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We're all human, and, yet,
we all look different.

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Now, a lot about the way
we look is down to our DNA,

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00:00:08,620 --> 00:00:12,700
as we can see so brilliantly
with these identical twins.

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From eye colour to hair colour,
to dimples, to height,

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each pair of twins
looks very similar.

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00:00:20,100 --> 00:00:24,140
But look a little more closely
and you'll see

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that each person here is unique.

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In this lecture, we'll explore
how much of the differences

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between us are down to genes,
and how much is due

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to everything else.

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We'll be looking at
what makes you unique.

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I'm Professor Alice Roberts.

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Welcome to the third
of this year's Royal Institution

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Christmas lectures.

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And this lecture is all about
us as a species.

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It's all about human diversity.

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But, first, let's start off
with a different species,

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which is very diverse indeed.

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If you stand here.

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So, we've got an amazing range
of different dogs here,

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and the astonishing thing about this
is that they are all dogs.

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They all belong to the same species,
and, yet, they look so incredibly

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different from each other.

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We've got...we've got a great Dane,
we've got a little shih tzu,

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and a tiny, little
miniature dachshund.

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Now, isn't it amazing that there's
all that variation in one species?

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Humans first started domesticating
dogs about 30,000 years ago,

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when our ancestors
were hunter-gatherers,

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and, then, over thousands of years,
we've somehow moulded

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all of these changes.

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So, we've bred dogs that are really
good at going down burrows

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and chasing animals,
like the dachshund,

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and this is all down to us
interacting with this other species.

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Now, to explore this diversity
and how it comes about in more

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detail, I need to introduce one
more species, and my friend,

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geneticist Professor
Aoife McLysaght.

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APPLAUSE

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I wasn't entirely clear
if you were referring to me

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as the additional species, or this
beautiful chihuahua in my arms.

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But this chihuahua, of course,
was bred as a companion dog,

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and you can see he's very,
very cute, and dogs are especially

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interesting in terms of genetics,
because this huge diversity

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that we can see in front of us
is actually down to

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quite a small amount
of genetic diversity.

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They are, after all, just one
species, and that makes it much

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easier to be able to figure out
how the genes contribute

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to the changes that we can
actually see on the outside.

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So, for example, this little
chihuahua, and other miniature dogs

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like this, the size variation
is largely down to

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just changes in just one gene.

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Now, we're actually able
to understand the genetic basis

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of some of this. Yeah, so, many of
the origins of these traits have

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been traced genetically, so we can
get a real handle on how variation

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in our genes contributes to the kind
of variance that we can see.

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So, let's have a think about how
all of this variation comes about.

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But, for now, let's say
thank you very much to our

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brilliant dog line-up.

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APPLAUSE

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So, all those differences have been
bred into different breeds of dogs

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by breeders choosing dogs
with particular traits

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and then breeding them
on to the next generation.

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That's something called
selective breeding.

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It's what Charles Darwin called
"artificial selection".

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And he imagined how he could
continue thinking about this to see,

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well, does this happen
in nature as well?

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How do we get natural selection?

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And, to really explain this,
we're going to play a game

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with this demo,
and we need two volunteers.

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OK, let's see.

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Yes, you there in the blue jumper.
Lovely Christmas jumper.

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Come on down. And I'll also pick
one there as well. Great.
APPLAUSE

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Freddie, lovely to meet you,
Freddie. What's your name?

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Rebecca. Rebecca.

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So, what you see beside you here
are two habitats,

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and you can see very quickly that
this is a mainly orange habitat.

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The floor is orange, and it's filled
with these balloons,

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which are mostly what we're calling
orange pebbles.

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And, over there, we've got a grey
habitat with grey floor

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and grey pebbles.

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But, in amongst the pebbles,
there is something else.

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So, here we have a mouse,

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and there's orange and grey mice
in each of these habitats,

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and, so, we're going to
put these in there,

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and, Freddie, and... Freddie, what
we didn't tell you

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is that your job is to actually
be a predator.

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You need to catch some mice, and you
need to catch some mice as well.

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So, you're going to have to go
in there, and I want you to catch

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mice but not pebbles,
so if you can go around the back.

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Just the ones with faces.

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Yeah, so, only the ones with faces
we're interested in.

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Go round the back, we'll let you in.

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Yeah, so don't start catching mice
yet, because that's far too easy,

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actually. Yeah, let's make it more
energetic.

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Yeah, we need to make something
a bit more difficult for you.

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LAUGHTER

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So, on our marks.
Well, we'll count down.

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ALL: Three, two, one. Go!

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JAUNTY MUSIC PLAYS

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BOTH: Three, two, one. Stop!

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APPLAUSE

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OK, you can come out.

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OK, you can come back out.

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How was that?
OK, let's have a look.

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Well, that's a mouse.

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These are pebbles,
so we'll put those back.

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What have you got in your box?

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We've managed to catch four orange
mice, and just one grey mouse.

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Freddie managed to catch
one of each.

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So, what did you think, Freddie?
What did you think of trying

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to catch the mice in there?
What was it like? Hard.

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Was it hard?
Was either colour easier?

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Not really, no?

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What about you over there?

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Orange was easy.

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It was easier to see the orange
on the grey background?

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Yeah, you were going after
the orange ones, weren't you?

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Yeah, and this is kind of what we
expect.

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We see this, that, naturally,
in parts of the world

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where we have, kind of, black rocks,
you tend to find more black mice,

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and in parts of the world where you
have these golden, sandy rocks,

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we tend to find these yellow,
sandy-coloured mice,

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because what we expect, especially
in the grey habitat over there,

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the orange mice were picked off
quite easily

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by this fierce predator, and...

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..and the grey mice actually have
survived to live

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another day and to pass on
their genes.

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But we did ask you to be
a predator. We did.

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You haven't quite finished
the job, have you? No.

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Could you stomp on those
balloons for me, please?

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Do you want to have a stomp?
Yes! Yeah!
APPLAUSE

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Thank you so much.

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So, artificial selection
has created all the dog breeds

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that we see today.

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Natural selection picked off some
orange mice in that demonstration,

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and natural selection has also acted
on us humans as well.

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So, our species originated in
Africa, hundreds of thousands of

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years ago, but, then, we spread out
of Africa and colonised the globe,

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so, we encountered all sorts of
different environments as we went.

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And there are lots of ways that
humans can

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fit into different environments.

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We're quite clever,
so we can create culture,

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and that can help us.

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So, if we move into a cold place,
we might make ourselves

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warm clothes to put on.

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There's also physiological
adaptation, and that means

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that your body can get
used to an environment

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over your lifetime, but you don't
pass those kind of changes

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on to your children.

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So, natural selection is when
there is a genetic difference,

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generation by generation,
and we can see some

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great examples of that in us humans.

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And one really good example
comes through the variation

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that we can see in skin colour,

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and it tends to map on to geography.

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Now, most of us tend to have a
fairly consistent skin colour

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that we've inherited from our
parents and from earlier ancestors.

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So, over most of your body,
your skin colour is fairly similar.

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But I want to introduce you to
somebody now who's got very striking

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differences in skin colour
across his body,

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and he is fashion model
Bashir Aziz.

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APPLAUSE

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Bashir, hello. Can I get a spud?

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00:09:14,100 --> 00:09:15,700
Thank you.

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Bashir, you've got
a really striking look.

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You've got two completely different
colours of skin, and hair as well.

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Yeah. So, how long have you had
that? Were you born like it?

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Yeah, all my life.
So, that's what I've known.

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So, across your body, you've got
areas, and obviously we can see

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on your face you've got
areas of quite pale skin,

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and then dark skin as well.
Look at your arm there, yeah.

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So, you've got a real mixture. Yeah.

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So, we can actually have a look
and see how much skin pigment

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you've got in different areas.

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So, we can use this instrument here.

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So, yeah, have a look at the back
of your hand there.

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And...there we go.

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So, that says you've got 70% skin
pigment on that area.

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Let's have a look at areas
of your skin that are pale, then.

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Can I...can I try it on that area
there? Yeah, of course you can.

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00:10:02,940 --> 00:10:04,820
If I just pop it on there,
it should just work.

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00:10:04,820 --> 00:10:07,180
I mean, look at the difference
there. That's astonishing.

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00:10:07,180 --> 00:10:10,580
So, where you've got pale skin,
there's only, what, about 9%...

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9%. ..pigment, so, a really,
really big difference.

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00:10:13,300 --> 00:10:16,820
So, Bashir, I've got
slides here of pale skin,

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rather like the pale areas you've
got, and then dark skin as well,

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00:10:19,740 --> 00:10:21,620
and you can see that they're very
different

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00:10:21,620 --> 00:10:24,660
when you first look at them. Yeah.
And this difference

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is all to do with the skin
pigment melanin,

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and there are very few granules
of melanin in this skin.

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But you can see, in this section
here, all of those cells completely

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00:10:34,980 --> 00:10:39,020
packed full of lots
and lots of melanin granules.

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I'm going to try it on me as well.

193
00:10:40,620 --> 00:10:43,300
Go on, go on. I want to see,
I want to see what I've got.

194
00:10:43,300 --> 00:10:46,620
I've got a... There's a little bit
of melanin there. Yeah. 19. 19.

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00:10:46,620 --> 00:10:49,460
There you are. Which is my hand,
though, so it is exposed to the sun

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00:10:49,460 --> 00:10:51,780
quite a bit. That's all right. Yeah.

197
00:10:51,780 --> 00:10:54,660
So, do you notice any difference
between your dark skin

198
00:10:54,660 --> 00:10:57,140
and your lighter skin?
What, as in, like, naturally?

199
00:10:57,140 --> 00:10:59,780
When you're exposed to the sun, do
you notice any difference there?

200
00:10:59,780 --> 00:11:01,140
Do I see any difference? Yeah.

201
00:11:01,140 --> 00:11:03,620
No, I don't feel a difference.
I don't notice a difference.

202
00:11:03,620 --> 00:11:06,580
I just walk the walk and talk
the talk. Yeah. I would like, say,

203
00:11:06,580 --> 00:11:09,940
put a little sunscreen
if it is very, very, very sunny.

204
00:11:09,940 --> 00:11:12,380
So, it's interesting,
because the difference in pigment

205
00:11:12,380 --> 00:11:15,780
and the kind of pigment that's
there to begin with anyway gives us

206
00:11:15,780 --> 00:11:19,300
a clue as to why we've got
this colour in our skin.

207
00:11:19,300 --> 00:11:22,060
Yeah. And it is to do with sun
protection.

208
00:11:22,060 --> 00:11:25,500
So, in fact, your dark skin's giving
you some pretty significant

209
00:11:25,500 --> 00:11:27,180
sun protection here.

210
00:11:27,180 --> 00:11:30,420
And Bashir's dark skin is coming out
as about factor 20 sunscreen.

211
00:11:30,420 --> 00:11:32,980
Naturally. So, you've got your own,
natural sunscreen.

212
00:11:32,980 --> 00:11:35,460
Oh, perfect, lovely. And if you have
got very pale skin,

213
00:11:35,460 --> 00:11:39,300
of course, you have to put sunscreen
on if you go out

214
00:11:39,300 --> 00:11:42,380
into bright sunshine,
because you could

215
00:11:42,380 --> 00:11:46,380
burn your skin, and every single
episode of sunburn means that you

216
00:11:46,380 --> 00:11:48,780
have a higher risk
of developing skin cancer.

217
00:11:48,780 --> 00:11:51,860
That's the seriousness of it
a bit later on.

218
00:11:51,860 --> 00:11:55,020
Bashir, thank you so much.
Thank you for having me. Thank you.

219
00:11:55,020 --> 00:11:56,900
APPLAUSE

220
00:12:02,980 --> 00:12:07,980
So, that connection between skin
colour and sun protection gives us

221
00:12:08,620 --> 00:12:11,740
a clue as to how it evolved
in humans as well.

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00:12:11,740 --> 00:12:15,860
So, our ancestors, who expanded
out of Africa, would have all had

223
00:12:15,860 --> 00:12:19,100
dark skin. So, the first Asians,
the first Europeans

224
00:12:19,100 --> 00:12:21,020
would all have had dark skin.

225
00:12:21,020 --> 00:12:24,620
And, in fact, it's not until much
later that some mutations started

226
00:12:24,620 --> 00:12:29,020
to pop up in genomes so that skin
started to get a bit paler,

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00:12:29,020 --> 00:12:31,740
particularly in
very, very northern areas,

228
00:12:31,740 --> 00:12:35,140
where the sun just isn't as bright
as it is in the tropics

229
00:12:35,140 --> 00:12:37,020
and around the equator.

230
00:12:37,020 --> 00:12:41,020
And, in fact, we still see
these patterns of skin colour today.

231
00:12:41,020 --> 00:12:44,660
So, we still see that people whose
ancestry is predominantly

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00:12:44,660 --> 00:12:48,540
from those sunnier places of
the world tend to have darker skin,

233
00:12:48,540 --> 00:12:52,060
and people who've got more ancestry
in the far north

234
00:12:52,060 --> 00:12:54,300
tend to have paler skin as well.

235
00:12:54,300 --> 00:12:57,340
Well, next, we're going to
look at another adaptation,

236
00:12:57,340 --> 00:13:00,380
another way that natural selection
has acted on humans,

237
00:13:00,380 --> 00:13:02,980
but, this time, it isn't
to do with interacting

238
00:13:02,980 --> 00:13:06,100
with the environment as we find it,
it's about interacting

239
00:13:06,100 --> 00:13:09,140
with an environment
that we've actually changed.

240
00:13:09,140 --> 00:13:12,180
And it's about
the beginning of farming.

241
00:13:12,180 --> 00:13:15,420
I'd like you to gently give

242
00:13:15,420 --> 00:13:19,220
a round of applause for Jade the cow

243
00:13:19,220 --> 00:13:20,900
and her calf, Hazel,

244
00:13:20,900 --> 00:13:22,500
who are going to come on now.

245
00:13:22,500 --> 00:13:24,820
Oh, she's lovely.

246
00:13:24,820 --> 00:13:26,020
Hello, Jade.

247
00:13:30,220 --> 00:13:31,500
Hello.

248
00:13:31,500 --> 00:13:34,340
So, Jade is a Dexter cow, isn't she?
Yes.

249
00:13:34,340 --> 00:13:36,340
And this is her little calf. Yes.

250
00:13:36,340 --> 00:13:40,020
Yeah. So, obviously, calves
drink their mother's milk,

251
00:13:40,020 --> 00:13:42,940
and when our ancestors started
farming and they started

252
00:13:42,940 --> 00:13:45,540
domesticating cattle,
they could keep cattle

253
00:13:45,540 --> 00:13:49,180
for their meat, of course,
but also for their milk.

254
00:13:49,180 --> 00:13:53,460
Now, we want to demonstrate some
milk here, so I want a volunteer

255
00:13:53,460 --> 00:13:57,340
from the audience who's going to
come down and milk Jade.

256
00:13:57,340 --> 00:13:59,500
Let's see, who shall we have?

257
00:13:59,500 --> 00:14:01,420
Another fantastic
Christmas jumper, I think.

258
00:14:01,420 --> 00:14:03,020
Just there, yes. Come down.

259
00:14:05,980 --> 00:14:07,380
Yeah.

260
00:14:09,340 --> 00:14:11,380
And what's your name? Nam.

261
00:14:11,380 --> 00:14:14,100
Nam. Do you want to come
and have a go at milking, then?

262
00:14:14,100 --> 00:14:16,460
Yes, please. I think Felicity
will help you.

263
00:14:16,460 --> 00:14:19,020
Look, we've got a milking stool
for you. So you can either sit

264
00:14:19,020 --> 00:14:22,460
on the stool or you can lean down,
and gently squeeze and pull,

265
00:14:22,460 --> 00:14:25,020
like that. OK.

266
00:14:25,020 --> 00:14:28,380
So, this is what our ancient farming
ancestors had to learn to do,

267
00:14:28,380 --> 00:14:30,420
just what Nam's doing right now.

268
00:14:30,420 --> 00:14:34,260
There's a bit of a problem here,
because it isn't so easy to drink

269
00:14:34,260 --> 00:14:38,260
milk, and there's a clue to that
in genetics. Yes, there is.

270
00:14:38,260 --> 00:14:42,580
So, the main sugar that we find
in milk is called lactose.

271
00:14:42,580 --> 00:14:44,380
You see this lactose here.

272
00:14:44,380 --> 00:14:47,460
And that's actually quite
a hard sugar to digest.

273
00:14:47,460 --> 00:14:50,900
It's a very big sugar, and, in order
to be able to digest that,

274
00:14:50,900 --> 00:14:52,500
it needs to be broken down.

275
00:14:52,500 --> 00:14:55,100
That gets broken down by an enzyme,

276
00:14:55,100 --> 00:14:58,820
and I need a volunteer to help me
demonstrate what's going on.

277
00:14:58,820 --> 00:15:01,060
So, let's see...

278
00:15:01,060 --> 00:15:03,340
Yes, you at the back with the
beautiful jumper

279
00:15:03,340 --> 00:15:05,220
with the red stripe on it.
Come on down.

280
00:15:08,180 --> 00:15:09,780
Catherine, lovely to meet you.

281
00:15:09,780 --> 00:15:12,300
So, Catherine, you are now
going to be an enzyme

282
00:15:12,300 --> 00:15:16,300
because we have enzymes which break
down these things that we eat.

283
00:15:16,300 --> 00:15:18,740
So, you're going to wear this,
please. And if you could

284
00:15:18,740 --> 00:15:21,740
come around here. What the enzyme
does... If you come over here.

285
00:15:21,740 --> 00:15:25,740
What the enzyme does is it breaks
the lactose into smaller sugars,

286
00:15:25,740 --> 00:15:27,900
so you can do that by turning this.

287
00:15:27,900 --> 00:15:30,940
Yeah, so, that's the way it works.
But stop for a second

288
00:15:30,940 --> 00:15:33,580
because the enzyme doesn't
just come from nowhere.

289
00:15:33,580 --> 00:15:37,420
The enzyme is produced
by a gene - that's me.

290
00:15:37,420 --> 00:15:41,100
And the enzyme is only produced
when the gene is switched on,

291
00:15:41,100 --> 00:15:43,900
so, when you're a baby,
this gene is switched on,

292
00:15:43,900 --> 00:15:46,420
and, in this baby calf,
this gene is switched on,

293
00:15:46,420 --> 00:15:48,980
so the enzyme can go ahead.
Yeah, keep... So, now the enzyme

294
00:15:48,980 --> 00:15:52,460
is working, working, working, and
it's breaking down this lactose into

295
00:15:52,460 --> 00:15:56,820
smaller, simpler sugars that we can
actually digest without any problem.

296
00:15:56,820 --> 00:15:59,340
So, this is what this
lovely, little calf has,

297
00:15:59,340 --> 00:16:01,620
and it's what all baby mammals have.

298
00:16:01,620 --> 00:16:05,380
But, then, at a certain point, what
happens is the gene switches off

299
00:16:05,380 --> 00:16:07,820
and the enzyme switches off.

300
00:16:07,820 --> 00:16:10,460
Very good. And, so, this is what
normally happens,

301
00:16:10,460 --> 00:16:13,180
but is there anybody in this room
who can drink milk and it's not

302
00:16:13,180 --> 00:16:15,900
a problem? Lots of you,
lots of you.

303
00:16:15,900 --> 00:16:18,220
And including some adults as well.

304
00:16:18,220 --> 00:16:21,860
That's because, in many humans,
there's an adaptation to dairy

305
00:16:21,860 --> 00:16:26,420
culture which means that the gene
stays on and the enzyme keeps going,

306
00:16:26,420 --> 00:16:29,300
and you're still able to break down
this lactose sugar

307
00:16:29,300 --> 00:16:32,180
well into adulthood, in fact,
for the rest of your life.

308
00:16:32,180 --> 00:16:35,180
And, when we look at what parts
of the world this happened in,

309
00:16:35,180 --> 00:16:38,140
it happens in parts of the world
where we have dairy culture.

310
00:16:38,140 --> 00:16:42,180
It happened in dairy cultures
in Africa and in Europe.

311
00:16:42,180 --> 00:16:43,620
So, thank you so much.

312
00:16:43,620 --> 00:16:45,740
I'll switch off the gene now
so you can have a rest.

313
00:16:45,740 --> 00:16:48,500
Thank you so much.
You were a wonderful volunteer.

314
00:16:48,500 --> 00:16:51,300
Thank you.
APPLAUSE

315
00:16:52,580 --> 00:16:53,940
Oh, my goodness.

316
00:16:55,020 --> 00:16:58,220
That's wonderful. And Nam did
an absolutely brilliant job.

317
00:16:58,220 --> 00:17:01,180
Thank you very much, Nam.
Well done. Thank you.

318
00:17:04,220 --> 00:17:06,460
I have never milked a cow.
Have you ever milked a cow?

319
00:17:06,460 --> 00:17:09,220
I don't think I have. Nam just did.
Well done, that's impressive.

320
00:17:09,220 --> 00:17:12,260
Thank you. Thank you very much,
Jade and Hazel, as well.

321
00:17:12,260 --> 00:17:13,660
Thank you.

322
00:17:13,660 --> 00:17:16,140
APPLAUSE

323
00:17:19,740 --> 00:17:24,540
So, this adaptation to drinking
milk that appeared in our farming

324
00:17:24,540 --> 00:17:29,460
ancestors then spread so that most
of us in Europe can now...

325
00:17:29,460 --> 00:17:31,860
..can now drink fresh milk.

326
00:17:31,860 --> 00:17:34,380
And the way that that gene
spread is through people

327
00:17:34,380 --> 00:17:36,580
moving, through migrations.

328
00:17:36,580 --> 00:17:38,700
And what we know is that,
throughout history,

329
00:17:38,700 --> 00:17:40,660
there have been
big migrations of people,

330
00:17:40,660 --> 00:17:42,940
and people have just kept moving,

331
00:17:42,940 --> 00:17:46,620
and that has spread different
characteristics around the world,

332
00:17:46,620 --> 00:17:48,620
and that spreading keeps on going.

333
00:17:48,620 --> 00:17:51,620
It's interesting that the ethnic
groups that we can spot today,

334
00:17:51,620 --> 00:17:54,740
and we can...we can sort of say
one population looks a bit different

335
00:17:54,740 --> 00:17:58,380
from another population, that's just
a snapshot in the here and now,

336
00:17:58,380 --> 00:18:01,220
and those ethnic groupings are
different from what they were

337
00:18:01,220 --> 00:18:03,660
a few thousand years ago,
and they'll keep changing

338
00:18:03,660 --> 00:18:07,820
because we humans keep moving and we
keep mixing ourselves around.

339
00:18:07,820 --> 00:18:11,380
So, we've got an illustration here
of just some of the global

340
00:18:11,380 --> 00:18:16,260
connectedness of everyone
in this theatre tonight.

341
00:18:16,260 --> 00:18:19,660
When you got your tickets,
we asked you where your parents

342
00:18:19,660 --> 00:18:23,020
and your grandparents came from,
and we've mapped those connections

343
00:18:23,020 --> 00:18:27,420
here. So, the centre of it all is,
of course, this lecture theatre

344
00:18:27,420 --> 00:18:29,660
in the Royal Institution in London.

345
00:18:29,660 --> 00:18:32,700
This is just a snapshot
of where you are this evening.

346
00:18:32,700 --> 00:18:35,340
But here are all your family
connections around the world,

347
00:18:35,340 --> 00:18:37,620
to North America, to South America,

348
00:18:37,620 --> 00:18:42,260
to West Africa, over here
to Southeast Asia and East Asia,

349
00:18:42,260 --> 00:18:45,060
and down to Australia as well.

350
00:18:45,060 --> 00:18:49,380
So, what a wonderful image
of global connectedness.

351
00:18:49,380 --> 00:18:50,940
Thank you very much.

352
00:18:50,940 --> 00:18:53,540
APPLAUSE

353
00:18:56,100 --> 00:19:00,980
We've looked at some variation
in humans that we can explain

354
00:19:00,980 --> 00:19:04,180
through adaptation,
and that we can experience

355
00:19:04,180 --> 00:19:07,780
ourselves. We can look at our own
skin colour, we can see differences

356
00:19:07,780 --> 00:19:10,820
in skin colour around us,
but there's another adaptation,

357
00:19:10,820 --> 00:19:13,180
or another gene variant,
that we want to introduce

358
00:19:13,180 --> 00:19:16,100
to you now, which is
a bit more hidden,

359
00:19:16,100 --> 00:19:19,660
and we'll need some volunteers
to help us show it as well.

360
00:19:19,660 --> 00:19:22,540
Yes. So, this is something
that is very much hidden,

361
00:19:22,540 --> 00:19:24,420
so, let's see... I'll pick somebody.

362
00:19:24,420 --> 00:19:26,460
Yes, you are very
enthusiastic there.

363
00:19:26,460 --> 00:19:28,740
Yeah, the boy with the lovely
Christmas jumper.

364
00:19:28,740 --> 00:19:32,380
How many do you want, Aoife? We need
six, so you pick three,

365
00:19:32,380 --> 00:19:35,020
I'll get three.
OK. Right, I've got two.

366
00:19:35,020 --> 00:19:37,980
All get close together into a line,
shoulder to shoulder. Yeah.

367
00:19:37,980 --> 00:19:40,180
What a lovely group of volunteers.
APPLAUSE

368
00:19:42,020 --> 00:19:46,420
Alice, I'd like... Alice, I'd like
you to join in this one as well.

369
00:19:46,420 --> 00:19:49,220
You can be our seventh volunteer.
Yeah, yeah, I owe you one.

370
00:19:49,220 --> 00:19:51,740
So, what I'm going to do now is
I'm going to ask you to taste

371
00:19:51,740 --> 00:19:54,180
something, OK? So, you're going to
get a piece of paper.

372
00:19:54,180 --> 00:19:56,220
If you just stick out your hand,
you're going to get

373
00:19:56,220 --> 00:19:58,460
a piece of paper. Just hold it in
your hand for a moment,

374
00:19:58,460 --> 00:20:00,900
and then I'm going to ask you to
just place it on your tongue.

375
00:20:00,900 --> 00:20:02,900
You're not to chew it
or swallow it or anything.

376
00:20:02,900 --> 00:20:05,140
There's going to be a mix of
flavours.

377
00:20:05,140 --> 00:20:07,020
So, some of you are going to taste
something,

378
00:20:07,020 --> 00:20:09,020
and some of you are not
going to taste something.

379
00:20:10,180 --> 00:20:11,420
OK.

380
00:20:11,420 --> 00:20:13,980
Let's see.

381
00:20:13,980 --> 00:20:16,460
Ah, there's a nasty reaction over
there. What do you think?

382
00:20:16,460 --> 00:20:19,100
Oh, my God! Take it out of your
mouth again. That's disgusting!

383
00:20:19,100 --> 00:20:22,260
And it... Yeah. So, who else thought
it tasted disgusting? Ugh!

384
00:20:22,260 --> 00:20:24,220
Did you get any taste? Yeah.
You got a taste.

385
00:20:24,220 --> 00:20:26,660
What did it taste like to you?
I don't know, like broccoli.

386
00:20:26,660 --> 00:20:28,740
Like broccoli? Interesting. What did
you think?

387
00:20:28,740 --> 00:20:30,340
I didn't taste anything. No taste.

388
00:20:30,340 --> 00:20:33,300
But you thought it tasted horrible.
I thought it tasted like soap.

389
00:20:33,300 --> 00:20:36,620
Like soap? So, this is interesting,
because we actually have genetic

390
00:20:36,620 --> 00:20:39,420
variation of our taste
receptor genes.

391
00:20:39,420 --> 00:20:42,100
You all got the same piece of paper,
but some of you could taste it and

392
00:20:42,100 --> 00:20:43,940
some of you couldn't taste it,

393
00:20:43,940 --> 00:20:47,140
and that's because we have different
versions of a gene that allows us

394
00:20:47,140 --> 00:20:48,940
to taste this bitter flavour or not.

395
00:20:48,940 --> 00:20:51,980
But you seemed to think it was
particularly horrible, did you?

396
00:20:51,980 --> 00:20:55,820
So, I mean, maybe there's something
I can show you here that might cause

397
00:20:55,820 --> 00:20:57,740
you some dread.

398
00:20:57,740 --> 00:21:00,780
LAUGHTER
What do you think?

399
00:21:00,780 --> 00:21:03,140
Do you like sprouts? No!

400
00:21:03,140 --> 00:21:05,300
Cos you can taste
the bitterness in them.

401
00:21:05,300 --> 00:21:07,660
But thank you very much,
wonderful volunteers.

402
00:21:13,500 --> 00:21:17,820
Yeah, so we've seen a few examples
of genetic variation.

403
00:21:17,820 --> 00:21:21,620
Geneticists in particular
are totally obsessed with variation.

404
00:21:21,620 --> 00:21:24,740
We want to understand
how the differences that we see

405
00:21:24,740 --> 00:21:27,580
between us are related
to differences in our genes.

406
00:21:27,580 --> 00:21:29,940
This works quite differently
in different cases.

407
00:21:29,940 --> 00:21:33,620
So, for example, for height,
the height that you will grow to

408
00:21:33,620 --> 00:21:37,140
as an adult is really strongly
determined by your genes.

409
00:21:37,140 --> 00:21:38,980
It's really a strong effect.

410
00:21:38,980 --> 00:21:41,820
Of course, what you eat and how much
you eat is going to contribute

411
00:21:41,820 --> 00:21:44,460
to that, but if I wanted
to guess your height as an adult,

412
00:21:44,460 --> 00:21:47,060
I would look at your parents,
and that'd be a fairly good guess.

413
00:21:47,060 --> 00:21:50,060
But there are other things which,
even though there is a genetic

414
00:21:50,060 --> 00:21:53,180
influence, it's really not
that strong, there's something

415
00:21:53,180 --> 00:21:54,700
else that comes in as well.

416
00:21:54,700 --> 00:21:58,620
So, can you please raise your right
hand if you are right-handed?

417
00:21:58,620 --> 00:22:01,220
OK, that's really a lot of people.

418
00:22:01,220 --> 00:22:05,260
Can you please raise your left hand
if you are left-handed?

419
00:22:05,260 --> 00:22:08,980
There's a few. OK, so when did you
decide to be left-handed?

420
00:22:08,980 --> 00:22:11,900
You never decided.
It's a trick question, of course.

421
00:22:11,900 --> 00:22:14,900
So, it's a strange one, because,
even though

422
00:22:14,900 --> 00:22:18,380
it's only partly genetic,
you are also born that way.

423
00:22:18,380 --> 00:22:21,620
So, in terms of whether
you're left-handed or right-handed,

424
00:22:21,620 --> 00:22:25,260
this is a really good example
of where genes and chance

425
00:22:25,260 --> 00:22:27,860
come together to make you
what you are.

426
00:22:27,860 --> 00:22:30,020
And we're going to
represent that here

427
00:22:30,020 --> 00:22:32,180
with this kind of obstacle course.

428
00:22:32,180 --> 00:22:35,300
So, this obstacle course we've got
here is representing the process

429
00:22:35,300 --> 00:22:38,140
of development, so that's
you growing in the womb.

430
00:22:38,140 --> 00:22:40,900
And, if we imagine, we've got
the start here, which is the start

431
00:22:40,900 --> 00:22:44,340
of development, and, at the end,
you either end up right-handed

432
00:22:44,340 --> 00:22:47,660
or left-handed. So, if this one
individual went through this process

433
00:22:47,660 --> 00:22:51,180
of development... I have one
individual in the shape of one

434
00:22:51,180 --> 00:22:54,140
yellow ball. ..they might end up
left-handed or right-handed.

435
00:22:54,140 --> 00:22:57,700
We can't tell at the beginning,
but let's see what happens.

436
00:22:57,700 --> 00:23:00,180
Let's see. We'll watch it go down.

437
00:23:00,180 --> 00:23:02,460
So we can't actually predict
what side it will end up on.

438
00:23:02,460 --> 00:23:05,260
But this one and ended up on the
left, so this individual ended up,

439
00:23:05,260 --> 00:23:06,740
let's say, left-handed.

440
00:23:06,740 --> 00:23:09,580
But if we have somebody else
with exactly the same genetics,

441
00:23:09,580 --> 00:23:11,900
they might turn out differently.

442
00:23:11,900 --> 00:23:14,220
So, this person ended up
right-handed, and we can do

443
00:23:14,220 --> 00:23:17,420
a few more,
and we can do a few more.

444
00:23:17,420 --> 00:23:20,740
I'm going to tip all these balls in
and we'll see what happens.

445
00:23:23,820 --> 00:23:25,860
Nice and easy.

446
00:23:25,860 --> 00:23:28,020
OK, so, in this case,
even though everybody

447
00:23:28,020 --> 00:23:31,620
here has the same genetics,
has got the same obstacle course,

448
00:23:31,620 --> 00:23:34,940
a lot more turned out right-handed
than turned out left-handed.

449
00:23:34,940 --> 00:23:36,940
So, on average in the population,

450
00:23:36,940 --> 00:23:38,860
90% of people are right-handed,

451
00:23:38,860 --> 00:23:41,180
and only 10% of people
are left-handed,

452
00:23:41,180 --> 00:23:43,500
and, so, the genetics
works a bit like this.

453
00:23:43,500 --> 00:23:47,980
So, your genes set up a probability,
but they don't determine exactly

454
00:23:47,980 --> 00:23:50,820
how you're going to end out.
No, they don't. You know, we might

455
00:23:50,820 --> 00:23:53,700
think about something as normal or
something as not normal, but that's

456
00:23:53,700 --> 00:23:56,900
really not the way it is.
Yeah, you've got two outcomes here.

457
00:23:56,900 --> 00:23:58,940
One of them is more probable
than the other one,

458
00:23:58,940 --> 00:24:01,380
but you can't say that being
right-handed is normal

459
00:24:01,380 --> 00:24:04,220
and being left-handed is abnormal.
No. But there's other things

460
00:24:04,220 --> 00:24:06,340
that have similar genetics to this,

461
00:24:06,340 --> 00:24:08,940
and one of those
is sexual preference.

462
00:24:08,940 --> 00:24:11,500
So, usually, men are
attracted to women,

463
00:24:11,500 --> 00:24:14,780
and women are attracted to men,
but sometimes it's not that way,

464
00:24:14,780 --> 00:24:17,180
and the genetics, actually,
is very, very similar,

465
00:24:17,180 --> 00:24:19,220
the percentage is very similar,

466
00:24:19,220 --> 00:24:22,540
and we have a similar situation
that the genes determine the shape

467
00:24:22,540 --> 00:24:26,140
of this obstacle course,
and sometimes it'll go one way,

468
00:24:26,140 --> 00:24:28,180
and sometimes it'll go
the other way.

469
00:24:28,180 --> 00:24:30,540
So, your genes aren't
completely in control.

470
00:24:30,540 --> 00:24:34,220
There's a lot of room
for chance as well. Yeah, yeah.

471
00:24:34,220 --> 00:24:38,500
And, in fact, in our own bodies,
we see the way that having the same

472
00:24:38,500 --> 00:24:41,380
genome - for instance,
on both sides of your body -

473
00:24:41,380 --> 00:24:43,260
can produce slightly
different effects.

474
00:24:43,260 --> 00:24:47,220
Yes, and you can see an example
of that by looking in the mirror.

475
00:24:47,220 --> 00:24:49,340
And, for this, I will need
another volunteer,

476
00:24:49,340 --> 00:24:52,540
and I'll need somebody
who is very good at staying still.

477
00:24:52,540 --> 00:24:55,460
Who can be very, very, very still?

478
00:24:55,460 --> 00:24:57,740
So, here is somebody who's
very nice and still.

479
00:24:57,740 --> 00:24:59,660
Yes, and with a beautiful jumper.
Yes, you.

480
00:25:02,940 --> 00:25:04,740
OK, so I'm going to ask you to do
something.

481
00:25:04,740 --> 00:25:07,180
Come round this side of the table.
So, what's your name?

482
00:25:07,180 --> 00:25:09,060
Kam. Kam, it's lovely to meet you.

483
00:25:09,060 --> 00:25:12,100
So, I'm going to ask you
to sit your head in your hands

484
00:25:12,100 --> 00:25:13,460
like that, right?

485
00:25:13,460 --> 00:25:16,220
I want you to keep your head
as straight as possible and looking

486
00:25:16,220 --> 00:25:18,940
straight at that camera. Now, we all
have quite symmetric faces,

487
00:25:18,940 --> 00:25:20,180
don't you think?

488
00:25:20,180 --> 00:25:23,420
But there are little asymmetries
that we can't even notice most

489
00:25:23,420 --> 00:25:26,340
of the time, and those asymmetries
are due to that kind of chance

490
00:25:26,340 --> 00:25:28,540
in development that we just
mentioned earlier.

491
00:25:28,540 --> 00:25:30,820
So, if we look at this picture
of Kam, we can see she looks

492
00:25:30,820 --> 00:25:33,900
very symmetric, like all of us do,
but she probably has some

493
00:25:33,900 --> 00:25:35,420
small, little asymmetries.

494
00:25:35,420 --> 00:25:39,620
So, if we just take the left-hand
side of Kam's face and flip

495
00:25:39,620 --> 00:25:42,900
it over and make a magic mirror
image, and then we move

496
00:25:42,900 --> 00:25:45,140
that over to the left
here of the picture,

497
00:25:45,140 --> 00:25:47,460
and we'll do the same
thing with the right.

498
00:25:47,460 --> 00:25:50,620
So we'll take the right-hand
side and flip it over.

499
00:25:50,620 --> 00:25:53,540
OK, so, now, keep
looking exactly straight.

500
00:25:53,540 --> 00:25:57,180
And, so, you can see here,
on the left we have the left-hand

501
00:25:57,180 --> 00:26:01,300
side of Kam's face made symmetric,
and the right-hand side of her face

502
00:26:01,300 --> 00:26:03,940
made symmetric, and they look a bit
different, don't they?

503
00:26:03,940 --> 00:26:05,740
So, it almost looks like Kam

504
00:26:05,740 --> 00:26:08,300
is her own identical twin
or something.

505
00:26:08,300 --> 00:26:11,580
But just look at me without moving
your head, without moving your head,

506
00:26:11,580 --> 00:26:14,060
and can you look at Alice
without moving your head?

507
00:26:14,060 --> 00:26:17,140
LAUGHTER
And back at me.
And look back at Alice.

508
00:26:17,140 --> 00:26:20,060
OK, thank you very much.
You were wonderful.

509
00:26:28,220 --> 00:26:32,100
Aoife, that was an example
of how a genome can play out

510
00:26:32,100 --> 00:26:34,460
slightly differently in one side
of your face compared

511
00:26:34,460 --> 00:26:37,180
with the other, but, sometimes,
we get the same genome

512
00:26:37,180 --> 00:26:39,220
in different individuals.

513
00:26:39,220 --> 00:26:42,460
Otherwise known as...
BOTH: ..identical twins.

514
00:26:42,460 --> 00:26:45,140
And we have some twins
who are here this evening

515
00:26:45,140 --> 00:26:48,340
who have kindly agreed in advance
to do some experiments with us.

516
00:26:48,340 --> 00:26:50,060
So, if you could please come down.

517
00:26:50,060 --> 00:26:52,460
We have Ronnie and Ritchie,
and Noah and Harris,

518
00:26:52,460 --> 00:26:54,300
and Rosanna and Caitlin.

519
00:26:54,300 --> 00:26:56,460
APPLAUSE

520
00:27:04,580 --> 00:27:05,620
OK.

521
00:27:08,220 --> 00:27:10,700
OK, so, which one of you is Ronnie
and which one's Ritchie?

522
00:27:10,700 --> 00:27:12,500
I'm Ronnie, he's Ritchie.
OK, thank you.

523
00:27:12,500 --> 00:27:15,460
So, what we're going to ask you
to do is to put your hand

524
00:27:15,460 --> 00:27:18,020
into this bucket of ice water
and to keep it there

525
00:27:18,020 --> 00:27:19,500
just until it feels uncomfortable,

526
00:27:19,500 --> 00:27:22,260
OK? So, you're going to take it out
as soon as it feels uncomfortable.

527
00:27:22,260 --> 00:27:24,900
And, because we want to compare you,
and because we don't want you

528
00:27:24,900 --> 00:27:27,380
to know what's happening with the
other twin, we're going to

529
00:27:27,380 --> 00:27:29,700
ask you to put on those ear
defenders so you can't hear

530
00:27:29,700 --> 00:27:32,140
what's happening around. So, I'm
going to go behind you,

531
00:27:32,140 --> 00:27:34,740
and I'm going to start these
stopwatches, and you can see me

532
00:27:34,740 --> 00:27:38,060
starting the stopwatch, and that's
when you're to put your hand in, OK?

533
00:27:38,060 --> 00:27:40,140
So, put the ear defenders on
and we'll get ready.

534
00:27:42,220 --> 00:27:44,660
OK, ready? Go.

535
00:27:46,860 --> 00:27:51,100
So, while, Aoife, you time the
twins, seeing how long they can keep

536
00:27:51,100 --> 00:27:54,700
their hand in the ice,
I've got Noah and Harris here,

537
00:27:54,700 --> 00:27:59,060
and Helen Earwaker, who is
a fingerprint researcher.

538
00:27:59,060 --> 00:28:02,180
And, so, Helen, you're going to be
looking at the twins'

539
00:28:02,180 --> 00:28:04,500
fingerprints and seeing
just how similar and different

540
00:28:04,500 --> 00:28:06,020
they really are. Yes, I am indeed.

541
00:28:06,020 --> 00:28:08,580
I'm going to take prints from both
of them. Shall we start

542
00:28:08,580 --> 00:28:10,260
with one of them, then? Fantastic.

543
00:28:10,260 --> 00:28:12,620
Are you Noah or Harris? I'm Noah.
You're Noah, OK.

544
00:28:12,620 --> 00:28:16,620
OK. So, we're going to take
Noah's right thumb,

545
00:28:16,620 --> 00:28:21,620
and we're going to very carefully
move the thumb round,

546
00:28:22,220 --> 00:28:25,660
all the way from one end
of the fingernail, all the way

547
00:28:25,660 --> 00:28:29,740
to the other... Getting lots of ink
on it. ..getting ink on

548
00:28:29,740 --> 00:28:32,340
all of the ridges of Noah's thumb.

549
00:28:32,340 --> 00:28:36,740
And then we're going to create
a record of that thumb

550
00:28:36,740 --> 00:28:40,420
by popping it down
on the paper and rolling...

551
00:28:42,300 --> 00:28:44,220
..all the way across.

552
00:28:44,220 --> 00:28:46,940
Look at that - that's a beautiful
thumbprint! Excellent. And up.

553
00:28:46,940 --> 00:28:50,220
Perfect. Helen, I'll leave you to do
the same with Harris... Thank you.

554
00:28:50,220 --> 00:28:53,020
..and I'll move over here, because
we've got Omar Mahroo, who's

555
00:28:53,020 --> 00:28:57,740
an eye doctor, and we've got another
pair of twins, Rosanna and Caitlin.

556
00:28:57,740 --> 00:29:00,620
Who's Rosanna? Hi.
You must be Caitlin.

557
00:29:00,620 --> 00:29:04,020
And Omar is going to have
a look at your irises.

558
00:29:04,020 --> 00:29:07,460
So, Rosanna, if you'd like
to sit down there.

559
00:29:07,460 --> 00:29:10,300
We're going to have a look
at the fine structure

560
00:29:10,300 --> 00:29:12,660
of these twins' eyes.
Are you comfortable there?

561
00:29:12,660 --> 00:29:14,460
And, Omar, what are you doing there?

562
00:29:14,460 --> 00:29:17,420
So, this allows us to take
a detailed picture of the iris

563
00:29:17,420 --> 00:29:20,500
of Rosanna's left eye. And what are
you interested in? Are you

564
00:29:20,500 --> 00:29:23,420
interested in the colour or the
structure? No, actually, the fine

565
00:29:23,420 --> 00:29:26,500
details of the structure, which you
can't normally see with the naked

566
00:29:26,500 --> 00:29:29,020
eye, but with a camera like this,
you can. Lovely.

567
00:29:29,020 --> 00:29:30,980
Oh! The ice has stopped.

568
00:29:30,980 --> 00:29:34,060
Yes, well, actually,
I didn't want to let them go

569
00:29:34,060 --> 00:29:37,140
past two minutes and they both got
that far, so they did the maximum

570
00:29:37,140 --> 00:29:39,940
amount of time. Wow, that's amazing!
Oh, my goodness, they're very

571
00:29:39,940 --> 00:29:42,420
strong! You can take your ear
defenders off.
APPLAUSE

572
00:29:48,940 --> 00:29:50,500
I wonder if...

573
00:29:50,500 --> 00:29:52,420
Was it really not
uncomfortable before then?

574
00:29:52,420 --> 00:29:54,460
Did you just keep going,
even though? Yeah.

575
00:29:54,460 --> 00:29:56,700
You did! Oh, you're so bad, but
it's...

576
00:29:56,700 --> 00:29:58,700
Yeah, they're both very strong,

577
00:29:58,700 --> 00:30:01,900
obviously, and they're both
the same as each other.

578
00:30:01,900 --> 00:30:04,020
Between twins, we'll see
this pain resistance

579
00:30:04,020 --> 00:30:06,660
is quite similar
between twins, but very strong.

580
00:30:06,660 --> 00:30:11,380
And possibly very competitive as
well. Possibly quite competitive!
LAUGHTER

581
00:30:11,380 --> 00:30:14,940
Now, Helen, what about Noah
and Harris and their thumbprints?

582
00:30:14,940 --> 00:30:17,980
They're beautiful thumbprints.
They are indeed. We managed some

583
00:30:17,980 --> 00:30:21,620
excellent prints here from both of
them. So, if we start by looking

584
00:30:21,620 --> 00:30:24,020
at Noah's prints.

585
00:30:24,020 --> 00:30:27,340
We're going to start by looking
at first-level detail,

586
00:30:27,340 --> 00:30:30,020
which is the type of overall
pattern that we can see.

587
00:30:30,020 --> 00:30:32,620
So, the question is
are they broadly similar, then?

588
00:30:32,620 --> 00:30:36,260
So, we would expect to see a level
of similarity due to some

589
00:30:36,260 --> 00:30:39,140
of the genetic ways in which those
fingerprints have formed,

590
00:30:39,140 --> 00:30:42,140
but also we'll expect to see some
differences due to the exact

591
00:30:42,140 --> 00:30:46,580
conditions in which that friction
ridge skin, those fingerprints,

592
00:30:46,580 --> 00:30:50,020
are formed within different areas of
the womb. OK, so what can you see?

593
00:30:50,020 --> 00:30:53,100
So, we can see here in Noah's print
that we have lines

594
00:30:53,100 --> 00:30:55,980
coming up and going around.
Yeah, there's a loop.

595
00:30:55,980 --> 00:30:57,860
There is a loop, indeed.

596
00:30:57,860 --> 00:31:00,860
And we look at Harris's print
and we can see, similarly,

597
00:31:00,860 --> 00:31:03,420
a loop coming up and around.

598
00:31:03,420 --> 00:31:08,140
But, if we look carefully,
we can also see another loop

599
00:31:08,140 --> 00:31:10,060
that heads back up. Indeed. Yeah.

600
00:31:10,060 --> 00:31:14,020
So, Harris has something
that we would call a twin loop.

601
00:31:14,020 --> 00:31:16,220
And Noah doesn't have that? No.

602
00:31:16,220 --> 00:31:18,940
Noah has what we would call
an ulnar loop coming around here.

603
00:31:18,940 --> 00:31:21,460
Yeah, just a single loop.
That's fascinating. I mean,

604
00:31:21,460 --> 00:31:24,780
it's very interesting, isn't it,
that you've got similar fingerprints

605
00:31:24,780 --> 00:31:27,700
but you're both individuals, you've
both got something special

606
00:31:27,700 --> 00:31:30,140
and different and unique
about your fingerprints.

607
00:31:30,140 --> 00:31:31,900
Brilliant. Thank you, Helen.

608
00:31:31,900 --> 00:31:35,380
How are you doing over here, Omar,
with Rosanna and Caitlin?

609
00:31:35,380 --> 00:31:38,460
How do their eyes look? We've got
some very nice pictures

610
00:31:38,460 --> 00:31:40,620
of the iris of
Rosanna and Caitlin here.

611
00:31:40,620 --> 00:31:42,540
And, here, you can see,
superficially,

612
00:31:42,540 --> 00:31:45,100
they do look very similar,
similar colours,

613
00:31:45,100 --> 00:31:47,260
but, if you look at the fine detail,

614
00:31:47,260 --> 00:31:51,020
you can see that Caitlin has
a couple of small depressions,

615
00:31:51,020 --> 00:31:54,460
we call them crypts, that Rosanna
doesn't have in the same place,

616
00:31:54,460 --> 00:31:56,380
and that's highlighted here.

617
00:31:56,380 --> 00:31:59,100
What's really interesting is that
when you look at their irises

618
00:31:59,100 --> 00:32:01,700
like that, I mean, they are
strikingly similar in terms of

619
00:32:01,700 --> 00:32:04,420
colour. Yes, absolutely. Yeah, yeah,
but it's the structure,

620
00:32:04,420 --> 00:32:06,580
it's the fine structure that is
actually different.

621
00:32:06,580 --> 00:32:09,940
Yes, and then another
difference is this ridge.

622
00:32:09,940 --> 00:32:12,660
It's a raised area we call
the collarette, and I've just

623
00:32:12,660 --> 00:32:15,580
highlighted them in both twins and
you can see the shape's subtly

624
00:32:15,580 --> 00:32:18,300
different, and, if you superimpose
them again,

625
00:32:18,300 --> 00:32:21,060
they're not identical at all.
Yeah. They're quite different.

626
00:32:21,060 --> 00:32:23,700
Isn't that interesting, that when we
really get into this level

627
00:32:23,700 --> 00:32:26,580
of detail, again,
you are each unique?

628
00:32:26,580 --> 00:32:30,020
Thank you very much, twins.
Thank you, Omar. Thank you, Helen.

629
00:32:30,020 --> 00:32:31,580
APPLAUSE

630
00:32:38,340 --> 00:32:42,900
So, Ronnie and Ritchie have stayed
around, because last week

631
00:32:42,900 --> 00:32:45,940
they did something else
for us, and that was this.

632
00:32:45,940 --> 00:32:48,340
So, what they're doing there
is they're taking a sample

633
00:32:48,340 --> 00:32:51,540
from inside their mouth, but it's
not a sample of their own DNA,

634
00:32:51,540 --> 00:32:55,100
it's a sample of things
that are living in and on all of us.

635
00:32:55,100 --> 00:32:58,500
We all have bacteria
that are growing on our skin

636
00:32:58,500 --> 00:33:00,660
and inside our mouth
and our intestines,

637
00:33:00,660 --> 00:33:03,540
and Ronnie and Ritchie very kindly
agreed to give a sample

638
00:33:03,540 --> 00:33:05,980
so that we could have a look at it.
And here to talk to us

639
00:33:05,980 --> 00:33:09,340
about that is Arwyn from
the University of Aberystwyth.

640
00:33:13,900 --> 00:33:15,660
Arwyn Edwards.

641
00:33:17,140 --> 00:33:18,740
It's lovely to see you.

642
00:33:18,740 --> 00:33:21,740
Thank you for doing this.
So, you have here something

643
00:33:21,740 --> 00:33:23,860
that has grown
from inside their mouths.

644
00:33:23,860 --> 00:33:26,980
Yes, so we have the bacteria
from Ronnie and Ritchie's mouths

645
00:33:26,980 --> 00:33:29,820
that have been plated
out on a nutrient media,

646
00:33:29,820 --> 00:33:32,700
so this nice nutrient jelly
that is basically bacteria food.

647
00:33:32,700 --> 00:33:34,700
But you can see some differences
between them.

648
00:33:34,700 --> 00:33:36,220
Which one of you is Ronnie? Him.

649
00:33:36,220 --> 00:33:38,860
OK, Ronnie, just give you
your bacteria back for a second,

650
00:33:38,860 --> 00:33:40,700
so, you can see some differences
there,

651
00:33:40,700 --> 00:33:43,540
but it's all kind of little spots
of this and that, so it's a bit

652
00:33:43,540 --> 00:33:48,220
difficult to tell, and that's
because only 1% of bacteria will

653
00:33:48,220 --> 00:33:51,460
grow on agar. So, to really get
in touch with our microbiomes,

654
00:33:51,460 --> 00:33:53,900
what we have to do
is do DNA sequencing.

655
00:33:53,900 --> 00:33:56,740
So, this is really a small sample
of what Ronnie and Ritchie

656
00:33:56,740 --> 00:33:59,060
are carrying around, and all of us
are carrying around?

657
00:33:59,060 --> 00:34:01,700
Everyone's carrying around, right
now. Everybody in this room.

658
00:34:01,700 --> 00:34:04,540
So, how do you, then, sample
the rest of the diversity?

659
00:34:04,540 --> 00:34:06,860
Well, that's a good question.
So, as well as collecting

660
00:34:06,860 --> 00:34:09,740
those swabs, what happens
was the samples of spit

661
00:34:09,740 --> 00:34:14,340
then had their DNA in that sample
extracted and we amplified bacterial

662
00:34:14,340 --> 00:34:18,060
genes in there to do a sort of DNA
fingerprint of the microbes present.

663
00:34:18,060 --> 00:34:19,460
OK. So you have something here.

664
00:34:19,460 --> 00:34:21,860
Ronnie, Ritchie, come over here
beside me and have a look.

665
00:34:21,860 --> 00:34:24,420
So, now you're loading
the sample in.

666
00:34:24,420 --> 00:34:27,060
I'm just preparing for the sample to
just go in. OK, that's...

667
00:34:27,060 --> 00:34:30,100
This is the sample going in here,
this kind of milky liquid here. OK.

668
00:34:30,100 --> 00:34:33,460
And how long does it take before
this sequencer starts actually

669
00:34:33,460 --> 00:34:35,980
generating some sequence?
It's already started.

670
00:34:35,980 --> 00:34:38,220
It's already started? Yeah.
Wonderful!

671
00:34:38,220 --> 00:34:41,300
That's incredible. So we've gone
from the dark green colours here,

672
00:34:41,300 --> 00:34:43,860
with nothing going through the
machine, and now we've got

673
00:34:43,860 --> 00:34:46,700
the light green colour and you can
see numbers here flashing up,

674
00:34:46,700 --> 00:34:49,340
saying that it's sequencing. But
this is going to take a while.

675
00:34:49,340 --> 00:34:51,980
I don't think we can wait for this
to finish. No, so here's one we

676
00:34:51,980 --> 00:34:54,220
made earlier. Yes. So, it takes...

677
00:34:54,220 --> 00:34:56,460
It's very fast, but it still
takes a few hours.

678
00:34:56,460 --> 00:35:00,140
So, we did the DNA sequencing
earlier and we sequenced 2 million

679
00:35:00,140 --> 00:35:03,860
DNA molecules from both
of you put together. Wow!

680
00:35:03,860 --> 00:35:06,580
And, from that, we have numbers
of types of species

681
00:35:06,580 --> 00:35:09,620
that we have there from bacteria
growing in your mouths.

682
00:35:09,620 --> 00:35:12,980
You're twins, obviously,
so you have more in common

683
00:35:12,980 --> 00:35:16,780
than you have apart, so 116 species
of bacteria growing in

684
00:35:16,780 --> 00:35:20,220
your mouth right now that you both
have and you're both sharing,

685
00:35:20,220 --> 00:35:23,060
but, then, Ronnie, you've got 18
species that are unique to you and

686
00:35:23,060 --> 00:35:26,180
your twin brother doesn't have those
species, and, then, Ritchie, you've

687
00:35:26,180 --> 00:35:29,540
got slightly more - you've got 25
species that are unique to you.

688
00:35:29,540 --> 00:35:32,740
So, even though your genomes
are identical and your daily habits

689
00:35:32,740 --> 00:35:35,620
are very, very similar,
you have some bacteria

690
00:35:35,620 --> 00:35:37,700
that make you unique. Yeah.

691
00:35:37,700 --> 00:35:40,380
And, so, these are totally separate
from the genome we've been

692
00:35:40,380 --> 00:35:43,980
talking about until now, so it's not
your genome, it's the genome

693
00:35:43,980 --> 00:35:47,260
of little things living on your skin
and in your mouth. Yeah.

694
00:35:47,260 --> 00:35:51,100
So, if somebody had a pet,
would that influence what's growing?

695
00:35:51,100 --> 00:35:54,340
Yes, so, if you have a pet dog
at home, you are likely to share

696
00:35:54,340 --> 00:35:56,820
many, many bacterial species
between you and your dog,

697
00:35:56,820 --> 00:35:59,620
so, next time you have dogs
in the audience here,

698
00:35:59,620 --> 00:36:02,420
give them a good pat, because
you're picking up friendly bacteria.

699
00:36:02,420 --> 00:36:05,020
So, would somebody be more like
their twin or more like their pet?

700
00:36:05,020 --> 00:36:08,580
That's a good question. Depends on
how much you like your twin brother.
LAUGHTER

701
00:36:08,580 --> 00:36:11,220
OK, well, thank you so much, Arwyn,
and thank you so much, Ronnie

702
00:36:11,220 --> 00:36:12,620
and Ritchie. You can keep those,

703
00:36:12,620 --> 00:36:14,780
and you've been wonderful
volunteers. Thank you.

704
00:36:17,940 --> 00:36:20,020
Aoife, that was incredible.

705
00:36:20,020 --> 00:36:22,980
I mean, I think that, you know,
it's interesting to see how many

706
00:36:22,980 --> 00:36:25,700
different species of bacteria
we've got living in our mouths,

707
00:36:25,700 --> 00:36:29,900
but also the fact that
the sequencing is so quick

708
00:36:29,900 --> 00:36:32,620
and so miniaturised now,
that amazing technology.

709
00:36:32,620 --> 00:36:34,540
It's incredible, yeah.

710
00:36:34,540 --> 00:36:37,980
So, I want to test you a bit now...
Oh, yeah? ..because we've been

711
00:36:37,980 --> 00:36:40,580
talking about various
characteristics

712
00:36:40,580 --> 00:36:42,900
that we can map on to our genetics,

713
00:36:42,900 --> 00:36:45,900
but if you didn't know what somebody
looked like and you didn't know

714
00:36:45,900 --> 00:36:49,900
who somebody was, how much
could you tell about them

715
00:36:49,900 --> 00:36:53,580
if you had their DNA sequence?
Yeah. So, now you're talking about

716
00:36:53,580 --> 00:36:55,780
basically the Holy Grail
of genetics.

717
00:36:55,780 --> 00:36:59,460
Can you take a DNA sequence
and describe the person?

718
00:36:59,460 --> 00:37:03,460
Well, it's quite hard because we've
already talked about examples

719
00:37:03,460 --> 00:37:05,860
where you might have
particular genes,

720
00:37:05,860 --> 00:37:08,620
and it gives you a chance
of being one thing or another,

721
00:37:08,620 --> 00:37:11,940
but it doesn't totally fix
the outcome, and then there's

722
00:37:11,940 --> 00:37:14,180
another side to it is there's lots
of stuff

723
00:37:14,180 --> 00:37:15,820
that we just don't know yet.

724
00:37:15,820 --> 00:37:19,180
There's lots of examples where we
just don't know how exactly

725
00:37:19,180 --> 00:37:22,300
the genes work, but... So, I've got
somebody's DNA results here.

726
00:37:22,300 --> 00:37:26,860
Yes, yes. So, we have a mystery
guest, and, honestly,

727
00:37:26,860 --> 00:37:29,420
I don't know who this guest is,
nor does Alice, but I have been

728
00:37:29,420 --> 00:37:31,180
looking at some of their DNA.

729
00:37:31,180 --> 00:37:34,300
So, this mystery guest
is going to come in, and don't say

730
00:37:34,300 --> 00:37:37,700
anything that might let us guess
who it is, because we have no idea

731
00:37:37,700 --> 00:37:42,420
who this is and we are going to make
some predictions of some

732
00:37:42,420 --> 00:37:45,540
of this person's traits, just based
on the DNA sequence analysis.

733
00:37:45,540 --> 00:37:48,020
So, please come in, mystery guest!

734
00:37:53,500 --> 00:37:55,820
OK, mystery guest, you don't
have to say anything to me,

735
00:37:55,820 --> 00:37:57,780
because I don't even
want to hear your voice,

736
00:37:57,780 --> 00:37:59,500
but thank you very much for coming.

737
00:37:59,500 --> 00:38:04,140
So, the mystery guest
over there has two bells,

738
00:38:04,140 --> 00:38:07,260
and they can use one of them for yes
and one of them for no,

739
00:38:07,260 --> 00:38:10,660
so the first thing that I'm
going to talk about with regards

740
00:38:10,660 --> 00:38:14,580
to this guest is that this person
has two X chromosomes.

741
00:38:14,580 --> 00:38:16,300
These are the sex chromosomes.

742
00:38:16,300 --> 00:38:19,100
So, usually, when somebody
has two X chromosomes

743
00:38:19,100 --> 00:38:21,820
then they're female. It's not 100%
but it's most of the time,

744
00:38:21,820 --> 00:38:25,700
so I'm going to go for that
we have a female guest.

745
00:38:25,700 --> 00:38:27,620
Am I correct?
BELL RINGS

746
00:38:27,620 --> 00:38:31,660
Yes. Ah. OK, one right, OK. You're
doing well, Aoife. Thank you.
THEY LAUGH

747
00:38:31,660 --> 00:38:33,620
Now, let's see.

748
00:38:33,620 --> 00:38:36,260
So, we also know that skin
colour is highly genetic,

749
00:38:36,260 --> 00:38:39,260
but we don't know
all the variants very well,

750
00:38:39,260 --> 00:38:44,300
so, based on the genetic variants,
I'm relatively confident

751
00:38:47,340 --> 00:38:50,820
so, a brown to dark brown.
Am I correct?

752
00:38:50,820 --> 00:38:52,540
BELL RINGS

753
00:38:52,540 --> 00:38:55,260
OK, good! Yes, OK.
I wasn't certain about that one.

754
00:38:55,260 --> 00:38:59,620
Perhaps you might have detached
ear lobes. So we have ear lobes

755
00:38:59,620 --> 00:39:02,660
that can be... My ear lobes are
detached and Alice's are attached.

756
00:39:02,660 --> 00:39:07,420
Mine are attached, yeah. So, do you
have detached ear lobes? Yes?

757
00:39:07,420 --> 00:39:09,860
BELL RINGS
Oh, great.

758
00:39:09,860 --> 00:39:13,420
So, we talked earlier about lactose
tolerance as well, and, so,

759
00:39:13,420 --> 00:39:16,060
this person does not carry
the variant

760
00:39:16,060 --> 00:39:19,020
that we normally see in European
individuals

761
00:39:19,020 --> 00:39:21,140
that allows them to drink milk.

762
00:39:21,140 --> 00:39:24,820
I'll go for that this person
is lactose intolerant.

763
00:39:24,820 --> 00:39:27,660
BELL RINGS
OK. There we go.

764
00:39:27,660 --> 00:39:30,500
So, some people, you know
the herb, coriander?

765
00:39:30,500 --> 00:39:32,220
The green herb, coriander?

766
00:39:32,220 --> 00:39:36,460
So, for me, that tastes really nice,
but for about 13% of people

767
00:39:36,460 --> 00:39:39,700
it tastes like soap, and this person
might be one of them.

768
00:39:39,700 --> 00:39:43,300
I'm not confident, but I'll say
for soapy coriander, yes?

769
00:39:43,300 --> 00:39:46,300
HORN HONKS
Oh, OK. There we go.

770
00:39:46,300 --> 00:39:49,460
Interesting. So, finally, this one
I'm quite confident that

771
00:39:49,460 --> 00:39:52,020
this person has either dark brown
or hazel eyes.

772
00:39:52,020 --> 00:39:54,660
BELL RINGS
OK, all right.

773
00:39:54,660 --> 00:39:57,300
Well, that's as much
as I'm going to do, but...

774
00:39:57,300 --> 00:40:00,340
But what's interesting about this
is you know some of those traits

775
00:40:00,340 --> 00:40:03,580
are better predictors than others,
but it's never going to be 100%.

776
00:40:03,580 --> 00:40:06,940
So, you might be right, sort of,
you know, seven, eight, nine times

777
00:40:06,940 --> 00:40:10,140
out of ten, but there's some people
that you're not going to guess right

778
00:40:10,140 --> 00:40:12,380
by knowing their genetics. No.

779
00:40:12,380 --> 00:40:15,900
OK, I think we just need to end
the suspense and see who actually

780
00:40:15,900 --> 00:40:18,980
is our mystery guest.
Do you think we should reveal it?

781
00:40:18,980 --> 00:40:22,460
I think we should reveal our mystery
guest. Let's see.
ALICE GASPS

782
00:40:22,460 --> 00:40:25,500
Hello! Oh! Ruby! How are you?
APPLAUSE

783
00:40:27,740 --> 00:40:30,820
Thank you very much.
Thank you so much for coming.

784
00:40:34,980 --> 00:40:36,860
Quite a surprise.

785
00:40:36,860 --> 00:40:39,580
Were you impressed that Aoife
managed to guess so much about you?

786
00:40:39,580 --> 00:40:41,460
Yeah, and I felt so bad that I love
coriander.

787
00:40:41,460 --> 00:40:43,140
You love coriander?
I love coriander.

788
00:40:43,140 --> 00:40:45,500
But your genes say that you should
taste the soapy taste.

789
00:40:45,500 --> 00:40:47,500
That's not right, then. Tastes
delicious to me.

790
00:40:47,500 --> 00:40:50,620
So that one didn't work. Oh, that's
amazing. Ruby, Star Baker.

791
00:40:50,620 --> 00:40:53,620
Thank you very much. Aww, thank you
for having me. Thank you.

792
00:41:01,060 --> 00:41:03,060
So, this is fascinating.

793
00:41:03,060 --> 00:41:07,020
We do seem to be able to make some
reasonably good predictions

794
00:41:07,020 --> 00:41:09,420
about people
based on their genetics,

795
00:41:09,420 --> 00:41:11,460
but that was a...
that was a bit of fun.

796
00:41:11,460 --> 00:41:14,180
It was a lot of fun,
and I got a cupcake,

797
00:41:14,180 --> 00:41:17,140
but there is a more serious
side to this, too, because we can

798
00:41:17,140 --> 00:41:21,060
use genetics to predict our risk of

799
00:41:21,060 --> 00:41:25,140
disease, and we need to think
really carefully about how we do

800
00:41:25,140 --> 00:41:28,500
that and whether we want to know
this information. So, to help us

801
00:41:28,500 --> 00:41:30,580
think through some of these issues,

802
00:41:30,580 --> 00:41:34,460
I would like you to welcome my
friend, bioethicist,

803
00:41:34,460 --> 00:41:37,540
Professor Heather Widdows. Heather.

804
00:41:37,540 --> 00:41:39,660
Hello.
APPLAUSE

805
00:41:41,900 --> 00:41:46,540
Now, Heather, first of all,
what is a bioethicist?

806
00:41:46,540 --> 00:41:49,980
Well, my job is to think
not about what we can do,

807
00:41:49,980 --> 00:41:52,660
but about what we should do,
so I think about the implications

808
00:41:52,660 --> 00:41:54,500
for all the stuff you've heard.

809
00:41:54,500 --> 00:41:57,580
And, now that we can predict
risk of some diseases,

810
00:41:57,580 --> 00:42:01,100
some better than others,
what are the advantages to knowing

811
00:42:01,100 --> 00:42:02,940
that kind of information?

812
00:42:02,940 --> 00:42:04,820
Well, some of it is
disease-specific,

813
00:42:04,820 --> 00:42:06,700
so if there's a treatment,
for instance,

814
00:42:06,700 --> 00:42:09,180
then you need to know,
but there are general things

815
00:42:09,180 --> 00:42:11,660
that people think that maybe
you have a right to know,

816
00:42:11,660 --> 00:42:14,580
that you should know, and that will
help you plan your future.

817
00:42:14,580 --> 00:42:16,940
So, that could be things
like lifestyle choices.

818
00:42:16,940 --> 00:42:20,500
So, if you have a disposition, say,
to something like a form of cancer,

819
00:42:20,500 --> 00:42:23,140
then you might want to plan
your life a bit differently.

820
00:42:23,140 --> 00:42:25,740
So, when you're thinking about
things like when you want

821
00:42:25,740 --> 00:42:27,780
to have children,
if you want to have children,

822
00:42:27,780 --> 00:42:30,300
you might want to have children
earlier, you might maybe

823
00:42:30,300 --> 00:42:32,700
want to do your bucket list,
you don't want to wait

824
00:42:32,700 --> 00:42:35,500
until you're retired to go
and, you know, climb Mount Everest.

825
00:42:35,500 --> 00:42:37,740
Yeah, so it can kind
of help with planning. Right.

826
00:42:37,740 --> 00:42:40,820
You could change your lifestyle
and hopefully lessen your risk then.

827
00:42:40,820 --> 00:42:44,260
But what are the negatives when it
comes to knowing your disease risk?

828
00:42:44,260 --> 00:42:46,580
So, just like some people
think you should know,

829
00:42:46,580 --> 00:42:48,940
other people feel very strongly
the other way.

830
00:42:48,940 --> 00:42:51,380
They think that you should
have an open future,

831
00:42:51,380 --> 00:42:54,340
that knowing is going to make
you think that you're ill,

832
00:42:54,340 --> 00:42:57,740
when in fact you're very well still.
So, even though you're not ill,

833
00:42:57,740 --> 00:42:59,740
you might start behaving
as if you are,

834
00:42:59,740 --> 00:43:02,740
and you kind of wish your life away.
So, for very many other people,

835
00:43:02,740 --> 00:43:06,900
they think that, in fact,
we really have a duty or a right not

836
00:43:06,900 --> 00:43:08,620
to know that's important.

837
00:43:08,620 --> 00:43:11,860
So, we'd like to explore
some of these areas

838
00:43:11,860 --> 00:43:15,460
with you, and, at your feet,
you've got voting cards.

839
00:43:15,460 --> 00:43:17,980
So, when we ask you to vote,
what I'd like you to do

840
00:43:17,980 --> 00:43:20,420
is hold up your answer
with the answer facing us.

841
00:43:20,420 --> 00:43:24,180
So we're going to talk about
a number of diseases and see

842
00:43:24,180 --> 00:43:27,180
what you think, see how you feel
about it. Have a good think about

843
00:43:27,180 --> 00:43:30,140
whether you'd really want
to know if you had a higher risk

844
00:43:30,140 --> 00:43:32,540
of developing such a disease.

845
00:43:32,540 --> 00:43:36,860
So, shall we have a think about
early onset Alzheimer's disease?

846
00:43:36,860 --> 00:43:41,860
Yes, so Alzheimer's is one form
of dementia, and usually the tests

847
00:43:42,140 --> 00:43:45,700
will only tell your susceptibility
and risk, and it's more about

848
00:43:45,700 --> 00:43:47,260
a cluster of the gene's environment.

849
00:43:47,260 --> 00:43:49,900
So, this is something
which would cause memory loss,

850
00:43:49,900 --> 00:43:52,700
eventually makes it difficult
for you to be independent

851
00:43:52,700 --> 00:43:54,100
and to look after yourself.

852
00:43:54,100 --> 00:43:56,380
At the moment, there is
no treatment for it,

853
00:43:56,380 --> 00:43:59,420
so, would you like to know
if you had a higher risk

854
00:43:59,420 --> 00:44:01,660
of developing early Alzheimer's?

855
00:44:03,460 --> 00:44:06,460
I think there is a majority
of yeses, actually,

856
00:44:06,460 --> 00:44:09,900
but there's quite a lot of people
who wouldn't like to know.

857
00:44:09,900 --> 00:44:12,260
So, let's think
about another disease.

858
00:44:12,260 --> 00:44:15,900
OK, so the next one we want to think
about it is type 2 diabetes.

859
00:44:15,900 --> 00:44:18,500
So, this is where your body
responds to sugar.

860
00:44:18,500 --> 00:44:20,420
It can affect your eyesight,

861
00:44:20,420 --> 00:44:22,900
and it can gradually
get more severe.

862
00:44:22,900 --> 00:44:27,860
It's a disease where you can manage
it very well by lifestyle changes.

863
00:44:27,860 --> 00:44:31,420
So, obesity is a key factor in
the disease, so, knowing means

864
00:44:31,420 --> 00:44:34,820
that you really can change
your lifestyle to address it.

865
00:44:34,820 --> 00:44:38,300
So, who would like to know
if they had a slightly higher risk

866
00:44:38,300 --> 00:44:41,860
of developing type 2 diabetes?

867
00:44:41,860 --> 00:44:44,220
That's really different. Even more.
Yes.

868
00:44:44,220 --> 00:44:47,780
So, the vast, vast majority
of you are saying yes.

869
00:44:47,780 --> 00:44:50,980
It's important to remember
with these kind of ethics questions,

870
00:44:50,980 --> 00:44:54,060
there is no right or wrong answer,
it's what's right and wrong for you.

871
00:44:54,060 --> 00:44:56,100
So, let's think about one
final disease, then.

872
00:44:56,100 --> 00:44:57,780
Let's think about cancer.

873
00:44:57,780 --> 00:45:00,500
Now, there are lots of
different types of cancer -

874
00:45:00,500 --> 00:45:05,100
some of them are treatable, some of
them are more difficult to treat -

875
00:45:05,100 --> 00:45:10,100
but if you could test for a higher
risk of a particular cancer

876
00:45:11,180 --> 00:45:13,540
where there was a treatment option,

877
00:45:13,540 --> 00:45:15,620
what would you feel about that?

878
00:45:15,620 --> 00:45:18,500
Would you...would you want to know
if you were going to develop

879
00:45:18,500 --> 00:45:20,780
this particular type of cancer?

880
00:45:22,580 --> 00:45:26,980
I think it's about two thirds yes
and about a third no? Yes.

881
00:45:26,980 --> 00:45:28,380
I think that looks...

882
00:45:28,380 --> 00:45:32,260
Now, our roving reporter, Aoife,
is going to come and ask you

883
00:45:32,260 --> 00:45:36,620
some of your opinions about this and
why you voted in various ways.

884
00:45:36,620 --> 00:45:38,860
Is there anybody who'd like to tell
me what they voted

885
00:45:38,860 --> 00:45:41,340
and why they voted? So, I'll come
around to you. Oh, sorry.

886
00:45:41,340 --> 00:45:43,620
I'll fall on the stairs as well.
What way did you vote

887
00:45:43,620 --> 00:45:46,660
on the Alzheimer's one, and...?
I voted no.

888
00:45:46,660 --> 00:45:48,780
And why did you vote no?

889
00:45:48,780 --> 00:45:52,380
I think you shouldn't
live knowing, like, in fear.

890
00:45:52,380 --> 00:45:55,180
You should, like, make your own
choices. Yeah, very interesting.

891
00:45:55,180 --> 00:45:58,100
Anybody else who wants to tell me
about one of their answers? Yeah?

892
00:45:58,100 --> 00:46:01,220
But what, which one...?
I voted yes on Alzheimer's.

893
00:46:01,220 --> 00:46:04,980
Yes? Because I think it would be
nice to warn your family... OK,

894
00:46:04,980 --> 00:46:07,420
very interesting. ..and, like,
share things.

895
00:46:07,420 --> 00:46:10,260
Yeah, yeah. Let's see if there's
somebody up here.

896
00:46:10,260 --> 00:46:13,180
You voted no. OK, do you want to
tell us, what did you vote no to

897
00:46:13,180 --> 00:46:18,180
and why? I voted no to the first
one because... Alzheimer's? Yes,

898
00:46:18,180 --> 00:46:22,420
because I didn't want to know,
because then it would make me feel

899
00:46:22,420 --> 00:46:26,620
scared, and then I won't enjoy my
life as much as I would have.

900
00:46:26,620 --> 00:46:29,340
Very... I mean, it's very
sophisticated opinions coming from

901
00:46:29,340 --> 00:46:32,460
our audience here, so give
yourselves a round of applause.

902
00:46:36,860 --> 00:46:39,660
Thank you very much for doing that
with us. There was some

903
00:46:39,660 --> 00:46:42,780
really, really thoughtful answers
there, I thought, Heather.

904
00:46:42,780 --> 00:46:45,380
Absolutely. Lots of the answers
you came up with are exactly

905
00:46:45,380 --> 00:46:48,220
the answers that ethicists
talk about, so...

906
00:46:48,220 --> 00:46:51,300
One really interesting
thing, of course, about DNA

907
00:46:51,300 --> 00:46:54,940
is that it connects us
with other people.

908
00:46:54,940 --> 00:46:57,340
So, this is something
you've thought about long

909
00:46:57,340 --> 00:47:00,900
and hard, Heather, that, in fact,
when you have your DNA sequenced,

910
00:47:00,900 --> 00:47:03,460
it's not just your genes
that you're looking at.

911
00:47:03,460 --> 00:47:07,820
Yeah, absolutely. The two key things
that make genetic information

912
00:47:07,820 --> 00:47:11,860
so different are that it's shared
and it is identifying,

913
00:47:11,860 --> 00:47:14,420
so, it's shared with other
members of your family,

914
00:47:14,420 --> 00:47:16,860
and we don't really know
how to balance that.

915
00:47:16,860 --> 00:47:20,180
So, if we think about something
like, you know, testing for

916
00:47:20,180 --> 00:47:22,340
the indicators for breast cancer,

917
00:47:22,340 --> 00:47:27,340
if you're 15 and you want
to be tested, and your mother is 35,

918
00:47:27,660 --> 00:47:30,460
40, and doesn't want to know,
and you know that there's

919
00:47:30,460 --> 00:47:33,900
kind of cancer in the family, if you
go and get tested and turn out to be

920
00:47:33,900 --> 00:47:37,180
positive, then you will have
information about your mother

921
00:47:37,180 --> 00:47:39,660
that she does not want,
and we need to think about

922
00:47:39,660 --> 00:47:41,380
how we ethically manage that.

923
00:47:41,380 --> 00:47:44,620
It feels like we're only
just catching up with the ethics

924
00:47:44,620 --> 00:47:46,540
of this whole area of biology.

925
00:47:46,540 --> 00:47:49,780
It feels like we're not
really kind of grasping how to deal

926
00:47:49,780 --> 00:47:52,500
with that information quite yet.
Yeah, no, I don't think we are

927
00:47:52,500 --> 00:47:55,100
at all. I think that's exactly
right. You know, the science has

928
00:47:55,100 --> 00:47:58,020
moved on quite dramatically.
This is all about unknowns

929
00:47:58,020 --> 00:48:00,500
in the future. Who will want
your information?

930
00:48:00,500 --> 00:48:02,940
Will it change what you can
do, employment wise?

931
00:48:02,940 --> 00:48:04,940
Will insurers want it?

932
00:48:04,940 --> 00:48:08,820
And, of course, there is one
particular area when a genetic test

933
00:48:08,820 --> 00:48:12,020
is carried out, it's actually not
on your own DNA but very much

934
00:48:12,020 --> 00:48:16,340
on the DNA of another individual,
and that's when we test babies

935
00:48:16,340 --> 00:48:20,580
in the womb when we do antenatal
testing, and we're able to test

936
00:48:20,580 --> 00:48:23,620
for more and more things now,
but, again, some really difficult

937
00:48:23,620 --> 00:48:26,740
decision-making when parents
are presented with results.

938
00:48:26,740 --> 00:48:30,380
Absolutely. So, you know, perhaps
the one that's most well-known is

939
00:48:30,380 --> 00:48:33,380
the test for Down syndrome.
That happens very routinely,

940
00:48:33,380 --> 00:48:37,260
so, that means that nearly every
pregnant woman in the UK will have

941
00:48:37,260 --> 00:48:40,140
that test and they will be offered
it routinely, and they may

942
00:48:40,140 --> 00:48:42,940
just think, "Oh, well, this is just
part of getting ready

943
00:48:42,940 --> 00:48:45,820
"to have the baby," and what they
may not realise is that,

944
00:48:45,820 --> 00:48:48,900
once that result comes back,
if that's a positive result,

945
00:48:48,900 --> 00:48:51,300
then the only thing to do is
either continue,

946
00:48:51,300 --> 00:48:55,420
so the test can help you prepare,
or you can end the pregnancy.

947
00:48:55,420 --> 00:48:58,820
And that may be something that they
hadn't quite realised was happening.

948
00:48:58,820 --> 00:49:00,660
So, very difficult decisions.

949
00:49:00,660 --> 00:49:03,300
I want to introduce you
to somebody who did

950
00:49:03,300 --> 00:49:06,820
have an antenatal test
for Down syndrome, and her daughter,

951
00:49:06,820 --> 00:49:10,140
so, please will you welcome
Donna and Frankie.

952
00:49:10,140 --> 00:49:11,780
APPLAUSE

953
00:49:17,940 --> 00:49:20,380
Oh, she gave us a lovely wave.

954
00:49:20,380 --> 00:49:22,540
She's excited to be here.

955
00:49:22,540 --> 00:49:26,300
So, Donna, you had an antenatal
test, so you knew that Frankie

956
00:49:26,300 --> 00:49:28,780
was going to be born
with Down syndrome.

957
00:49:28,780 --> 00:49:32,740
We had a blood test and she came
back as a high chance

958
00:49:32,740 --> 00:49:34,180
of having Down syndrome.

959
00:49:34,180 --> 00:49:36,900
We didn't know until she was born
that she had Down syndrome,

960
00:49:36,900 --> 00:49:39,380
but we knew there was
a high chance of it.

961
00:49:39,380 --> 00:49:42,060
Yeah. And did it...did it
help you prepare?

962
00:49:42,060 --> 00:49:43,940
Yeah, definitely.

963
00:49:43,940 --> 00:49:46,780
I mean, I think I went
through my pregnancy, in my head,

964
00:49:46,780 --> 00:49:49,300
thinking, "Baby has Down syndrome."

965
00:49:49,300 --> 00:49:52,940
It wasn't anything that
was negative for me.

966
00:49:52,940 --> 00:49:57,340
I was quite happy and quite excited
about my first baby. Yeah.

967
00:49:57,340 --> 00:50:00,660
It didn't matter how she came out
- she was Frankie.

968
00:50:00,660 --> 00:50:03,260
Yeah. Aren't you?

969
00:50:03,260 --> 00:50:06,700
And she's...and she's different,
but she's lovely.

970
00:50:06,700 --> 00:50:09,300
She's yeah, you know,
no child is the same.

971
00:50:09,300 --> 00:50:12,860
She is so unique in so many ways...
Yeah. ..but I wouldn't change

972
00:50:12,860 --> 00:50:15,180
a thing about her. She's perfect.

973
00:50:15,180 --> 00:50:18,020
Yeah, and we're all unique. Exactly.

974
00:50:18,020 --> 00:50:21,500
Thank you very much.
Donna, Frankie and Heather.

975
00:50:21,500 --> 00:50:23,340
APPLAUSE

976
00:50:30,380 --> 00:50:32,140
So, Aoife, we've been looking at

977
00:50:32,140 --> 00:50:35,220
what we can do
with this new technology.

978
00:50:35,220 --> 00:50:38,980
It is new, and it's getting faster
and faster and cheaper and cheaper

979
00:50:38,980 --> 00:50:41,860
and we can read DNA and
we can make some predictions

980
00:50:41,860 --> 00:50:43,900
about what we're going to be.

981
00:50:43,900 --> 00:50:47,500
But we can actually
change DNA now as well. Yeah.

982
00:50:47,500 --> 00:50:50,060
And we have a really
wonderful example of this,

983
00:50:50,060 --> 00:50:53,900
so, if you could please welcome a
leader in this field of gene therapy

984
00:50:53,900 --> 00:50:56,820
from Great Ormond Street Hospital,
Professor Bobby Gaspar.

985
00:50:56,820 --> 00:50:59,420
APPLAUSE

986
00:50:59,420 --> 00:51:02,020
Thank you so much for coming here.
Please sit down.

987
00:51:04,100 --> 00:51:06,260
So, you've been working
in the area of gene therapy,

988
00:51:06,260 --> 00:51:09,580
so, being able to change genes
to help patients

989
00:51:09,580 --> 00:51:12,260
for quite a number of years now.

990
00:51:12,260 --> 00:51:14,540
Yes, well, I actually started
right at the beginning

991
00:51:14,540 --> 00:51:17,180
when I was a junior doctor
at Great Ormond Street Hospital,

992
00:51:17,180 --> 00:51:19,820
about 25 years ago. Wow.

993
00:51:19,820 --> 00:51:23,940
And, really, what we're trying to do
is, in some diseases,

994
00:51:23,940 --> 00:51:27,740
it comes about because
a gene is defective or missing.

995
00:51:27,740 --> 00:51:30,380
And what we want to try and do is
put a working copy of the gene

996
00:51:30,380 --> 00:51:33,660
back into those cells,
so they now have the correct gene,

997
00:51:33,660 --> 00:51:35,460
the gene works,
it makes the right signals

998
00:51:35,460 --> 00:51:37,900
to be able to correct that disease.

999
00:51:37,900 --> 00:51:40,380
So, it's a very fundamental way
of correcting diseases.

1000
00:51:40,380 --> 00:51:42,820
So, you're really getting
to the root cause.

1001
00:51:42,820 --> 00:51:45,420
And you helped
the first-ever patient

1002
00:51:45,420 --> 00:51:48,100
to be helped with a gene therapy.
The first worldwide.

1003
00:51:48,100 --> 00:51:51,820
And he's the first successfully
treated child by gene therapy

1004
00:51:51,820 --> 00:51:54,140
in our team at University College,

1005
00:51:54,140 --> 00:51:57,540
and Great Ormond Street helped
treat him back in 2001.

1006
00:51:57,540 --> 00:51:59,540
And he's here this evening to come
and show off

1007
00:51:59,540 --> 00:52:02,460
how strong and healthy is.
Please welcome Rhys.

1008
00:52:02,460 --> 00:52:05,140
APPLAUSE

1009
00:52:06,740 --> 00:52:09,980
Hello, Rhys. I must say,
you are looking very healthy.

1010
00:52:09,980 --> 00:52:15,020
We have a picture of you from about
one-year-old, I think, up there.

1011
00:52:15,100 --> 00:52:18,300
What you can just about see there
is a plastic bubble around Rhys.

1012
00:52:18,300 --> 00:52:20,900
So, you spent a lot of time
in that bubble.

1013
00:52:20,900 --> 00:52:23,340
When I was born, I had to be
put into this bubble

1014
00:52:23,340 --> 00:52:26,620
because I wasn't born
with an immune system

1015
00:52:26,620 --> 00:52:30,500
and, so, any sort of bacteria
or viruses in the atmosphere

1016
00:52:30,500 --> 00:52:33,020
that I would inhale or breathe in,

1017
00:52:33,020 --> 00:52:38,060
it would then harm me because my
system wasn't very strong at all.

1018
00:52:38,060 --> 00:52:42,860
And Professor Bobby Gaspar
was your doctor? Yes.

1019
00:52:42,860 --> 00:52:44,460
So, what did you do for Rhys?

1020
00:52:44,460 --> 00:52:47,300
Well, Rhys, as he says, there was
a single gene that was missing

1021
00:52:47,300 --> 00:52:49,300
in his bone marrow,
not working properly.

1022
00:52:49,300 --> 00:52:50,980
He couldn't make immune cells.

1023
00:52:50,980 --> 00:52:54,500
And, so, my colleague and myself,
we were working on a new way

1024
00:52:54,500 --> 00:52:57,540
of treating this condition
through gene therapy

1025
00:52:57,540 --> 00:53:00,260
and that meant taking
Rhys' own cells.

1026
00:53:00,260 --> 00:53:02,580
So, he went to the operating theatre

1027
00:53:02,580 --> 00:53:05,220
and we took out your
bone marrow stem cell

1028
00:53:05,220 --> 00:53:07,900
and we put, in the lab, we put
a working copy of that gene,

1029
00:53:07,900 --> 00:53:10,860
the gene that was missing,
we put the working copy of that

1030
00:53:10,860 --> 00:53:12,780
back into his bone marrow cells

1031
00:53:12,780 --> 00:53:16,460
and then gave those
gene-modified cells back to Rhys.

1032
00:53:16,460 --> 00:53:19,900
And, then, over a few months,
his immune system started to grow

1033
00:53:19,900 --> 00:53:23,740
and this was the first time
we'd seen it in any child in the UK.

1034
00:53:23,740 --> 00:53:25,580
And, then, after about six months,

1035
00:53:25,580 --> 00:53:28,420
it was growing
and working really well.

1036
00:53:28,420 --> 00:53:31,460
So, we were really, really delighted
how well it worked.

1037
00:53:31,460 --> 00:53:34,660
Wow. And, so, Rhys, this has
totally changed your life. Yep.

1038
00:53:34,660 --> 00:53:37,420
No, I don't think I'd be alive,
honestly.

1039
00:53:37,420 --> 00:53:40,220
It's such a wonderful example
of how genetics

1040
00:53:40,220 --> 00:53:44,220
can transform medicine
and we can have these new therapies.

1041
00:53:44,220 --> 00:53:46,540
Now that we're able to identify
all of these different genes

1042
00:53:46,540 --> 00:53:48,300
that cause diseases,

1043
00:53:48,300 --> 00:53:51,180
now we'll see genetic treatments
for eye diseases,

1044
00:53:51,180 --> 00:53:54,620
certain leukaemias can be treated
by genetic therapies

1045
00:53:54,620 --> 00:53:56,780
and there'll be other conditions
as well

1046
00:53:56,780 --> 00:53:58,660
that will be treated by
gene therapy.

1047
00:53:58,660 --> 00:53:59,980
It's such a positive story.

1048
00:53:59,980 --> 00:54:02,660
So, thank you so much, Rhys and
Bobby, for coming in and telling us.

1049
00:54:02,660 --> 00:54:03,700
Thank you. Thank you.

1050
00:54:03,700 --> 00:54:05,660
APPLAUSE

1051
00:54:10,100 --> 00:54:12,540
Rhys' story was just amazing.

1052
00:54:12,540 --> 00:54:15,260
And this does feel like
a new frontier in medicine,

1053
00:54:15,260 --> 00:54:18,140
being able to fix faulty genes.

1054
00:54:18,140 --> 00:54:21,020
And I wonder how far we go with this

1055
00:54:21,020 --> 00:54:24,620
because fixing disease seems
like a very positive thing to do,

1056
00:54:24,620 --> 00:54:26,900
but you could make other changes.

1057
00:54:26,900 --> 00:54:29,980
I mean, parents could be choosing,
I don't know,

1058
00:54:29,980 --> 00:54:33,420
eye colour, skin colour
of their babies

1059
00:54:33,420 --> 00:54:36,140
and that, I think,
is a very, very different issue.

1060
00:54:36,140 --> 00:54:38,580
Definitely.
I have a personal view on that

1061
00:54:38,580 --> 00:54:41,020
and that is that
it shouldn't be done.

1062
00:54:41,020 --> 00:54:43,460
I don't think it's a suitable use
of the technology

1063
00:54:43,460 --> 00:54:45,580
and it's something
that should be avoided.

1064
00:54:45,580 --> 00:54:48,060
And this science and this technology
is moving really fast,

1065
00:54:48,060 --> 00:54:51,140
so, all of you will have to think
about this really carefully

1066
00:54:51,140 --> 00:54:53,220
over the course of your lives.

1067
00:54:53,220 --> 00:54:54,660
Science is fantastic.

1068
00:54:54,660 --> 00:54:59,180
It tells us so much about the world
around us and about ourselves,

1069
00:54:59,180 --> 00:55:02,020
and it provides us with
amazing technological tools.

1070
00:55:02,020 --> 00:55:05,380
But we have to work out
how we're going to use those tools

1071
00:55:05,380 --> 00:55:08,380
and that's not just a question
for scientists and ethicists,

1072
00:55:08,380 --> 00:55:10,900
it is a question for everybody

1073
00:55:10,900 --> 00:55:14,100
because this science and this
technology belongs to all of us.

1074
00:55:14,100 --> 00:55:17,060
Yeah. And just because
we can do something

1075
00:55:17,060 --> 00:55:18,740
doesn't mean that we should.

1076
00:55:18,740 --> 00:55:21,340
But one thing that we do see
in all of this is that

1077
00:55:21,340 --> 00:55:24,660
each of us is a total one-off,
even the twins.

1078
00:55:24,660 --> 00:55:28,620
We're a unique parcel of
talents, strengths,

1079
00:55:28,620 --> 00:55:30,620
weaknesses, foibles and chance.

1080
00:55:30,620 --> 00:55:35,660
We started out wondering
who we were, what makes us unique,

1081
00:55:36,260 --> 00:55:39,020
what makes you, you,

1082
00:55:39,020 --> 00:55:41,020
and we found an answer to that.

1083
00:55:41,020 --> 00:55:42,860
That it's your past,

1084
00:55:42,860 --> 00:55:46,620
it's all your ancestors who passed
down their genes to you.

1085
00:55:46,620 --> 00:55:49,380
But it's also your own past,
what happened to you in the womb

1086
00:55:49,380 --> 00:55:51,820
and what's happened to you since
you've been born,

1087
00:55:51,820 --> 00:55:54,380
combined with a lot of chance
as well,

1088
00:55:54,380 --> 00:55:58,460
makes each one of you
a unique individual.

1089
00:55:58,460 --> 00:56:02,740
And there is no such thing
as a perfect human,

1090
00:56:02,740 --> 00:56:05,180
there is no normal human.

1091
00:56:05,180 --> 00:56:08,660
Humanity is all of us.

1092
00:56:08,660 --> 00:56:10,500
Each one of you is different

1093
00:56:10,500 --> 00:56:13,700
and each one of you has
something special to give.

1094
00:56:13,700 --> 00:56:16,220
Now, to finish off,

1095
00:56:16,220 --> 00:56:19,060
we have been working with people
from all over the country,

1096
00:56:19,060 --> 00:56:21,220
from lots and lots of
different schools,

1097
00:56:21,220 --> 00:56:22,780
and we've got a special treat.

1098
00:56:22,780 --> 00:56:24,500
This is the B Positive Choir

1099
00:56:24,500 --> 00:56:27,140
who want you all to stand up

1100
00:56:27,140 --> 00:56:29,700
and join in, as we finish
the Christmas lectures

1101
00:56:29,700 --> 00:56:34,620
with a celebration of
difference and diversity.

1102
00:56:37,100 --> 00:56:40,220
PIANO INTRODUCTION

1103
00:56:42,620 --> 00:56:47,620
# I'm not a stranger to the dark

1104
00:56:47,620 --> 00:56:49,780
# Hide away, they say

1105
00:56:49,780 --> 00:56:53,380
# Cos we don't want
your broken parts

1106
00:56:53,380 --> 00:56:56,500
# But I won't let them
break me down to dust

1107
00:56:56,500 --> 00:57:00,180
# I know that there's a place for us

1108
00:57:00,180 --> 00:57:05,220
# For we are glorious

1109
00:57:06,940 --> 00:57:08,980
# When the sharpest words
wanna cut me down

1110
00:57:08,980 --> 00:57:11,660
# Cut me down

1111
00:57:11,660 --> 00:57:14,500
# I'm gonna send a flood,
gonna drown them out

1112
00:57:14,500 --> 00:57:16,740
# Drown them out

1113
00:57:16,740 --> 00:57:21,740
# I am brave, I am bruised
I am who I'm meant to be

1114
00:57:21,740 --> 00:57:24,940
# This is me
Look out, cos here I come

1115
00:57:24,940 --> 00:57:27,060
# Here I come

1116
00:57:27,060 --> 00:57:29,620
# And I'm marching on
to the beat I drum

1117
00:57:29,620 --> 00:57:31,460
# The beat I drum

1118
00:57:31,460 --> 00:57:36,460
# I'm not scared to be seen
I make no apologies

1119
00:57:37,820 --> 00:57:45,820
# Oh-oh-oh-oh
Oh-oh-oh-oh

1120
00:57:45,820 --> 00:57:48,580
# Oh-oh-oh!
# Oh-oh-oh!

1121
00:57:48,580 --> 00:57:51,580
# Oh-oh-oh, oh, oh

1122
00:57:51,580 --> 00:57:54,620
# We are bursting
through the barricades

1123
00:57:54,620 --> 00:57:56,620
# Reaching for the sun

1124
00:57:56,620 --> 00:57:58,580
# We are warriors

1125
00:57:58,580 --> 00:58:02,140
# Yes, that's what we've become
That's what we've become

1126
00:58:02,140 --> 00:58:04,940
# I won't let them break me down
to dust

1127
00:58:04,940 --> 00:58:08,260
# I know that there's a place for us

1128
00:58:08,260 --> 00:58:11,820
# For we are glorious

1129
00:58:11,820 --> 00:58:15,180
# When the sharpest words
wanna cut me down

1130
00:58:16,780 --> 00:58:21,220
# I'm gonna send a flood,
gonna drown them out

1131
00:58:21,220 --> 00:58:23,700
# This is brave, this is bruised

1132
00:58:23,700 --> 00:58:28,380
# I am who I'm meant to be
This is me

1133
00:58:28,380 --> 00:58:32,940
# Look out cos here I come

1134
00:58:32,940 --> 00:58:36,100
# And I'm marching on
to the beat I drum

1135
00:58:36,100 --> 00:58:38,220
# Marching on to the beat I drum

1136
00:58:38,220 --> 00:58:42,500
# I'm not scared to be seen
I make no apologies

1137
00:58:42,500 --> 00:58:44,340
# This is me! #

1138
00:58:45,260 --> 00:58:48,300
APPLAUSE AND CHEERING