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These are the user uploaded subtitles that are being translated: 1 00:00:06,805 --> 00:00:07,838 ♪ 2 00:00:07,871 --> 00:00:13,305 NARRATOR: A family secret exposed. 3 00:00:13,338 --> 00:00:16,605 DANI SHAPIRO: If my father wasn't my biological father, who was? 4 00:00:16,638 --> 00:00:19,205 {\an1}Something very, very important was kept from me. 5 00:00:19,238 --> 00:00:21,705 NARRATOR: A hidden legacy... 6 00:00:21,738 --> 00:00:23,871 revealed. 7 00:00:23,905 --> 00:00:27,971 TYQUINE GOLDEN: Somewhere in slavery that 20% might've been integrated 8 00:00:28,005 --> 00:00:29,071 with our DNA, 9 00:00:29,105 --> 00:00:31,271 {\an1}and that might not have been voluntary. 10 00:00:31,305 --> 00:00:33,871 NARRATOR: A life-threatening illness... 11 00:00:33,905 --> 00:00:36,338 prevented. 12 00:00:36,371 --> 00:00:38,405 JESSICA ALGAZI: They quite possibly saved my life. 13 00:00:38,438 --> 00:00:44,205 NARRATOR: And a decades-old murder finally solved. 14 00:00:45,038 --> 00:00:46,538 CHELSEA RUSTAD: Without my DNA, 15 00:00:46,571 --> 00:00:48,011 {\an1}it would have been dead in the water. 16 00:00:49,105 --> 00:00:50,781 NARRATOR: Just a few of the millions of stories 17 00:00:50,805 --> 00:00:53,405 {\an1}launched by one of the most popular 18 00:00:53,438 --> 00:00:57,938 {\an1}and promising new technologies... 19 00:00:57,971 --> 00:01:02,838 {\an1}consumer DNA testing. 20 00:01:02,871 --> 00:01:06,271 {\an1}With a swab, or a bit of spit, 21 00:01:06,305 --> 00:01:08,505 {\an1}some 30 million of us have turned over 22 00:01:08,538 --> 00:01:11,238 {\an1}our most personal information 23 00:01:11,271 --> 00:01:13,371 {\an1}hoping to discover 24 00:01:13,405 --> 00:01:14,938 {\an1}what's hidden inside us. 25 00:01:14,971 --> 00:01:17,805 {\an1}But what do the tests really deliver? 26 00:01:17,838 --> 00:01:20,605 {\an1}Spain, Portugal... 27 00:01:20,638 --> 00:01:21,938 {\an1}Norway?! 28 00:01:21,971 --> 00:01:24,205 NARRATOR: How good is the science? 29 00:01:24,238 --> 00:01:27,405 {\an1}And how are the tests changing our lives? 30 00:01:27,438 --> 00:01:28,781 JUNE SMITH: I just couldn't believe it. 31 00:01:28,805 --> 00:01:31,805 {\an1}I was on the phone with my older sister. 32 00:01:31,838 --> 00:01:34,738 NARRATOR: In search of clues... 33 00:01:34,771 --> 00:01:36,738 {\an1}"The Secrets in Our DNA," 34 00:01:36,771 --> 00:01:40,105 {\an1}right now, on "NOVA"! 35 00:01:40,138 --> 00:01:48,138 ♪ 36 00:01:55,071 --> 00:02:00,705 ♪ 37 00:02:01,638 --> 00:02:02,671 NARRATOR: It's a promise 38 00:02:02,705 --> 00:02:06,871 {\an1}many of us just can't resist. 39 00:02:06,905 --> 00:02:12,271 {\an7}Send in your DNA and unlock secrets about family... 40 00:02:12,838 --> 00:02:15,705 {\an8}...ancestry... 41 00:02:15,738 --> 00:02:17,805 {\an1}...and even health. 42 00:02:17,838 --> 00:02:21,771 {\an7}It's rare that something comes along that is truly new. 43 00:02:21,805 --> 00:02:24,171 {\an7}And this is something that's truly new. 44 00:02:25,438 --> 00:02:27,005 NARRATOR: But just how reliable 45 00:02:27,038 --> 00:02:28,538 {\an1}are consumer DNA tests, 46 00:02:28,571 --> 00:02:32,305 {\an1}and their scientific-looking ancestry percentages? 47 00:02:32,338 --> 00:02:33,638 ♪ 48 00:02:33,671 --> 00:02:38,271 {\an1}Should we worry about our privacy? 49 00:02:38,305 --> 00:02:41,905 {\an1}What are the unforeseen consequences when we reveal 50 00:02:41,938 --> 00:02:44,938 {\an1}the "Secrets in Our DNA"? 51 00:02:44,971 --> 00:02:50,138 ♪ 52 00:03:04,071 --> 00:03:05,671 {\an8}In the suburbs of Olympia, Washington, 53 00:03:05,705 --> 00:03:09,938 {\an1}one woman finds out just how unpredictable 54 00:03:09,971 --> 00:03:13,371 {\an1}those consequences can be. 55 00:03:13,405 --> 00:03:16,905 Chelsea Rustad, who works as an I.T. specialist, 56 00:03:16,938 --> 00:03:20,238 is an avid family historian. 57 00:03:20,271 --> 00:03:21,871 In 2015, 58 00:03:21,905 --> 00:03:24,071 she takes a test with the biggest 59 00:03:24,105 --> 00:03:27,971 {\an1}of the direct-to-consumer companies... AncestryDNA. 60 00:03:28,005 --> 00:03:29,238 RUSTAD: People end up 61 00:03:29,271 --> 00:03:31,838 {\an1}doing it oftentimes because, "I just wanna learn 62 00:03:31,871 --> 00:03:33,938 {\an1}about my ancestral background." 63 00:03:33,971 --> 00:03:36,705 {\an1}But then something else pops up that they really 64 00:03:36,738 --> 00:03:38,305 {\an7}were not expecting at all, 65 00:03:38,338 --> 00:03:39,547 {\an7}and that's exactly what this was for me. 66 00:03:39,571 --> 00:03:41,571 NARRATOR: The test results 67 00:03:41,605 --> 00:03:43,805 {\an1}suggest that Chelsea is mostly of Norwegian 68 00:03:43,838 --> 00:03:46,471 {\an1}and German ancestry. 69 00:03:46,505 --> 00:03:50,905 {\an1}Then, because she's also curious to find new relatives, 70 00:03:50,938 --> 00:03:54,105 {\an1}she downloads her raw file from Ancestry, 71 00:03:54,138 --> 00:03:58,805 {\an1}and uploads it to a free website called GEDmatch. 72 00:03:58,838 --> 00:04:01,005 {\an1}It's a place where anyone 73 00:04:01,038 --> 00:04:04,338 {\an1}can search for matches no matter what company they tested with. 74 00:04:06,371 --> 00:04:09,238 {\an1}GEDmatch shows Chelsea everyone else on the site 75 00:04:09,271 --> 00:04:12,671 {\an1}who shares DNA with her. 76 00:04:12,705 --> 00:04:15,071 RUSTAD: It's kind of humbling 77 00:04:15,105 --> 00:04:17,071 {\an1}and interesting to see those interconnections, 78 00:04:17,105 --> 00:04:20,538 {\an1}to realize the sheer number of people that we share 79 00:04:20,571 --> 00:04:23,105 {\an1}some percentage of DNA with and don't even realize it. 80 00:04:23,138 --> 00:04:28,438 NARRATOR: On GEDmatch, Chelsea sees an aunt whom she knows, 81 00:04:28,471 --> 00:04:30,971 {\an1}but no new close relatives. 82 00:04:31,005 --> 00:04:32,305 (clicks) 83 00:04:32,338 --> 00:04:35,938 She logs off, and doesn't check the site again. 84 00:04:35,971 --> 00:04:38,038 {\an1}(birds twittering) 85 00:04:38,071 --> 00:04:40,605 {\an1}Three years go by. 86 00:04:40,638 --> 00:04:45,205 {\an1}And then, on the evening of May 17, 2018, 87 00:04:45,238 --> 00:04:48,938 {\an1}Chelsea gets some unexpected visitors. 88 00:04:48,971 --> 00:04:50,281 RUSTAD: I look through the peephole 89 00:04:50,305 --> 00:04:53,971 and see that there are two cops waiting outside there. 90 00:04:54,005 --> 00:04:57,371 {\an1}And when I opened the door, they introduced themselves 91 00:04:57,405 --> 00:05:00,638 {\an1}as investigators who are looking into a homicide 92 00:05:00,671 --> 00:05:05,138 {\an1}that was a cold case from 31 years ago. 93 00:05:05,171 --> 00:05:08,171 NARRATOR: They've come to her door as a result of that DNA file 94 00:05:08,205 --> 00:05:10,505 {\an1}she posted on GEDmatch. 95 00:05:10,538 --> 00:05:14,605 {\an1}To her amazement, they tell her that her DNA 96 00:05:14,638 --> 00:05:17,405 {\an1}has led them to a suspect. 97 00:05:17,438 --> 00:05:22,671 ♪ 98 00:05:22,705 --> 00:05:26,938 {\an1}It was just really a lotto take in and really shocking. 99 00:05:26,971 --> 00:05:28,905 {\an1}Every step of what they explained to me 100 00:05:28,938 --> 00:05:29,905 {\an1}is a horror story. 101 00:05:29,938 --> 00:05:33,938 ♪ 102 00:05:33,971 --> 00:05:36,571 {\an1}(leaves and branches rustling) 103 00:05:36,605 --> 00:05:38,471 NARRATOR: Chelsea's hopeful search for relatives 104 00:05:38,505 --> 00:05:40,205 {\an1}has taken a dark turn... 105 00:05:40,238 --> 00:05:42,771 {\an1}into the hunt for a killer. 106 00:05:44,071 --> 00:05:48,571 {\an1}Someone she's related to. 107 00:05:51,005 --> 00:05:53,405 {\an1}Though her story is unusual, it shows that 108 00:05:53,438 --> 00:05:55,771 {\an1}consumer DNA companies can fulfill 109 00:05:55,805 --> 00:05:58,371 {\an1}one of their biggest promises 110 00:05:58,405 --> 00:06:01,671 extremely well: connecting us to our relatives. 111 00:06:01,705 --> 00:06:05,938 ♪ 112 00:06:05,971 --> 00:06:08,205 {\an1}Direct-to-consumer, 113 00:06:08,238 --> 00:06:10,471 {\an1}or DTC DNA testing, 114 00:06:10,505 --> 00:06:12,538 {\an1}is a billion-dollar business 115 00:06:12,571 --> 00:06:15,738 {\an1}made possible by the simple rules of heredity. 116 00:06:15,771 --> 00:06:17,905 CECE MOORE: We inherit our DNA 117 00:06:17,938 --> 00:06:20,038 {\an1}from both of our parents. 118 00:06:20,071 --> 00:06:22,905 {\an1}50% from mom, 50% from dad. 119 00:06:22,938 --> 00:06:25,471 {\an7}And they inherit it from their parents. 120 00:06:25,505 --> 00:06:28,838 {\an7}And their parents, of course, inherited it from their parents. 121 00:06:28,871 --> 00:06:34,038 NARRATOR: Our parents each contribute about 50% to our DNA. 122 00:06:34,071 --> 00:06:38,271 {\an1}And the same is true for them and their parents. 123 00:06:38,305 --> 00:06:41,605 {\an1}So the amount of DNA we inherit from any ancestor 124 00:06:41,638 --> 00:06:46,071 {\an1}drops by half with each preceding generation. 125 00:06:46,105 --> 00:06:49,938 {\an1}We also share DNA with anyone who shares a common ancestor 126 00:06:49,971 --> 00:06:54,371 {\an1}with us: siblings, half-siblings, first cousins, 127 00:06:54,405 --> 00:06:56,538 {\an1}second cousins and so on. 128 00:06:56,571 --> 00:07:00,305 ♪ 129 00:07:00,338 --> 00:07:03,405 The way that the DTCs determine those relationships 130 00:07:03,438 --> 00:07:06,071 {\an1}is by comparing people's DNA. 131 00:07:06,105 --> 00:07:09,171 {\an1}The amount that is shared is measured in a unit 132 00:07:09,205 --> 00:07:12,738 {\an1}called centimorgans. 133 00:07:12,771 --> 00:07:14,181 {\an1}The more centimorgans two people share, 134 00:07:14,205 --> 00:07:16,171 {\an1}the closer they are related. 135 00:07:16,205 --> 00:07:18,538 {\an1}And the fewer centimorgans they share, 136 00:07:18,571 --> 00:07:20,938 {\an1}the more distantly related they are. 137 00:07:22,205 --> 00:07:25,505 NARRATOR: But with the DTCs, a relationship to someone 138 00:07:25,538 --> 00:07:29,838 {\an1}can't always be determined just by counting centimorgans. 139 00:07:29,871 --> 00:07:32,738 {\an1}Because the numbers fall within ranges. 140 00:07:32,771 --> 00:07:35,405 {\an1}You might share the same number with a cousin, 141 00:07:35,438 --> 00:07:37,905 {\an1}and a great-uncle, for example. 142 00:07:37,938 --> 00:07:40,371 {\an1}Just because you have an amount of shared DNA doesn't mean 143 00:07:40,405 --> 00:07:45,305 {\an7}you actually know for sure what that person's relationship is, 144 00:07:45,338 --> 00:07:46,738 {\an1}it's just a probability... 145 00:07:46,771 --> 00:07:49,638 {\an1}a spectrum of possible relationships. 146 00:07:51,105 --> 00:07:55,771 NARRATOR: June Smith lives in New Jersey, not far from Philadelphia. 147 00:07:55,805 --> 00:07:59,638 In 2018, she takes a consumer DNA test, 148 00:07:59,671 --> 00:08:03,671 hoping to solve a longstanding mystery. 149 00:08:03,705 --> 00:08:08,938 She's spent years searching for her roots. 150 00:08:08,971 --> 00:08:11,638 {\an1}When June was 16, growing up in Philadelphia, 151 00:08:11,671 --> 00:08:16,605 {\an1}the woman she knew as her mother revealed a secret. 152 00:08:16,638 --> 00:08:20,871 {\an7}She said, "Your mother was a white woman," 153 00:08:20,905 --> 00:08:22,938 {\an7}and I said, "A white woman?" 154 00:08:22,971 --> 00:08:25,205 {\an7}which was totally shocking to me. 155 00:08:25,238 --> 00:08:30,271 {\an1}Her biological mother's name was Ann D'Amico. 156 00:08:30,305 --> 00:08:34,038 {\an1}June has never learned the identity of her father. 157 00:08:34,071 --> 00:08:37,371 {\an1}When June takes her test 158 00:08:37,405 --> 00:08:39,605 {\an1}with AncestryDNA, she checks the box 159 00:08:39,638 --> 00:08:43,038 {\an1}asking to be linked to any customers with whom 160 00:08:43,071 --> 00:08:46,238 she shares DNA. 161 00:08:46,271 --> 00:08:49,338 {\an1}Though she knows Ann has died, 162 00:08:49,371 --> 00:08:53,838 {\an1}there's someone else she desperately wants to find. 163 00:08:53,871 --> 00:08:57,805 {\an1}While digging into Ann's life story, June learned that 164 00:08:57,838 --> 00:09:01,771 {\an1}she'd given birth to another biracial daughter, 165 00:09:01,805 --> 00:09:03,971 {\an1}who had a different father. 166 00:09:04,005 --> 00:09:07,038 {\an1}A girl named Joan Moser, 167 00:09:07,071 --> 00:09:09,771 {\an1}June's older half-sister. 168 00:09:09,805 --> 00:09:11,738 {\an1}I set out to search for her. 169 00:09:11,771 --> 00:09:13,871 {\an1}And I would go on websites, I would do 170 00:09:13,905 --> 00:09:17,538 {\an1}all kind of people searches looking for Joan Moser. 171 00:09:17,571 --> 00:09:20,805 {\an1}But we could never come up with her. 172 00:09:20,838 --> 00:09:24,538 NARRATOR: One day, June receives a message on her Ancestry page, 173 00:09:24,571 --> 00:09:27,305 {\an1}telling her she has a new match 174 00:09:27,338 --> 00:09:29,071 {\an1}with a close relative... 175 00:09:29,105 --> 00:09:33,338 {\an1}a woman named Sigrid Gilchrist. 176 00:09:33,371 --> 00:09:35,205 {\an1}She'd also grown up in Philadelphia, 177 00:09:35,238 --> 00:09:36,971 {\an1}the only child of a Black couple 178 00:09:37,005 --> 00:09:39,938 {\an1}active in the civil rights movement. 179 00:09:41,905 --> 00:09:45,305 {\an1}But at 16, Sigrid learned a long-hidden truth 180 00:09:45,338 --> 00:09:47,971 from her mother. 181 00:09:48,005 --> 00:09:50,571 {\an7}She told me I was adopted. 182 00:09:50,605 --> 00:09:54,438 {\an7}That my mother was Italian and my father was Black. 183 00:09:54,471 --> 00:09:56,738 It was crushing. 184 00:09:56,771 --> 00:09:58,571 I had no idea. 185 00:09:58,605 --> 00:10:01,105 NARRATOR: In the years that followed, 186 00:10:01,138 --> 00:10:02,371 {\an1}Sigrid never connected 187 00:10:02,405 --> 00:10:05,038 with any of her biological relatives. 188 00:10:05,071 --> 00:10:09,338 {\an1}Until, by pure chance, right around the time 189 00:10:09,371 --> 00:10:14,038 {\an1}that June tests with Ancestry, Sigrid does too. 190 00:10:14,071 --> 00:10:16,638 {\an1}Ancestry reports that the two women, 191 00:10:16,671 --> 00:10:22,071 {\an1}who share 1,641 centimorgans, may be first cousins. 192 00:10:22,105 --> 00:10:25,105 {\an1}But June can't help wondering: 193 00:10:25,138 --> 00:10:29,538 {\an1}might Sigrid be someone even closer? 194 00:10:32,071 --> 00:10:33,071 {\an1}The two women agree 195 00:10:33,105 --> 00:10:35,338 {\an1}to talk on the phone. 196 00:10:35,371 --> 00:10:38,071 {\an1}She said, "I have three questions to ask you." 197 00:10:38,105 --> 00:10:39,538 I said, "Okay." 198 00:10:39,571 --> 00:10:41,938 {\an1}I said, "Were you adopted?" 199 00:10:41,971 --> 00:10:44,971 {\an1}She said, "I was." 200 00:10:45,005 --> 00:10:47,505 {\an1}I said, "Are you biracial?" 201 00:10:47,538 --> 00:10:49,871 {\an1}She said, "I am." 202 00:10:49,905 --> 00:10:53,705 {\an1}I said, "Would your birth mothername happen to be Ann D'Amico?" 203 00:10:53,738 --> 00:10:58,005 {\an1}I said, "Yes, that was her name, my biological mother." 204 00:10:58,038 --> 00:11:00,738 {\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." 206 00:11:04,338 --> 00:11:07,771 {\an1}I said, "Oh my God, you're my sister. 207 00:11:07,805 --> 00:11:09,838 {\an1}You're not my cousin." 208 00:11:09,871 --> 00:11:12,371 {\an1}We cried and I just couldn't believe it. 209 00:11:12,405 --> 00:11:15,738 {\an1}I was on the phone with my older sister. 210 00:11:18,671 --> 00:11:20,571 Yes. 211 00:11:20,605 --> 00:11:24,971 JOHNSON: It was just like we've known each other forever. 212 00:11:25,005 --> 00:11:29,838 {\an1}One-on-one spirit feeling that you can't describe. 213 00:11:29,871 --> 00:11:33,038 ♪ 214 00:11:33,071 --> 00:11:35,105 SMITH: Finding my sister gave me 215 00:11:35,138 --> 00:11:38,638 {\an1}a sense of belonging. 216 00:11:38,671 --> 00:11:42,138 {\an1}It gave me a sense of saying, 217 00:11:42,171 --> 00:11:44,338 "Hey, you know, we got the same blood." 218 00:11:44,371 --> 00:11:46,105 But I do see... 219 00:11:46,138 --> 00:11:47,371 Looks like me... you. 220 00:11:47,405 --> 00:11:48,671 Yes. Mm-hmm. 221 00:11:48,705 --> 00:11:50,838 Look at the chin.Yeah. I can tell. 222 00:11:50,871 --> 00:11:53,905 It's good havingan older sister. 223 00:11:53,938 --> 00:11:56,405 I don't like being older, but it's okay. 224 00:11:56,438 --> 00:12:01,605 (laughing): I love having a younger sister. 225 00:12:01,638 --> 00:12:02,971 She understands. 226 00:12:03,005 --> 00:12:04,471 Yeah, yeah. 227 00:12:04,505 --> 00:12:07,105 ♪ 228 00:12:07,138 --> 00:12:09,171 NARRATOR: People like Sigrid and June 229 00:12:09,205 --> 00:12:11,771 {\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, 232 00:12:21,138 --> 00:12:24,705 {\an1}which we carry in almost every cell in our body, 233 00:12:24,738 --> 00:12:29,205 {\an1}contains the code that directs our lives. 234 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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