TEDMED 2018
Yaniv Erlich: How we're building the world's largest family tree
亞尼夫 · 厄里奇: 我們如何建造世界上最大的家譜樹
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計算遺傳學家亞尼夫 · 厄里奇 (Yaniv Erlich) 協助打造了世界上最大的家譜——上面有一千三百萬人，可追溯到五百年前。他與我們分享這個迷人的人類家譜圖騰——裡面涵蓋著我們的愛情生活、健康，甚至數十年未破的刑事案件——並說明眾包的系譜學資料庫如何不只能照亮過去，也能照亮未來。
Yaniv Erlich - Computational geneticist
Yaniv Erlich is fascinated by the connection between DNA and data. Full bio
Yaniv Erlich is fascinated by the connection between DNA and data. Full bio
Double-click the English transcript below to play the video.
00:12
People use the internet
for various reasons.
for various reasons.
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人們因各種原因使用網際網路。
00:17
It turns out that one of the most
popular categories of website
popular categories of website
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結果發現，最熱門的網站類型之一
00:21
is something that people
typically consume in private.
typically consume in private.
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是人們私下瀏覽的東西。
00:25
It involves curiosity,
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它和好奇心有關，
00:28
non-insignificant levels
of self-indulgence
of self-indulgence
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和看不太出來但又明顯的
放蕩不羈程度有關，
放蕩不羈程度有關，
00:31
and is centered around recording
the reproductive activities
the reproductive activities
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整天沉浸在記錄別人
繁殖活動的圈圈裡。
繁殖活動的圈圈裡。
00:35
of other people.
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00:36
(Laughter)
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（笑聲）
00:37
Of course, I'm talking about genealogy --
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當然，我在說的是家譜學——
00:39
(Laughter)
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（笑聲）
00:41
the study of family history.
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家族史的研究。
00:43
When it comes to detailing family history,
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說到詳細的家族歷史，
00:45
in every family, we have this person
that is obsessed with genealogy.
that is obsessed with genealogy.
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在每個家庭中，都會
有一個人特別迷戀家譜。
有一個人特別迷戀家譜。
00:49
Let's call him Uncle Bernie.
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咱們就稱他為柏尼叔叔吧。
00:51
Uncle Bernie is exactly the last person
you want to sit next to
you want to sit next to
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感恩節晚餐時，你最不希望
坐到的位子
就是柏尼叔叔的旁邊，
就是柏尼叔叔的旁邊，
00:54
in Thanksgiving dinner,
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00:56
because he will bore you to death
with peculiar details
with peculiar details
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因為他會一直講某個
古老親戚的獨特細節，
古老親戚的獨特細節，
00:59
about some ancient relatives.
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講到讓你無聊死。
01:02
But as you know,
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但，各位都知道，
01:03
there is a scientific side for everything,
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凡事都有科學的一面，
01:06
and we found that Uncle Bernie's stories
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而我們發現，柏尼叔叔的故事
01:09
have immense potential
for biomedical research.
for biomedical research.
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非常有潛力可以用在
生物醫學研究上。
生物醫學研究上。
01:13
We let Uncle Bernie
and his fellow genealogists
and his fellow genealogists
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我們讓柏尼叔叔
和他的家譜學者夥伴們
和他的家譜學者夥伴們
01:16
document their family trees through
a genealogy website called geni.com.
a genealogy website called geni.com.
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透過家譜網站 geni.com
來記錄他們的家譜。
來記錄他們的家譜。
01:21
When users upload
their trees to the website,
their trees to the website,
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當使用者將他們的家譜
上傳到該網站，
上傳到該網站，
01:23
it scans their relatives,
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網站會掃描他們的親戚，
01:25
and if it finds matches to existing trees,
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如果發現和既有的家譜樹有吻合，
01:27
it merges the existing
and the new tree together.
and the new tree together.
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就會把既有的家譜
和那新的家譜合併起來。
和那新的家譜合併起來。
01:31
The result is that large
family trees are created,
family trees are created,
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結果就是建造出了很大的家譜，
01:34
beyond the individual level
of each genealogist.
of each genealogist.
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超越了家譜學者
個人能做到的程度。
個人能做到的程度。
01:38
Now, by repeating this process
with millions of people
with millions of people
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如今，針對全世界數百萬人
重覆這個流程，
01:42
all over the world,
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01:44
we can crowdsource the construction
of a family tree of all humankind.
of a family tree of all humankind.
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我們就能將全人類的家譜
外包給群眾來做。
外包給群眾來做。
01:51
Using this website,
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我們用這個網站，
01:52
we were able to connect 125 million people
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將一億兩千五百萬人連結起來，
01:57
into a single family tree.
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成為單一家譜樹。
02:00
I cannot draw the tree
on the screens over here
on the screens over here
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我無法在這裡的螢幕上
畫出這個家譜樹，
畫出這個家譜樹，
02:03
because they have less pixels
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因為這個家譜樹中的人數
02:05
than the number of people in this tree.
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比螢幕的畫素還要多。
02:08
But here is an example of a subset
of 6,000 individuals.
of 6,000 individuals.
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但，可以取其中一部分
六千人的家譜給各位看。
六千人的家譜給各位看。
02:14
Each green node is a person.
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每個綠色節點代表一個人。
02:17
The red nodes represent marriages,
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紅色節點代表婚姻關係，
02:19
and the connections represent parenthood.
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連線則代表親子關係。
02:22
In the middle of this tree,
you see the ancestors.
you see the ancestors.
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在家譜的中間可以看到祖先。
02:24
And as we go to the periphery,
you see the descendants.
you see the descendants.
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在外圍則是後代。
這個家譜樹大約涵蓋了七個世代。
02:27
This tree has seven
generations, approximately.
generations, approximately.
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02:31
Now, this is what happens
when we increase the number of individuals
when we increase the number of individuals
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當我們把人數增加到七萬人時，
02:34
to 70,000 people --
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就會變成這樣——
02:36
still a tiny subset
of all the data that we have.
of all the data that we have.
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相對我們所有的資料，
這仍然只是冰山一角。
這仍然只是冰山一角。
02:41
Despite that, you can already see
the formation of gigantic family trees
the formation of gigantic family trees
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儘管如此，各位已經可以
看出有巨大的家譜樹形成了，
看出有巨大的家譜樹形成了，
02:46
with many very distant relatives.
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當中有許多遠親。
02:49
Thanks to the hard work
of our genealogists,
of our genealogists,
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仰賴家譜學者的努力，
02:52
we can go back in time
hundreds of years ago.
hundreds of years ago.
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我們可以回到數百年前。
02:56
For example, here is Alexander Hamilton,
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比如，這是亞歷山大 · 漢密爾頓，
02:59
who was born in 1755.
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生於 1755 年。
03:02
Alexander was the first
US Secretary of the Treasury,
US Secretary of the Treasury,
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亞歷山大是美國第一位財政部長，
03:06
but mostly known today
due to a popular Broadway musical.
due to a popular Broadway musical.
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但主要由於一部流行的
百老匯音樂劇而廣為人知。
百老匯音樂劇而廣為人知。
03:11
We found that Alexander has deeper
connections in the showbiz industry.
connections in the showbiz industry.
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我們發現亞歷山大
在娛樂圈有更深厚的人脈。
在娛樂圈有更深厚的人脈。
03:16
In fact, he's a blood relative of ...
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事實上，他是……
03:18
Kevin Bacon!
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凱文貝肯的血親！
03:20
(Laughter)
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（笑聲）
03:22
Both of them are descendants
of a lady from Scotland
of a lady from Scotland
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他們兩人都是十三世紀
03:24
who lived in the 13th century.
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一位蘇格蘭女子的後裔。
03:27
So you can say that Alexander Hamilton
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所以，可以說亞歷山大漢密爾頓
03:30
is 35 degrees of Kevin Bacon genealogy.
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是凱文貝肯的三十五度宗譜。
（改自「六度分離」）
（改自「六度分離」）
03:33
(Laughter)
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（笑聲）
03:34
And our tree has millions
of stories like that.
of stories like that.
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我們的家譜樹有數百萬個
像這樣的故事。
像這樣的故事。
03:40
We invested significant efforts
to validate the quality of our data.
to validate the quality of our data.
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我們投入許多心力
去驗證我們資料的品質。
去驗證我們資料的品質。
03:45
Using DNA, we found that .3 percent of
the mother-child connections in our data
the mother-child connections in our data
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利用 DNA，我們發現，
我們的資料中有 0.3% 的
母子關係是錯的，
母子關係是錯的，
03:50
are wrong,
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03:51
which could match the adoption rate
in the US pre-Second World War.
in the US pre-Second World War.
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這很符合在二次大戰之前
美國的領養率。
美國的領養率。
03:56
For the father's side,
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就父系的這一面來說，
03:58
the news is not as good:
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狀況就沒這麼好了：
04:02
1.9 percent of the father-child
connections in our data are wrong.
connections in our data are wrong.
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我們的資料中，1.9% 的
父子關係是錯的。
父子關係是錯的。
04:07
And I see some people smirk over here.
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我看到這邊有些人在笑。
04:10
It is what you think --
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就如各位所想的——
04:11
there are many milkmen out there.
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世界上有很多師奶殺手級的男人。
04:13
(Laughter)
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（笑聲）
04:14
However, this 1.9 percent error rate
in patrilineal connections
in patrilineal connections
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然而，這 1.9% 的父子關係錯誤率
不是我們數據獨有的 。
04:18
is not unique to our data.
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04:20
Previous studies found
a similar error rate
a similar error rate
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過去用臨床等級家譜所做的研究，
04:23
using clinical-grade pedigrees.
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也有發現近似的錯誤率。
04:26
So the quality of our data is good,
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所以我們的資料品質算不錯，
04:28
and that should not be a surprise.
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那並不讓人意外。
04:30
Our genealogists have
a profound, vested interest
a profound, vested interest
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我們的系譜學家對正確記錄
他們的家族史有著濃厚的興趣。
04:34
in correctly documenting
their family history.
their family history.
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04:40
We can leverage this data to learn
quantitative information about humanity,
quantitative information about humanity,
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我們可以善用這些資料，
來了解人類的量化資訊，
來了解人類的量化資訊，
04:45
for example, questions about demography.
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比如，人口統計相關的問題。
04:47
Here is a look at all our profiles
on the map of the world.
on the map of the world.
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這是我們的資料在世界地圖上的樣子。
04:52
Each pixel is a person
that lived at some point.
that lived at some point.
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每一個畫素就是
活在某個時點的一個人。
活在某個時點的一個人。
04:56
And since we have so much data,
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因為我們有非常多資料，
04:58
you can see the contours
of many countries,
of many countries,
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各位可以看見許多國家的輪廓，
05:01
especially in the Western world.
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特別是西方世界的國家。
05:03
In this clip, we stratified
the map that I've showed you
the map that I've showed you
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在這段影片中，我們根據
1400~1900 年間出生的人，
1400~1900 年間出生的人，
05:06
based on the year of births of individuals
from 1400 to 1900,
from 1400 to 1900,
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將剛才那張地圖做分層，
05:12
and we compared it
to known migration events.
to known migration events.
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再將結果和已知的
移民事件做比對。
移民事件做比對。
05:15
The clip is going to show you
that the deepest lineages in our data
that the deepest lineages in our data
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這支影片會讓各位看到，
我們資料中最深遠的連結，
我們資料中最深遠的連結，
05:18
go all the way back to the UK,
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會一路連到記錄
保存得比較好的英國，
保存得比較好的英國，
05:20
where they had better record keeping,
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05:22
and then they spread along
the routes of Western colonialism.
the routes of Western colonialism.
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接著再隨西方殖民路線散播出去。
05:25
Let's watch this.
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咱們來看看影片。
05:27
(Music)
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（音樂）
05:28
[Year of birth: ]
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〔出生年：〕
05:31
[1492 - Columbus sails the ocean blue]
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〔1492 年：哥倫布藍色海洋航行時期〕
05:35
[1620 - Mayflower lands in Massachusetts]
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〔1620 年：五月花號在麻州靠岸〕
05:38
[1652 - Dutch settle in South Africa]
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〔1652 年：荷蘭人在南非定居〕
05:44
[1788 - Great Britain penal
transportation to Australia starts]
transportation to Australia starts]
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〔1788 年：英國開始將受刑者運往澳洲〕
05:47
[1836 - First migrants use Oregon Trail]
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〔1836 年：奧勒岡小徑
初次被移民使用〕
初次被移民使用〕
05:50
[all activity]
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〔所有活動〕
05:55
I love this movie.
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我很愛這支影片。
05:57
Now, since these migration events
are giving the context of families,
are giving the context of families,
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既然有這些移民事件
作為家族的脈絡，
作為家族的脈絡，
06:02
we can ask questions such as:
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我們就能問像這樣的問題：
06:04
What is the typical distance
between the birth locations
between the birth locations
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先生和太太的出生地，
06:08
of husbands and wives?
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通常距離多遠？
06:11
This distance plays
a pivotal role in demography,
a pivotal role in demography,
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在人口統計學上，
這距離扮演很關鍵的角色，
這距離扮演很關鍵的角色，
06:14
because the patterns in which
people migrate to form families
people migrate to form families
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因為人們遷移建構家庭的模式
06:18
determine how genes spread
in geographical areas.
in geographical areas.
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會決定基因在地理
區域上如何散播。
區域上如何散播。
06:22
We analyzed this distance using our data,
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我們用我們的資料
來分析這個距離，
來分析這個距離，
06:25
and we found that in the old days,
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我們發現，在過去
用的方式並不困難。
用的方式並不困難。
06:27
people had it easy.
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06:28
They just married someone
in the village nearby.
in the village nearby.
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他們只會和鄰近村落的人結婚。
06:31
But the Industrial Revolution
really complicated our love life.
really complicated our love life.
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但，工業革命讓我們的
愛情生活變複雜了。
愛情生活變複雜了。
06:35
And today, with affordable flights
and online social media,
and online social media,
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現今，機票大家可以付擔得起，
再加上線上社群媒體，
再加上線上社群媒體，
06:40
people typically migrate more than
100 kilometers from their place of birth
100 kilometers from their place of birth
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人們通常從出生地遷移一百多公里，
06:45
to find their soul mate.
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去尋找靈魂伴侶。
現在各位可能會問：
好吧，從一個地方遷移到另一個地方
好吧，從一個地方遷移到另一個地方
06:48
So now you might ask:
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06:49
OK, but who does the hard work
of migrating from places to places
of migrating from places to places
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去建構家庭的苦差事是誰在做呢？
06:54
to form families?
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06:55
Are these the males or the females?
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是男方或女方？
06:59
We used our data to address this question,
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我們用我們的資料來解這個問題，
07:01
and at least in the last 300 years,
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至少，在過去三百年間，
07:04
we found that the ladies do the hard work
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我們發現從一地移民到另一地
去組成家庭的苦差事是女方在做。
07:08
of migrating from places
to places to form families.
to places to form families.
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07:11
Now, these results
are statistically significant,
are statistically significant,
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這些結果在統計上是顯著的，
07:14
so you can take it as scientific fact
that males are lazy.
that males are lazy.
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所以男人比較懶是有科學根據的。
07:18
(Laughter)
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（笑聲）
07:21
We can move from questions
about demography
about demography
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我們可以從人口統計相關的問題
07:23
and ask questions about human health.
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換到詢問人類健康相關的問題。
07:26
For example, we can ask
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比如，我們可以問
07:28
to what extent genetic variations
account for differences in life span
account for differences in life span
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人與人之間的壽命差異，
受到遺傳變異的影響有多大？
07:33
between individuals.
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07:34
Previous studies analyzed the correlation
of longevity between twins
of longevity between twins
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過去有研究分析
雙胞胎壽命的相關性
雙胞胎壽命的相關性
07:39
to address this question.
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來解答這個問題。
07:41
They estimated that the genetic
variations account for
variations account for
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他們估計，人與人
之間的壽命差異，
之間的壽命差異，
07:44
about a quarter of the differences
in life span between individuals.
in life span between individuals.
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有四分之一是來自遺傳變異。
07:48
But twins can be correlated
due to so many reasons,
due to so many reasons,
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但，雙胞胎之間的關聯性
有許多可能成因，
有許多可能成因，
07:51
including various environmental effects
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包括各種環境的影響，
07:53
or a shared household.
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或共同的家庭。
07:56
Large family trees give us the opportunity
to analyze both close relatives,
to analyze both close relatives,
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大型家譜樹讓我們有機會
分析這些近親，
分析這些近親，
08:00
such as twins,
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比如雙胞胎，
08:01
all the way to distant relatives,
even fourth cousins.
even fourth cousins.
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到遠房親戚，甚至第四代表親。
08:04
This way we can build robust models
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這樣我們就能建立穩健的模型，
08:07
that can tease apart the contribution
of genetic variations
of genetic variations
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從環境因素中
分離出遺傳變異的貢獻來。
08:11
from environmental factors.
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08:13
We conducted this analysis using our data,
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我們用我們的資料進行這項分析，
08:16
and we found that genetic variations
explain only 15 percent
explain only 15 percent
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我們發現，遺傳變異只解釋了
15% 的個體壽命差異 。
08:22
of the differences in life span
between individuals.
between individuals.
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08:26
That is five years, on average.
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平均而言，就是五年之差。
08:30
So genes matter less than
what we thought before to life span.
what we thought before to life span.
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所以，基因對壽命的影響
沒有我們以前想的那麼大。
沒有我們以前想的那麼大。
08:35
And I find it great news,
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我認為這是大好消息，
08:38
because it means that
our actions can matter more.
our actions can matter more.
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因為那就表示我們的行為
與壽命有較大的關係。
與壽命有較大的關係。
08:42
Smoking, for example, determines
10 years of our life expectancy --
10 years of our life expectancy --
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比如，抽菸就能影響
十年的壽命——
十年的壽命——
08:46
twice as much as what genetics determines.
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是基因影響的兩倍。
08:50
We can even have more surprising findings
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我們還有更驚人的發現，
08:52
as we move from family trees
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就在我們從做家譜樹到
08:54
and we let our genealogists
document and crowdsource DNA information.
document and crowdsource DNA information.
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請家譜學家幫我們整理 DNA 資訊
並做眾包後發現的。
並做眾包後發現的。
08:58
And the results can be amazing.
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結果很驚人。
09:01
It might be hard to imagine,
but Uncle Bernie and his friends
but Uncle Bernie and his friends
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可能很難想像，
但柏尼叔叔和他的朋友
但柏尼叔叔和他的朋友
09:05
can create DNA forensic capabilities
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所創造出來的 DNA 法醫鑑定能力
09:07
that even exceed
what the FBI currently has.
what the FBI currently has.
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甚至比目前的聯邦調查局還要強。
09:12
When you place the DNA
on a large family tree,
on a large family tree,
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當你把 DNA 放入大型的家譜樹中，
09:15
you effectively create a beacon
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就能有效地創造出
如燈塔般的光束，
如燈塔般的光束，
從 DNA 的源頭者放射出與
09:17
that illuminates the hundreds
of distant relatives
of distant relatives
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09:20
that are all connected to the person
that originated the DNA.
that originated the DNA.
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數百名遠親的連結光束。
09:24
By placing multiple beacons
on a large family tree,
on a large family tree,
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在家譜中放入數個燈塔，
09:27
you can now triangulate the DNA
of an unknown person,
of an unknown person,
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就能針對一個未知的人
做 DNA 三角定位，
做 DNA 三角定位，
09:31
the same way that the GPS system
uses multiple satellites
uses multiple satellites
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原理和 GPS 使用多個衛星
來定位一個地點的方法相同。
09:35
to find a location.
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09:37
The prime example
of the power of this technique
of the power of this technique
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有個主要的例子可以說明
這項技術有多強大，
這項技術有多強大，
09:40
is capturing the Golden State Killer,
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那就是追捕金州（加州）殺手，
09:44
one of the most notorious criminals
in the history of the US.
in the history of the US.
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他是美國史上
最惡名昭彰的罪犯之一。
最惡名昭彰的罪犯之一。
09:49
The FBI had been searching
for this person for over 40 years.
for this person for over 40 years.
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聯邦調查局尋找這個人
已經超過四十年。
09:55
They had his DNA,
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他們有他的 DNA，
09:57
but he never showed up
in any police database.
in any police database.
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但他從來沒有出現在
任何警方資料庫中。
任何警方資料庫中。
10:01
About a year ago, the FBI
consulted a genetic genealogist,
consulted a genetic genealogist,
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大約一年前，聯邦調查局
去諮詢了一位基因系譜學家，
去諮詢了一位基因系譜學家，
10:06
and she suggested that they submit
his DNA to a genealogy service
his DNA to a genealogy service
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她建議他們將他的 DNA
上傳到一項家譜服務中，
上傳到一項家譜服務中，
10:10
that can locate distant relatives.
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這項服務能找出遠親。
10:13
They did that,
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他們照做了，
10:14
and they found a third cousin
of the Golden State Killer.
of the Golden State Killer.
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找到了金州殺手的第三代表親。
10:18
They built a large family tree,
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他們建立了一個很大的家譜樹，
10:20
scanned the different
branches of that tree,
branches of that tree,
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掃描樹狀圖上的不同分支，
直到他們找到完美匹配
10:22
until they found a profile
that exactly matched
that exactly matched
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金州殺手資訊的檔案。
10:25
what they knew about
the Golden State Killer.
the Golden State Killer.
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10:27
They obtained DNA from this person
and found a perfect match
and found a perfect match
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他們從這個人身上取得 DNA
並發現跟他們手上的 DNA 相匹配。
10:31
to the DNA they had in hand.
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10:33
They arrested him
and brought him to justice
and brought him to justice
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他們逮捕了這個人，
這麼多年後終於將他繩之以法。
這麼多年後終於將他繩之以法。
10:35
after all these years.
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10:38
Since then, genetic genealogists
have started working with
have started working with
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從那之後，基因系譜學家就開始
和美國執法單位合作，
10:41
local US law enforcement agencies
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10:44
to use this technique
in order to capture criminals.
in order to capture criminals.
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使用這項技術來抓罪犯。
10:47
And only in the past six months,
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光是在過去六個月，
10:50
they were able to solve
over 20 cold cases with this technique.
over 20 cold cases with this technique.
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他們就用這項技術破了
超過二十件長年未破的案件。
超過二十件長年未破的案件。
10:56
Luckily, we have people like Uncle
Bernie and his fellow genealogists
Bernie and his fellow genealogists
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很幸運，我們有柏尼叔叔
和他的家譜學家夥伴們。
和他的家譜學家夥伴們。
11:01
These are not amateurs
with a self-serving hobby.
with a self-serving hobby.
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這些人不只是業餘愛好者。
11:04
These are citizen scientists
with a deep passion to tell us who we are.
with a deep passion to tell us who we are.
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他們還是滿懷熱情
能說「我們是誰」的公民科學家，
11:11
And they know that the past
can hold a key to the future.
can hold a key to the future.
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他們知道過去是通向未來的鑰匙。
11:16
Thank you very much.
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感謝各位。
11:17
(Applause)
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（掌聲）
ABOUT THE SPEAKER
Yaniv Erlich - Computational geneticistYaniv Erlich is fascinated by the connection between DNA and data.
Why you should listen
As a professor and researcher at Columbia University and as CSO of MyHeritage.com, Yaniv Erlich has performed foundational work in genetic privacy and large-scale studies of crowdsourced genomic data. Dubbed a "genome hacker" by the journal Nature, Erlich and his team discovered a privacy loophole enabling reidentification of allegedly anonymous male research participants using just internet searches and their Y chromosome. Later, he discovered that 60 percent of all US individuals with European descent can be identified by forensic genetics using open genetic genealogy databases, which Science magazine called one of the top 10 breakthroughs of 2018.
Erlich is also responsible for the construction of the world's largest family tree, comprising 13 million people, as well as the development of the website DNA.land, which has compiled the genotypes of more than 150,000 donors. He has also worked to discover the genetic bases for several conditions in Israeli families. His team has demonstrated stable DNA data storage, reaching a density of 215 petabyte per gram of DNA. He's been awarded numerous prizes, has published more than 45 papers and authored seven patents.
Yaniv Erlich | Speaker | TED.com