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♪
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NARRATOR:
A family secret exposed.
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DANI SHAPIRO:
If my father wasn't
my biological father, who was?
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{\an1}Something very, very important
was kept from me.
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NARRATOR:
A hidden legacy...
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revealed.
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TYQUINE GOLDEN:
Somewhere in slavery that 20%
might've been integrated
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with our DNA,
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{\an1}and that might not have been
voluntary.
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NARRATOR:
A life-threatening illness...
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prevented.
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JESSICA ALGAZI:
They quite possibly
saved my life.
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NARRATOR:
And a decades-old murder
finally solved.
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CHELSEA RUSTAD:
Without my DNA,
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{\an1}it would have been dead
in the water.
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NARRATOR:
Just a few of the millions
of stories
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{\an1}launched by one of
the most popular
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{\an1}and promising new technologies...
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{\an1}consumer DNA testing.
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{\an1}With a swab, or a bit of spit,
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{\an1}some 30 million of us
have turned over
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{\an1}our most personal information
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{\an1}hoping to discover
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{\an1}what's hidden inside us.
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{\an1}But what do the tests
really deliver?
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{\an1}Spain, Portugal...
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{\an1}Norway?!
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NARRATOR:
How good is the science?
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{\an1}And how are the tests
changing our lives?
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JUNE SMITH:
I just couldn't believe it.
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{\an1}I was on the phone
with my older sister.
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NARRATOR:
In search of clues...
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{\an1}"The Secrets in Our DNA,"
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{\an1}right now, on "NOVA"!
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♪
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♪
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NARRATOR:
It's a promise
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{\an1}many of us just can't resist.
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{\an7}Send in your DNA and unlock
secrets about family...
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{\an8}...ancestry...
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{\an1}...and even health.
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{\an7}It's rare that something
comes along that is truly new.
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{\an7}And this is something
that's truly new.
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NARRATOR:
But just how reliable
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{\an1}are consumer DNA tests,
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{\an1}and their scientific-looking
ancestry percentages?
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♪
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{\an1}Should we worry about
our privacy?
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{\an1}What are the unforeseen
consequences when we reveal
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{\an1}the "Secrets in Our DNA"?
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♪
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{\an8}In the suburbs
of Olympia, Washington,
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{\an1}one woman finds out
just how unpredictable
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{\an1}those consequences can be.
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Chelsea Rustad, who
works as an I.T. specialist,
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is an avid family historian.
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In 2015,
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she takes a test
with the biggest
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{\an1}of the direct-to-consumer
companies... AncestryDNA.
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RUSTAD:
People end up
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{\an1}doing it oftentimes because,
"I just wanna learn
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{\an1}about my ancestral background."
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{\an1}But then something else pops up
that they really
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{\an7}were not expecting at all,
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{\an7}and that's exactly what this was
for me.
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NARRATOR:
The test results
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{\an1}suggest that Chelsea is mostly
of Norwegian
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{\an1}and German ancestry.
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{\an1}Then, because she's also curious
to find new relatives,
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{\an1}she downloads her raw file
from Ancestry,
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{\an1}and uploads it to a free website
called GEDmatch.
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{\an1}It's a place where anyone
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{\an1}can search for matches no matter
what company they tested with.
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{\an1}GEDmatch shows Chelsea
everyone else on the site
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{\an1}who shares DNA with her.
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RUSTAD:
It's kind of humbling
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{\an1}and interesting to see
those interconnections,
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{\an1}to realize the sheer number
of people that we share
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{\an1}some percentage of DNA with
and don't even realize it.
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NARRATOR:
On GEDmatch, Chelsea sees
an aunt whom she knows,
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{\an1}but no new close relatives.
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(clicks)
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She logs off, and doesn't check
the site again.
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{\an1}(birds twittering)
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{\an1}Three years go by.
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{\an1}And then, on the evening
of May 17, 2018,
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{\an1}Chelsea gets some unexpected
visitors.
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RUSTAD:
I look through the peephole
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and see that there are two cops
waiting outside there.
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{\an1}And when I opened the door,
they introduced themselves
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{\an1}as investigators who are looking
into a homicide
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{\an1}that was a cold case
from 31 years ago.
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NARRATOR:
They've come to her door
as a result of that DNA file
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{\an1}she posted on GEDmatch.
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{\an1}To her amazement,
they tell her that her DNA
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{\an1}has led them to a suspect.
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♪
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{\an1}It was just really a lotto
take in and really shocking.
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{\an1}Every step of what
they explained to me
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{\an1}is a horror story.
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♪
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{\an1}(leaves and branches rustling)
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NARRATOR:
Chelsea's hopeful search
for relatives
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{\an1}has taken a dark turn...
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{\an1}into the hunt for a killer.
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{\an1}Someone she's related to.
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{\an1}Though her story is unusual,
it shows that
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{\an1}consumer DNA companies
can fulfill
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{\an1}one of their biggest promises
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extremely well: connecting
us to our relatives.
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♪
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{\an1}Direct-to-consumer,
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{\an1}or DTC DNA testing,
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{\an1}is a billion-dollar business
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{\an1}made possible by the simple
rules of heredity.
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CECE MOORE:
We inherit our DNA
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{\an1}from both of our parents.
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{\an1}50% from mom, 50% from dad.
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{\an7}And they inherit it
from their parents.
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{\an7}And their parents, of course,
inherited it from their parents.
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NARRATOR:
Our parents each contribute
about 50% to our DNA.
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{\an1}And the same is true for them
and their parents.
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{\an1}So the amount of DNA we inherit
from any ancestor
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{\an1}drops by half with each
preceding generation.
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{\an1}We also share DNA with anyone
who shares a common ancestor
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{\an1}with us: siblings,
half-siblings, first cousins,
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{\an1}second cousins and so on.
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♪
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The way that the DTCs determine
those relationships
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{\an1}is by comparing people's DNA.
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{\an1}The amount that is shared
is measured in a unit
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{\an1}called centimorgans.
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{\an1}The more centimorgans
two people share,
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{\an1}the closer they are related.
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{\an1}And the fewer centimorgans
they share,
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{\an1}the more distantly related
they are.
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NARRATOR:
But with the DTCs,
a relationship to someone
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{\an1}can't always be determined
just by counting centimorgans.
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{\an1}Because the numbers fall
within ranges.
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{\an1}You might share the same number
with a cousin,
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{\an1}and a great-uncle, for example.
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{\an1}Just because you have an amount
of shared DNA doesn't mean
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{\an7}you actually know for sure what
that person's relationship is,
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{\an1}it's just a probability...
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{\an1}a spectrum of possible
relationships.
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NARRATOR: June Smith lives in New Jersey,
not far from Philadelphia.
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In 2018,
she takes a consumer DNA test,
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hoping to solve
a longstanding mystery.
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She's spent years searching for
her roots.
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00:08:08,971 --> 00:08:11,638
{\an1}When June was 16,
growing up in Philadelphia,
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{\an1}the woman she knew as her mother
revealed a secret.
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{\an7}She said, "Your mother
was a white woman,"
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{\an7}and I said, "A white woman?"
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{\an7}which was totally shocking
to me.
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{\an1}Her biological mother's name
was Ann D'Amico.
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{\an1}June has never learned
the identity of her father.
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{\an1}When June takes her test
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{\an1}with AncestryDNA,
she checks the box
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{\an1}asking to be linked
to any customers with whom
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she shares DNA.
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{\an1}Though she knows Ann has died,
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{\an1}there's someone else
she desperately wants to find.
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{\an1}While digging into Ann's
life story, June learned that
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{\an1}she'd given birth
to another biracial daughter,
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{\an1}who had a different father.
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{\an1}A girl named Joan Moser,
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{\an1}June's older half-sister.
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{\an1}I set out to search for her.
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{\an1}And I would go on websites,
I would do
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{\an1}all kind of people searches
looking for Joan Moser.
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{\an1}But we could never come up
with her.
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NARRATOR: One day, June receives a message
on her Ancestry page,
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{\an1}telling her she has a new match
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{\an1}with a close relative...
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{\an1}a woman named Sigrid Gilchrist.
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{\an1}She'd also grown up
in Philadelphia,
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{\an1}the only child of a Black couple
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{\an1}active in the civil rights
movement.
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{\an1}But at 16, Sigrid learned
a long-hidden truth
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from her mother.
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{\an7}She told me I was adopted.
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{\an7}That my mother was Italian
and my father was Black.
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It was crushing.
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I had no idea.
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NARRATOR:
In the years that followed,
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{\an1}Sigrid never connected
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with any of her
biological relatives.
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{\an1}Until, by pure chance,
right around the time
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{\an1}that June tests with Ancestry,
Sigrid does too.
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{\an1}Ancestry reports that
the two women,
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{\an1}who share 1,641 centimorgans,
may be first cousins.
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{\an1}But June can't help wondering:
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{\an1}might Sigrid be someone
even closer?
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{\an1}The two women agree
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{\an1}to talk on the phone.
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{\an1}She said, "I have three
questions to ask you."
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I said, "Okay."
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{\an1}I said, "Were you adopted?"
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{\an1}She said, "I was."
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{\an1}I said, "Are you biracial?"
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{\an1}She said, "I am."
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{\an1}I said, "Would your birth mothername
happen to be Ann D'Amico?"
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{\an1}I said, "Yes, that was her name,
my biological mother."
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{\an1}She said, "Are you Joan Moser?"
205
00:11:00,771 --> 00:11:04,305
{\an1}And then I said, "That was the
name on my birth certificate."
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00:11:04,338 --> 00:11:07,771
{\an1}I said, "Oh my God,
you're my sister.
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00:11:07,805 --> 00:11:09,838
{\an1}You're not my cousin."
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00:11:09,871 --> 00:11:12,371
{\an1}We cried and I just couldn't
believe it.
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00:11:12,405 --> 00:11:15,738
{\an1}I was on the phone
with my older sister.
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00:11:18,671 --> 00:11:20,571
Yes.
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JOHNSON:
It was just like we've known
each other forever.
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{\an1}One-on-one spirit feeling
that you can't describe.
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00:11:29,871 --> 00:11:33,038
♪
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00:11:33,071 --> 00:11:35,105
SMITH:
Finding my sister gave me
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00:11:35,138 --> 00:11:38,638
{\an1}a sense of belonging.
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{\an1}It gave me a sense of saying,
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"Hey, you know,
we got the same blood."
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But I do see...
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Looks like me... you.
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00:11:47,405 --> 00:11:48,671
Yes.
Mm-hmm.
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00:11:48,705 --> 00:11:50,838
Look at the chin.Yeah. I can tell.
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It's good havingan older sister.
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00:11:53,938 --> 00:11:56,405
I don't like being older,
but it's okay.
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00:11:56,438 --> 00:12:01,605
(laughing):
I love having
a younger sister.
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00:12:01,638 --> 00:12:02,971
She understands.
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00:12:03,005 --> 00:12:04,471
Yeah, yeah.
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00:12:04,505 --> 00:12:07,105
♪
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00:12:07,138 --> 00:12:09,171
NARRATOR:
People like Sigrid and June
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{\an1}can be connected by the DTCs
230
00:12:11,805 --> 00:12:16,771
{\an1}thanks to an amazing
recent discovery about DNA.
231
00:12:16,805 --> 00:12:21,105
{\an1}We've known for a long time
that the DNA molecule,
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00:12:21,138 --> 00:12:24,705
{\an1}which we carry in almost
every cell in our body,
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00:12:24,738 --> 00:12:29,205
{\an1}contains the code that directs
our lives.
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00:12:29,238 --> 00:12:34,771
{\an1}The code is carried in chemical
building blocks called bases.
235
00:12:34,805 --> 00:12:38,171
{\an1}Known as A, C, G and T,
236
00:12:38,205 --> 00:12:41,671
{\an1}they form pairs to create
the familiar ladder-like
237
00:12:41,705 --> 00:12:44,438
{\an1}structure of DNA.
238
00:12:44,471 --> 00:12:47,938
{\an1}It takes a whopping three
billion of those base pairs
239
00:12:47,971 --> 00:12:51,771
{\an1}to make up our complete genome.
240
00:12:51,805 --> 00:12:53,571
But since 2003,
241
00:12:53,605 --> 00:12:57,338
{\an1}when scientists first readthrough
all of those base pairs,
242
00:12:57,371 --> 00:13:00,338
{\an1}they've discovered
a surprising fact
243
00:13:00,371 --> 00:13:03,271
{\an1}about more than 99% of them.
244
00:13:03,305 --> 00:13:05,471
If you look at any two people,
245
00:13:05,505 --> 00:13:10,271
the vast, vast majority of their
DNA is exactly the same.
246
00:13:10,305 --> 00:13:13,905
{\an1}Because all of the things
that keep you alive,
247
00:13:13,938 --> 00:13:16,238
{\an1}I mean, all of that has to be
the same, it can't change.
248
00:13:16,271 --> 00:13:17,838
{\an1}Otherwise it doesn't work.
249
00:13:17,871 --> 00:13:19,305
♪
250
00:13:19,338 --> 00:13:22,171
NARRATOR: But there are places in our DNA
that do vary.
251
00:13:22,205 --> 00:13:23,371
{\an1}Some of them are called
252
00:13:23,405 --> 00:13:29,205
{\an1}single nucleotide polymorphisms,
or SNPs.
253
00:13:29,238 --> 00:13:32,405
{\an1}They're spots where most of us
have one kind of base pair
254
00:13:32,438 --> 00:13:35,971
{\an1}but some of us have another.
255
00:13:36,005 --> 00:13:39,538
{\an1}So instead of trying to identify
all three billion
256
00:13:39,571 --> 00:13:41,838
{\an7}of a customer's base pairs,
257
00:13:41,871 --> 00:13:43,605
{\an7}the DTCs do something
258
00:13:43,638 --> 00:13:45,971
{\an7}that's cheaper and faster.
259
00:13:46,005 --> 00:13:48,671
{\an7}They only check out
a customer's SNPs.
260
00:13:48,705 --> 00:13:52,771
{\an7}Usually about 700,000 of them.
261
00:13:52,805 --> 00:13:56,705
{\an7}And comparing people's SNPs
is an efficient way
262
00:13:56,738 --> 00:13:58,638
{\an7}to see if they're related.
263
00:13:58,671 --> 00:14:00,338
{\an7}Because when their SNPs
match up,
264
00:14:00,371 --> 00:14:05,371
{\an7}all the DNA in between the SNPs
is usually identical too.
265
00:14:05,405 --> 00:14:07,305
{\an7}And matching DNA segments
266
00:14:07,338 --> 00:14:12,571
{\an1}are the telltale signs
of a family relationship.
267
00:14:12,605 --> 00:14:15,971
BOLNICK:
By looking at the amount
of shared DNA,
268
00:14:16,005 --> 00:14:19,938
{\an7}direct-to-consumer tests can
give a quite accurate picture
269
00:14:19,971 --> 00:14:24,405
{\an7}of relationships between
individuals.
270
00:14:24,438 --> 00:14:29,905
NARRATOR: FamilyTreeDNA in Houston is one
of the four biggest DTCs.
271
00:14:31,105 --> 00:14:34,905
{\an1}Like many of them,
the lynchpin of its operation
272
00:14:34,938 --> 00:14:37,471
{\an1}is its technology
for reading SNPs.
273
00:14:37,505 --> 00:14:43,605
{\an1}And this is it: a small piece
of glass called a SNP chip.
274
00:14:43,638 --> 00:14:47,971
{\an1}It contains hundreds of
thousands of tiny beads.
275
00:14:48,005 --> 00:14:52,771
{\an1}Each one holds a short piece
of DNA called a probe.
276
00:14:52,805 --> 00:14:56,305
{\an7}And we put an individual's DNA
on the chip,
277
00:14:56,338 --> 00:15:00,171
{\an8}and the part of
an individual's DNA
278
00:15:00,205 --> 00:15:03,138
{\an1}that matches the little probe,
279
00:15:03,171 --> 00:15:05,105
{\an1}they will bind together.
280
00:15:05,138 --> 00:15:08,205
{\an8}NARRATOR:
Once bound,
the identity of the SNP
281
00:15:08,238 --> 00:15:10,771
{\an8}is revealed by a
fluorescent dye.
282
00:15:10,805 --> 00:15:15,638
{\an1}For example, if you have an A,
you'll see green.
283
00:15:15,671 --> 00:15:18,505
{\an1}If you have a G, you'll see red.
284
00:15:18,538 --> 00:15:20,938
{\an1}(machinery whirring)
285
00:15:20,971 --> 00:15:25,038
NARRATOR:
The SNP data enables the lab
to see how much DNA is shared
286
00:15:25,071 --> 00:15:29,071
{\an1}by customers who've opted for
family matching.
287
00:15:29,105 --> 00:15:32,905
{\an1}The company website shows them
their list of matches.
288
00:15:32,938 --> 00:15:37,138
BORMANS:
It will show everyone
that you're related to,
289
00:15:37,171 --> 00:15:39,371
and the estimated relationship.
290
00:15:39,405 --> 00:15:42,138
♪
291
00:15:42,171 --> 00:15:47,271
NARRATOR:
But sometimes, that match list
can reveal a painful truth.
292
00:15:47,305 --> 00:15:48,905
♪
293
00:15:48,938 --> 00:15:53,005
This anonymity and taking these
secrets to the grave,
294
00:15:53,038 --> 00:15:57,271
{\an1}with the advent of DNA testing,
it really doesn't exist anymore.
295
00:15:57,305 --> 00:16:03,138
NARRATOR:
That's what Dani Shapiro
was shocked to discover.
296
00:16:03,171 --> 00:16:04,838
{\an1}A novelist and memoirist,
297
00:16:04,871 --> 00:16:08,238
{\an1}she's written about growing up
in an Orthodox Jewish family
298
00:16:08,271 --> 00:16:09,271
in New Jersey,
299
00:16:09,305 --> 00:16:13,438
{\an1}and about her parents,
Irene and Paul.
300
00:16:13,471 --> 00:16:15,638
{\an7}I was very, very bonded
with my dad...
301
00:16:15,671 --> 00:16:17,338
{\an7}much more so than with my mom.
302
00:16:17,371 --> 00:16:20,871
{\an1}He worked on the floor of the
New York Stock Exchange.
303
00:16:20,905 --> 00:16:22,905
{\an1}And I would meet him for lunch
sometimes.
304
00:16:22,938 --> 00:16:25,038
{\an1}And he would come out
and he would just like
305
00:16:25,071 --> 00:16:27,705
{\an1}fling his arms open, just like,
306
00:16:27,738 --> 00:16:30,871
{\an1}(voice breaking):
"Hiya darling,"
give me this huge hug.
307
00:16:30,905 --> 00:16:32,271
{\an1}It's going to make me cry.
308
00:16:32,305 --> 00:16:35,705
{\an1}I loved my father.
309
00:16:35,738 --> 00:16:37,805
NARRATOR:
From childhood on,
310
00:16:37,838 --> 00:16:40,671
{\an1}this Jewish daughter
draws comments.
311
00:16:40,705 --> 00:16:42,105
SHAPIRO:
"You don't look Jewish."
312
00:16:42,138 --> 00:16:43,147
"You can't possibly be Jewish."
313
00:16:43,171 --> 00:16:44,505
"There's no way you're Jewish."
314
00:16:44,538 --> 00:16:46,614
"Did your mother have an affair
with a Swedish milkman?"
315
00:16:46,638 --> 00:16:47,971
{\an1}"Shapiro your married name?"
316
00:16:48,005 --> 00:16:49,371
I could go on.
317
00:16:49,405 --> 00:16:54,005
NARRATOR:
One day in 2016, her husband,
Michael Maren,
318
00:16:54,038 --> 00:16:58,271
{\an1}decides to take a DNA test
from Ancestry.
319
00:16:58,305 --> 00:17:02,638
{\an1}Without thinking about it much,
Dani decides to take one too.
320
00:17:02,671 --> 00:17:06,405
{\an1}She knows that both of her
parents are of Ashkenazi,
321
00:17:06,438 --> 00:17:10,638
{\an1}or eastern European Jewish,
descent.
322
00:17:10,671 --> 00:17:14,771
{\an1}Several weeks later
they get their results.
323
00:17:14,805 --> 00:17:18,305
SHAPIRO:
We open them,
and he's like, "Huh.
324
00:17:18,338 --> 00:17:20,038
{\an1}"According to this,
you're about 50-50,
325
00:17:20,071 --> 00:17:22,871
{\an1}"Eastern European Ashkenazi
326
00:17:22,905 --> 00:17:25,338
{\an1}"and the rest is all
Western European...
327
00:17:25,371 --> 00:17:28,738
{\an1}French, Irish, English,
Swedish, German."
328
00:17:28,771 --> 00:17:33,905
{\an1}My only response was, "Oh, well
they must've made a mistake."
329
00:17:33,938 --> 00:17:37,571
{\an1}It was only a few days later,
my husband came in
330
00:17:37,605 --> 00:17:40,138
and he said,
"You have a first cousin
331
00:17:40,171 --> 00:17:42,205
{\an1}"on your Ancestry.com page.
332
00:17:42,238 --> 00:17:44,071
{\an1}"A first cousin who
we don't know, we don't,
333
00:17:44,105 --> 00:17:45,671
{\an1}we don't know this
first cousin."
334
00:17:45,705 --> 00:17:50,138
NARRATOR: In search of clues,
Dani turns to someone she's sure
335
00:17:50,171 --> 00:17:52,405
is a blood relative.
336
00:17:52,438 --> 00:17:53,647
SHAPIRO: I have a much older half-sister
337
00:17:53,671 --> 00:17:56,671
{\an1}from a first marriage
of my dad's.
338
00:17:56,705 --> 00:17:58,371
I recalled that
339
00:17:58,405 --> 00:18:00,805
{\an1}a number of years ago
she had done I think 23andMe.
340
00:18:00,838 --> 00:18:03,671
{\an1}And I sent her an email
and I said,
341
00:18:03,705 --> 00:18:08,705
{\an1}"Do you have your results from,
from the DNA test you did?"
342
00:18:08,738 --> 00:18:10,905
And she did
and she sent them to me.
343
00:18:10,938 --> 00:18:14,405
NARRATOR:
Dani gives the half-sister's
file to her husband.
344
00:18:14,438 --> 00:18:19,571
Using GEDmatch, he checks to
seehow much DNA she and Dani share
345
00:18:19,605 --> 00:18:22,838
{\an1}and discovers the truth.
346
00:18:22,871 --> 00:18:24,971
{\an1}He said, "You're not sisters."
347
00:18:25,005 --> 00:18:28,871
And I said,
"Not, not half-sisters?"
348
00:18:28,905 --> 00:18:30,505
{\an1}'Cause that's what we were.
349
00:18:30,538 --> 00:18:32,205
And he said,
"No kind of sisters.
350
00:18:32,238 --> 00:18:33,371
{\an1}You're not related."
351
00:18:33,405 --> 00:18:34,905
♪
352
00:18:34,938 --> 00:18:37,705
{\an1}And so that was the moment
for me when all of the pieces
353
00:18:37,738 --> 00:18:41,171
{\an1}began to just click into place
where I thought,
354
00:18:41,205 --> 00:18:45,905
{\an1}"Well, if he's not one of our
fathers, he's not my father."
355
00:18:45,938 --> 00:18:47,971
♪
356
00:18:48,005 --> 00:18:50,805
{\an1}Something very, very important
was kept from me.
357
00:18:50,838 --> 00:18:56,738
{\an1}And it felt to me like
my identity was... um...
358
00:18:56,771 --> 00:18:58,705
in pieces.
359
00:19:00,371 --> 00:19:02,571
NARRATOR:
Her parents are both deceased.
360
00:19:02,605 --> 00:19:05,638
{\an1}But she remembers her motheronce
saying she had a hard time
361
00:19:05,671 --> 00:19:08,005
{\an1}getting pregnant,
362
00:19:08,038 --> 00:19:12,271
{\an1}and mentioning a fertility
clinic in Philadelphia.
363
00:19:12,305 --> 00:19:15,138
{\an1}Dani and her husband track down
the first cousin
364
00:19:15,171 --> 00:19:17,838
{\an1}who popped up on Ancestry.
365
00:19:17,871 --> 00:19:23,705
{\an1}His uncle turns out to be
Dani's biological father.
366
00:19:23,738 --> 00:19:27,905
{\an1}A retired doctor, he'd gone
tomedical school in Philadelphia,
367
00:19:27,938 --> 00:19:30,771
{\an1}and had been a sperm donor
at the clinic.
368
00:19:32,105 --> 00:19:33,638
{\an1}She searches the internet,
369
00:19:33,671 --> 00:19:36,671
{\an1}and sees a video of him
giving a talk.
370
00:19:36,705 --> 00:19:38,171
SHAPIRO:
I knew what I was seeing.
371
00:19:38,205 --> 00:19:41,371
{\an1}And I remember getting up
and walking into the bathroom,
372
00:19:41,405 --> 00:19:43,871
{\an1}and looking at my facein
the mirror for the first time
373
00:19:43,905 --> 00:19:46,605
{\an1}after seeing him,
374
00:19:46,638 --> 00:19:49,471
{\an1}and understanding my face
for the first time in my life.
375
00:19:49,505 --> 00:19:53,838
NARRATOR:
Dani feels compelled
to write a new book
376
00:19:53,871 --> 00:19:58,038
{\an1}about family, identity,
and her own experience.
377
00:19:58,071 --> 00:20:02,005
{\an1}Its title: "Inheritance."
378
00:20:02,038 --> 00:20:04,138
{\an1}My book is dedicated
to my father.
379
00:20:04,171 --> 00:20:08,705
{\an1}And sometimes someone will say
to me, "Which father"?
380
00:20:08,738 --> 00:20:10,638
{\an1}And I'm like, "Are you kidding?"
381
00:20:10,671 --> 00:20:14,571
{\an1}My mother wanted to
bear a child.
382
00:20:14,605 --> 00:20:19,505
{\an1}And I think it must reallynot
have been easy for my father
383
00:20:19,538 --> 00:20:22,438
{\an1}to have gotten to this place
where he was
384
00:20:22,471 --> 00:20:26,638
{\an1}willing to genetically
replace himself.
385
00:20:26,671 --> 00:20:28,771
{\an1}That's what that is.
386
00:20:28,805 --> 00:20:32,205
{\an1}It's saying one of us is going
to be the biological parent
387
00:20:32,238 --> 00:20:34,705
of this child
and one of us is not.
388
00:20:34,738 --> 00:20:39,271
{\an1}And no one's ever gonna know
except for us.
389
00:20:39,305 --> 00:20:44,471
♪
390
00:20:44,505 --> 00:20:46,471
NARRATOR:
Dani is far from alone.
391
00:20:46,505 --> 00:20:49,905
{\an1}According to one estimate,
some one million people
392
00:20:49,938 --> 00:20:52,738
{\an8}have discovered
from consumer DNA tests
393
00:20:52,771 --> 00:20:55,338
{\an7}that the man who raised them
394
00:20:55,371 --> 00:20:57,205
{\an7}is not their biological father.
395
00:20:57,238 --> 00:21:01,405
{\an7}Or that they have a half-sibling
they never knew about.
396
00:21:02,538 --> 00:21:05,271
{\an1}And there are even
darker secrets that sometimes
397
00:21:05,305 --> 00:21:08,138
come to light.
398
00:21:08,171 --> 00:21:10,705
{\an1}In Washington State, in 2018,
399
00:21:10,738 --> 00:21:15,205
{\an1}the secret that Chelsea Rustad's
DNA helps to reveal
400
00:21:15,238 --> 00:21:16,705
could be the key
401
00:21:16,738 --> 00:21:21,805
{\an1}to cracking a 31-year-old
cold case.
402
00:21:21,838 --> 00:21:24,005
{\an1}It's really upsetting, very
distressing to think about.
403
00:21:24,038 --> 00:21:27,405
{\an7}Only a monster could do
such things to people.
404
00:21:29,071 --> 00:21:32,171
NARRATOR:
On November 18, 1987,
405
00:21:32,205 --> 00:21:34,405
{\an1}two young Canadians...
406
00:21:34,438 --> 00:21:36,805
{\an1}Jay Cook, 20 years old,
407
00:21:36,838 --> 00:21:40,938
{\an1}and his girlfriend,
Tanya van Cuylenborg, 18...
408
00:21:40,971 --> 00:21:45,805
{\an1}leave their hometown, a suburb
of Victoria, British Columbia,
409
00:21:45,838 --> 00:21:51,538
{\an1}heading to Seattle, to run
an errand for Jay's dad.
410
00:21:51,571 --> 00:21:56,605
Six days later,
Tanya's partially clothed body
411
00:21:56,638 --> 00:21:58,338
{\an1}is found by the side
of this road
412
00:21:58,371 --> 00:22:00,738
{\an1}in Skagit County, Washington.
413
00:22:02,005 --> 00:22:03,738
{\an1}She's been shot in the head.
414
00:22:03,771 --> 00:22:07,271
{\an1}And there's evidence of rape.
415
00:22:07,305 --> 00:22:10,605
{\an1}Two days after that,
some 65 miles away
416
00:22:10,638 --> 00:22:13,571
{\an1}in Snohomish County,
beneath this bridge,
417
00:22:13,605 --> 00:22:17,905
{\an1}hunters find Jay's body.
418
00:22:17,938 --> 00:22:19,005
{\an1}He's been strangled
419
00:22:19,038 --> 00:22:21,271
{\an1}with twine and dog collars...
420
00:22:21,305 --> 00:22:24,438
{\an1}his head beaten with rocks.
421
00:22:24,471 --> 00:22:28,171
{\an8}We had two young
totally innocent kids
422
00:22:28,205 --> 00:22:32,138
{\an7}that got kidnapped
and brutally murdered.
423
00:22:32,171 --> 00:22:36,605
NARRATOR:
During the investigation,
police recover
424
00:22:36,638 --> 00:22:40,605
{\an1}potentially precious evidence
from Tanya's body:
425
00:22:40,638 --> 00:22:43,871
{\an1}the assailant's DNA.
426
00:22:43,905 --> 00:22:47,205
{\an1}They will run it through
a lab procedure that is still
427
00:22:47,238 --> 00:22:51,271
{\an1}the gold standard for proving
identity with DNA.
428
00:22:51,305 --> 00:22:55,771
{\an1}It zeroes in on just 20 or so
places in the genome
429
00:22:55,805 --> 00:23:00,805
{\an1}where a short string of letters,
for example G-A-T-A,
430
00:23:00,838 --> 00:23:02,705
{\an7}just keeps on repeating.
431
00:23:02,738 --> 00:23:08,438
They're called
short tandem repeats, or STRs.
432
00:23:08,471 --> 00:23:09,771
{\an1}And scientists can count
433
00:23:09,805 --> 00:23:13,571
{\an1}the number of times they repeat.
434
00:23:13,605 --> 00:23:15,581
{\an1}STEVEN ARMENTROUT:
And those counts vary
person to person
435
00:23:15,605 --> 00:23:18,305
{\an1}just like the ridge lines
on a fingerprint.
436
00:23:18,338 --> 00:23:21,771
{\an7}It's a very powerful technique
because with enough locations,
437
00:23:21,805 --> 00:23:25,105
{\an7}you can do an identity match
with very high probability
438
00:23:25,138 --> 00:23:26,914
{\an1}because of these slight
differences one person
439
00:23:26,938 --> 00:23:28,105
to the next.
440
00:23:29,305 --> 00:23:31,571
NARRATOR:
But like a crime scene
fingerprint,
441
00:23:31,605 --> 00:23:35,038
{\an1}a crime scene STR profile
is only useful
442
00:23:35,071 --> 00:23:38,205
{\an1}if it matches one that's already
in the possession
443
00:23:38,238 --> 00:23:41,138
{\an7}of law enforcement.
444
00:23:41,171 --> 00:23:43,671
For decades,
the profile in this case
445
00:23:43,705 --> 00:23:48,871
{\an1}doesn't match anyone known
to the police.
446
00:23:48,905 --> 00:23:53,138
{\an1}The case goes cold.
447
00:23:53,171 --> 00:23:55,105
{\an1}Until the day when
Chelsea Rustad
448
00:23:55,138 --> 00:23:59,705
{\an1}uploads a DNA file to GEDmatch,
449
00:23:59,738 --> 00:24:01,405
{\an1}where it becomes a clue
450
00:24:01,438 --> 00:24:04,371
{\an1}that will eventually lead
the police to a major break
451
00:24:04,405 --> 00:24:06,871
in the case.
452
00:24:06,905 --> 00:24:10,205
(sirens blaring, radio chatter)
453
00:24:10,238 --> 00:24:15,205
{\an1}Chelsea's experience
will make headlines.
454
00:24:15,238 --> 00:24:18,171
{\an1}But most DNA test-takers
just want to know,
455
00:24:18,205 --> 00:24:21,071
{\an1}"What are my roots?"
456
00:24:21,105 --> 00:24:24,605
{\an1}A seemingly simple question
that often leads to its own
457
00:24:24,638 --> 00:24:27,038
{\an1}set of mysteries.
458
00:24:27,071 --> 00:24:29,771
BESSIE LAWTON:
Don't open anything
until we ask you to.
459
00:24:29,805 --> 00:24:33,771
NARRATOR:
These 14 people are about
to experience
460
00:24:33,805 --> 00:24:36,671
{\an1}DNA ancestry testing
for themselves.
461
00:24:36,705 --> 00:24:38,805
{\an1}'Cause there are so many kids
I'm growing up with
462
00:24:38,838 --> 00:24:40,738
who are all in
the same situation.
463
00:24:40,771 --> 00:24:42,471
We don't know our heritage.
464
00:24:42,505 --> 00:24:43,871
We could probably safely assume
465
00:24:43,905 --> 00:24:46,838
{\an7}that our ancestors' ancestors
had something to do
466
00:24:46,871 --> 00:24:48,605
{\an8}with like slavery
and things like that.
467
00:24:48,638 --> 00:24:51,771
But we don't really know
where we came from.
468
00:24:51,805 --> 00:24:55,238
NARRATOR: Cherry Richardson is taking part
in a research study
469
00:24:55,271 --> 00:24:58,638
{\an1}at West Chester University
in Pennsylvania.
470
00:24:58,671 --> 00:25:01,771
{\an1}So we have a research
protocolby which we collect data
471
00:25:01,805 --> 00:25:03,438
{\an1}for this particular project.
472
00:25:03,471 --> 00:25:06,538
NARRATOR:
The study is run by two
communications professors...
473
00:25:06,571 --> 00:25:10,271
Bessie Lawton and Anita Foeman.
474
00:25:10,305 --> 00:25:12,538
The question they're asking is:
475
00:25:12,571 --> 00:25:17,005
how does DNA testing affect our
understanding of who we are?
476
00:25:17,038 --> 00:25:18,471
{\an1}And also, our ability
477
00:25:18,505 --> 00:25:20,771
{\an1}to understand what makes us
different?
478
00:25:20,805 --> 00:25:22,381
{\an1}LAWTON: And after we receivethe results,
479
00:25:22,405 --> 00:25:23,471
{\an1}we bring you together...
480
00:25:23,505 --> 00:25:25,405
{\an1}The whole idea is to listen
to each other
481
00:25:25,438 --> 00:25:26,738
{\an1}and talk with one another...
482
00:25:26,771 --> 00:25:28,971
NARRATOR:
Anita was inspired to start
the project
483
00:25:29,005 --> 00:25:31,071
{\an1}because of her experiences
484
00:25:31,105 --> 00:25:33,038
{\an1}as a diversity trainer.
485
00:25:33,071 --> 00:25:35,205
FOEMAN:
I thought looking at our DNA
486
00:25:35,238 --> 00:25:38,971
was a really interesting way
toapproach this whole conversation
487
00:25:39,005 --> 00:25:42,805
{\an7}about race and diversity
in a way that was not going
488
00:25:42,838 --> 00:25:44,371
{\an1}to make people defensive.
489
00:25:44,405 --> 00:25:45,505
{\an1}And that has happened.
490
00:25:45,538 --> 00:25:47,771
{\an1}We don't identify ourselves
with Africa.
491
00:25:47,805 --> 00:25:49,105
We just say we're Black.
492
00:25:49,138 --> 00:25:50,205
You know, we literally
493
00:25:50,238 --> 00:25:52,071
{\an1}separated from that
which we came from.
494
00:25:52,105 --> 00:25:54,871
NARRATOR:
In a previous test
with Ancestry,
495
00:25:54,905 --> 00:25:56,238
{\an1}Tyquine Golden was told
496
00:25:56,271 --> 00:25:58,538
{\an1}his roots were 80% West African,
497
00:25:58,571 --> 00:26:00,805
and 20% British.
498
00:26:00,838 --> 00:26:02,105
They got everybody.
499
00:26:02,138 --> 00:26:04,238
NARRATOR:
In today's test
with FamilyTreeDNA,
500
00:26:04,271 --> 00:26:07,371
{\an1}he hopes to learn more.
501
00:26:07,405 --> 00:26:11,738
{\an1}My suspicions might lead me
to say, somewhere in slavery,
502
00:26:11,771 --> 00:26:17,505
{\an7}20% might've came in and have
been integrated with our DNA.
503
00:26:17,538 --> 00:26:20,171
{\an1}And that might not have been
voluntary.
504
00:26:20,205 --> 00:26:22,705
{\an1}I think as an African American,
it's a tough thing
505
00:26:22,738 --> 00:26:25,305
{\an7}to grapple with when you think
about the origin
506
00:26:25,338 --> 00:26:28,671
{\an1}of your Caucasian,
or white ancestry,
507
00:26:28,705 --> 00:26:31,738
{\an1}that often happened due to rape
and mistreatment.
508
00:26:31,771 --> 00:26:33,071
{\an1}But it is part of your history.
509
00:26:33,105 --> 00:26:37,805
{\an1}So you have to confront iton
some level and understand it.
510
00:26:37,838 --> 00:26:39,247
{\an1}It's part of how you got here.
511
00:26:39,271 --> 00:26:41,338
{\an1}I don't want to hide
from the truth.
512
00:26:41,371 --> 00:26:44,905
No matter how bad it could be.
513
00:26:46,505 --> 00:26:48,805
NARRATOR: Now it's time to collect DNA...
514
00:26:48,838 --> 00:26:50,205
LAWTON:
You can turn it around
515
00:26:50,238 --> 00:26:51,505
a little bit to capture more.
516
00:26:51,538 --> 00:26:53,438
NARRATOR:
and ship the samples off
to Houston.
517
00:26:56,571 --> 00:27:00,371
{\an1}So how do DTCs like
FamilyTreeDNA come up
518
00:27:00,405 --> 00:27:02,571
with a breakdown
of your ancestry?
519
00:27:02,605 --> 00:27:04,238
{\an1}(machinery whirring)
520
00:27:04,271 --> 00:27:06,705
{\an1}It's a process that also
centers around SNPs...
521
00:27:06,738 --> 00:27:09,171
{\an1}those places in our DNA
522
00:27:09,205 --> 00:27:13,971
{\an1}that most frequently vary
between people.
523
00:27:14,005 --> 00:27:16,471
{\an7}The company compares your SNPs
524
00:27:16,505 --> 00:27:20,605
{\an7}with those of people in what
are called reference groups...
525
00:27:20,638 --> 00:27:24,105
{\an7}people alive today whose DNA
has been tested
526
00:27:24,138 --> 00:27:26,138
{\an7}and who share patterns of SNPs
527
00:27:26,171 --> 00:27:27,571
{\an7}that scientists have found to be
528
00:27:27,605 --> 00:27:30,738
{\an7}typical for the region in which
they live.
529
00:27:31,871 --> 00:27:35,005
{\an7}Those patterns are compiled into
a database.
530
00:27:35,038 --> 00:27:38,105
{\an7}But how well does it represent
test-takers?
531
00:27:39,905 --> 00:27:41,071
{\an8}FOEMAN:
They're telling you
532
00:27:41,105 --> 00:27:43,338
{\an8}this is your background based on
our database.
533
00:27:43,371 --> 00:27:44,947
{\an1}Well, if something's not
in their database,
534
00:27:44,971 --> 00:27:47,471
{\an1}they can't tell you that it's in
your background.
535
00:27:48,771 --> 00:27:50,405
NARRATOR:
The DTCs have less data
536
00:27:50,438 --> 00:27:53,638
{\an1}about people of African
and Asian descent than they do
537
00:27:53,671 --> 00:27:57,138
{\an1}about people of European
descent.
538
00:27:57,171 --> 00:28:00,705
{\an7}Most of the genetic testing
that has been done
539
00:28:00,738 --> 00:28:04,305
{\an7}has been done on North Atlantic
Europeans.
540
00:28:04,338 --> 00:28:08,871
{\an1}So our reference databases
are biased.
541
00:28:08,905 --> 00:28:11,105
{\an8}(bird crowing)
542
00:28:13,671 --> 00:28:15,114
{\an8}FOEMAN:
Why don't we all just
take a minute,
543
00:28:15,138 --> 00:28:16,838
and open your results,
544
00:28:16,871 --> 00:28:20,005
{\an1}and take a look at the map
for the first time.
545
00:28:20,038 --> 00:28:23,571
NARRATOR:
FamilyTreeDNA has given
Nick Pasvanis,
546
00:28:23,605 --> 00:28:26,338
{\an1}whose parents trace
their ancestors to Greece,
547
00:28:26,371 --> 00:28:30,238
{\an1}Germany, England, and Scotland,
a detailed breakdown.
548
00:28:30,271 --> 00:28:33,105
{\an1}PASVANIS: I'm 45%Southeastern European,
549
00:28:33,138 --> 00:28:36,038
{\an1}which is aboutwhat I expected.
550
00:28:36,071 --> 00:28:39,705
{\an1}I've always felt like I wasjust
a general European mutt.
551
00:28:39,738 --> 00:28:42,438
{\an1}And that's pretty muchwhat the map shows.
552
00:28:42,471 --> 00:28:45,538
{\an1}RICHARDSON: So, I was
wonderingwhen I got it, like,
553
00:28:45,571 --> 00:28:47,471
{\an1}if it would say if I was Black,
554
00:28:47,505 --> 00:28:50,205
{\an1}and I am 94% West African,
555
00:28:50,238 --> 00:28:52,705
(chuckling):
so, yeah, I'm pretty Black.
556
00:28:52,738 --> 00:28:58,471
NARRATOR: But Cherry Richardson's African
bubble provides little detail.
557
00:29:00,671 --> 00:29:03,671
{\an1}Hana Wiessmann and Viola Wang,
558
00:29:03,705 --> 00:29:05,605
{\an1}who were both born in China,
559
00:29:05,638 --> 00:29:08,571
{\an1}have even bigger bubbles.
560
00:29:08,605 --> 00:29:10,881
WIESSMANN: I mean, I have just these giant
bubbles, and they're like,
561
00:29:10,905 --> 00:29:13,938
{\an1}"You're super Asian," like,
Ikind of already knew that, so...
562
00:29:13,971 --> 00:29:16,705
{\an1}Basically, people have huge
bubbles are considered
563
00:29:16,738 --> 00:29:19,138
{\an1}"the minorities."
564
00:29:19,171 --> 00:29:22,805
{\an1}And it's unfortunate because
it perpetuates
565
00:29:22,838 --> 00:29:29,071
{\an1}a kind of Eurocentrism that has
tainted our scholarship.
566
00:29:29,105 --> 00:29:32,238
{\an1}That is a foundation
for notions,
567
00:29:32,271 --> 00:29:35,705
false notions
of white supremacy.
568
00:29:35,738 --> 00:29:38,238
{\an1}And it highlights
the disparities
569
00:29:38,271 --> 00:29:42,105
{\an1}that are currently prevalent
throughout science
570
00:29:42,138 --> 00:29:44,171
{\an1}and particularly in genetics.
571
00:29:44,205 --> 00:29:48,471
{\an1}There's also 23% southeast with
Italy and Greece highlighted,
572
00:29:48,505 --> 00:29:50,605
{\an1}which was never on our radar.
573
00:29:50,638 --> 00:29:55,238
NARRATOR: But there's another problem
withthe way DTCs calculate ancestry.
574
00:29:55,271 --> 00:29:57,005
MAN:
64% European...
575
00:29:57,038 --> 00:29:59,971
NARRATOR: The DNA of
peoplewho lived in a place long ago...
576
00:30:00,005 --> 00:30:02,071
your ancestors...
577
00:30:02,105 --> 00:30:04,071
{\an1}may be different from the DNA
of the people
578
00:30:04,105 --> 00:30:08,971
{\an1}in the reference groups
who live there today.
579
00:30:09,005 --> 00:30:11,471
{\an1}That's because for centuries,
people,
580
00:30:11,505 --> 00:30:12,871
and their DNA,
581
00:30:12,905 --> 00:30:16,905
{\an1}have been moving around
the globe.
582
00:30:16,938 --> 00:30:20,205
JACKSON:
You really have to get over
the hurdle of static thinking
583
00:30:20,238 --> 00:30:22,971
{\an1}about human populations.
584
00:30:23,005 --> 00:30:26,538
{\an1}That there are Irish genes,
and Italian genes,
585
00:30:26,571 --> 00:30:31,838
{\an1}and, and Nigerian genes,
and Zimbabwean genes
586
00:30:31,871 --> 00:30:35,605
{\an1}and that's just not the way
that human evolution works.
587
00:30:35,638 --> 00:30:38,838
{\an1}Because static feeds into
the racist paradigm,
588
00:30:38,871 --> 00:30:43,971
{\an1}feeds into the me versus you,
you know, us versus them.
589
00:30:44,005 --> 00:30:46,271
♪
590
00:30:46,305 --> 00:30:48,371
NARRATOR: And yet it is true that certain
591
00:30:48,405 --> 00:30:51,471
SNP patterns are more prevalent
in some places than others.
592
00:30:51,505 --> 00:30:54,271
♪
593
00:30:54,305 --> 00:30:55,614
CUNNINGHAM:
There are several clues
594
00:30:55,638 --> 00:30:58,271
that can link you back to areas
595
00:30:58,305 --> 00:31:02,605
{\an1}and specific regions
where your ancestors evolved.
596
00:31:02,638 --> 00:31:04,905
{\an1}The companies are doingthe
best they can with the data
597
00:31:04,938 --> 00:31:06,338
{\an1}that they have.
598
00:31:06,371 --> 00:31:10,038
{\an7}And that's why all the DNA
testing companies are trying
599
00:31:10,071 --> 00:31:15,738
{\an7}to add more discrete populations
to their database,
600
00:31:15,771 --> 00:31:22,071
{\an1}so that when they don't assign
your population perfectly,
601
00:31:22,105 --> 00:31:25,105
they're as close
as they possibly can be.
602
00:31:25,138 --> 00:31:28,971
NARRATOR:
Bessie and Anita are finding
that whatever their flaws,
603
00:31:29,005 --> 00:31:34,438
{\an1}DNA ancestry tests, by
makingpeople think about their roots,
604
00:31:34,471 --> 00:31:38,305
{\an1}can help them to better
appreciate human diversity.
605
00:31:38,338 --> 00:31:40,505
The north of Africa,
Middle East,
606
00:31:40,538 --> 00:31:42,471
the western Europe, but I was...
607
00:31:42,505 --> 00:31:43,871
{\an8}LAWTON:
It makes people think of
608
00:31:43,905 --> 00:31:49,205
{\an7}their stories in relation toother
people in the whole story
609
00:31:49,238 --> 00:31:50,738
{\an1}of human migration.
610
00:31:50,771 --> 00:31:54,505
{\an1}Most people have felt this to be
a positive experience.
611
00:31:54,538 --> 00:31:58,338
NARRATOR:
Tyquine Golden's results
from FamilyTreeDNA
612
00:31:58,371 --> 00:31:59,505
are very close
613
00:31:59,538 --> 00:32:02,005
{\an1}to those he received
from Ancestry.
614
00:32:02,038 --> 00:32:03,214
GOLDEN:
Can't ignore it now.
(chuckles)
615
00:32:03,238 --> 00:32:04,905
The whole, like,
616
00:32:04,938 --> 00:32:08,871
{\an1}Ireland and U.K. part
of the DNA.
617
00:32:08,905 --> 00:32:10,405
FOEMAN:
Let me ask,
do you think you're
618
00:32:10,438 --> 00:32:13,105
as authentically Black
as she is?
619
00:32:13,138 --> 00:32:14,871
{\an1}I don't think it makes
a difference.
620
00:32:14,905 --> 00:32:16,505
FOEMAN:
They sat there
621
00:32:16,538 --> 00:32:19,371
{\an1}and had a conversation
about race
622
00:32:19,405 --> 00:32:23,671
{\an1}that was fun and exciting
and joining.
623
00:32:23,705 --> 00:32:25,138
{\an1}And if that can happen
624
00:32:25,171 --> 00:32:28,571
more and more,
what are the possibilities?
625
00:32:28,605 --> 00:32:31,738
♪
626
00:32:31,771 --> 00:32:35,238
NARRATOR: But as difficultas
determining ancestry may be,
627
00:32:35,271 --> 00:32:38,871
{\an1}the toughest challenge
the DTCs are taking on
628
00:32:38,905 --> 00:32:43,405
may be assessing
our genetic disease risks.
629
00:32:43,438 --> 00:32:44,781
{\an1}Because when it comes
to the accuracy
630
00:32:44,805 --> 00:32:50,405
of those tests,
the stakes couldn't be higher.
631
00:32:50,438 --> 00:32:52,638
{\an1}We all face the risk
of developing
632
00:32:52,671 --> 00:32:55,205
{\an1}life-threatening diseases.
633
00:32:55,238 --> 00:32:56,671
{\an1}But some of us face
634
00:32:56,705 --> 00:33:04,705
{\an1}a greater risk because of
variations in our genes...
635
00:33:06,938 --> 00:33:08,338
{\an1}that form the genetic code
636
00:33:08,371 --> 00:33:10,638
{\an1}for making proteins,
637
00:33:10,671 --> 00:33:14,205
{\an1}the critical molecules
that keep our bodies working.
638
00:33:14,238 --> 00:33:16,971
{\an7}It is hard to believe that
a single letter change
639
00:33:17,005 --> 00:33:19,138
{\an7}could affect a human being
so profoundly
640
00:33:19,171 --> 00:33:22,005
{\an7}among this huge string
of three billion letters.
641
00:33:22,038 --> 00:33:25,005
{\an1}But then you get those
critical places
642
00:33:25,038 --> 00:33:27,771
{\an1}where if you've made
that specific change,
643
00:33:27,805 --> 00:33:30,871
{\an1}the protein simply doesn't work
anymore.
644
00:33:30,905 --> 00:33:34,705
NARRATOR:
Several of the DTCs
now offer testing
645
00:33:34,738 --> 00:33:37,305
{\an1}for genetic health risks.
646
00:33:37,338 --> 00:33:40,238
{\an1}But how reliable are they?
647
00:33:40,271 --> 00:33:41,971
{\an1}Most of those tests
648
00:33:42,005 --> 00:33:50,005
{\an1}look only at selected SNPs and
ignore the rest of the genome,
649
00:33:52,905 --> 00:33:57,105
{\an1}where other risks
23andMe's controversial teste:
650
00:33:57,138 --> 00:34:00,005
{\an1}for breast cancer risk.
651
00:34:00,038 --> 00:34:03,438
{\an7}It looks at two genes
called B-R-C-A,
652
00:34:03,471 --> 00:34:06,071
{\an7}or "bra-ka" genes.
653
00:34:06,105 --> 00:34:10,105
{\an7}They code for proteins
that control cell growth.
654
00:34:10,138 --> 00:34:12,438
{\an7}But certain base pair variations
655
00:34:12,471 --> 00:34:14,138
{\an1}derail the BRCA genes,
656
00:34:14,171 --> 00:34:18,205
{\an1}and make some cancers...
Such as pancreatic,
657
00:34:18,238 --> 00:34:23,238
{\an1}prostate, and especially ovarianand
breast cancer... more likely.
658
00:34:23,271 --> 00:34:28,971
{\an1}Scientists have documentedclose
to 4,000 such variations.
659
00:34:29,005 --> 00:34:34,905
{\an7}23andMe sells a SNP test
that looks for three of them.
660
00:34:34,938 --> 00:34:39,071
{\an1}They're among the variationsthat
put women at very high risk
661
00:34:39,105 --> 00:34:40,705
{\an1}for breast cancer.
662
00:34:40,738 --> 00:34:44,605
{\an1}Each can be reliably detected
by SNP testing.
663
00:34:44,638 --> 00:34:48,371
{\an1}And each is ten times
more common in women who have
664
00:34:48,405 --> 00:34:52,438
{\an1}Ashkenazi Jewish ancestry.
665
00:34:52,471 --> 00:34:57,638
{\an1}Jessica Algazi, a 52-year-old
entertainment lawyer
666
00:34:57,671 --> 00:35:02,105
{\an1}in Los Angeles, has three
Ashkenazi grandparents.
667
00:35:03,471 --> 00:35:08,238
{\an1}In 2018, she takes the 23andMe
BRCA test,
668
00:35:08,271 --> 00:35:11,871
having no idea
it will change her life.
669
00:35:11,905 --> 00:35:16,171
{\an1}One day, when she's playing
golf, she gets an email.
670
00:35:16,205 --> 00:35:19,205
ALGAZI: I get the resultsas
I'm sitting on a golf course
671
00:35:19,238 --> 00:35:22,938
in a golf cart and I looked down
and like, "Oh my God,
672
00:35:22,971 --> 00:35:24,371
{\an7}I can't believe this."
673
00:35:24,405 --> 00:35:27,438
NARRATOR:
23andMe reports that she has
674
00:35:27,471 --> 00:35:30,905
{\an1}a BRCA 1 variation
that makes it highly likely
675
00:35:30,938 --> 00:35:34,338
{\an1}she will develop ovarian
or breast cancer.
676
00:35:34,371 --> 00:35:37,405
{\an1}A second test by a DNA lab
677
00:35:37,438 --> 00:35:41,305
{\an1}that specializes in BRCA testing
confirms it.
678
00:35:41,338 --> 00:35:44,171
{\an1}Although she is cancer-free
for now,
679
00:35:44,205 --> 00:35:46,105
{\an1}she makes a decision.
680
00:35:46,138 --> 00:35:50,371
ALGAZI: My gynecologist said, you know,
681
00:35:50,405 --> 00:35:52,705
{\an1}"Jess, you got to do
something now.
682
00:35:52,738 --> 00:35:55,138
{\an1}"You'll have your ovaries
and tubes removed
683
00:35:55,171 --> 00:35:59,838
{\an1}and you need to havea
double mastectomy right away."
684
00:35:59,871 --> 00:36:03,805
{\an1}And so, I'm just grateful that
I was able to find out in time
685
00:36:03,838 --> 00:36:05,471
to do something
before I got sick.
686
00:36:05,505 --> 00:36:09,038
{\an1}I'm eternally grateful
to the folks at 23andMe
687
00:36:09,071 --> 00:36:11,471
{\an1}for giving me that opportunity.
688
00:36:11,505 --> 00:36:14,805
{\an1}They quite possibly
saved my life.
689
00:36:14,838 --> 00:36:18,771
NARRATOR:
But most women who have
BRCA variations don't have
690
00:36:18,805 --> 00:36:22,638
{\an1}any of the three that 23andMe
tests for.
691
00:36:22,671 --> 00:36:26,005
{\an1}Women like Pamela Munster.
692
00:36:26,038 --> 00:36:27,238
{\an1}She happens to be
693
00:36:27,271 --> 00:36:29,438
{\an1}an oncologist in San Francisco
694
00:36:29,471 --> 00:36:32,405
who specializes
in breast cancer.
695
00:36:32,438 --> 00:36:33,971
I have the BRCA1 gene...
696
00:36:34,005 --> 00:36:38,138
NARRATOR:
She has no Ashkenazi Jewish
ancestry.
697
00:36:38,171 --> 00:36:44,205
In 2010, Pamela takes 23andMe's
BRCA test herself.
698
00:36:44,238 --> 00:36:45,505
MUNSTER:
What I learned is that
699
00:36:45,538 --> 00:36:48,705
{\an7}I didn't have much of
a breast cancer risk,
700
00:36:48,738 --> 00:36:50,638
{\an7}and by 23andMe's reckon,
701
00:36:50,671 --> 00:36:52,538
{\an1}my breast cancer risk
was actually quite low.
702
00:36:52,571 --> 00:36:58,238
NARRATOR: But in 2012, Pamela is diagnosed
with breast cancer.
703
00:36:58,271 --> 00:37:02,571
MUNSTER:
And the way that my cancer
looked under the microscope,
704
00:37:02,605 --> 00:37:05,338
{\an1}I had the sense that
this breast cancer
705
00:37:05,371 --> 00:37:06,871
{\an1}was associated with a
BRCA mutation.
706
00:37:06,905 --> 00:37:11,271
NARRATOR:
To confirm her hunch,
Pamela has her DNA tested
707
00:37:11,305 --> 00:37:14,438
by what's known
as a clinical lab,
708
00:37:14,471 --> 00:37:16,871
{\an1}the kind doctors use.
709
00:37:16,905 --> 00:37:20,371
{\an1}They don't just look at
scattered SNPs.
710
00:37:20,405 --> 00:37:24,505
{\an1}They look at every single
base pair in genes...
711
00:37:25,871 --> 00:37:29,871
{\an1}A process known as sequencing.
712
00:37:29,905 --> 00:37:32,805
{\an1}They go through the entire
BRCA gene.
713
00:37:32,838 --> 00:37:37,171
{\an1}And they... remember, these are
like 80,000 base pairs.
714
00:37:37,205 --> 00:37:38,938
{\an1}And they can tell you
is the letter there,
715
00:37:38,971 --> 00:37:40,005
{\an1}is the letter not there.
716
00:37:40,038 --> 00:37:43,505
NARRATOR:
Pamela turns out to be right.
717
00:37:43,538 --> 00:37:46,505
She does have a BRCA2 mutation.
718
00:37:46,538 --> 00:37:50,871
{\an1}But it's not any of the three
variants 23andMe tests for.
719
00:37:50,905 --> 00:37:54,505
{\an1}It's one of the thousands
of others.
720
00:37:54,538 --> 00:37:58,338
{\an1}If I just want to know
who I'm related to, 23andMe,
721
00:37:58,371 --> 00:38:00,871
{\an1}Ancestry are very good tests.
722
00:38:00,905 --> 00:38:03,905
{\an1}If you want to know,
do you carry a BRCA gene
723
00:38:03,938 --> 00:38:06,305
{\an1}and are you at risk
for breast cancer?
724
00:38:06,338 --> 00:38:11,205
I think 23andMe
is not an ideal test.
725
00:38:11,238 --> 00:38:15,938
NARRATOR:
But 23andMe says that
its BRCA test has alerted
726
00:38:15,971 --> 00:38:20,171
{\an1}some 3,000 people
to their cancer risk.
727
00:38:20,205 --> 00:38:23,405
{\an1}And that choosing these
three variants makes sense,
728
00:38:23,438 --> 00:38:27,538
{\an1}because they confer
such high risks.
729
00:38:27,571 --> 00:38:30,371
SHIRLEY WU:
What these variations mean
for someone's risks
730
00:38:30,405 --> 00:38:32,938
{\an1}is very, very well understood.
731
00:38:32,971 --> 00:38:36,171
{\an7}The studies that have shown
near, nearly half of people
732
00:38:36,205 --> 00:38:38,371
{\an7}carrying one of these variants
don't realize it.
733
00:38:38,405 --> 00:38:42,738
{\an1}So it's great for those people
who were not even thinking
734
00:38:42,771 --> 00:38:44,047
{\an1}they were carrying that mutation
735
00:38:44,071 --> 00:38:46,838
{\an1}to pick it up with
direct-to-consumer testing.
736
00:38:46,871 --> 00:38:49,705
{\an1}It's not a good thing
if those people think
737
00:38:49,738 --> 00:38:54,905
{\an1}they have been exhaustively
tested because they have not.
738
00:38:54,938 --> 00:38:57,405
♪
739
00:38:57,438 --> 00:38:59,471
NARRATOR:
And there are also concerns
740
00:38:59,505 --> 00:39:03,571
{\an1}about how test-takers' data
is used.
741
00:39:03,605 --> 00:39:04,938
In 2018,
742
00:39:04,971 --> 00:39:09,071
{\an1}23andMe agrees to share
anonymized information
743
00:39:09,105 --> 00:39:11,271
{\an1}about millions of its customers
744
00:39:11,305 --> 00:39:14,538
{\an1}with GlaxoSmithKline
to use in the development
745
00:39:14,571 --> 00:39:17,338
of new drugs.
746
00:39:17,371 --> 00:39:22,305
{\an1}23andMe says some 80% of its
customers have given consent
747
00:39:22,338 --> 00:39:26,271
{\an1}for their data to be used
in research.
748
00:39:27,805 --> 00:39:30,538
{\an1}Most have also filled in
health questionnaires,
749
00:39:30,571 --> 00:39:34,338
{\an1}enabling valuable linksto
be made between their genes,
750
00:39:34,371 --> 00:39:36,938
{\an1}and their health histories.
751
00:39:36,971 --> 00:39:38,981
{\an1}The potential of what you can do
with that information
752
00:39:39,005 --> 00:39:40,571
{\an1}is just astounding.
753
00:39:40,605 --> 00:39:43,338
NARRATOR:
But while the possible rewards
754
00:39:43,371 --> 00:39:46,238
{\an1}of the deal seem clear, to some,
755
00:39:46,271 --> 00:39:48,805
{\an1}it raises ethical questions.
756
00:39:48,838 --> 00:39:50,781
{\an7}You're actually paying
your money to give your data
757
00:39:50,805 --> 00:39:51,905
{\an8}to a company.
758
00:39:51,938 --> 00:39:54,338
{\an7}And then it will be
capitalized on
759
00:39:54,371 --> 00:39:57,505
{\an1}potentially without benefit
to you.
760
00:39:57,538 --> 00:39:59,247
{\an1}When you're dealing with
such a new technology,
761
00:39:59,271 --> 00:40:03,405
{\an1}I think the full implications
can't possibly be understood
762
00:40:03,438 --> 00:40:06,138
{\an1}by consumers because things are
just too new.
763
00:40:07,705 --> 00:40:13,538
NARRATOR: So how safe is the
data of23andMe's 12 million customers?
764
00:40:13,571 --> 00:40:14,914
{\an7}JACQUIE HAGGARTY:
We do not sell data.
765
00:40:14,938 --> 00:40:19,171
{\an7}We do not share your data
with any insurance company
766
00:40:19,205 --> 00:40:23,071
{\an7}or any employer, hard stop,
without your consent.
767
00:40:24,405 --> 00:40:27,071
NARRATOR:
Federal law prohibits
most employers from using
768
00:40:27,105 --> 00:40:31,138
{\an1}genetic data to make
workplace decisions.
769
00:40:31,171 --> 00:40:33,771
{\an1}And prohibits health insurers
from using it
770
00:40:33,805 --> 00:40:36,505
{\an1}to change or deny coverage.
771
00:40:36,538 --> 00:40:38,471
But disability
and life insurance companies
772
00:40:38,505 --> 00:40:40,905
{\an1}are free to use it.
773
00:40:40,938 --> 00:40:45,638
{\an1}While 23andMe and FamilyTreeDNA
talked with "NOVA"
774
00:40:45,671 --> 00:40:47,671
{\an1}about these issues,
775
00:40:47,705 --> 00:40:52,905
{\an1}AncestryDNA declined
to participate in this film.
776
00:40:52,938 --> 00:40:54,838
♪
777
00:40:54,871 --> 00:40:57,338
{\an1}The risks inherent
in new technologies
778
00:40:57,371 --> 00:40:58,938
{\an1}often become obvious
779
00:40:58,971 --> 00:41:01,738
{\an1}only in hindsight.
780
00:41:01,771 --> 00:41:05,505
{\an1}Chelsea Rustad could neverhad
predicted that her DNA test
781
00:41:05,538 --> 00:41:09,538
{\an1}might lead the police
to a dangerous murder suspect.
782
00:41:09,571 --> 00:41:13,838
{\an1}They found him using
a new investigative technique
783
00:41:13,871 --> 00:41:18,905
{\an1}that springs directly from
the rise of consumer testing.
784
00:41:18,938 --> 00:41:21,771
{\an1}It's called genetic genealogy.
785
00:41:21,805 --> 00:41:24,971
{\an1}And before it was used
to solve crimes,
786
00:41:25,005 --> 00:41:29,038
{\an1}it was used by people looking
for their birth parents.
787
00:41:29,071 --> 00:41:32,938
{\an1}One of its pioneers
is a retired patent lawyer
788
00:41:32,971 --> 00:41:34,738
{\an1}named Barbara Rae-Venter.
789
00:41:34,771 --> 00:41:35,847
RAE-VENTER:
I really backed into
790
00:41:35,871 --> 00:41:37,538
{\an7}this whole thing.
791
00:41:37,571 --> 00:41:42,505
{\an7}Because I was doing, uh...
unknown parentage type work
792
00:41:42,538 --> 00:41:44,405
with adoptees.
793
00:41:44,438 --> 00:41:46,805
For adoptees, DNA has been huge,
794
00:41:46,838 --> 00:41:49,838
{\an1}because for them to try
and figure out
795
00:41:49,871 --> 00:41:52,271
{\an1}who their birth relatives were
just using paper,
796
00:41:52,305 --> 00:41:53,871
{\an1}very, very difficult.
797
00:41:53,905 --> 00:41:57,638
{\an8}NARRATOR:
Barbara starts by connecting
the adoptee to the people
798
00:41:57,671 --> 00:42:00,705
{\an7}in their DNA match list.
799
00:42:00,738 --> 00:42:07,371
{\an7}Then by digging through records,
she finds more relatives.
800
00:42:07,405 --> 00:42:12,905
{\an7}The goal: find an ancestor
who links everyone together
801
00:42:12,938 --> 00:42:16,005
{\an7}and points directly
to the birth parent.
802
00:42:16,038 --> 00:42:22,671
{\an1}In 2017, Barbara is asked
by investigators in California
803
00:42:22,705 --> 00:42:25,538
to try to solve
a different kind of mystery:
804
00:42:25,571 --> 00:42:29,705
{\an1}one of the nation's
most notorious cold cases.
805
00:42:30,938 --> 00:42:33,205
The so-called
Golden State Killer
806
00:42:33,238 --> 00:42:34,405
{\an1}was suspected of committing
807
00:42:34,438 --> 00:42:38,471
{\an1}at least 13 murders
and more than 50 rapes
808
00:42:38,505 --> 00:42:42,038
{\an1}during the 1970s and '80s.
809
00:42:42,071 --> 00:42:44,671
♪
810
00:42:44,705 --> 00:42:46,738
{\an1}Police have long had his DNA,
811
00:42:46,771 --> 00:42:49,505
{\an1}but they have no idea who he is.
812
00:42:49,538 --> 00:42:50,938
♪
813
00:42:50,971 --> 00:42:52,105
{\an1}Barbara agrees to help.
814
00:42:54,071 --> 00:42:57,105
{\an1}From the crime scene DNA,
a SNP profile is made,
815
00:42:57,138 --> 00:43:00,371
{\an1}and then uploaded to GEDmatch.
816
00:43:00,405 --> 00:43:05,705
{\an1}Using the relatives who pop up,
Barbara creates a family tree
817
00:43:05,738 --> 00:43:08,171
{\an1}and eventually zeroes in
818
00:43:08,205 --> 00:43:11,671
{\an1}on a man named Joseph DeAngelo.
819
00:43:11,705 --> 00:43:16,605
{\an1}A one-time policeman, DeAngelohad
never been under suspicion.
820
00:43:16,638 --> 00:43:22,305
{\an1}Police collect his DNA
and run an STR test.
821
00:43:22,338 --> 00:43:25,438
The result:
a perfect match with the DNA
822
00:43:25,471 --> 00:43:29,338
{\an1}of the Golden State Killer.
823
00:43:29,371 --> 00:43:30,671
{\an1}Murder in the first degree...
824
00:43:30,705 --> 00:43:32,771
{\an1}that charge, sir,
how do you plead?
825
00:43:32,805 --> 00:43:36,305
NARRATOR:
In June 2020,
Joseph DeAngelo pleads guilty
826
00:43:36,338 --> 00:43:38,305
{\an1}to 13 counts of murder.
827
00:43:38,338 --> 00:43:39,471
Guilty.
828
00:43:39,505 --> 00:43:41,705
NARRATOR:
He is sentenced
to life in prison.
829
00:43:43,571 --> 00:43:45,538
At the time
of DeAngelo's arrest,
830
00:43:45,571 --> 00:43:48,138
{\an1}Detective Jim Scharf
is amazed to learn
831
00:43:48,171 --> 00:43:52,871
{\an1}what's been accomplished
using genetic genealogy.
832
00:43:52,905 --> 00:43:56,505
{\an1}He quickly thinks about
Tanya and Jay.
833
00:43:56,538 --> 00:43:59,171
He reaches out
to a computer scientist
834
00:43:59,205 --> 00:44:04,938
{\an1}he's been working within
Virginia... Steve Armentrout.
835
00:44:04,971 --> 00:44:07,138
{\an1}So do I need to hardwirethe number in here
836
00:44:07,171 --> 00:44:08,905
{\an1}or am I doing a calculation?
837
00:44:08,938 --> 00:44:12,371
NARRATOR:
Steve's company,
Parabon NanoLabs,
838
00:44:12,405 --> 00:44:15,538
{\an1}has developed methodsand
software for sifting through
839
00:44:15,571 --> 00:44:17,538
{\an1}hundreds of thousands of SNPs.
840
00:44:17,571 --> 00:44:21,205
ARMENTROUT:
We first have to get DNA
from the crime scene
841
00:44:21,238 --> 00:44:25,205
{\an1}into a format that can be used
for uploading.
842
00:44:25,238 --> 00:44:28,105
{\an7}Jim gave us the okay
on a Thursday.
843
00:44:28,138 --> 00:44:29,071
{\an8}On Friday,
844
00:44:29,105 --> 00:44:32,705
{\an1}we were uploading to GEDmatch.
845
00:44:33,838 --> 00:44:35,205
NARRATOR:
Steve has teamed up
846
00:44:35,238 --> 00:44:36,605
{\an1}with a genetic genealogist
847
00:44:36,638 --> 00:44:39,871
{\an1}in California, CeCe Moore.
848
00:44:39,905 --> 00:44:41,305
MOORE:
On Saturday morning,
849
00:44:41,338 --> 00:44:44,705
{\an7}I rolled out of bedbefore
I even put my contact in,
850
00:44:44,738 --> 00:44:48,571
{\an7}and flipped open my laptop to
see if we had that match list.
851
00:44:48,605 --> 00:44:49,805
And we did.
852
00:44:49,838 --> 00:44:55,571
{\an1}GEDmatch shows two people
who each share around 3%
853
00:44:55,605 --> 00:44:59,005
{\an1}with the unknown suspect.
854
00:44:59,038 --> 00:45:03,405
{\an1}So to have two people that
shared about 3% of their DNA
855
00:45:03,438 --> 00:45:05,805
{\an1}or enough to be a second cousin
with the suspect
856
00:45:05,838 --> 00:45:08,338
{\an1}did feel like getting struck
by lightning.
857
00:45:08,371 --> 00:45:12,105
{\an1}Second cousins will share
858
00:45:12,138 --> 00:45:13,638
{\an1}a set of great-grandparents,
859
00:45:13,671 --> 00:45:15,114
{\an1}and that's not that far back
in the tree.
860
00:45:15,138 --> 00:45:16,571
In genealogy,
861
00:45:16,605 --> 00:45:20,171
{\an1}I can almost always get backto
someone's great-grandparents.
862
00:45:20,205 --> 00:45:27,105
NARRATOR:
One of CeCe's two top matches
is Chelsea Rustad.
863
00:45:27,138 --> 00:45:32,171
{\an1}The other is a cousin
who'snever been publicly identified.
864
00:45:32,205 --> 00:45:35,071
{\an7}They both share DNA
with the suspect.
865
00:45:35,105 --> 00:45:38,638
{\an7}But don't share any
with each other.
866
00:45:38,671 --> 00:45:40,805
{\an7}That meant that they represented
different branches
867
00:45:40,838 --> 00:45:42,905
{\an1}of the suspect's family tree.
868
00:45:42,938 --> 00:45:44,838
{\an1}I really lucked out.
869
00:45:44,871 --> 00:45:50,238
{\an1}I found an obituary from a woman
who was carrying the surname
870
00:45:50,271 --> 00:45:53,738
{\an1}that I had just seen in
the other match's family tree.
871
00:45:53,771 --> 00:45:54,971
So that told me
872
00:45:55,005 --> 00:45:56,938
{\an1}we have a woman from this tree
873
00:45:56,971 --> 00:45:59,605
{\an1}and a man from this tree
who have married.
874
00:45:59,638 --> 00:46:01,238
{\an1}And hopefully had children.
875
00:46:01,271 --> 00:46:05,738
NARRATOR:
CeCe knows that if they did,
those children would carry
876
00:46:05,771 --> 00:46:10,205
{\an1}a mix of DNA very similar
to that of the suspect.
877
00:46:10,238 --> 00:46:13,805
{\an1}The couple had four children.
878
00:46:13,838 --> 00:46:18,138
{\an1}We got really lucky that therewas
only one male in this family
879
00:46:18,171 --> 00:46:21,605
{\an1}because the genetic genealogy
was pointing at one person
880
00:46:21,638 --> 00:46:23,105
{\an1}and only one person,
881
00:46:23,138 --> 00:46:25,405
{\an8}and that was
William Earl Talbott II.
882
00:46:25,438 --> 00:46:28,738
{\an8}♪
883
00:46:30,205 --> 00:46:32,238
NARRATOR:
At the time of the murders,
884
00:46:32,271 --> 00:46:34,771
{\an1}Talbott lived a few miles
from the bridge
885
00:46:34,805 --> 00:46:38,838
{\an1}where Jay Cook's body was found.
886
00:46:38,871 --> 00:46:41,871
Now, he is 55.
887
00:46:41,905 --> 00:46:43,305
A truck driver.
888
00:46:43,338 --> 00:46:46,505
{\an1}The police follow him.
889
00:46:46,538 --> 00:46:49,305
{\an1}They want his DNA
890
00:46:49,338 --> 00:46:50,705
{\an1}to see if it matches the DNA
891
00:46:50,738 --> 00:46:53,771
{\an1}from the crime scene.
892
00:46:53,805 --> 00:46:56,138
{\an1}One day they get lucky.
893
00:46:56,171 --> 00:47:00,271
{\an1}A drinking cup falls out
of his truck.
894
00:47:00,305 --> 00:47:02,838
{\an1}Jim Scharf brings the cup
895
00:47:02,871 --> 00:47:05,038
{\an1}to the Washington State Patrol
Crime Lab
896
00:47:05,071 --> 00:47:07,338
for STR testing.
897
00:47:07,371 --> 00:47:11,805
{\an1}Lab supervisor Lisa Collins
asks him to wait.
898
00:47:11,838 --> 00:47:14,771
{\an1}Soon, she returns.
899
00:47:14,805 --> 00:47:18,738
SCHARF:
Lisa turned and handed me
the report and said,
900
00:47:18,771 --> 00:47:20,205
{\an8}"Jim, it's him.
901
00:47:20,238 --> 00:47:22,071
{\an7}There's a match."
902
00:47:22,105 --> 00:47:24,938
{\an7}And I couldn't believe it.
903
00:47:24,971 --> 00:47:27,405
{\an7}My eyes teared up.
904
00:47:27,438 --> 00:47:29,471
{\an1}I yelled out a scream.
905
00:47:29,505 --> 00:47:31,105
{\an1}"This is wonderful.
906
00:47:31,138 --> 00:47:33,638
{\an1}We finally got this guy."
907
00:47:36,238 --> 00:47:39,138
NARRATOR:
On May 17, 2018,
908
00:47:39,171 --> 00:47:41,271
{\an1}William Earl Talbott II
909
00:47:41,305 --> 00:47:44,271
{\an1}is arrested on a charge
of first degree murder
910
00:47:44,305 --> 00:47:48,505
{\an1}for a 31-year-old crime.
911
00:47:48,538 --> 00:47:51,205
{\an7}He's a man who was identified
912
00:47:51,238 --> 00:47:54,738
{\an7}not because he took a DNA test,
913
00:47:54,771 --> 00:47:56,605
{\an1}but because a relative did.
914
00:47:56,638 --> 00:47:59,305
{\an1}Someone he'd never even met.
915
00:48:01,005 --> 00:48:05,971
{\an1}In June 2019, the jury
delivers its verdict.
916
00:48:06,005 --> 00:48:09,071
{\an8}JUROR:
We the jury find the defendant
William Earl Talbott II
917
00:48:09,105 --> 00:48:11,338
{\an7}guilty of the crime
of first degree murder
918
00:48:11,371 --> 00:48:13,671
{\an7}as charged in count one.
919
00:48:13,705 --> 00:48:17,738
NARRATOR: Talbott is the first
suspectidentified by genetic genealogy
920
00:48:17,771 --> 00:48:21,338
ever to be convicted by a jury.
921
00:48:21,371 --> 00:48:22,438
He is soon sentenced
922
00:48:22,471 --> 00:48:26,505
{\an1}to two consecutive life terms
in prison.
923
00:48:26,538 --> 00:48:28,671
{\an1}It has been reiterated to me
924
00:48:28,705 --> 00:48:31,171
so many times
by the investigators
925
00:48:31,205 --> 00:48:35,405
{\an1}that they wouldn't have come
this far without my DNA.
926
00:48:35,438 --> 00:48:37,571
{\an1}It would have been
dead in the water.
927
00:48:37,605 --> 00:48:41,338
NARRATOR:
Since Talbott's conviction,
the Parabon team has used
928
00:48:41,371 --> 00:48:43,871
{\an1}genetic genealogy to identify
929
00:48:43,905 --> 00:48:47,338
{\an1}more than a hundred
criminal suspects.
930
00:48:47,371 --> 00:48:50,538
{\an1}But just being named
by a genealogist isn't enough
931
00:48:50,571 --> 00:48:51,805
{\an1}to get a person arrested.
932
00:48:51,838 --> 00:48:56,305
SCHARF: We have to get confirmation DNA
933
00:48:56,338 --> 00:48:59,605
{\an1}using STR testing
before we have probable cause
934
00:48:59,638 --> 00:49:01,905
{\an1}to make an arrest.
935
00:49:01,938 --> 00:49:06,805
NARRATOR:
Even so, to critics,
the use of genetic genealogy
936
00:49:06,838 --> 00:49:10,805
{\an1}by law enforcement
raises privacy questions.
937
00:49:10,838 --> 00:49:14,305
NELSON:
Do we want to catch people who
have committed heinous crimes?
938
00:49:14,338 --> 00:49:16,071
Absolutely, yes.
939
00:49:16,105 --> 00:49:19,005
But what DNA profiles are being
trolled through?
940
00:49:19,038 --> 00:49:21,838
{\an7}What failed attempts
to find suspects
941
00:49:21,871 --> 00:49:22,971
{\an1}are we not hearing about
942
00:49:23,005 --> 00:49:25,038
{\an1}and the data violations
and privacy violations
943
00:49:25,071 --> 00:49:26,571
{\an1}that happen along the way?
944
00:49:26,605 --> 00:49:30,771
NARRATOR:
The genetic genealogy team
at Parabon says the fears
945
00:49:30,805 --> 00:49:32,805
are exaggerated.
946
00:49:32,838 --> 00:49:34,171
GREYTAK:
People have control
947
00:49:34,205 --> 00:49:38,005
{\an7}over whether their DNA is used
in these investigations.
948
00:49:38,038 --> 00:49:41,371
{\an7}Simply taking a DNA test
at 23andMe, at Ancestry,
949
00:49:41,405 --> 00:49:44,905
{\an1}your DNA is in their
private database.
950
00:49:44,938 --> 00:49:49,305
NARRATOR:
But there's little regulation,
and policies vary.
951
00:49:49,338 --> 00:49:55,205
{\an1}In 2019, FamilyTreeDNA
apologized for letting the FBI
952
00:49:55,238 --> 00:49:57,838
{\an1}search its database
for people who share DNA
953
00:49:57,871 --> 00:50:01,838
{\an1}with crime scene samples
without customers' permission.
954
00:50:01,871 --> 00:50:03,471
{\an1}FamilyTreeDNA and GEDmatch
955
00:50:03,505 --> 00:50:08,738
{\an1}both now say they only do so
with explicit permission.
956
00:50:08,771 --> 00:50:12,171
{\an1}And another worry:
consumer DNA companies,
957
00:50:12,205 --> 00:50:17,771
{\an1}like any that collect data,
are vulnerable to hackers.
958
00:50:17,805 --> 00:50:23,738
{\an1}Yet the risks are clearly
not deterring everyone.
959
00:50:23,771 --> 00:50:27,605
{\an1}No one is forcing anyone to take
a DNA test.
960
00:50:27,638 --> 00:50:32,505
{\an7}If your paranoia,
and fear of Big Brother
961
00:50:32,538 --> 00:50:35,371
{\an7}is greater than your interest
962
00:50:35,405 --> 00:50:38,338
{\an1}in reading the medical
and history book
963
00:50:38,371 --> 00:50:41,871
{\an1}written into your cells, then
Ithink that you should not test.
964
00:50:41,905 --> 00:50:44,038
♪
965
00:50:44,071 --> 00:50:46,505
{\an1}There's beauty in, you know,
understanding where you're from,
966
00:50:46,538 --> 00:50:47,581
{\an1}and then searching for that.
967
00:50:47,605 --> 00:50:50,005
NARRATOR:
The consumer DNA phenomenon
968
00:50:50,038 --> 00:50:53,338
is changing many people's lives
969
00:50:53,371 --> 00:50:55,771
{\an1}by revealing the secrets
that lie hidden
970
00:50:55,805 --> 00:50:58,871
{\an1}deep inside ourselves.
971
00:50:58,905 --> 00:51:04,805
{\an1}But are its benefits worth
its cost and risks?
972
00:51:04,838 --> 00:51:07,205
{\an7}Do I want to know that I'm at
risk for Alzheimer's
973
00:51:07,238 --> 00:51:10,971
{\an7}when there's absolutely nothing
I can do about it?
974
00:51:11,005 --> 00:51:12,271
Maybe not.
975
00:51:12,305 --> 00:51:15,971
SHAPIRO:
With these DNA tests
as popular as they are,
976
00:51:16,005 --> 00:51:17,171
the chances are
977
00:51:17,205 --> 00:51:19,505
{\an1}that everyone who has had
a secret of this nature
978
00:51:19,538 --> 00:51:21,871
kept from them
is gonna find out.
979
00:51:21,905 --> 00:51:28,271
{\an7}Our hearts and our minds don't
know fully how to grapple with
980
00:51:28,305 --> 00:51:30,505
{\an7}what we're being asked
to grapple with.
981
00:51:31,971 --> 00:51:37,905
LAWTON: I think the surge in DNA testing
over the last 20 years
982
00:51:37,938 --> 00:51:40,338
{\an7}has opened people's minds
to the possibility
983
00:51:40,371 --> 00:51:43,705
{\an7}that they share more
with other people
984
00:51:43,738 --> 00:51:45,405
{\an7}than what they thought they did.
985
00:51:45,438 --> 00:51:48,471
{\an7}That 1% that makes us different
986
00:51:48,505 --> 00:51:53,605
{\an7}is really just the beautifuldiversity
in the natural world.
987
00:51:53,638 --> 00:51:56,271
{\an1}And it's not that
one genotype or genome
988
00:51:56,305 --> 00:51:57,605
{\an1}is better than another.
989
00:51:57,638 --> 00:51:59,405
{\an1}It's just they're beautifully
different.
990
00:51:59,438 --> 00:52:01,371
{\an7}The more we are tested,
991
00:52:01,405 --> 00:52:04,905
{\an7}the more we see how connected
we are to each other.
992
00:52:04,938 --> 00:52:07,905
{\an1}And perhaps, if we see that
we're connected to each other,
993
00:52:07,938 --> 00:52:10,471
{\an1}we'll treat each other
a little bit better.
994
00:52:10,505 --> 00:52:14,905
♪
995
00:52:41,171 --> 00:52:46,305
{\an8}♪
996
00:52:57,205 --> 00:53:01,538
{\an8}ANNOUNCER:
To order this program on DVD,
visit ShopPBS
997
00:53:01,571 --> 00:53:04,838
{\an7}or call 1-800-PLAY-PBS.
998
00:53:04,871 --> 00:53:07,571
{\an7}Episodes of "NOVA" are available
with Passport.
999
00:53:07,605 --> 00:53:11,105
{\an7}"NOVA" is also available
on Amazon Prime Video.
1000
00:53:11,138 --> 00:53:16,271
{\an8}♪
82453
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