enzymes and our organs and our

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brain cells and everything else
that really make us us?

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So this is a computer graphics
representation of DNA, and I'm

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sure many of y'all have heard
of the double helix.

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And that's in reference to the
structure that DNA takes.

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And you can see here it's
a double helix.

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As you can see here, you have
two of these lines, and

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they're intertwined
with each other.

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You see there, that's one of
them, and then you see another

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one intertwined like that.

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And then they're connected by--
you can almost view it as

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like these bridges between the
two helixes, and they twist

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around each other.

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I think you get the idea.

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So the double helix just
describes the structure, the

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shape that DNA takes, and
it leads to all sorts of

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interesting repercussions in
terms of how heredity takes

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place and how natural selection
and variation might

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take place as well.

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And actually, in the future, I
do want to actually read with

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you Watson and Crick's paper on
the double helix where they

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essentially talk about
their discovery.

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The best thing about that paper,
besides the fact that

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it was probably one of the
biggest discoveries in the

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history of mankind, is that the
paper is only a page and a

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half long, and it goes to my
general view that if you have

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something good to say,
it shouldn't take you

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that long to say it.

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But with that said, let's think
a little bit about how

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this can actually generate the
proteins and whatever else

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that make up all of us.

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So right here this is a
zoomed-up version of that

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graphic that I just showed you a
little bit earlier, and this

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is each of the helixes.

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So if this is the magenta side,
if you unwound this

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helix-- right now it shows it
in its wound state, but if I

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unwind this helix, one side
would maybe be this magenta

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side of our helix and
then one side is

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this green side, right?

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And if you twist it up,
you get back to

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this drawing up here.

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And then these bridges that you
see in this drawing in the

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double helix, those are these
connections right here.

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These are the bridges.

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Now, what allows us to code
information is that the blocks

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that make up the bridges are
made of different molecules.

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And the four different molecules
that are made up in

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DNA are adenine-- and
it's written here

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on this little chart.

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I got all of this from
Wikipedia, so if you want more

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information I encourage
you to go there.

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Adenine, that's up here.

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This is the molecular structure
of adenine.

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It's connected to a sugar
right here, ribose.

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I won't go into a deoxyribose.

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And then you have your
phosphate group.

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But these kind of form the
backbone of the DNA: the sugar

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and the phosphate groups.

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And I'm not going to go into
the microbiology of it,

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because that's not important
right now to understanding

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just how does this intuitively
code for what we are.

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So along the backbone, which
is identical, and

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we'll talk about it.

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They run in different
directions.

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It's called antiparallel,
so they label the ends.

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And I'm not going to go into
detail there, but the

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important thing are
these bases here.

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So you have adenine, and adenine
pairs with thymine,

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and you see that up here.

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If you have an adenine molecule
here, an adenine base

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here, it'll pair with
thymine, and this is

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called the base pair.

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Adenine and thymine pair
with each other.

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If you have thymine, it's going
to pair with adenine.

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And then you have guanine and
it pairs with cytosine.

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And the names of these, you
should know these names, just

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because they are almost-- well,
if you ever enter any

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discussion about DNA
and base pairs,

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this is expected knowledge.

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But the names of the molecules
and how they're structured,

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not important just yet.

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But what's important is the fact
that there are four of

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them and that they essentially
code information.

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So you can view one of these
strands in kind of a

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simplified way.

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You can just view it as a strand
of-- so this one, if it

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has an adenine and then
it has a cytosine,

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then it has a guanine.

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That's a guanine.

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They did it in purple.

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And then it has a-- oh, no, it
has a thymine, not a guanine.

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So it has a thymine in
purple, and then in

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blue, it has a guanine.

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So this strand right
here codes ACTG.

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And if you were to code the
opposite side of the strand,

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you could immediately-- I don't
even have to look here.

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I can look at this side and
say, OK, adenine will pair

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with thymine, cytosine pairs
with guanine, thymine pairs

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with adenine, and guanine
pairs with cytosine.

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So they're complementary
strands.

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So if you think about
it, they're really

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coding the same thing.

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If you have one of them, you
have all of the information

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for the other.

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Now, in our DNA, in a human's
DNA, you might say, hey, Sal,

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how do I go from these little
chains of these molecules?

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How does that turn into me?

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How does that turn into
this complex organism?

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And the simple answer is, well,
the human genome has

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three billion of these
base pairs.

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And that's actually just in
half of your chromosomes.

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And I'll tell you, maybe in this
video or a future video,

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why we only consider half of
your chromosomes, and that's

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because essentially you have
a pair of every chromosome.

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I'll talk in more detail
about that.

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And this number, to some people,
they might say, it

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only takes three billion base
pairs to describe who I am?

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And some people would say, wow,
it takes three billion

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base pairs to describe
who I am.

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I never thought I was
that complex.

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So depending on your point of
view, this is either a large

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or small number.

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But when you take these three
billion base pairs, you're

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actually encoding all of the
information that it takes to

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make in this case
a human being.

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And actually it turns out a
lot of primates don't have

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that many different base pairs
than human beings.

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The amazing thing is even things
like roundworms and

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fruit flies also number in a
surprisingly large fraction of

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the base pairs of
a human being.

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Maybe I'll do another
video where I go

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into comparative biology.

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But how do these base pairs
actually lead to proteins?

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I mean, it's fair enough.

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That's information.

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It's like you can view these
as ones and zeroes in some

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type of computer language, but
really they're not just ones

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and zeroes, because they can
take on four different values.

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They can take on an A, a T, a
C or a G, so you could think

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of them as zero, ones, twos
and threes, but I won't go

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into that whole aspect
of it just now.

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So how does that actually
code information?

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So DNA when it actually
transcribes something-- the

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process is called transcription,
and I'm going

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to do a pretty gross
simplification of it, but I

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think it'll give you the gist of
how it codes for proteins.

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So what happens when
transcription happens is that

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these two strands split up, and
one of the strands-- let

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me just take one of them.

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Let's say it looks like this.

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I'll do it all in one color.

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Let's say it's just ATGGACG--
I'm just making up stuff-- TA.

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Let's say that that's the strand
that got split up.

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And what happens is
it transcribes--

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and I won't say itself.

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There's a whole bunch of enzymes
and proteins and a

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whole bunch of chemical
reactions that have to happen,

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but this DNA essentially
transcribes a

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complementary mRNA.

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And I'll introduce RNA.

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It's essentially the exact same
thing as-- well, the word

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is ribonucleic acid, so it's
literally-- you get rid of the

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deoxy, so you can kind of say
it's got its oxy, and it's

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ribonucleic acid, but it's
very similar to DNA.

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It codes in the exact
same way.

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The only difference between RNA,
instead of a thymine, it

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has something called a uracil.

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So every place where you would
have expected a thymine, you

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would have expected a T,
you'll now see a U.

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So, for example, if this is the
DNA strand, then an RNA,

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an mRNA, in a messenger RNA
strand, will be built

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complementary to this.

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So it'll be built-- let's see.

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With A, you'd normally have
thymine when you're talking

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DNA, but now we're talking RNA,
so it'll be a uracil,

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then an adenine, cytosine,
cytosine, uracil, then we got

00:10:09.260 --> 00:10:14.070
a guanine, a cytosine,
an adenine, and then

00:10:14.070 --> 00:10:14.770
we'll have a uracil.

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So this is the mRNA
strand here.

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And all of this is occurring
inside the

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nucleus of your cells.

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And we'll do a whole series of
videos in the future about the

00:10:25.670 --> 00:10:30.995
structure of our cells, but I
think most of us know that our

00:10:30.995 --> 00:10:34.910
cells-- and I'll talk more
about eukaryotic and

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prokaryotic organisms in the
future, but most complex

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organisms, they have a cell
nucleus where we have all of

00:10:39.860 --> 00:10:42.540
our chromosomes that contain
all of our DNA.

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And so this mRNA then detaches
itself from the DNA that it

00:10:48.690 --> 00:10:52.400
was transcribed from, and then
it leaves the nucleus, and it

00:10:52.400 --> 00:10:54.950
goes to these structures
called ribosomes.

00:10:54.950 --> 00:10:57.360
I'm oversimplifying it a
little bit, but at the

00:10:57.360 --> 00:11:02.510
ribosomes, this mRNA is
translated into proteins.

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So let me do that.

00:11:03.450 --> 00:11:06.360
So let's say this is the mRNA.

00:11:06.360 --> 00:11:08.780
It was transcribed from that
DNA, so let me get

00:11:08.780 --> 00:11:12.320
rid of that DNA now.

00:11:12.320 --> 00:11:13.300
I got rid of the DNA.

00:11:13.300 --> 00:11:15.990
This is the mRNA that we were
able to transcribe from that

00:11:15.990 --> 00:11:19.220
DNA, and they have these
other things called

00:11:19.220 --> 00:11:21.600
tRNA or transfer RNA.

00:11:21.600 --> 00:11:23.230
And what these are--
and this is the

00:11:23.230 --> 00:11:24.930
really interesting part.

00:11:24.930 --> 00:11:28.230
So you may or may not know that
pretty much everything we

00:11:28.230 --> 00:11:30.200
are is made up of proteins.

00:11:30.200 --> 00:11:32.610
And these proteins, the building
blocks of proteins

00:11:32.610 --> 00:11:33.790
are amino acids.

00:11:33.790 --> 00:11:37.380
And for those of you who like
to lift weights, I'm sure

00:11:37.380 --> 00:11:41.120
you've seen ads for amino
acid supplements and

00:11:41.120 --> 00:11:42.640
things of the like.

00:11:42.640 --> 00:11:45.420
And the reason why they talk
about amino acids is because

00:11:45.420 --> 00:11:49.400
those are the building
blocks of proteins.

00:11:49.400 --> 00:11:52.200
My son actually has an allergy
to milk protein, so we had to

00:11:52.200 --> 00:11:55.690
get him a formula that was just
pure amino acids, just

00:11:55.690 --> 00:11:58.520
all of the milk proteins
broken down.

00:11:58.520 --> 00:12:04.260
So if you look at a protein,
it's actually a chain of these

00:12:04.260 --> 00:12:07.240
amino acids and usually
a fairly long chain.

00:12:07.240 --> 00:12:11.750
We'll look at some protein
structures in the very near

00:12:11.750 --> 00:12:14.090
future, just to give you
an idea of things.

00:12:14.090 --> 00:12:17.550
It's a very long chain of these
amino acids, and there

00:12:17.550 --> 00:12:20.700
are actually 20 different
amino acids.

00:12:20.700 --> 00:12:23.760
Twenty different amino acids are
pretty much the structure

00:12:23.760 --> 00:12:24.990
of all of our proteins.

00:12:24.990 --> 00:12:26.240
Let me write that.

00:12:30.790 --> 00:12:34.070
So a very obvious question is
how can these things code for

00:12:34.070 --> 00:12:36.050
20 different amino acids?

00:12:36.050 --> 00:12:40.370
I can only have four different
things in this little bucket

00:12:40.370 --> 00:12:41.410
right here.

00:12:41.410 --> 00:12:44.880
And then you just have to go
back to your combinatorics, or

00:12:44.880 --> 00:12:48.510
if you can't go back to it
to watch the playlist on

00:12:48.510 --> 00:12:51.290
probability and combinatorics,
and say, OK, there's only four

00:12:51.290 --> 00:12:56.090
ways that I can have for
each of these bases.

00:12:56.090 --> 00:12:58.600
There's only four different
bases that I can have here,

00:12:58.600 --> 00:13:02.540
either an adenine guanine,
cytosine or, depending on

00:13:02.540 --> 00:13:04.770
whether we're talking
about DNA or RNA,

00:13:04.770 --> 00:13:06.980
a uracil or a thymine.

00:13:06.980 --> 00:13:08.810
But how can we increase
the combinations?

00:13:08.810 --> 00:13:13.450
Well, if we include two of them,
if we include two bases,

00:13:13.450 --> 00:13:16.350
then how many combinations
can we have?

00:13:16.350 --> 00:13:18.260
Well, we have four possibilities
here, then we'd

00:13:18.260 --> 00:13:22.190
have four possibilities here, so
we'd have 16 possibilities.

00:13:22.190 --> 00:13:23.850
But that's still not enough.

00:13:23.850 --> 00:13:27.800
That's still not enough to code
for one of 20 amino acids

00:13:27.800 --> 00:13:31.080
to say, hey, this is going to
code for amino acid number

00:13:31.080 --> 00:13:33.950
five, and we'll talk more about
their actual names.

00:13:33.950 --> 00:13:34.820
So what do we have to do?

00:13:34.820 --> 00:13:36.740
Well, we have to use
three of them.

00:13:36.740 --> 00:13:40.040
So three of them, there's
actually four times four times

00:13:40.040 --> 00:13:44.020
four possibilities here, so
they could code for 64

00:13:44.020 --> 00:13:45.610
different things.

00:13:45.610 --> 00:13:49.170
They could take on 64 different
combinations or

00:13:49.170 --> 00:13:51.670
permutations, this
UAC right here.

00:13:51.670 --> 00:13:54.990
So if we have three of these
bases, we can actually code

00:13:54.990 --> 00:13:56.400
for an amino acid.

00:13:56.400 --> 00:13:58.580
Actually, it's overkill, because
we can actually have

00:13:58.580 --> 00:14:02.510
64 combinations here, and there
are only 20 amino acids,

00:14:02.510 --> 00:14:05.410
so we can even have redundant
combinations code for

00:14:05.410 --> 00:14:06.470
different amino acids.

00:14:06.470 --> 00:14:11.210
For example, we might say
that, and this isn't the

00:14:11.210 --> 00:14:14.350
actual code, but maybe UAC, and
I should look these up.

00:14:14.350 --> 00:14:18.020
This codes for amino
acid number 1.

00:14:18.020 --> 00:14:24.730
And if it was AAU, then this
codes for amino acid number 2.

00:14:24.730 --> 00:14:29.430
And if I have-- I mean, I
think you get the idea.

00:14:29.430 --> 00:14:35.110
If I have GGG, this codes for
amino acid number 10.

00:14:35.110 --> 00:14:38.490
And what happens is when this
messenger RNA leaves the

00:14:38.490 --> 00:14:41.330
nucleus, it goes to the
ribosomes, and at the

00:14:41.330 --> 00:14:44.620
ribosomes-- we're going to look
at that diagram in a few

00:14:44.620 --> 00:14:49.470
seconds-- but at the ribosomes--
let me take my

00:14:49.470 --> 00:14:53.940
same mRNA molecule.

00:14:53.940 --> 00:14:55.570
And they're much longer than
what I'm showing here.

00:14:55.570 --> 00:14:57.700
This is just a fraction
of an mRNA molecule.

00:15:01.080 --> 00:15:04.700
So I'll take my mRNA molecule,
and what they do is they

00:15:04.700 --> 00:15:07.630
essentially act as a template
for tRNA molecules.

00:15:07.630 --> 00:15:12.270
And tRNA molecules are these
molecules that are attached to

00:15:12.270 --> 00:15:15.310
the-- they're almost like the
trucks for the amino acids.

00:15:15.310 --> 00:15:18.610
So let's say I have some amino
acid right here, and then I

00:15:18.610 --> 00:15:22.370
have another amino acid that's
right here like that, and then

00:15:22.370 --> 00:15:25.110
I have another amino acid
that's like that.

00:15:25.110 --> 00:15:27.300
They'll be attached
to tRNA molecules.

00:15:27.300 --> 00:15:33.880
So let's say that this tRNA
molecule has on it-- so this

00:15:33.880 --> 00:15:37.380
amino acid is attached to a
tRNA molecule that has the

00:15:37.380 --> 00:15:42.570
code on it A-- let me do
it in a darker color.

00:15:42.570 --> 00:15:44.415
It has the code AUG.

00:15:48.810 --> 00:15:56.900
This one right here has
the code-- let me

00:15:56.900 --> 00:15:57.650
pick another one.

00:15:57.650 --> 00:15:58.900
Let's say it has GGAC.

00:16:03.300 --> 00:16:04.290
So what's going to happen?

00:16:04.290 --> 00:16:07.210
When you're in the ribosome, and
it's a complex situation,

00:16:07.210 --> 00:16:09.750
but actually what's happening
isn't too fancy.

00:16:09.750 --> 00:16:14.380
This tRNA, it wants to bond
to this part of the mRNA.

00:16:14.380 --> 00:16:14.840
Why?

00:16:14.840 --> 00:16:19.670
Because adenine bonds with
uracil, uracil bonds with

00:16:19.670 --> 00:16:22.940
adenine, and guanine bonds with
cyotsine, so it'll pull

00:16:22.940 --> 00:16:23.930
up right here.

00:16:23.930 --> 00:16:25.970
It'll pull up right next to this
thing, and actually, I

00:16:25.970 --> 00:16:29.920
should probably-- well, I don't
know if I can rotate it.

00:16:29.920 --> 00:16:32.530
But it'll just pull up
right here and attach

00:16:32.530 --> 00:16:33.800
to this mRNA molecule.

00:16:33.800 --> 00:16:35.060
And this right here is tRNA.

00:16:37.930 --> 00:16:39.450
This is mRNA.

00:16:39.450 --> 00:16:40.410
And the names don't matter.

00:16:40.410 --> 00:16:42.510
I really just want to give you
the big picture idea of how

00:16:42.510 --> 00:16:44.490
the proteins are actually
formed.

00:16:44.490 --> 00:16:45.960
And this is an amino acid.

00:16:45.960 --> 00:16:49.600
I don't know, let's call it
amino acid 1, amino acid 5,

00:16:49.600 --> 00:16:52.090
amino acid 20.

00:16:52.090 --> 00:16:54.670
This guy, he's going to
pull up right here.

00:16:54.670 --> 00:16:57.530
The guanine is attracted to the
cytosine, and if you watch

00:16:57.530 --> 00:16:59.740
the chemistry videos, these are
actually hydrogen bonds

00:16:59.740 --> 00:17:01.410
that form the base pairs.

00:17:01.410 --> 00:17:05.380
Adenine, wants to pull up to
uracil, cytosine to guanine,

00:17:05.380 --> 00:17:06.579
and so on and so forth.

00:17:06.579 --> 00:17:08.430
And so once all of these
guys have pulled

00:17:08.430 --> 00:17:09.970
up-- let me do that.

00:17:09.970 --> 00:17:13.030
So once you've pulled up, let's
say that this is-- I

00:17:13.030 --> 00:17:14.740
could do it up here.

00:17:14.740 --> 00:17:16.720
This is my mRNA molecule.

00:17:16.720 --> 00:17:19.180
I'm not going to draw the
specifics right there.

00:17:19.180 --> 00:17:24.339
My little tRNA's pull up, pull
up next to it, and they each

00:17:24.339 --> 00:17:26.470
hold a payload, right?

00:17:26.470 --> 00:17:29.250
So this first one holds this
payload right here of this

00:17:29.250 --> 00:17:30.230
amino acid.

00:17:30.230 --> 00:17:33.840
The second one holds this
payload of this amino acid and

00:17:33.840 --> 00:17:36.800
so forth and so on.

00:17:36.800 --> 00:17:40.030
And so it might keep going,
and there's another green

00:17:40.030 --> 00:17:40.870
amino acid here.

00:17:40.870 --> 00:17:43.230
They really don't have those
colors, but I'm just-- just

00:17:43.230 --> 00:17:45.300
for the sake of simplicity
like that.

00:17:45.300 --> 00:17:47.880
And then the amino acids bond
to each other when they're

00:17:47.880 --> 00:17:49.600
held like that close
to each other.

00:17:49.600 --> 00:17:51.360
This doesn't happen
all by itself.

00:17:51.360 --> 00:17:53.860
The ribosome serves a purpose,
and there are enzymes that

00:17:53.860 --> 00:17:58.210
facilitate this process, but
once these guys bond together,

00:17:58.210 --> 00:18:01.160
the tRNA detaches,
and you have this

00:18:01.160 --> 00:18:04.330
chain of amino acids.

00:18:04.330 --> 00:18:08.590
And then the chain of amino
acids starts to bend around so

00:18:08.590 --> 00:18:10.910
they have all of these-- and
it's actually a fascinating--

00:18:10.910 --> 00:18:14.920
I mean, people spend their lives
studying how proteins

00:18:14.920 --> 00:18:17.680
fold, and that's actually where
they get most of their

00:18:17.680 --> 00:18:18.770
structural properties.

00:18:18.770 --> 00:18:21.030
It's not just the chain of the
amino acids, but what's more

00:18:21.030 --> 00:18:23.660
important is how these amino
acids actually fold.

00:18:23.660 --> 00:18:26.880
So once you fold them, they form
these really ultracomplex

00:18:26.880 --> 00:18:30.990
patterns based on what amino
acid is attracted to what

00:18:30.990 --> 00:18:33.180
other amino acid in these
very intricate

00:18:33.180 --> 00:18:34.820
three-dimensional shapes.

00:18:34.820 --> 00:18:38.250
And what I took here from
Wikipedia is these are some

00:18:38.250 --> 00:18:38.920
amino acids.

00:18:38.920 --> 00:18:44.150
And just to be able to relate
this to the DNA, this right

00:18:44.150 --> 00:18:45.220
here is insulin.

00:18:45.220 --> 00:18:49.850
It's key in our ability to
process glucose in our body.

00:18:49.850 --> 00:18:51.300
So this right here is insulin.

00:18:51.300 --> 00:18:52.430
It's a hormone.

00:18:52.430 --> 00:18:54.970
So sometimes you hear people
talk about your immune system.

00:18:54.970 --> 00:18:57.110
Sometimes you hear people
talking about your endocrine

00:18:57.110 --> 00:19:00.200
system and hormones, sometimes
your digestive system.

00:19:00.200 --> 00:19:05.700
This is hemoglobin, what
essentially transports our

00:19:05.700 --> 00:19:07.090
oxygen in our blood.

00:19:07.090 --> 00:19:10.020
But all of these things are
proteins, and all these

00:19:10.020 --> 00:19:12.510
little, little folds you see,
these are all little amino-- I

00:19:12.510 --> 00:19:16.520
mean, they're just little
dots of amino acids.

00:19:16.520 --> 00:19:19.810
Some of these are multiple
chains of amino acids kind of

00:19:19.810 --> 00:19:22.250
fitting together like a big
puzzle, but some of them or

00:19:22.250 --> 00:19:23.950
just single chains
of amino acids.

00:19:23.950 --> 00:19:27.310
For insulin right here, this
is 50 amino acids.

00:19:27.310 --> 00:19:30.850
And then once the chain forms,
it all bundles together and

00:19:30.850 --> 00:19:34.710
forms this little blob like you
see, but the shape of that

00:19:34.710 --> 00:19:38.350
blob is super important for
insulin being able to perform

00:19:38.350 --> 00:19:41.870
the function that it needs to
perform in our systems.

00:19:41.870 --> 00:19:47.040
But this right here is
approximately 50-- I forgot

00:19:47.040 --> 00:19:49.145
the exact number--
amino acids.

00:19:53.210 --> 00:19:59.670
This right here, this
immunoglobulin G, which is

00:19:59.670 --> 00:20:01.760
part of our immune
system, this is

00:20:01.760 --> 00:20:09.700
roughly 1,500 amino acids.

00:20:09.700 --> 00:20:12.160
So how much DNA or how
many base pairs

00:20:12.160 --> 00:20:12.990
had to code for this?

00:20:12.990 --> 00:20:15.180
Well, three times
as much, right?

00:20:15.180 --> 00:20:19.350
Because you have to have three
base pairs that code for one

00:20:19.350 --> 00:20:21.490
amino acid, and actually, three
base pairs, this is

00:20:21.490 --> 00:20:27.180
called a codon, because it
codes for amino acids.

00:20:27.180 --> 00:20:29.380
So three base pairs
make a codon.

00:20:29.380 --> 00:20:32.170
So if you have 50 amino acids
that make up insulin, that

00:20:32.170 --> 00:20:34.230
means you're going to have to
have 50 codons, which means

00:20:34.230 --> 00:20:39.940
you have to have 150 bases
or 150 of these

00:20:39.940 --> 00:20:41.770
A's and G's and T's.

00:20:41.770 --> 00:20:45.100
If you have 1,500 amino acids,
that means you're going to

00:20:45.100 --> 00:20:47.420
have to have 1,500 codons, which
means you're going to

00:20:47.420 --> 00:20:54.660
have roughly 4,500 of these base
pairs that code for it.

00:20:54.660 --> 00:20:59.280
Now, there are some notions that
get confused a lot, so I

00:20:59.280 --> 00:21:02.480
went to kind of the smallest
level of our DNA right here,

00:21:02.480 --> 00:21:05.180
and this is the level at which--
well, this is RNA that

00:21:05.180 --> 00:21:08.300
I'm pointing to right there, but
this is the smallest level

00:21:08.300 --> 00:21:10.580
of DNA, and that's the level
at which the information is

00:21:10.580 --> 00:21:11.320
actually coded.

00:21:11.320 --> 00:21:14.490
But how does that relate to
things like genes and

00:21:14.490 --> 00:21:16.700
chromosomes and things
that you might talk

00:21:16.700 --> 00:21:18.183
about in other contexts?

00:21:20.860 --> 00:21:25.880
So let's say the 150 base pairs
that coded for insulin,

00:21:25.880 --> 00:21:27.515
these make up a gene.

00:21:30.600 --> 00:21:36.450
And these 4,500 base pairs
make up another gene.

00:21:36.450 --> 00:21:40.070
Now, all of the genes don't make
proteins, but all of the

00:21:40.070 --> 00:21:41.720
proteins are made by genes.

00:21:41.720 --> 00:21:45.940
So let's say I have just a
bunch of-- I'll just make

00:21:45.940 --> 00:21:51.770
another A, G, and it goes down,
down, down, and you have

00:21:51.770 --> 00:21:54.920
a T and then a C and a
C, and let's say I

00:21:54.920 --> 00:21:57.840
have 4,500 of these.

00:21:57.840 --> 00:22:01.480
These could code
for a protein.

00:22:01.480 --> 00:22:03.320
These could code for protein,
or they could have all of

00:22:03.320 --> 00:22:07.480
these other kind of regulatory
functions telling what other

00:22:07.480 --> 00:22:10.400
parts of the DNA should and
should not be coded and how

00:22:10.400 --> 00:22:13.870
the DNA behaves, so it becomes
super, super complex.

00:22:13.870 --> 00:22:18.050
But this kind of section of our
DNA, this is what we refer

00:22:18.050 --> 00:22:24.400
to as a gene, and a gene can
have anywhere from a couple of

00:22:24.400 --> 00:22:28.990
hundreds of these base pairs
or these bases to several

00:22:28.990 --> 00:22:30.860
thousand of these base pairs.

00:22:30.860 --> 00:22:34.220
Now, a gene is that part of our
chromosome that codes for

00:22:34.220 --> 00:22:37.920
a particular protein or serves
a certain function.

00:22:37.920 --> 00:22:40.285
Now, there are different
versions of genes.

00:22:43.000 --> 00:22:45.580
It's a gross oversimplification,
but let me

00:22:45.580 --> 00:22:49.815
say this is the gene
for insulin.

00:22:53.040 --> 00:22:56.650
Now, there might be slight
variations in how insulin can

00:22:56.650 --> 00:22:59.880
be coded for, and I'm kind of
going out of my domain right

00:22:59.880 --> 00:23:00.870
here, because I don't
know if that's true.

00:23:00.870 --> 00:23:02.580
And maybe I shouldn't just
speak specifically about

00:23:02.580 --> 00:23:04.860
insulin, but it's coding for
some protein, but there's

00:23:04.860 --> 00:23:06.990
maybe multiple different
ways that that

00:23:06.990 --> 00:23:08.470
protein can be coded.

00:23:08.470 --> 00:23:11.540
Maybe instead of a T here,
sometimes there's a C there.

00:23:11.540 --> 00:23:13.000
It still codes for
the same protein.

00:23:13.000 --> 00:23:16.330
It doesn't change it quite
enough, but that protein acts

00:23:16.330 --> 00:23:18.730
just a little bit different.

00:23:18.730 --> 00:23:20.420
It's a slight variant.

00:23:20.420 --> 00:23:21.750
I'll use that word.

00:23:21.750 --> 00:23:24.850
Now, each variant of this gene
is called an allele.

00:23:27.540 --> 00:23:34.845
It's a specific variant
of your gene.

00:23:37.460 --> 00:23:45.230
Now, if you take this DNA chain,
and this chain over

00:23:45.230 --> 00:23:45.840
here-- let's see.

00:23:45.840 --> 00:23:47.910
This is one base pair.

00:23:47.910 --> 00:23:50.000
This might be like one base.

00:23:50.000 --> 00:23:51.200
This is another base.

00:23:51.200 --> 00:23:54.430
Maybe this is an adenine and
then this would be a thymine

00:23:54.430 --> 00:23:55.900
over here in green.

00:23:55.900 --> 00:23:59.220
This is an adenine and this
would be a thymine.

00:23:59.220 --> 00:24:02.570
If right here this is a guanine,
then right here would

00:24:02.570 --> 00:24:03.710
be a cytosine.

00:24:03.710 --> 00:24:05.610
This would be just a
very small section.

00:24:05.610 --> 00:24:10.800
If I were to like zoom out, and
let's say we have a big

00:24:10.800 --> 00:24:14.180
chain of DNA where each of these
little dots are a base

00:24:14.180 --> 00:24:19.510
pair that I'm drawing here,
maybe this section

00:24:19.510 --> 00:24:23.310
codes for gene 1.

00:24:23.310 --> 00:24:25.630
And then there's some noise or
things that we haven't fully

00:24:25.630 --> 00:24:26.120
understood yet.

00:24:26.120 --> 00:24:26.940
Now, I want to be clear.

00:24:26.940 --> 00:24:29.790
Just with a simple discussion of
DNA, we're already kind of

00:24:29.790 --> 00:24:32.110
approaching the frontiers of
what we know and what we don't

00:24:32.110 --> 00:24:35.890
know, because DNA is hugely
complex, and there's all of

00:24:35.890 --> 00:24:38.300
these feedback structures, and
certain genes tell you to code

00:24:38.300 --> 00:24:40.600
for other genes and not to code
for other genes and to

00:24:40.600 --> 00:24:43.250
code under certain
circumstances, hugely complex.

00:24:43.250 --> 00:24:45.050
So there's huge sections of
DNA that we still don't

00:24:45.050 --> 00:24:46.990
understand what exactly
they do.

00:24:46.990 --> 00:24:48.930
But then maybe they'll have
another section here that

00:24:48.930 --> 00:24:50.470
codes for gene 2.

00:24:50.470 --> 00:24:52.570
Maybe gene 2 is a little
bit longer.

00:24:52.570 --> 00:24:54.510
Maybe it's 1,000 base pairs.

00:24:54.510 --> 00:25:00.380
But when you take all of these
and you turn it into a-- it

00:25:00.380 --> 00:25:04.990
kind of winds in on
itself like this.

00:25:04.990 --> 00:25:05.610
Let me do it.

00:25:05.610 --> 00:25:08.980
So it'll wind up, winding in on
itself like this and do all

00:25:08.980 --> 00:25:10.440
sorts of crazy things.

00:25:10.440 --> 00:25:14.880
Remember, it completely bundles
itself up, and then it

00:25:14.880 --> 00:25:16.300
looks something like that.

00:25:16.300 --> 00:25:17.800
Then you get a chromosome.

00:25:20.550 --> 00:25:24.620
And just to get an idea of how
large a chromosome is compared

00:25:24.620 --> 00:25:29.090
to the actual base pairs,
chromosome number one in the

00:25:29.090 --> 00:25:31.600
human genome-- so we
have 23 pairs.

00:25:31.600 --> 00:25:34.140
If you look at it inside of a
nucleus-- so let's say that's

00:25:34.140 --> 00:25:34.620
the nucleus.

00:25:34.620 --> 00:25:35.720
Let's say this is the cell.

00:25:35.720 --> 00:25:37.960
The cell is much bigger
than what I'm showing.

00:25:37.960 --> 00:25:39.925
But we have 23 pairs
of chromosomes.

00:25:44.020 --> 00:25:45.620
I won't do all of them.

00:25:45.620 --> 00:25:47.280
You can actually see
chromosomes in a

00:25:47.280 --> 00:25:50.290
not-too-expensive microscope, so
we're already getting to a

00:25:50.290 --> 00:25:51.580
scale that we can start
to look at.

00:25:51.580 --> 00:25:55.200
But the largest chromosome,
which is chromosome number one

00:25:55.200 --> 00:25:58.370
in the human genome, just to
give an idea of how much

00:25:58.370 --> 00:26:02.760
information it's packing, that
thing right there has 220

00:26:02.760 --> 00:26:06.640
million base pairs.

00:26:06.640 --> 00:26:08.960
Sometimes people talk about
chromosomes and genetics and

00:26:08.960 --> 00:26:11.070
genes and base pairs
interchangeably, but it's very

00:26:11.070 --> 00:26:12.730
important to kind of get
an idea of scale.

00:26:12.730 --> 00:26:15.910
These chromosomes are a
super-long strand of DNA

00:26:15.910 --> 00:26:18.850
that's all configured and
bundled up, and it contains

00:26:18.850 --> 00:26:21.060
220 million base pairs.

00:26:21.060 --> 00:26:23.920
So the actual elements that are
coding for the information

00:26:23.920 --> 00:26:27.530
are unbelievably small
relative to

00:26:27.530 --> 00:26:29.150
the chromosome itself.

00:26:29.150 --> 00:26:31.260
But now that we understand a
little bit, and actually I

00:26:31.260 --> 00:26:34.490
want to take a look back at
this, because this kind of

00:26:34.490 --> 00:26:36.960
blows my mind, that if you
just take those little

00:26:36.960 --> 00:26:40.370
combinations of those amino
acids, you can form these very

00:26:40.370 --> 00:26:42.890
intricate, very advanced
structures that we're still

00:26:42.890 --> 00:26:46.500
fully understanding how they
actually interact with each

00:26:46.500 --> 00:26:51.155
other and regulate how all of
our biological processes work.

00:26:51.155 --> 00:26:54.850
And what's even more amazing is
that this scheme that I've

00:26:54.850 --> 00:26:58.340
talked about in this video about
DNA to mRNA to tRNA to

00:26:58.340 --> 00:27:02.580
these molecules, this is true
for all of life on our planet,

00:27:02.580 --> 00:27:05.580
so we all share this
same mechanism.

00:27:05.580 --> 00:27:09.930
Me and this plant, we share
that common root

00:27:09.930 --> 00:27:11.340
that we all have DNA.

00:27:11.340 --> 00:27:14.580
As different as me and that
roach that I might not like to

00:27:14.580 --> 00:27:18.240
be in the same room, we all
share that same common root of

00:27:18.240 --> 00:27:21.880
DNA and that all of it codes to
proteins in this exact same

00:27:21.880 --> 00:27:24.440
way, that there's this
commonality amongst all life.

00:27:24.440 --> 00:27:25.700
That, to me, is mind blowing.

00:27:25.700 --> 00:27:28.970
Then even more mind blowing is
how these very complex shapes

00:27:28.970 --> 00:27:31.360
are formed by the DNA.

00:27:31.360 --> 00:27:33.860
And this isn't speculation.

00:27:33.860 --> 00:27:36.710
This is observed behavior.

00:27:36.710 --> 00:27:38.800
This is a fascinating structure
right here, but it's

00:27:38.800 --> 00:27:43.060
just based on 20 amino acid--
you can almost view the amino

00:27:43.060 --> 00:27:46.500
acid as the LEGOS, and you put
the LEGOS together, and just

00:27:46.500 --> 00:27:51.890
the chemical interactions form
these fairly impressive

00:27:51.890 --> 00:27:53.090
structures right here.

00:27:53.090 --> 00:27:55.460
So now that we know a little bit
about DNA and how it codes

00:27:55.460 --> 00:27:58.400
into protein, we can take a
little jump back and talk a

00:27:58.400 --> 00:28:01.480
little bit more about how
variation is actually

00:28:01.480 --> 00:28:04.210
introduced into a population.


Natural Selection and the Owl Butterfly

WEBVTT
Kind: captions
Language: en

00:00:00.600 --> 00:00:03.330
In the first video on evolution,
I gave the example

00:00:03.330 --> 00:00:06.170
of the peppered moth during the
Industrial Revolution in

00:00:06.170 --> 00:00:09.630
England and how, before the
Industrial Revolution, there

00:00:09.630 --> 00:00:11.920
were a bunch of moths: some were
dark, some were light,

00:00:11.920 --> 00:00:12.910
some were in between.

00:00:12.910 --> 00:00:16.309
But then once everything became
soot filled, all of a

00:00:16.309 --> 00:00:20.160
sudden, the dark moths were less
likely to be caught by

00:00:20.160 --> 00:00:23.260
predators and so all of the
white moths were less likely

00:00:23.260 --> 00:00:26.060
to be able to reproduce
successfully, so the black

00:00:26.060 --> 00:00:29.140
moth trait, or that variant,
dominated.

00:00:29.140 --> 00:00:31.600
And then if you came a little
bit later and you saw all the

00:00:31.600 --> 00:00:32.850
moths had turned black,
you'd say all

00:00:32.850 --> 00:00:34.070
these moths are geniuses.

00:00:34.070 --> 00:00:38.760
They appear to have somehow
engineered their way to stay

00:00:38.760 --> 00:00:39.680
camouflaged.

00:00:39.680 --> 00:00:42.060
And the point I was making
there is that, look, that

00:00:42.060 --> 00:00:46.060
wasn't engineered or an explicit
move on the part of

00:00:46.060 --> 00:00:49.090
the moths or the DNA, that was
just a natural byproduct of

00:00:49.090 --> 00:00:52.000
them having some variation, and
some of that variation was

00:00:52.000 --> 00:00:53.080
selected for.

00:00:53.080 --> 00:00:55.850
So that example, that was pretty
simple: black or white.

00:00:55.850 --> 00:00:58.200
But what about more complicated
things?

00:00:58.200 --> 00:01:01.600
So, for example, here I've got a
couple of pictures of what's

00:01:01.600 --> 00:01:04.319
commonly called the
owl butterfly.

00:01:04.319 --> 00:01:06.790
And what's amazing here, and
it's pretty obvious, as I

00:01:06.790 --> 00:01:11.750
probably don't have to point out
to you, is its wing looks

00:01:11.750 --> 00:01:13.370
like half of an owl's eye.

00:01:13.370 --> 00:01:17.980
I can almost draw a beak here
and draw another wing there

00:01:17.980 --> 00:01:20.400
and you can imagine an owl
staring at us, right?

00:01:20.400 --> 00:01:23.310
And here, too, I could imagine
a beak here and you would

00:01:23.310 --> 00:01:25.170
think an owl there, too.

00:01:25.170 --> 00:01:28.880
And so the question is how does
something this good show

00:01:28.880 --> 00:01:30.890
up randomly, right?

00:01:30.890 --> 00:01:33.840
I mean, you could imagine, OK,
little spots or black and

00:01:33.840 --> 00:01:36.630
white or grey, but how does
something that looks so much

00:01:36.630 --> 00:01:39.360
like an eye generate randomly?

00:01:39.360 --> 00:01:42.430
Now the answer is-- well,
there's a couple of answers.

00:01:42.430 --> 00:01:46.820
One is why does this eye
exist, or this eye-like

00:01:46.820 --> 00:01:49.960
pattern or this owl-like
eye's pattern?

00:01:49.960 --> 00:01:52.500
And there, the jury's
still out on that.

00:01:52.500 --> 00:01:56.270
I read a little bit about it on
Wikipedia and all of these

00:01:56.270 --> 00:01:57.540
images I got from Wikipedia.

00:01:57.540 --> 00:01:59.950
In Wikipedia, they said,
look, there's two

00:01:59.950 --> 00:02:00.970
competing theories here.

00:02:00.970 --> 00:02:05.060
One theory is that this, even
though to us humans, the way

00:02:05.060 --> 00:02:07.690
we see things, it looks like
an owl's eye, that this is

00:02:07.690 --> 00:02:09.830
actually a decoy.

00:02:09.830 --> 00:02:16.610
When some predator wants to eat
one of these things, they

00:02:16.610 --> 00:02:18.870
go for the thing that looks
most substantive.

00:02:18.870 --> 00:02:23.000
So instead of going for the
butterfly's body, which

00:02:23.000 --> 00:02:24.350
doesn't look that substantive,
they go for

00:02:24.350 --> 00:02:25.250
the big, black thing.

00:02:25.250 --> 00:02:27.330
They say, oh, that looks like
it's protein rich and it'll be

00:02:27.330 --> 00:02:28.160
a good meal.

00:02:28.160 --> 00:02:31.310
So they try to snap and bite at
that, and if they bite at

00:02:31.310 --> 00:02:34.440
that, sure, the guy's wing's
going to be clipped a little

00:02:34.440 --> 00:02:38.840
bit and it's going to suck,
but the animal itself, the

00:02:38.840 --> 00:02:42.540
actual butterfly, would survive,
and maybe it can

00:02:42.540 --> 00:02:43.320
repair its swings.

00:02:43.320 --> 00:02:46.110
I don't know the actual biology
of the owl butterfly.

00:02:46.110 --> 00:02:48.710
That's one theory, and then the
argument against it goes,

00:02:48.710 --> 00:02:51.090
well, no, if that was the case,
then you would want the

00:02:51.090 --> 00:02:54.070
black spot even further back
along its-- you'd want the

00:02:54.070 --> 00:02:55.980
spot way far away
from the body.

00:02:55.980 --> 00:02:58.280
You'd want it back here instead
of right here, because

00:02:58.280 --> 00:03:00.540
there's still a chance, if
something chomps at this

00:03:00.540 --> 00:03:02.780
little black spot, that
it'll still get the

00:03:02.780 --> 00:03:04.750
abdomen of the butterfly.

00:03:04.750 --> 00:03:08.160
Now, the other theory as to
why this exists-- and, you

00:03:08.160 --> 00:03:08.710
know, who knows?

00:03:08.710 --> 00:03:09.870
Maybe it's a little
bit of both.

00:03:09.870 --> 00:03:11.000
Maybe both of these are true.

00:03:11.000 --> 00:03:12.960
Maybe this offers
two advantages.

00:03:12.960 --> 00:03:15.510
The other theory, and this is
kind of the one that jumps out

00:03:15.510 --> 00:03:17.780
at us when we see this , is,
hey, this looks like an owl.

00:03:17.780 --> 00:03:21.980
Maybe this is to scare away the
things that are likely to

00:03:21.980 --> 00:03:24.400
eat this dude.

00:03:24.400 --> 00:03:28.440
And it does turn out in my
reading that there are lizards

00:03:28.440 --> 00:03:31.120
that like to eat these type of
butterflies, and those lizards

00:03:31.120 --> 00:03:34.470
probably don't like to be around
birds or owls because

00:03:34.470 --> 00:03:36.780
those owls eat them, so that
might be a deterrent.

00:03:36.780 --> 00:03:39.360
And then the other example, they
said is, look, they tend

00:03:39.360 --> 00:03:41.370
to be eaten by this lizard
right here-- this is what

00:03:41.370 --> 00:03:43.740
Wikipedia told me-- and that
this lizard tends to be eaten

00:03:43.740 --> 00:03:47.850
by this frog right there, and
that the eyes of this

00:03:47.850 --> 00:03:50.660
butterfly are not too
dissimilar to the

00:03:50.660 --> 00:03:52.070
eyes of this frog.

00:03:52.070 --> 00:03:54.080
And, you know, we can debate
whether or not that's the

00:03:54.080 --> 00:03:57.050
case, and if this was the
predator we're trying to

00:03:57.050 --> 00:03:59.350
mimic, you could make an
argument that maybe we would

00:03:59.350 --> 00:04:01.620
have had more green on our wing,
but that's not the point

00:04:01.620 --> 00:04:02.210
of this video.

00:04:02.210 --> 00:04:05.540
But it's a fun discussion to
have as to what is useful

00:04:05.540 --> 00:04:06.140
about this eye.

00:04:06.140 --> 00:04:09.270
But let's have the question: How
did that eye come about?

00:04:09.270 --> 00:04:11.350
And when I say that eye, I mean
the pattern on that wing.

00:04:11.350 --> 00:04:13.980
What set of events allowed
this to happen?

00:04:13.980 --> 00:04:16.709
Because when I described
evolution, and we know that

00:04:16.709 --> 00:04:20.610
everything in our biological
kingdom is just a set of

00:04:20.610 --> 00:04:23.540
proteins and then stuff that
maybe the protein-- but mainly

00:04:23.540 --> 00:04:26.920
protein, and that protein's
all coded for by DNA.

00:04:26.920 --> 00:04:29.310
I'm going to do future videos
on DNA, but DNA is just a

00:04:29.310 --> 00:04:31.690
sequence of base pairs.

00:04:31.690 --> 00:04:33.420
It's a sequence of
these molecules.

00:04:33.420 --> 00:04:36.630
And we represent adenine,
and guanine and

00:04:36.630 --> 00:04:37.910
cytosine and thymine.

00:04:37.910 --> 00:04:40.460
Then maybe you have a couple of
adenines in a row and some

00:04:40.460 --> 00:04:41.760
guanine and thymine.

00:04:41.760 --> 00:04:44.840
I'll do a lot more on this in
the future, but the idea is

00:04:44.840 --> 00:04:49.580
it's just coded for by this
sequence of these molecules.

00:04:49.580 --> 00:04:52.010
How do you go from a butterfly
that has no eye to all of a

00:04:52.010 --> 00:04:53.100
sudden an eye that goes there?

00:04:53.100 --> 00:04:55.470
Obviously, just one change
that happens

00:04:55.470 --> 00:04:56.570
from a random mutation.

00:04:56.570 --> 00:05:01.380
Maybe that G turns into an A or
maybe this C and this T get

00:05:01.380 --> 00:05:04.650
deleted so everything-- that
alone isn't going to develop

00:05:04.650 --> 00:05:08.580
this beautiful of a pattern or
this useful of a pattern.

00:05:08.580 --> 00:05:10.880
So how do the random
changes explain

00:05:10.880 --> 00:05:13.030
something that's this intricate?

00:05:13.030 --> 00:05:14.190
And this is my explanation.

00:05:14.190 --> 00:05:16.840
And obviously, I wasn't sitting
there watching over

00:05:16.840 --> 00:05:20.420
the thousands or millions of
years as these owl butterflies

00:05:20.420 --> 00:05:23.520
emerged, so this is just my
theory of how natural

00:05:23.520 --> 00:05:27.330
selection does explain this
type of phenomenon.

00:05:27.330 --> 00:05:30.780
You have a world where in some
environment you have

00:05:30.780 --> 00:05:34.980
butterflies, and their wings
look like-- let's say you have

00:05:34.980 --> 00:05:38.930
some butterflies that are
generally like this.

00:05:38.930 --> 00:05:42.006
That's their wing, and it's a
very bad drawing, but I think

00:05:42.006 --> 00:05:44.290
you get the idea, and there's
just some general patterns.

00:05:44.290 --> 00:05:45.170
We've seen it before.

00:05:45.170 --> 00:05:47.080
There's variation.

00:05:47.080 --> 00:05:50.220
And the variation does show up
from these little random

00:05:50.220 --> 00:05:51.390
changes in DNA.

00:05:51.390 --> 00:05:52.920
I think we can all believe
that, that most of these

00:05:52.920 --> 00:05:54.180
changes are kind of benign.

00:05:54.180 --> 00:05:56.150
Maybe they just set up
differently where a little

00:05:56.150 --> 00:05:59.730
pattern will show up or a little
speck of pigment will

00:05:59.730 --> 00:06:01.630
show up with a slightly
different color.

00:06:01.630 --> 00:06:03.470
And we even see amongst
these owl

00:06:03.470 --> 00:06:05.030
butterflies, there is variation.

00:06:05.030 --> 00:06:07.670
This dude's wing is different
than that guy's wing with the

00:06:07.670 --> 00:06:10.040
commonality that they do have
these eye-looking shapes.

00:06:10.040 --> 00:06:11.680
And there's not just one;
there's actually multiple.

00:06:11.680 --> 00:06:13.610
This guy has this other thing
up here that looks

00:06:13.610 --> 00:06:16.110
interesting, and they have
multiple things, but the one

00:06:16.110 --> 00:06:20.830
really noticeable feature is
this eye-looking thing.

00:06:20.830 --> 00:06:23.400
So how do we go from this
to an eye-looking thing?

00:06:23.400 --> 00:06:25.080
So the idea is you have
some variation.

00:06:25.080 --> 00:06:27.070
One guy might look like that.

00:06:27.070 --> 00:06:33.630
Another guy, or gal, might--
just randomly, their dot might

00:06:33.630 --> 00:06:35.410
be something like that.

00:06:35.410 --> 00:06:39.520
Another gal or guy-- these wings
are really badly drawn,

00:06:39.520 --> 00:06:40.730
but you get the idea.

00:06:40.730 --> 00:06:41.450
This is the butterfly.

00:06:41.450 --> 00:06:43.670
This is its antenna
right there.

00:06:43.670 --> 00:06:45.290
That's its body.

00:06:45.290 --> 00:06:52.850
Another butterfly's patterns
might look like this, right?

00:06:52.850 --> 00:06:54.640
And so, they're just random.

00:06:54.640 --> 00:06:56.760
But when they go into a certain
environment for

00:06:56.760 --> 00:06:59.250
whatever reason, maybe one of
its predators-- maybe that

00:06:59.250 --> 00:07:02.190
theory that these are supposed
to look like eyes is true.

00:07:02.190 --> 00:07:04.750
And so, actually, maybe
this guy just has a

00:07:04.750 --> 00:07:08.120
random pattern here.

00:07:08.120 --> 00:07:10.830
And so this guy-- and I'm not
saying that it's like

00:07:10.830 --> 00:07:11.980
definitely better.

00:07:11.980 --> 00:07:16.080
They're both going to be found
and killed by predators, but

00:07:16.080 --> 00:07:18.380
it's all probablistic, right?

00:07:18.380 --> 00:07:22.270
Maybe this guy has a 1% less
chance of getting a predator,

00:07:22.270 --> 00:07:24.475
because when a predator just
looks at him out of the corner

00:07:24.475 --> 00:07:28.220
of that eye, that little really
hazy region kind of

00:07:28.220 --> 00:07:30.470
looks like an eye and the
predator would be better off

00:07:30.470 --> 00:07:32.480
just not messing with it, and
they'd rather go after the

00:07:32.480 --> 00:07:33.740
dude that looks like this.

00:07:33.740 --> 00:07:35.670
So it's just a slight
probability.

00:07:35.670 --> 00:07:37.520
Now, you might, say, OK,
what's 1% going to do?

00:07:37.520 --> 00:07:40.990
But when you compound that 1%
over thousands and thousands

00:07:40.990 --> 00:07:44.930
of generations, all of a sudden,
this trait might

00:07:44.930 --> 00:07:48.590
dominate because he's just going
to be killed that less

00:07:48.590 --> 00:07:50.680
frequently, 1% less
frequently.

00:07:50.680 --> 00:07:54.220
Now, maybe this guy has a
similar trait, but his spot is

00:07:54.220 --> 00:07:55.430
closer to the abdomen.

00:07:55.430 --> 00:07:59.010
And here, it's a tradeoff,
because maybe some predators

00:07:59.010 --> 00:08:01.950
get scared away by this
concentration of pigment.

00:08:01.950 --> 00:08:05.310
And once again, I'm not saying
that we're here yet.

00:08:05.310 --> 00:08:07.920
We're not at this very advanced,
sophisticated

00:08:07.920 --> 00:08:08.460
pattern yet.

00:08:08.460 --> 00:08:11.070
We're at this random
concentration of pigment that

00:08:11.070 --> 00:08:12.000
just shows up.

00:08:12.000 --> 00:08:14.570
So we see that people who have
this concentration of pigment

00:08:14.570 --> 00:08:17.050
further away from their
abdomen, they do well.

00:08:17.050 --> 00:08:19.330
But when it's too close, maybe
some predators think that

00:08:19.330 --> 00:08:21.290
that's actually an insect and
they want to eat it, so that's

00:08:21.290 --> 00:08:24.640
actually a bad trait.

00:08:24.640 --> 00:08:27.420
So what happens is this guy
dominates, and so within this

00:08:27.420 --> 00:08:30.470
population, you start having a
lot of variation, because he

00:08:30.470 --> 00:08:33.620
starts representing--
he's more likely to

00:08:33.620 --> 00:08:34.789
pass on these traits.

00:08:34.789 --> 00:08:37.340
And I want to make that
point very clear.

00:08:37.340 --> 00:08:39.049
This isn't what happens
over the course

00:08:39.049 --> 00:08:40.440
of an animal's lifetime.

00:08:40.440 --> 00:08:43.100
It's not like if somehow I
experience something, or at

00:08:43.100 --> 00:08:45.970
least our current theory if I
experience something, that I

00:08:45.970 --> 00:08:48.920
could somehow pass on that
knowledge to my child.

00:08:48.920 --> 00:08:53.570
What it says is if my DNA just
happens to have just some

00:08:53.570 --> 00:08:57.690
variation that happens to be
more useful or more likely for

00:08:57.690 --> 00:09:00.540
me to survive to reproduction
and for my children to

00:09:00.540 --> 00:09:03.660
survive, then that will start to
dominate in the population.

00:09:03.660 --> 00:09:05.490
So then the population, you're
going to have variations

00:09:05.490 --> 00:09:06.750
within that.

00:09:06.750 --> 00:09:09.345
Maybe some guys, you know, it's
going to get a little bit

00:09:09.345 --> 00:09:10.520
to look like that.

00:09:10.520 --> 00:09:14.070
Maybe another one's going to
look a little bit like that.

00:09:14.070 --> 00:09:15.400
Maybe it has some spots there.

00:09:15.400 --> 00:09:19.190
You can kind of view it as the
variation as "exploring." But

00:09:19.190 --> 00:09:21.680
I want to be very clear not to
use any active verbs here

00:09:21.680 --> 00:09:26.630
because this is all being done
really as almost a common

00:09:26.630 --> 00:09:28.690
sense process, where
everything changes.

00:09:28.690 --> 00:09:30.890
The changes that are most suited
are the ones that are

00:09:30.890 --> 00:09:32.350
going to survive more
frequently.

00:09:32.350 --> 00:09:34.360
And then the next generation's
going to have more of that and

00:09:34.360 --> 00:09:37.550
then you'll have variation
within that change.

00:09:37.550 --> 00:09:39.500
And then this one might
be like that, and

00:09:39.500 --> 00:09:41.270
maybe this is the one.

00:09:41.270 --> 00:09:43.540
These were good compared to
that, but now when you're

00:09:43.540 --> 00:09:47.660
competing amongst themselves,
this one is able to reproduce

00:09:47.660 --> 00:09:51.410
1% more than this
guy or this guy.

00:09:51.410 --> 00:09:54.240
And so this guy becomes-- and
maybe it's some combination of

00:09:54.240 --> 00:09:55.520
all of the above, and
they mix and match.

00:09:55.520 --> 00:09:57.620
It's a hugely complex system.

00:09:57.620 --> 00:10:00.360
But then this guy represents
most of the population, when I

00:10:00.360 --> 00:10:03.790
say this guy, I'm saying this
guy's genetic information, at

00:10:03.790 --> 00:10:06.060
least as it pertains
to his wings.

00:10:06.060 --> 00:10:07.850
And then you get variation
amongst that.

00:10:07.850 --> 00:10:10.790
Maybe some of it, they have a
little small dot and there's

00:10:10.790 --> 00:10:11.830
some dots around it.

00:10:11.830 --> 00:10:14.110
Maybe it's like this.

00:10:14.110 --> 00:10:16.630
Maybe one of them digresses and
goes back here, but then

00:10:16.630 --> 00:10:19.890
he has trouble competing so
he gets knocked out again.

00:10:19.890 --> 00:10:22.060
And then some other people
have it back here.

00:10:22.060 --> 00:10:23.660
I think you get the
point that this

00:10:23.660 --> 00:10:24.920
isn't happening overnight.

00:10:27.470 --> 00:10:30.310
These changes can be fairly
incremental, but we're doing

00:10:30.310 --> 00:10:32.330
it over thousands
of generations.

00:10:32.330 --> 00:10:34.590
So when you're talking about
thousands of generations, or

00:10:34.590 --> 00:10:38.600
even millions of generations,
even a 1% advantage can be

00:10:38.600 --> 00:10:41.450
significant, and when you
accumulate those variations

00:10:41.450 --> 00:10:45.340
over a large period of time,
you can get to fairly

00:10:45.340 --> 00:10:47.550
intricate patterns like this.

00:10:47.550 --> 00:10:49.960
So I just wanted to explain
that, because this is often

00:10:49.960 --> 00:10:53.820
used as, sure, I can believe
the butterfly moth or I can

00:10:53.820 --> 00:10:57.310
even maybe believe the examples
of the antibiotics

00:10:57.310 --> 00:11:00.290
and the bacteria or the flu,
because those are kind of

00:11:00.290 --> 00:11:01.130
real-time examples.

00:11:01.130 --> 00:11:02.950
But how does something this
intricate show up?

00:11:02.950 --> 00:11:05.280
And I actually want to
make a point here.

00:11:05.280 --> 00:11:07.430
We think this is more intricate
because we can

00:11:07.430 --> 00:11:09.410
relate to it in our
everyday lives.

00:11:09.410 --> 00:11:12.500
But if you actually look at a
structure of a bacteria and

00:11:12.500 --> 00:11:15.860
how it operates or what a virus
does to infiltrate an

00:11:15.860 --> 00:11:18.830
immune system or a cell, that's
actually on a lot more

00:11:18.830 --> 00:11:21.680
levels a lot more intricate
than a design.

00:11:21.680 --> 00:11:23.770
In fact, the whole reason why
I'm using this as an example

00:11:23.770 --> 00:11:28.130
is because this is a fairly
simple example as opposed to

00:11:28.130 --> 00:11:30.300
kind of explaining the
metabolism of a certain type

00:11:30.300 --> 00:11:32.500
of bacteria and how that might
change and how it might become

00:11:32.500 --> 00:11:34.510
immune to penicillin
or whatever else.

00:11:34.510 --> 00:11:36.840
But I want to make this very
clear that these very

00:11:36.840 --> 00:11:38.210
intricate things, they don't
happen overnight.

00:11:38.210 --> 00:11:45.410
It's not like one butterfly
was completely one uniform

00:11:45.410 --> 00:11:48.080
hot-pink color and then all of
a sudden they have a child

00:11:48.080 --> 00:11:49.820
whose wings looked
just like this.

00:11:49.820 --> 00:11:50.120
No!

00:11:50.120 --> 00:11:52.500
It happens over large periods of
time, although there might

00:11:52.500 --> 00:11:54.880
be some little weird hormonal
change that does this, but I'm

00:11:54.880 --> 00:11:57.740
not going to go there,
but that is possible.

00:11:57.740 --> 00:11:59.570
But I just wanted to make this
point because I think the more

00:11:59.570 --> 00:12:02.630
examples we see, the more it'll
kind of hit home that

00:12:02.630 --> 00:12:04.900
this is a passive process.

00:12:04.900 --> 00:12:08.100
We're not talking about these
things happening overnight.

00:12:08.100 --> 00:12:12.070
And it's actually really
interesting to look at our

00:12:12.070 --> 00:12:15.070
world around us and look at
ecosystems as they are today

00:12:15.070 --> 00:12:18.040
and try to think really hard
about how something came to

00:12:18.040 --> 00:12:20.580
be, what it's useful for,
why it might have

00:12:20.580 --> 00:12:21.630
been selected for.

00:12:21.630 --> 00:12:27.430
For example, are traits that
occur after reproduction

00:12:27.430 --> 00:12:28.070
selected for?

00:12:28.070 --> 00:12:30.860
Well, probably not unless they
affect the reproduction of the

00:12:30.860 --> 00:12:31.600
next cycle.

00:12:31.600 --> 00:12:34.220
For example, you might say,
oh, well, the trait to be

00:12:34.220 --> 00:12:37.590
nurturing after your
reproductive years, that's

00:12:37.590 --> 00:12:38.620
after reproductive years.

00:12:38.620 --> 00:12:43.460
No, but it helps your
offspring reproduce.

00:12:43.460 --> 00:12:47.030
But we already see a lot of
diseases, especially once we

00:12:47.030 --> 00:12:50.800
get beyond our reproductive and
our child-rearing years.

00:12:50.800 --> 00:12:53.280
So once we get into our fifties
and sixties, the

00:12:53.280 --> 00:12:57.120
incidences of diseases increases
exponentially from

00:12:57.120 --> 00:12:58.940
when we're younger and because
they're no longer being

00:12:58.940 --> 00:13:03.020
selected for, because it no
longer affects our ability to

00:13:03.020 --> 00:13:04.890
reproduce, because we've
already reproduced.

00:13:04.890 --> 00:13:06.220
We've already raised
our children so

00:13:06.220 --> 00:13:07.330
that they could reproduce.

00:13:07.330 --> 00:13:10.140
So the only thing that happens
at that point is now not being

00:13:10.140 --> 00:13:11.000
selected for.

00:13:11.000 --> 00:13:12.790
So anyway, hopefully, this video
will give you a little

00:13:12.790 --> 00:13:15.160
bit more nuance on evolution,
and I want to do a couple of

00:13:15.160 --> 00:13:17.670
videos like this, because I
really want to make it clear

00:13:17.670 --> 00:13:20.510
that it's not making some wild
claim that all of a sudden

00:13:20.510 --> 00:13:23.660
this appears spontaneously, that
it really is a thing that

00:13:23.660 --> 00:13:27.750
happens over millennia and
eons and very gradually.


Introduction to Evolution and Natural Selection

WEBVTT
Kind: captions
Language: en

00:00:00.680 --> 00:00:04.380
I think what is probably the
most misunderstood concept in

00:00:04.380 --> 00:00:07.930
all of science, and as we all
know is now turning into one

00:00:07.930 --> 00:00:10.160
of the most contentious
concepts, maybe not in

00:00:10.160 --> 00:00:13.980
science, but in our popular
culture, and that's the idea

00:00:13.980 --> 00:00:15.230
of evolution.

00:00:19.150 --> 00:00:21.400
Whenever we hear this word, I
mean, even if we don't hear it

00:00:21.400 --> 00:00:24.910
in the biological context, we
imagine that something is

00:00:24.910 --> 00:00:26.850
changing, it is evolving.

00:00:26.850 --> 00:00:30.880
And so when people use the word
evolution in our everyday

00:00:30.880 --> 00:00:35.190
context, they think of this
notion of change, that-- this

00:00:35.190 --> 00:00:38.410
is going to test my drawing
ability-- but you

00:00:38.410 --> 00:00:42.000
see an ape bent over.

00:00:42.000 --> 00:00:45.590
We've all seen this picture at
the natural museum, and he's

00:00:45.590 --> 00:00:49.230
walking hunchback like that, and
his head's bent down and--

00:00:49.230 --> 00:00:51.490
oh, I'm doing my best.
That's the ape.

00:00:51.490 --> 00:00:53.750
Maybe he's also wearing a hat.

00:00:53.750 --> 00:00:56.280
And then they show this picture
where he slowly,

00:00:56.280 --> 00:00:59.760
slowly becomes more and more
upright, and eventually, he

00:00:59.760 --> 00:01:03.000
turns into some dude, who's
just walking on his way to

00:01:03.000 --> 00:01:07.330
work, also just as happy,
and now he's

00:01:07.330 --> 00:01:08.940
walking completely upright.

00:01:08.940 --> 00:01:11.170
And it's some kind of
implication that walking

00:01:11.170 --> 00:01:13.810
upright is better than
not walking upright,

00:01:13.810 --> 00:01:14.710
et cetera, et cetera.

00:01:14.710 --> 00:01:16.570
Oh, he doesn't have
a tail anymore.

00:01:16.570 --> 00:01:19.170
Let me eliminate that.

00:01:19.170 --> 00:01:21.640
This guy does have a tail.

00:01:21.640 --> 00:01:25.980
Let me do it in an appropriate
width.

00:01:25.980 --> 00:01:27.920
This guy has a tail, so you're
going to have to excuse my

00:01:27.920 --> 00:01:29.670
drawings skills, but we've
all seen this.

00:01:29.670 --> 00:01:32.370
If you've ever gone to a natural
history museum, and

00:01:32.370 --> 00:01:35.770
they'll just make more and
more upright apes, and

00:01:35.770 --> 00:01:37.750
eventually you get to a human
being, and it's this idea that

00:01:37.750 --> 00:01:41.550
the apes somehow changed
into a human being.

00:01:41.550 --> 00:01:45.850
And I've seen this in multiple
contexts, even inside of

00:01:45.850 --> 00:01:48.060
biology classes and even the
scientific community.

00:01:48.060 --> 00:01:50.630
They'll say, oh, the ape evolved
into the human or the

00:01:50.630 --> 00:01:55.270
ape evolved into the pre-human,
the guy that almost

00:01:55.270 --> 00:01:59.020
stood upright, the guy that was
a little bit hunchback, so

00:01:59.020 --> 00:02:00.760
he looked a little bit like an
ape and a little bit like a

00:02:00.760 --> 00:02:02.970
human and so on and so forth.

00:02:02.970 --> 00:02:04.650
And I want to be very
clear here.

00:02:04.650 --> 00:02:08.800
Even though this process did
happen, that you did have

00:02:08.800 --> 00:02:13.640
creatures that over time
accumulated changes that maybe

00:02:13.640 --> 00:02:15.760
their ancestors might have
looked more like this, and

00:02:15.760 --> 00:02:21.070
eventually they looked more like
this, there was no active

00:02:21.070 --> 00:02:23.500
process going on called
evolution.

00:02:23.500 --> 00:02:26.960
It's not like the ape said, gee,
I would like my kids to

00:02:26.960 --> 00:02:32.050
look more like this dude, so
somehow, I'm going to get my

00:02:32.050 --> 00:02:36.740
DNA to get enough changes
to look more like this.

00:02:36.740 --> 00:02:38.250
And it's not like
the DNA knew.

00:02:38.250 --> 00:02:41.730
The DNA didn't say, hey, it is
better to be walking than to

00:02:41.730 --> 00:02:44.540
be kind of hunchbacked
like an ape.

00:02:44.540 --> 00:02:48.740
And so therefore, I'm going to
try to somehow spontaneously

00:02:48.740 --> 00:02:50.440
change into this dude.

00:02:50.440 --> 00:02:51.890
That's not what evolution is.

00:02:51.890 --> 00:02:55.810
It's not like-- you know, some
people imagine that maybe

00:02:55.810 --> 00:02:58.400
there was a tree.

00:02:58.400 --> 00:03:01.420
There's a tree, and on that
tree, there's a bunch of good

00:03:01.420 --> 00:03:02.670
fruit at the top of the tree.

00:03:07.980 --> 00:03:09.500
Maybe they're apples.

00:03:09.500 --> 00:03:14.410
And then maybe you have some
type of cow-like creature, or

00:03:14.410 --> 00:03:16.140
maybe it's some type of
horse-like creature that says,

00:03:16.140 --> 00:03:19.250
gee, I would like to get to
those apples, and that just

00:03:19.250 --> 00:03:21.740
because they want to get
there, maybe the next

00:03:21.740 --> 00:03:25.360
generation-- they keep trying to
raise their neck, and then

00:03:25.360 --> 00:03:27.890
after generation after
generation, their necks get

00:03:27.890 --> 00:03:29.870
longer and longer,
and eventually

00:03:29.870 --> 00:03:31.280
they turn into giraffes.

00:03:31.280 --> 00:03:33.680
That is not what evolution
is and that's not what it

00:03:33.680 --> 00:03:36.950
implies, although sometimes
the everyday notion of the

00:03:36.950 --> 00:03:39.960
word seems to make us
think that way.

00:03:39.960 --> 00:03:42.290
What evolution is-- and
actually, this is the word

00:03:42.290 --> 00:03:47.200
that I prefer to use-- it's
natural selection.

00:03:47.200 --> 00:03:50.540
Let me write that word down.

00:03:50.540 --> 00:03:55.240
Natural selection.

00:03:55.240 --> 00:03:59.670
And literally, what it means is
that in any population of

00:03:59.670 --> 00:04:02.560
living organisms, you're going
to have some variation, and

00:04:02.560 --> 00:04:05.310
this is an important
keyword here.

00:04:05.310 --> 00:04:08.850
Variation just means, look,
there's just some change.

00:04:08.850 --> 00:04:12.380
If you look at the kids in your

00:04:12.380 --> 00:04:13.480
school, you'll see variation.

00:04:13.480 --> 00:04:15.410
Some people are tall, some
people are short, some people

00:04:15.410 --> 00:04:17.550
have blond hair, some people
have black hair,

00:04:17.550 --> 00:04:18.720
so on and so forth.

00:04:18.720 --> 00:04:20.829
There's always variation.

00:04:20.829 --> 00:04:24.700
And what natural selection is is
this process that sometimes

00:04:24.700 --> 00:04:29.750
environmental factors will
select for certain variation.

00:04:29.750 --> 00:04:31.830
Some variations might not
matter at all, but some

00:04:31.830 --> 00:04:33.290
variations matter a lot.

00:04:33.290 --> 00:04:36.150
One example that's given in
every biology book, but it

00:04:36.150 --> 00:04:38.500
really is interesting is-- I
believe they're called the

00:04:38.500 --> 00:04:39.310
peppered moth.

00:04:39.310 --> 00:04:45.480
And this was in pre-Industrial
Revolution England that these

00:04:45.480 --> 00:04:49.590
moths-- some of the moths were--
let me see if I can

00:04:49.590 --> 00:04:50.400
draw a moth.

00:04:50.400 --> 00:04:53.200
I think you get the idea.

00:04:53.200 --> 00:04:55.160
Let me draw a couple of them.

00:04:55.160 --> 00:04:56.770
Let me draw a few
peppered moths.

00:05:00.700 --> 00:05:02.550
A couple of peppered
moths there.

00:05:02.550 --> 00:05:05.040
Let me draw one more.

00:05:05.040 --> 00:05:07.700
So most peppered moths, there
was just this variation.

00:05:07.700 --> 00:05:10.820
Some of them were-- I guess we
could call them more peppered

00:05:10.820 --> 00:05:11.430
than others.

00:05:11.430 --> 00:05:14.120
So some of them might
look like this.

00:05:14.120 --> 00:05:17.310
You know, they had-- let
me do other colors.

00:05:17.310 --> 00:05:19.300
Let me do a white.

00:05:19.300 --> 00:05:21.770
So it had spots like that.

00:05:21.770 --> 00:05:25.852
Some of them might have
looked more like that.

00:05:25.852 --> 00:05:29.730
And, of course, they had some
black spots on them.

00:05:29.730 --> 00:05:32.680
And then some of them might
have been-- just

00:05:32.680 --> 00:05:33.790
barely have any spots.

00:05:33.790 --> 00:05:35.330
You just have this natural
variation.

00:05:35.330 --> 00:05:37.190
Like you'd see in any population
of animals, you'll

00:05:37.190 --> 00:05:38.920
see some variation in colors.

00:05:38.920 --> 00:05:41.450
Now, they were all happy,
probably for thousands of

00:05:41.450 --> 00:05:44.150
years, just this natural
variation.

00:05:44.150 --> 00:05:48.190
It was a non-important trait
for these peppered moths.

00:05:48.190 --> 00:05:51.000
But then, all of a sudden, the
Industrial Revolution happens

00:05:51.000 --> 00:05:54.270
in England, and all this soot
gets released from all of

00:05:54.270 --> 00:05:59.080
these factories that are running
these steam engines

00:05:59.080 --> 00:06:00.370
powered by coal.

00:06:00.370 --> 00:06:03.260
And so, all of a sudden, a lot
of the things that once were

00:06:03.260 --> 00:06:06.680
grey or white, for example,
maybe some tree trunks.

00:06:06.680 --> 00:06:08.670
Let me draw some tree trunks.

00:06:08.670 --> 00:06:10.370
Maybe there were some tree
trunks that used

00:06:10.370 --> 00:06:12.440
to look like this.

00:06:12.440 --> 00:06:16.940
You know, maybe it looked like
a-- maybe it kept a-- maybe

00:06:16.940 --> 00:06:20.190
some tree trunks used to look
something like this, and a

00:06:20.190 --> 00:06:22.400
peppered moth would
be pretty OK.

00:06:22.400 --> 00:06:24.230
Maybe there are some tree trunks
that were pretty dark.

00:06:24.230 --> 00:06:26.610
But all of a sudden, the
Industrial Revolution happens.

00:06:26.610 --> 00:06:29.010
Everything gets covered with
soot from the coal being

00:06:29.010 --> 00:06:30.870
burned, and then all of
a sudden, all the

00:06:30.870 --> 00:06:31.900
trees look like this.

00:06:31.900 --> 00:06:34.320
They're just completely pitch
black or they're a lot darker

00:06:34.320 --> 00:06:35.980
than they were before.

00:06:35.980 --> 00:06:40.100
Now, all of a sudden, you've
had a major change to these

00:06:40.100 --> 00:06:42.810
moths' environment, and you have
to think what is going to

00:06:42.810 --> 00:06:44.910
select for these moths?

00:06:44.910 --> 00:06:48.730
Well, one thing that might get
these moths are birds and the

00:06:48.730 --> 00:06:51.380
ability of the birds
to see the moths.

00:06:51.380 --> 00:06:54.300
So all of a sudden, if the
environment became a lot

00:06:54.300 --> 00:06:57.310
blacker than it was before,
you can guess

00:06:57.310 --> 00:06:58.550
what's going to happen.

00:06:58.550 --> 00:07:03.280
The birds are going to see this
dude a lot easier than

00:07:03.280 --> 00:07:04.990
they're going to see this dude,
because this dude on a

00:07:04.990 --> 00:07:06.980
black background, he's going
to be a lot harder to see.

00:07:06.980 --> 00:07:09.150
And it's not like the birds
won't catch this guy.

00:07:09.150 --> 00:07:11.670
They'll catch all of them, but
they're going to catch this

00:07:11.670 --> 00:07:14.080
guy a lot more frequently.

00:07:14.080 --> 00:07:15.340
So you can imagine
what happens.

00:07:15.340 --> 00:07:19.020
If the birds start catching
these guys before they can

00:07:19.020 --> 00:07:21.300
reproduce, or maybe while
they're reproducing, what's

00:07:21.300 --> 00:07:22.590
going to happen?

00:07:22.590 --> 00:07:25.820
This guy, the darker dudes, are
going to reproduce a lot

00:07:25.820 --> 00:07:27.430
more often, and all of a sudden,
you're going to have a

00:07:27.430 --> 00:07:32.100
lot more moths that
look like this.

00:07:32.100 --> 00:07:36.560
You're going to have a lot
more of these dudes.

00:07:36.560 --> 00:07:37.430
So what happened here?

00:07:37.430 --> 00:07:42.540
Was there any design or was
there any active change by any

00:07:42.540 --> 00:07:43.250
of the moths?

00:07:43.250 --> 00:07:46.230
Did any of the moths-- I mean,
it looks like a really smart

00:07:46.230 --> 00:07:47.840
thing to do to become
black, right?

00:07:47.840 --> 00:07:50.320
Your surroundings became black,
and you wait a couple

00:07:50.320 --> 00:07:52.120
of generations of these moths,
and now all of a sudden, the

00:07:52.120 --> 00:07:52.860
moths are black.

00:07:52.860 --> 00:07:55.200
And you might say, wow, those
moths are geniuses.

00:07:55.200 --> 00:07:59.820
They all somehow decided to
evolve into black moths in

00:07:59.820 --> 00:08:02.100
order to hide from the
birds more easily.

00:08:02.100 --> 00:08:03.890
But that's not what happened.

00:08:03.890 --> 00:08:08.260
You had a lot of variation in
your peppered moth population.

00:08:08.260 --> 00:08:10.850
And what happened was that when
everything turned darker

00:08:10.850 --> 00:08:15.160
and darker, these dudes right
here-- and dudettes-- had a

00:08:15.160 --> 00:08:18.450
lot less success
in reproducing.

00:08:18.450 --> 00:08:21.160
These guys just reproduced more
and more and more, and

00:08:21.160 --> 00:08:24.170
these guys got eaten up before
they were able to reproduce or

00:08:24.170 --> 00:08:25.940
maybe while they were
reproducing so that they

00:08:25.940 --> 00:08:29.470
couldn't produce as many
offspring, and then this trait

00:08:29.470 --> 00:08:30.750
just became dominant.

00:08:30.750 --> 00:08:32.990
And then the peppered moth just
became-- you can kind of

00:08:32.990 --> 00:08:35.059
view it as a black moth.

00:08:35.059 --> 00:08:36.110
Now, you might say, OK, Sal.

00:08:36.110 --> 00:08:37.730
That's one example.

00:08:37.730 --> 00:08:38.500
I need more.

00:08:38.500 --> 00:08:40.340
This is natural selection.

00:08:40.340 --> 00:08:42.510
It's purported to apply
to everything.

00:08:42.510 --> 00:08:51.520
It purports to explain why we
evolved from basic bacteria or

00:08:51.520 --> 00:08:54.370
maybe even self-replicating RNA,
which I will talk about

00:08:54.370 --> 00:08:55.660
more in the future.

00:08:55.660 --> 00:08:56.930
I need more evidence of this.

00:08:56.930 --> 00:08:58.670
I need to see it in real time.

00:08:58.670 --> 00:09:01.990
And the best example of this
is really the flu.

00:09:04.950 --> 00:09:08.140
And I'll do other videos in the
future on what viruses are

00:09:08.140 --> 00:09:09.170
and how they replicate.

00:09:09.170 --> 00:09:10.900
Viruses are actually
fascinating, because it's not

00:09:10.900 --> 00:09:12.510
even clear that they're alive.

00:09:12.510 --> 00:09:17.530
They're literally just little
buckets of DNA and sometimes

00:09:17.530 --> 00:09:20.950
RNA, which we'll learn is
genetic information, and

00:09:20.950 --> 00:09:24.200
they're just contained in
these little protein

00:09:24.200 --> 00:09:27.990
containers that are these neat
geometrical shapes, and that's

00:09:27.990 --> 00:09:30.020
all they are.

00:09:30.020 --> 00:09:36.000
They're not like regular living
organisms that actively

00:09:36.000 --> 00:09:39.090
move and that actively have
metabolisms and all that.

00:09:39.090 --> 00:09:41.295
What they do is they take that
little DNA, and they inject it

00:09:41.295 --> 00:09:43.980
into other things that can
process it, and then they use

00:09:43.980 --> 00:09:46.050
that DNA to produce
more viruses.

00:09:46.050 --> 00:09:49.880
But anyway, we can do a whole
series of videos on viruses,

00:09:49.880 --> 00:09:51.960
but the flu is a virus.

00:09:51.960 --> 00:09:55.910
And what happens every year is
you have a certain type a

00:09:55.910 --> 00:10:01.580
virus, and they have
some variation.

00:10:01.580 --> 00:10:07.680
I'll just make the variation
by how many dots they have.

00:10:07.680 --> 00:10:09.530
And they infect-- let's
say it's a human flu.

00:10:09.530 --> 00:10:13.400
They infect humans, and slowly
our immune systems, which we

00:10:13.400 --> 00:10:16.730
can make a whole set of videos
on as well, start to recognize

00:10:16.730 --> 00:10:20.050
the virus and are able to attack
them before they can do

00:10:20.050 --> 00:10:21.110
a lot of damage.

00:10:21.110 --> 00:10:23.160
So now you can imagine what
happens if, let's say, that

00:10:23.160 --> 00:10:24.650
this is the current flu.

00:10:24.650 --> 00:10:25.390
Let me do all of them.

00:10:25.390 --> 00:10:28.080
They all have these little two
dots and that's how-- and

00:10:28.080 --> 00:10:30.720
we'll talk in the future what
these dots are and how they

00:10:30.720 --> 00:10:31.460
can be recognized.

00:10:31.460 --> 00:10:33.940
But let's say that's how our
immune system recognizes them.

00:10:33.940 --> 00:10:35.960
They start realizing, oh, any
time I get this little green

00:10:35.960 --> 00:10:39.230
dude with two dots on it's,
that's not a good thing to

00:10:39.230 --> 00:10:41.190
have around so I'm going to
attack it in some way and

00:10:41.190 --> 00:10:46.120
destroy it before he infects my
DNA and all the rest. And

00:10:46.120 --> 00:10:50.210
so you have a very strong
natural selection once immune

00:10:50.210 --> 00:10:53.690
systems learn what this virus
is-- and we'll talk more about

00:10:53.690 --> 00:10:56.770
what learning means for an
immune system-- that they'll

00:10:56.770 --> 00:11:00.670
start attacking these
guys, right?

00:11:00.670 --> 00:11:04.060
But flu, you can kind of think
of them as being tricky, but

00:11:04.060 --> 00:11:05.010
they're not really tricky.

00:11:05.010 --> 00:11:07.980
They're not sentient objects,
but what they do do is they

00:11:07.980 --> 00:11:09.440
constantly change.

00:11:09.440 --> 00:11:12.630
So what you have is, in any flu
population, you're always

00:11:12.630 --> 00:11:14.040
having a little bit of change.

00:11:14.040 --> 00:11:16.870
So maybe the great majority of
them have those two dots, but

00:11:16.870 --> 00:11:19.470
maybe every now and then, one
of them has one dot, one of

00:11:19.470 --> 00:11:23.780
them has three dots, and maybe
that's just a random mutation.

00:11:23.780 --> 00:11:26.400
This just randomly happened.

00:11:26.400 --> 00:11:29.880
Maybe this is one in every--
I'll make up a number: One in

00:11:29.880 --> 00:11:34.020
every million of these viruses
have this only one dot instead

00:11:34.020 --> 00:11:35.000
of two dots.

00:11:35.000 --> 00:11:38.220
But what's going to happen as
soon as the human immune

00:11:38.220 --> 00:11:40.910
system gets used to attacking
the virus

00:11:40.910 --> 00:11:42.790
with the two red dots?

00:11:42.790 --> 00:11:46.080
Well, then this guy isn't going
to have to compete with

00:11:46.080 --> 00:11:48.580
the other virus capsules
for infecting people.

00:11:48.580 --> 00:11:51.510
He's going to have people's
DNA all to himself.

00:11:51.510 --> 00:11:54.360
And so he or she, or whatever
you want to call this virus,

00:11:54.360 --> 00:11:56.770
is then going to be
more successful.

00:11:56.770 --> 00:11:59.970
So by next year's flu season
when people start sneezing and

00:11:59.970 --> 00:12:02.250
are able to spread it on
doorknobs and whatever else

00:12:02.250 --> 00:12:06.150
again, this guy's going to
be the new flu virus.

00:12:06.150 --> 00:12:09.520
So when you see this process
of every year there's a new

00:12:09.520 --> 00:12:13.000
flu virus, that is evolution
and natural

00:12:13.000 --> 00:12:14.260
selection in real time.

00:12:14.260 --> 00:12:15.040
It is happening.

00:12:15.040 --> 00:12:18.980
It isn't this thing that only
happens over eons and eons of

00:12:18.980 --> 00:12:22.420
time, although most of the kind
of the substantial things

00:12:22.420 --> 00:12:25.410
that we see in our lives or even
ourselves are based on

00:12:25.410 --> 00:12:28.640
these things that happened over
eons and eons of time,

00:12:28.640 --> 00:12:30.550
but it happens on
a yearly basis.

00:12:30.550 --> 00:12:32.040
Another example is if
you think about

00:12:32.040 --> 00:12:33.510
antibiotics and bacteria.

00:12:33.510 --> 00:12:36.040
Bacteria are these little cells
that move around, and

00:12:36.040 --> 00:12:37.490
we'll talk more about them.

00:12:37.490 --> 00:12:40.390
They actually are definitely
living.

00:12:40.390 --> 00:12:44.910
They have metabolisms
and whatever else.

00:12:44.910 --> 00:12:46.200
And this is just a nice note.

00:12:46.200 --> 00:12:49.840
When people talk about
infections, it could either be

00:12:49.840 --> 00:12:52.430
a viral infection, which are
these things that go and

00:12:52.430 --> 00:12:55.210
infect your DNA and then use
your cell mechanisms to

00:12:55.210 --> 00:12:57.870
reproduce, or it could be a
bacterial infection, which are

00:12:57.870 --> 00:13:00.850
literally little cells that move
around and they release

00:13:00.850 --> 00:13:03.290
toxins that make you sick
and whatever else.

00:13:03.290 --> 00:13:06.000
So bacteria, these are what
antibiotics kill.

00:13:10.730 --> 00:13:11.980
Actually, I don't think
there's a hyphen.

00:13:15.550 --> 00:13:18.050
They attack bacteria.

00:13:18.050 --> 00:13:19.380
They kill them.

00:13:19.380 --> 00:13:21.750
If you know a couple of doctors
or whatever and you

00:13:21.750 --> 00:13:22.590
say, hey, I'm sick.

00:13:22.590 --> 00:13:24.330
I think I have a bacterial
infection.

00:13:24.330 --> 00:13:26.090
Give me some antibiotics.

00:13:26.090 --> 00:13:29.840
A responsible doctor says no,
I won't give you antibiotics

00:13:29.840 --> 00:13:32.310
just willy-nilly, because what
happens is, the more

00:13:32.310 --> 00:13:36.070
antibiotics you use, you're
more likely to create

00:13:36.070 --> 00:13:39.190
versions-- and I want to be very
careful about the word

00:13:39.190 --> 00:13:41.370
create, because you're not
actively creating them.

00:13:41.370 --> 00:13:44.080
But let's say-- and let
me finish my sentence.

00:13:44.080 --> 00:13:49.880
You're very likely to
help select for

00:13:49.880 --> 00:13:52.290
antibiotic-resistant
bacterias.

00:13:52.290 --> 00:13:53.540
Now, how does that work?

00:13:57.390 --> 00:13:59.110
Let's say that these are all
bacteria and you have

00:13:59.110 --> 00:14:00.360
gazillions of them, right?

00:14:00.360 --> 00:14:01.900
Every now and then,
you get one that's

00:14:01.900 --> 00:14:05.510
slightly different, right?

00:14:05.510 --> 00:14:11.290
Now in a population of bacteria,
these all will make

00:14:11.290 --> 00:14:14.820
you equally sick, and this is
just some random difference in

00:14:14.820 --> 00:14:15.440
the bacteria.

00:14:15.440 --> 00:14:18.510
Maybe on its DNA some slight
different changes happened,

00:14:18.510 --> 00:14:20.870
but whatever happened, these
all are a kind of bacteria.

00:14:20.870 --> 00:14:22.700
You don't want to get a lot
of them in your system.

00:14:22.700 --> 00:14:24.720
Your immune system can attack
them and fight them off, but

00:14:24.720 --> 00:14:26.590
if you get a lot of them, then
they might kill you or make

00:14:26.590 --> 00:14:28.140
you sick or whatever else.

00:14:28.140 --> 00:14:31.780
Now, if everyone just starts
using antibiotics when they're

00:14:31.780 --> 00:14:35.460
not sick or when they don't
really need to in a

00:14:35.460 --> 00:14:38.070
life-or-death situation, you
might have an antibiotic that

00:14:38.070 --> 00:14:40.260
is really good at killing
the green bacteria.

00:14:40.260 --> 00:14:43.390
But what happens if you
all of a sudden kill a

00:14:43.390 --> 00:14:45.110
lot the green bacteria?

00:14:45.110 --> 00:14:50.240
Well, now the blue bacteria have
the whole ecosystem that

00:14:50.240 --> 00:14:54.850
before it was competing with all
these green dudes to get

00:14:54.850 --> 00:14:57.880
at all the good stuff inside of
your body, but now he's all

00:14:57.880 --> 00:15:01.830
alone, and now he can replicate
willy-nilly.

00:15:01.830 --> 00:15:06.790
So now he's going to replicate
willy-nilly, and obviously--

00:15:06.790 --> 00:15:10.300
once again, it wasn't like there
was any design, there

00:15:10.300 --> 00:15:13.400
was any intelligent process
here that said look, this

00:15:13.400 --> 00:15:17.435
bacteria should-- some bacteria
said, oh, I'm going

00:15:17.435 --> 00:15:22.040
to be little bit smarter and
design myself to resist this

00:15:22.040 --> 00:15:23.140
antibiotic threat.

00:15:23.140 --> 00:15:23.790
No!

00:15:23.790 --> 00:15:26.160
There's just these random
changes that happen, and

00:15:26.160 --> 00:15:30.410
mutations and viruses and
bacteria happen frequently and

00:15:30.410 --> 00:15:32.360
these random changes that
happen, and this might be a

00:15:32.360 --> 00:15:36.300
one in one billion
change, right?

00:15:36.300 --> 00:15:38.810
But all of a sudden, if you
start killing off all of the

00:15:38.810 --> 00:15:41.570
people it's competing with, this
guy can start replicating

00:15:41.570 --> 00:15:44.800
really fast and then become
the dominant bacteria.

00:15:44.800 --> 00:15:49.280
And then all of a sudden, that
antibiotic that you had

00:15:49.280 --> 00:15:52.470
developed very carefully to
destroy the green dudes is

00:15:52.470 --> 00:15:55.070
useless, and you have
this superbug.

00:15:55.070 --> 00:15:56.860
You might have heard
the word superbug.

00:15:56.860 --> 00:15:58.380
That's what a superbug is.

00:15:58.380 --> 00:16:00.350
It's not like it designed
itself somehow.

00:16:00.350 --> 00:16:02.140
It's just that we got very
good at killing its

00:16:02.140 --> 00:16:05.340
competition, and so we allowed
it to take over, and we can't

00:16:05.340 --> 00:16:07.920
kill it, because all of the
drugs were just good at

00:16:07.920 --> 00:16:09.050
killing its competition.

00:16:09.050 --> 00:16:12.150
These bacteria just keep
mutating and keep mutating,

00:16:12.150 --> 00:16:14.720
and if we use these antibiotics
a little bit too

00:16:14.720 --> 00:16:18.150
heavily, we'll always be
selecting for the things that

00:16:18.150 --> 00:16:20.130
won't be affected by
the antibiotics.

00:16:20.130 --> 00:16:22.330
Well, anyway, I think I've
spoken long enough, but this

00:16:22.330 --> 00:16:23.890
is a fascinating, fascinating
topic.

00:16:23.890 --> 00:16:30.190
And I really wanted to make this
my very first video or

00:16:30.190 --> 00:16:33.820
lecture if you will, on biology,
because if you really

00:16:33.820 --> 00:16:36.410
went to-- you know, biology is
the study of life, and we can

00:16:36.410 --> 00:16:37.970
talk about what life
is, whether

00:16:37.970 --> 00:16:40.490
viruses are living, whatnot.

00:16:40.490 --> 00:16:42.850
But if you really want to study
living systems, you

00:16:42.850 --> 00:16:44.880
really can't make any
assumptions other

00:16:44.880 --> 00:16:45.970
than natural selection.

00:16:45.970 --> 00:16:49.310
We could go to another planet
where the creatures don't have

00:16:49.310 --> 00:16:53.040
DNA, or maybe they have some
other type of hereditary

00:16:53.040 --> 00:16:56.700
information stored in their
cells, or they replicate some

00:16:56.700 --> 00:16:58.480
other way, or they're not
even carbon based.

00:16:58.480 --> 00:16:59.960
Maybe they're silicon based.

00:16:59.960 --> 00:17:02.450
And if we went to that type of
a planet in order study the

00:17:02.450 --> 00:17:06.210
biology on that planet,
everything else we know about

00:17:06.210 --> 00:17:09.970
biology, about viruses and
DNA, would be useless.

00:17:09.970 --> 00:17:13.410
But if we do understand this one
concept, this one concept

00:17:13.410 --> 00:17:17.940
of natural selection, that your
environment will select,

00:17:17.940 --> 00:17:19.089
and it's not-- you
know, there's no

00:17:19.089 --> 00:17:20.260
active process here.

00:17:20.260 --> 00:17:22.670
It's just random stuff happened
and they randomly

00:17:22.670 --> 00:17:23.920
select for random changes.

00:17:23.920 --> 00:17:27.410
And over large swaths of time,
and these are unimaginably

00:17:27.410 --> 00:17:31.570
large swaths of time, those
changes essentially

00:17:31.570 --> 00:17:33.820
accumulate, and they might
accumulate into fairly, fairly

00:17:33.820 --> 00:17:34.660
significant things.

00:17:34.660 --> 00:17:36.520
We'll talk more about this
in another video.

00:17:36.520 --> 00:17:38.190
See you soon.