2017 Killian Lecture: Eric Lander, “Secrets of the Human Genome”

Good afternoon, and welcome
to the 45th Annual James R. Killian Faculty
Achievement Award Lecture. I’m Krishna Rajagopal,
chair of the MIT faculty. Before we begin, I
would ask everyone to please silence
their cell phones, any other electronic devices. The James R. Killian Junior
Faculty Achievement Award was established in
the spring of 1971 as a permanent tribute
to Dr. James Killian, who was the president of
MIT from 1948 to 1959, and the chairman of the
corporation from 1959 to 1971. The purpose of the
award is to recognize extraordinary professional
achievement by MIT faculty members, and to communicate
their accomplishments to members of the
Institute community. The title of Killian
Lecturer is the highest honor that the MIT faculty may
bestow on one of its own. It is our privilege
today to be addressed by Eric Lander, professor
of biology and president and founding director
of the Broad Institute of Harvard and MIT. As noted by our colleagues on
the Killian Award Committee, which was chaired by
Professor Janet Sonnenberg, Professor Lander’s contributions
to science are deep and wide ranging, and include
scientific discoveries, writing crucial science
policy, leadership in both the local and
global research communities, and a long history of inspiring
a love of biology in students. And before I go
any further, I’ve been told that there is
an interruption coming in from my right, if they’re ready? Cueing off of inspiring love
of biology and students– Excuse me, is there
an Eric Lander here? Yes. Come on, guys. [LAUGHTER] Professor Lander,
we’re the MIT Logs. Hi, Professor. And we have a song
to sing for you. And we actually have a
seat for you right here. Excellent. [LAUGHTER] [PITCH PIPE SOUNDING] 1, 2, 3, 4. [SINGING STEVIE WONDER’S
“SIGNED, SEALED, DELIVERED” A CAPPELLA STYLE] Whoo! Whoo! [APPLAUSE] Again, everyone, we are
the MIT Logarhythms. So the powers that be
and I worked on a script, and this was not in the script. [LAUGHTER] And I have to say, that’s
a tough act to follow, but I’m going to go
back to the script. [LAUGHTER] In fairness to Eric. So in addition to inspiring a
love of biology and students, as you’ve just seen, under
Professor Lander’s leadership, the Broad Institute
is internationally recognized as a leading model
of interdisciplinary and cross-institutional
collaboration. Professor Lander is widely
known for his pathbreaking work in mapping of the human
genome, which changed how biological research is pursued. This effort yielded the complete
inventory of human genes, as well as catalogs of
human genetic variation and conserved genetic elements. It launched entire new
fields of research, including the discovery of
thousands of genes underlying human diseases, and
the global effort to understand their
biological functions. Professor Lander was key
to this project, which built on methods
for genetic mapping that he co-developed with
Professor David Botstein at MIT. Unlocking the
information in genomes has been the defining scientific
revolution of the past quarter century. Quoting from the letter
from the Killian Committee– this citation from the
Killian Committee– “Professor Lander has
influenced public policy through his writing,
most notably in an amicus brief that was a
critical factor in the Supreme Court’s decision to make
genes non-patentable. And further, he has
been the co-chair of President Obama’s
Council of Advisors on Science and Technology, to
which he was appointed in 2008. His leadership there was
key to the production of dozens of PCAST
reports on major topics, including antibiotic
resistance, flu preparedness, and advanced manufacturing,
many of which translated into executive orders
or major policy initiatives. “A highly regarded
teacher, Professor Lander co-developed MIT’S
introductory biology course with Professor Nancy
Hopkins in 1991 and ’92, work for
which the two of them were named Class of 1960
Fellows for Outstanding Teaching and Course Development. Today, he continues to teach
this incredibly popular course, which was brought to the
edX platform in 2013, and has now also become one
of the most popular courses online. Professor Lander joined
the MIT faculty in 1989, and his achievements have
been recognized over the years with many awards, including
the MacArthur Fellowship, the American Association
for Advancement of Sciences Award for Public
Understanding of Science and Technology, and
the Dan David Prize. He is a member of the American
Academy for the Advancement of Science, the
Institute of Medicine, the National
Academy of Sciences, and the Royal Swedish
Academy of Sciences– Class of Biosciences,
among others.” Eric, will you please
join me at the lectern? [APPLAUSE] Eric, it’s my privilege to
represent the MIT faculty in honoring you with the James
R. Killian Faculty Achievement Award, through
which we recognize your extraordinary contributions
that have transformed the study of biology,
your roles as the leader, teacher, mentor, and
public advocate for science at the very highest level. Congratulations. Thank you so much. [APPLAUSE] Thank you so much. Wow. It Isn’t always that you
get serenaded like that. That was awesome. This is just such a wonderful,
warm honor and occasion. You know, it’s nice
getting recognized by people outside, who
barely know you and pick you for some award based
on a couple of hours conversation in some committee. There’s nothing that
resembles getting recognized by your colleagues, who actually
lived with you for decades. Because they, like,
really know the truth. [LAUGHTER] So you take it a lot
more seriously when your own colleagues do that. And so I am just so, so deeply
honored and warmed to do this. And just want to share
some thoughts today. In fact, for this
Killian Lecture, I have divided into three parts. Part one, in keeping with
the day, is a love letter. Part two is an adventure story. And part three is a trip report. That will be roughly the
structure of today’s lecture. It will become clear, I
think, over the course of time what I mean by each
of those things. But I gotta say, you
guys did an amazing job by scheduling this
lecture in 10-250. That may not be obvious
to you, but there is no room on the
MIT campus that is more important
to me than 10-250. To And I will explain, as
part of part one of this talk. So let me start with
the love letter, which is to just what an
amazing place MIT is. You know, some people
have their careers all planned out in advance. That was not me. I was a good student. I went to Stuyvesant
High School in Manhattan. Loved math, was
on the math team. Went to Princeton, got
my undergraduate degree in mathematics. Went to Oxford, got
my PhD in mathematics. But I know I didn’t want to
do mathematics as a career. And I had no idea what
I really wanted to do. And it was only after
completing my PhD at Oxford that I came to grips with
what I might want to do. And I cast about, as one does in
one’s early 20s, pretty unsure. I somehow talked my
way into a job teaching on the faculty of the
Harvard Business School, teaching Managerial Economics. I think they figured, if I
had a PhD in mathematics, I must be able to do that. And I managed to stay
ahead of the MBA students in the course of that. But within a year or
two, it was obvious to me that my heart was
not in that– that I loved the depth of
mathematics and science, but really didn’t
know what to do. And my younger
brother, Arthur, who is a developmental
neurobiologist, and an MD-PhD, said, well, you know, you’d
written a book on coding theory for your thesis. You should study the brain. The brain has a lot of
that kind of coding theory. And being hopelessly naive,
as one is in one’s early 20s, I said, sure, I’ll
learn about the brain. I have a few free months. And so I began sitting in on
random courses around Harvard and elsewhere. I sat in at the medical school
on a neurobiology, neuroanatomy course. And it was cool, but
it was pretty clear I had to know some cell biology. Then, I sat in a cell biology
course, which made it clear that there was some
molecular biology. And to know molecular
biology, you really had to know genetics. And I fell in love
with genetics. And a couple of
Harvard professors gave me a bench in
the lab to learn a little bit of fly genetics. I’m grateful to them. And then, I still didn’t
know how this was ever going to turn into a career– I was teaching Managerial
Economics by day, pushing flies by night– and somehow talked the
Harvard Business School into letting me take
a leave of absence to come down to MIT for a year. Just one year. I think they thought
I was going to study the artificial intelligence
industry in the mid-1980s. In fact, what I
was going to do was hang in Bob Horvitz’
lab doing worm genetics, because I’d heard a
talk by Bob and it was amazing and so interesting. And for whatever reason,
Bob had a soft spot for wayward mathematicians and
gave me a bench in his lab, and gave me a mutant, unc-8. And I made suppressors
of unc-8 and really got to know the MIT community
for the first time. This was 1984. What an amazing place it was. I still didn’t know
what I was doing, and I was quite unsettled. Bob was partly on
sabbatical that year, but was hanging around the
lab some, and we were talking. I’m going to go to
this slide here– this slide– Mentors
and Champions– should have gone there. In Building 56, pushing
worms, Bob greeted me there, let me let me work. But next door to Bob’s lab
was Barbara Meyer, then on the faculty of the
MIT biology department, now at Berkeley. And I also talked a bunch
to Barbara during that year. So you know, Barbara
knew I wasn’t sure what I wanted to go do with all
of these things, and Bob knew. And I came every week to
colloquium– the department’s colloquium– which was
held here in 10-250. One day, after colloquium,
we’re walking back just right outside this hall, and the
single most important thing in my life that ever
happened to me happened to me just outside this
room, which was Barbara grabbed me and dragged
me over to David Botstein, another
biology professor here in the department,
and says to Botstein, here’s this mathematician
working in Bob Horvitz’ lab. I hated being
introduced that way, because biologists
run the other way when they hear this, or at
least, in those days, they ran the other
way when they heard there’s a mathematician around. But Barbara knew exactly whereof
she spoke, because Botstein was very interested,
in those days, in the early concepts of
mapping human genetic diseases, and had written just a landmark
theoretical paper in 1980, but didn’t have anybody
to talk to about it and to develop the
ideas any further. And we got introduced. And right here, and
walking back to 56, we began our first
conversation– I guess, actually, argument. David’s from the Bronx. I’m from Brooklyn. The form of discourse amongst
people from those boroughs is argument. And we had a great
argument, because David– being David Botstein–
immediately pronounced, yeah, we mapped single
gene diseases, but it would be completely impossible
to map multigene diseases. And I, of course, disagreed. We started arguing. We found the chalkboard. And we had such a
good time arguing, we agreed to get together the
next day to argue further. And I pretty much
dropped everything else I was doing in the
world, including little plates of
unc-8 suppressors that grew mold in Bob
Horvitz’ cold room, in order to work
on this idea of, could you map genes in
humans for complex traits? Somehow, David Botstein
managed to talk David Baltimore into giving me an appointment
as a Whitehead Fellow, while still on the faculty of
the Harvard Business School, by the way, teaching MBAs. That had not actually
been done before, but Balt didn’t
seem to really care. That’s another thing amazing
about MIT, is it does things like that. And within a few years,
Baltimore somehow, with some help from
others, managed to convince the MIT biology
department to give me a tenured appointment in
biology, notwithstanding what, by any objective
criteria, would be some serious
lack of credentials. I had written some papers
in biology by then. And it was just the beginning
of the start of the Human Genome Project, around ’86. And we applied to be the first
genome center under the Human Genome Project,
and needed space. And Phil Sharp somehow
managed to come up with some space in
the cancer center, and come up with some
justification somehow for it, and let us start in
some embryonic form. And eventually, Gerry
Fink– at the Whitehead, took over from David
Baltimore– managed to get us a lot more
space, as needed. And I’ve only put up a
few representative faces, as I will have on each of
these slides, just a few of the many
extraordinary people. But I can think of no other
institutions in the world, who would have taken in somebody
like me at that time so warmly, and somehow made it
possible to do all of these things– from,
initially, Bob letting me to come to his lab to
people eventually renting entire buildings
for a genome center. So I think everybody
here should appreciate what an extraordinary place this
is that has people like this. The other thing
about room 10-250 is this is where I first started
teaching introductory biology. Nancy Hopkins and I got asked
if we would kindly develop bio as a Institute requirement. It was going to become
an Institute requirement. They really wanted
to remake the course. And we worked together
hard to come up with a new curriculum that would
be accessible and appropriate for the whole Institute. And we did, and we
taught it for two years. And it’s fair to say
that curriculum still stands as the backbone of
the curriculum we use today, what Nancy and I
developed in those days. And we taught it right
here in this room, so I feel very comfortable. When Nancy stopped
teaching that course, Harvey Lodish came and
taught for a number of years. And then, for the
past 18 years– I don’t know Bob, a long time– Bob Weinberg and I
have been teaching the introductory course 7.012. We teach in the larger room now. But it’s just been a pleasure. And for me, the excitement
of coming and teaching 7.012 each fall to a roomful of
freshmen, reminding you why biology is so amazing by
seeing it for the first time through their eyes,
is such a gift. The gift of teaching is
the gift of being just re-inspired by young people
every year, again and again. And then, we got to share it
with the rest of the world. And this was, again, due to
MIT’s extraordinary foresight. In 7.012, Chuck Vest and others
had created this OpenCourseWare that would tape many of our
lectures that were online. And we began to get a sense
of what a difference it made to people, because I
got random emails from all over the world. And then Rafael stepped forward
with this MITx edX thing, and we felt we
just had to do it. We had to put this online. And so we pulled together all
the past TAs from of course, and about 18 assistants, and
just pulled together a group to make 7.00x– The Secret of Life,
which is online. And between 7.012, that’s had– I don’t have an exact
count, but my best estimate is something like 13,000
students have taken the course, and this online course so
far, 140,000 have signed up. The number of people who have
really dived in seriously is north of 10,000. And I get these letters
from around the world. And teaching has just been
such an amazing part of my life here at MIT. It is why we’re here. And it’s not an accident that
the best research in the world gets done in one of
the best teaching environments in the world. And I am enormously grateful
for that opportunity. And again, this room figures
heavily in that story. And then, MIT students, the
ones who come work in my lab. I have not been able
to put up, and wouldn’t want to put up, every single
picture of every single person who’s come through in
one form or another, but I picked two early
representative students to say, wow, what a
remarkable group of people. My first graduate
student that I ever took was Julie Segre in the
microbiology department. And one of my very first
freshman advisees– I think it was the first year I
was taking freshman advisees– was Pardis Sabeti. I’ve stayed in close touch
with both of those people ever since. And I will just
say how proud I am, and how representative they are,
of the amazing things people do. Julie, a couple of
years ago, she’s shown here receiving an
award from President Obama for service to America,
the highest award given to a federal civil servant. She works at the NIH. And when the NIH
Clinical Center had an infection of
carbapenem-resistant enterobacteriaceae,
Julie swung into action and developed a whole
plan to sequence every isolate in every patient
and trace the transmission, and helped shut it down, and
set an entirely new standard for how you can do infectious
disease surveillance in a clinical setting. And Pardis, who came back
after doing her graduate work to be a postdoc in my lab, and
as a faculty member at Harvard, and connected with
the Broad Institute, similarly swung into
action on Ebola, and did amazing work
sequencing the Ebola outbreak in the course of that outbreak
of this horrendous virus. And when Time magazine put
out its Person of the Year and called it the
Ebola Fighters, amongst the dozen or so
people who were profiled, there is Pardis
with her picture. So these are the people you get
assigned as freshman advisees and have as graduate students
showing up in your lap. I could go on and on
and pick more examples, but I thought I’d
just pick a few to say, wow, in most places
you’d never find anything like this. And then, finally, this
business of founding the Broad Institute. I’ve only put a few of the
names here that I’ll call out, but there were so many. But this idea, after
the Human Genome Project was done, of creating
something to capture the spirit of the
Human Genome Project, the connection between MIT
and Harvard and the hospitals, was the most unlikely of things. The idea that we would get MIT
and Harvard to work together was, at the time,
considered, you know, comparable to solving
the Israeli-Palestinian sort of thing. [LAUGHTER] And then, getting
five hospitals, too. But there was extraordinary
leadership at MIT, in Chuck Vest and Bob Brown,
the president and provost then, who said, yeah,
let’s figure out how to make it happen. It’s the right thing. And MIT has this long
history of just figuring out how to make the right thing
happen, not being hung up on structures, having all
sorts of interdisciplinary labs and centers, and just
not being bound by rules, but being bound by what
the right thing is. And they worked together
with Larry Summers and Steve Hyman at Harvard. At the time, then, Sue
Lindquist, and very, very quickly thereafter,
David Page at the Whitehead, all swung in and helped
make it possible. And I should, of
course, say that, then, as we’ve continued to grow
the Broad and develop it, Susan Hockfield, and now
Rafael Reif, as partners, have been extraordinary
in letting us build a totally crazy idea of
an institution that has somehow grown to be a model for many
things around the world. And you couldn’t have
done it, but for MIT. Harvard also played
a critical role, but I will say in this
room loud and clear, had it not been for MIT
sticking with the idea from beginning to end, this
could have never happened. And again, it’s a sign
of what can happen here. And I want to also thank
my amazing colleagues at the Broad, David Altshuler,
Todd Golub, Stuart Schreiber, who were founding faculty
members of the Broad, and Aviv Regev, who has
since stepped into leadership at the Broad, who was the
first faculty member we hired, Stacey Gabriel, Justine
Levin-Allerhand, Samantha Singer, leadership of the Broad. It’s been an amazing thing. And we’ve now got
about 3,200 people connected to this community. So anyway, this is a
very brief love letter, with a tiny number
of the pictures I should be putting up. But you wouldn’t be able
to see them, otherwise. I put up the little
MIT Great Dome there to reflect the
infinite corridor, to say that there’s essentially
an infinite number of people who make this place great and
amazing, and I am so lucky. I can take zero credit for
having chosen to end up at MIT. But boy, am I lucky. And I think you all are, too. What an amazing place. So that’s part one–
the love letter. Part two– the adventure story. Now, I realize,
it’s a mixed room. Some of you will be biologists,
and some of you won’t be. I’m going to tell
a biological story. I want to roughly tell
the arc of the history of the human genome, and the
genetic basis of human disease. I’m going to deliberately
do it kind of quickly, because I think– well, the aficionados– some
of them– know the story, and there isn’t enough time
to go into full detail. But I want to tell
the arc of the story, particularly because we have
a number of young people in the room, who
don’t yet realize how much is going to happen
in the course of your career. And so if you take away only one
thing from the adventure story, it’s where you start, and
then where things can end up in science, and how much
further things can go than you could ever possibly imagine. So basic point– genetics
is powerful stuff. Genetics is the one
thing in all of biology that lets you ask in a
hypothesis-free way, what’s responsible for a process? Whether it’s development or
vision or muscles or whatever, a geneticist says, hey,
you know, I’m not so smart. Ask the organism. It’s a very wise thing. And genetics is simply
a systematic way to ask the organism,
look for mutations, look for mutants out in
the world, in the lab, and find out what’s going on. Everything else, you
need a hypothesis. And I think it’s fair to
call that hypothesis limited science. Genetics, you’re going in
and your hypothesis-free. Find a mutant. The problem is you couldn’t
do this for human beings. You could do it for fruit flies. You could do it for worms. You could do it where
you could set up a cross, maybe even mutagenize the
animals or the plants, cross them together, and look
for weird stuff coming out the other end. The problem was, human genetics,
understanding human disease, was incredibly important,
but there’s no real way to do human genetics. Except for this paper
that I’ve already referred to by David Botstein in 1980. David Botstein and
three colleagues wrote a beautifully simple,
theoretical paper that said, you know, it’s not so
different than fruit flies. What fruit fly geneticists
did back in 1911, of setting up crosses
and using markers, like curly wings and
white eyes, yeah, we can’t set up the crosses. But there’s a lot of naturally
occurring human crosses. And we can’t use curly
wings and white eyes, but there’s a lot of DNA
spelling differences. They’re more boring than
curly wings and white eyes, but DNA spelling differences
are markers, too. And it ought to be
possible to trace the inheritance
of a disease gene, that you didn’t know what it
was, or anything like that, or where it was, simply by
taking a pedigree of family, looking at the transmission
of the disease in the family, and correlating its inheritance
within your DNA spelling difference. Now, you wouldn’t
know where to look. So you just tried lots of them,
up and down the chromosomes, until you found something
that showed coinheritance with the disease. And that’s what Botstein and
his colleagues wrote in 1980. And it worked for simple
one gene Mendelian diseases in theory. It’s a landmark paper. Within four years, folks did
this for the first disease– Huntington’s disease. Just done by Jim Gusella,
across the river there, and mapped it to
chromosome number 4. And then, I remember
the day, in 1985, that David Botstein called me
into his office, shut the door, and whispered, that
gene for cystic fibrosis is on chromosome 7. Big news and really
exciting, that people had mapped it to
chromosome 7, and they were able to get a
nearby genetic marker. Admittedly, it was
like 15% recombination. Very far away. But soon, within a few months,
within 1% recombination. And 1% recombina– oh, my
god, that translated still to a million bases of DNA. It took them five years to
go from 1% recombination away to find the disease gene, but
they found the disease gene, and found out what it was. And all this was borne
out in a beautiful way by about 1989, 1990. But I met Botstein just
before cystic fibrosis had been mapped. The only disease gene
that had been mapped was Huntington’s
disease to chromosome 4. And he and I began arguing
over the question of, could you do this
for real life traits? Not just– no, I’m sorry,
that’s not the right word. Simple Mendelian traits
are real life traits. But for common disease traits. Heart disease, Alzheimer’s
disease, schizophrenia, things that are complex, that
don’t show simple Mendelian one gene inheritance. And that’s what we began
arguing about on the chalkboards here at building 56. And we started with
a bunch of ideas. Well, let’s see, we’re going
have to get rid of families. We can’t have all
these big families. How do we map without families? So we started talking
about, what could you do if you just had inbred kids? Inbred kids bring together
a chromosome, inherited down to different roots,
to make homozygous, to get a double dose, of a
particular spelling difference. You really wouldn’t
need the parents. You could just look at the kids. So we came up with an
idea of mapping diseases based on affected individuals. And then, we said, you
know, the same sort of idea could work in an
isolated population. It so happens, in 1985,
we went to Finland for the human gene
mapping meeting. And over dinner of
salmon and reindeer, we found out about the
history of Finland, which all traces back
to a founding population 2,000 years ago with
maybe 100 people. And you can trace all
those chromosomes. And basically, if anybody has
a genetic disease in Finland, it all comes from a common
ancestor, almost certainly. And then, you could say, well,
how would you recognize that? There’d be a set of spelling
differences on that chromosome, and you could recognize
the region, the haplotype, that had come from
2,000 years ago, even though you didn’t have all
the intermediate generations, by just looking
at the population as if it was one big family. And then, we began
thinking about the fact that, hey, you know, you
could do this beyond Finland. You could probably
do this for Europe. You could probably maybe
do it for the whole world, if, in each case, you had a
denser and denser and denser genetic map of
markers, you could look further and further
back into history, and see how all those things
were happening in a population. And so, in the late
1980s, we already had these ideas of
how you might be able to map very efficiently
single gene diseases and multigene diseases
in populations. And there’s only one problem– this human genome was a
very, very, very big place. Three billion bases of DNA,
3,000 base genes on average, and a mutation was one base. And finding what you
wanted in that big genome was almost impossible
back in the late 1980s. But we wrote these theoretical
papers anyway, that said, here’s what you would do if only
you could do it, if you could work with the human genome. But it was becoming clear, with
the ideas of a Human Genome Project, that maybe we could
work with the human genome. And so, the next
phase of my life shifted from thinking about
the theoretical to thinking about the very practical. How were we going to get
a human genome in hand? And we began here to
build out a genome center. The Whitehead
Institute/MIT Center for Genome Research,
where, eventually, we– well, it got done. What can I say? I’m going to skip over
the extraordinary 13-year international collaboration
across six nations, but I’ll note, in this room,
MIT made the single largest contribution of any
place in the world to the Human Genome Project. About a third of the entire
project was done here. A tremendous amount of the
methodology was developed here. Automation, all sorts of
things, were done here. And it got done. And we woke up and we
had a human genome. Actually, we celebrated
it many times. [LAUGHTER] There was a big celebration
in the White House, in June of 2000, when we
announced to the world that we had a rough draft
sequence of the human genome. There was absolutely no
evidence to support the claim at the time, because no
paper had been published. But it was decided that
it should be announced. And so it was announced. But I just note,
there were actually underlying facts, but just
none in evidence at the time. Now, beyond that point,
we published a paper in February of 2001. And then, we set a
deadline of completion– that was just a rough draft. 90% was there. Lots of errors, lots of holes. And we all said, let’s get
it done by April 25, 2003. And we did. Everybody pulled all-nighters
to be done by April 25, 2003. And if anybody doesn’t
know why, the picture below gives the hint. That’s the 50th
anniversary, to the day, of the Watson-Crick
double helix paper. And we thought, how
cool would that be, to finish sequencing the human
genome by the 50th anniversary? And it got done. And it just tells
you what can get done in the course of 50 years. It’s pretty amazing. So all right. So then, you had a human genome. Adventure story. Now, this mapping
of disease genes. Could it really work
like, like it laid out in the hallways and
the whiteboards of MIT? Well, for simple one
gene Mendelian diseases, worked like a charm. That red curve shoots up. It gets up to 1,800 by
the turn of the century, or so, and today, about 4,000. And what used to be
a five year effort to find the cystic fibrosis
gene is a good rotation project for a student. And it’s just like mind
boggling that that is the case. But these common disease
things, that’s hard. We weren’t finding many of
them in this whole period. And why was that? Well, because common diseases
aren’t like Mendelian diseases. They’re not simple,
single gene diseases that show a single transmission
pattern in a family. In fact, what we were
going to have to use was those ideas that we
developed with Botstein on the whiteboards of treating
the population as if it was a family, where you couldn’t
see all those people, by using lots of different
polymorphic markers, and tracing ancestral
segments of chromosomes. Or, alternatively,
you’d have to like sequence zillions of people. Those would be the two ways– trace lots of markers,
sequence zillions of people. And we found ourselves
back at square one. Because we just finished
sequencing the human genome– by the way, it cost $3 billion– and, like, what
are we going to do, have to sequence
thousands of more people? You know, you start multiplying
8,000 people, $3 billion, it gets up to about US GDP. You don’t really
want to do that. And so, we quickly
found ourselves having to go back to mapping
the human genome again. As soon as we finished
mapping the human genome, we had to go back to
mapping human genome. And so, folks came together, and
to make a very long story very short, we had to find these
common genetic variants. We went from having
only 4,000 of them to, pretty soon, having
tens of millions of them. We figured out how they were
correlated with each other. And “we” is many people
around this community and collaborators
worldwide– but again, I’ll say here, led very much
from Kendall Square. And then, we had to figure
out how to genotype them. Well, in prehistoric times,
namely around 1999 or so, you did them one at a time. But within a few years,
we figured out ways to do them a million at a time. And then, sequencing has
seen this amazing drop. We did spend $3 billion
on the first genome, but it’s now two million times
cheaper to do the second. To do another genome,
it’s down to $1,500. And here, in Kendall
Square alone, one new complete human genome
is being sequenced every 11 minutes, which blows your mind,
to realize how rapidly things are coming off the pipeline. So as soon as we were done
mapping and sequencing the human genome, we
had to make more maps and more maps and more maps. We had a Google map
of the human genome, but we had to layer on
top the traffic patterns and pizzerias, this,
that, everything had to get put on top of it. You know, conservation of
genes, 3D folding, this, that. To do it, we had to
compare lots of animals. So we found also
lots of cute animals, and sequenced them, and compared
their genomes, and found out, could you see genes by the
pattern or conservation? Could you see non-coding
regulatory regions by the patterns of con–
and we found the genome was filled with surprises. It had all sorts of sequence. It had been advertised
as having 100,000 genes, but it only had 20,000 genes. That was very interesting. It turns out that I’d been
teaching my students in 7.012 that the picture of a
gene was all these regions that code for a protein,
and a little promoter and some regulatory
stuff up at the front. That was totally wrong. It turned out there were six
times as much regulatory stuff as there was the
protein coding stuff. We just didn’t know about it. And I’m still trying
to write letters to all of those students
to correct this. [LAUGHTER] And it turns out
that most of what drives mammalian
differences in evolution, what makes a mouse and
an elephant different, are the changes in
that regulation. We found how transposons,
jumping genes, spread evolution. We found all sorts
of amazing things. And again, “we” is this
amazing community here. So then, what about mapping
these disease genes? Well, we want to map the genes
for common genetic diseases. That was what Botstein
and I first started talking about outside 10-250. Well, very briefly, it
didn’t look good for a while. Each year, the
worldwide production of new discoveries
of genes responsible for any common disease
whatsoever was one per year. In 2000, a single gene was found
that affected a single disease. It happens to have
been type 2 diabetes. And it was David Altshuler,
a postdoc in my group, who found it. It was the only such
discovery that year. This was pretty
much the production. But then, those tools
we were talking about began to come online. And in 2005, four genes
were discovered worldwide. And in 2006, eight
genes were discovered. And in 2007, lots of
genes were discovered. Because suddenly,
there was critical mass and the tools were there. And by today, there’s something
like 6,000 genes associated with common genetic diseases
that have been discovered. Now, of course, geneticists
are never happy with anything. They saw this, and
they immediately said, oh, this isn’t
very good, you know, because any given
disease doesn’t have that many genes yet. You know, they’re mostly not
in the protein coding regions. They’re out there in the
non-coding, regulatory space. And they don’t have that big
an effect on the disease gene. And when you add up all their
effect on the heritability, it doesn’t explain
that all much. And this is the wonderful
thing about science. You get all excited about it. We got something
really exciting. And somebody says, that’s nice. OK, now show me
something really. And so, anyway, there’s been
this wonderful back and forth over the next several
years, as people said, hey, maybe all that stuff’s
just technical artifacts. And there were lots of theories
about why it might just be a technical artifact. And anyway, even if it’s real,
is it biologically useful? Could we interpret it? And then, people
said, OK, so forget all these common variance,
how about these rare variants? That’s what we should go
do, sequence lots of people. So anyway, folks around
this community stuck to it. I’ll just show you an example. Folks here undertook the
mapping of schizophrenia. 3,000 patients
with schizophrenia, 3,000 patients
without schizophrenia, a million genetic markers across
each of those 6,000 people, and they found absolutely
nothing significant. Not a thing. And the NIH study section
said, OK, enough of that. Let’s go on something else. But the folks around here
actually know some math. They looked at the
distribution of p-values, and they said, if there
was nothing to find, the p-values would be uniformly
distributed between 0 and 1. There’s too many
p-values near 0. The data are whispering, I’m
trying to be significant. Give me a larger sample size. [LAUGHTER] And if you know how
to listen to the data, that’s what it was saying. And so, they got a
larger sample size. 20,000 samples, and now
five significant loci. But the data were
still whispering. 50,000 samples yielded 62 loci. 110,000 samples
yielded 108 loci. It’s now up to 152 genes
involved in schizophrenia right now. And not only that, an Australian
statistician showed that even the stuff that
wasn’t significant you could figure out
how much, in aggregate, it was contributing,
and it was a lot. And by today, something like
50% of all the heritability of these diseases
can be explained by these common
genetic variants. So anyway, the
pendulum swung back to common genetic variants. But wait, wait, wait, let’s not
give up on those rare variants. Now, with sequencing genomes
at a greater and greater clip, people were beginning to
study rare genetic variants. They’re sequencing,
and the first studies of 100 samples, or a 1,000
samples, yielded nothing. And of course, people
said, well, enough of that. But no, people,
especially around here, have been pressing on. And again, it was
just a power question. And as the sample sizes are
getting larger and larger, those rare variants
are mattering. And so common variants,
rare variants, it’s possible, finally,
to dissect and find, for a typical common disease,
50, 100, 150, 200 genes in the human genome that
have an effect on that. Now, you know, that took
roughly from a conversation in the hallway outside 10-250
that took place in 1985 to somewhere around 2010. But it’s mind blowing. We never thought we’d
ever get to that point. And what’s amazing, and I’ll
just briefly touch on it, is how much is getting learned
now that we have those genes. To my mind, it’s very much like
doing a mutagenesis in worms, the sort of thing that might
happen in Bob Horvitz’ lab, or in a fly lab. But the human population
has done it already. And I’ll just mention
just very, very briefly– and here, for the interest
of time, I’ll go fast, and I’ll quote some
examples of my colleagues at the Broad, who
have been working on these inflammatory
bowel disease. 200 Loci have been found
in the human genome that play a role in
inflammatory bowel disease. They affect all sorts
of biological pathways. And I won’t read all
of them to you here, but they make sense
in all sorts of ways. And when you begin to take
these human genetic variants and put them into mice, you
can see they have real effects, and they affect very,
very sensible pathways. They have effects
on real proteins, and they suggest
therapeutic hypotheses. Coronary artery disease, work
of Sekar Kathiresan, a MGH colleague, who’s at the Broad
and is down here all the time. He and his colleagues
around the world have looked now it’s actually
up to about a quarter of a million people, and have
mapped genes for LDL, and HDL, and triglycerides, and
early onset heart attack of the sort that we
know is very common, when people will die of a
heart attack in their 40s. And I’ll just tell
you an example of what has come from such studies. Everybody knows that LDL
is bad and HDL is good, that high LDL is bad for you–
make you have a heart attack– and high HDL is protective. So the genetics confirms this. Specific mutations in LDL will
show that this is correct. These strong mutations give
rise to high and low risk of heart attack. And based on that, the
pharmaceutical company has made all sorts of drugs
for lowering your LDL levels, and they work incredibly
well, and they save lives. So obviously, it stands to
reason that the same thing should be true for HDL. You want to get drugs that
will raise your HDL level. You should be taking those,
as well as your statins for lowering your LDL. So a bunch of
pharmaceutical companies jumped in and made
HDL raising drugs. Four different
companies have done it, because it will
obviously decrease your risk of heart attack. The only problem was
there’s no genetic support for that hypothesis. It’s pure epidemiology. And if you were
churlish, you could say, hey, you know, maybe it’s just
a correlation, not causation. Nah. But anyway, Sekar decided
to take all his genes that have an effect on
slightly raising and lowering your LDL levels and HDL
levels, and all that, and try an experiment. He said, the people who inherit
these modest LDL raising alleles show higher
risks of heart attack. And the answer was,
yes, the LDL raising alleles, the modest
ones you inherit, increase your risk
of heart attack. So now he said, what about
the people who inherit the HDL raising alleles? Do they show protection? And the answer was, not at all. No effect. The hypothesis does not get
supported by the genetics. Oh, and by the way, the
clinical trials, each of which cost about $1.5 billion,
have all failed so far. So it sort of shows you that
the power of this genetics is pretty cool, and
actually it looks like it is just a correlation. Triglycerides are
anticorrelated with HDL. The effect from
the genetics says it’s probably the triglycerides,
not the HDL, that’s driving the effect, and
that’s what you really should be working on. But I note that, in terms
of early heart attack, that’s only 20% of all
early heart attack. 80% of the loci that
have been found so far don’t affect your lipids,
which means 80% of the answer is doing something else
we hadn’t hypothesized. Sekar has found one of
those so far– corin. And he’s working
to find many more. One last example, and I’ll
just go through it quickly– schizophrenia. Schizophrenia is the sort
of disease you despair of studying because,
well, you’re not going to do it in a Petri plate. What are you looking for? There’s no way to see
neurons in a Petri plate having a delusion. You’re not going to
do it in a mouse, because you don’t know what
to look for in a mouse. There’s only one model
system for schizophrenia, and that’s the human being. So as I told you already, these
big studies that Mark Daly and Beth Stevens and Steve
McCarroll have been involved in, these big studies
have given rise to 108 different loci–
it’s actually up to 154. I’ll tell you the story
of just one very quickly. That thing there
on chromosome 6 is in the major histocompatibility
complex, a region having to do with
immune protection, which have caused people to
say, oh, schizophrenia must be caused by
some infectious agent. There was even an
article in The Atlantic saying that you could
get schizophrenia from your cat because
of toxoplasma gondii. I do not believe that, so
you can forget that piece. Anyway, to make a
very long story short, Steve McCarroll
eventually pinned down what the gene was there. It’s a gene called C4, and
it’s a horrendously hard region of the genome to work with. But he figured out what it was. And he found that– just to jump ahead– the level of
expression of this C4A correlated with the
risk of schizophrenia. And I’ll leave out
all the controls that geneticists would
care about there. But clearly, excess C4
increases risk of schizophrenia. What is this C4 thing? Well, it does have a job
in the immune system. It turns out that it’s part
of the complement system. C4 is for complement
component 4. And the complement system
marks microbes for destruction. Sounds pretty good. Ah, but a colleague
here in Boston, Beth Stevens at
Children’s Hospital, found that the complement
system has a second job. In addition to working its
main job in the immune system, it moonlights in the brain. It turns out that
same thing that is used in the immune system to
mark microbes for destruction is used in the brain to mark
synapses for destruction. That’s how you prune synapses. So suddenly, it turns
out the excess of C4, the excess of pruning, is now
associated with schizophrenia. That actually turns
out to explain some dusty, old observations. If you look at the brains
of schizophrenic patients, fewer synapses. But nobody knew if that
was a cause or an effect. The genetics gives you
some insight into that. Moreover, the greatest
period of pruning, tremendous pruning of synaptic
connections between neurons, is late adolescence. That happens to be the period
of onset of schizophrenia. So you could
imagine that there’s a serious therapeutic
hypothesis here, that it’s a disease which
is at least, in part, an excess of synoptic pruning. And modulating the level
of synoptic pruning, turning that dial, could end up
having a potentially beneficial therapeutic effect. Lots more to do. Another 107 loci. Oh, by the way, some
of those 107 loci also are connected to C4. And so we’re beginning
to get to the point where the genetics is going
to lay out some of that. I’m going to skip over a story
of Manolis Kellis, a faculty member here in computer
science, a story about obesity. He’s done beautiful work
with Melina Claussnitzer from the Beth Israel
Hospital on obesity. Beautiful work to pin down
the cause of this condition. And basically, it
uses everything in the entire kitchen to do it. Big data from here,
there, everywhere, all stirred together, plus some
biology, plus some editing, to come up with
a model that says that a mysterious genetic
polymorphism is really controlling thermogenesis. And it’s striking and beautiful,
and I refer you to the papers. So I just want to summarize my
entire career on this slide. You know, it’s sort
of funny or wonderful. There’s something
wonderful if you feel like the arc of what
you’ve been working on is coherent enough you
can put it on one slide. You know, this early period
of theoretical principles for Mendelian diseases that
David Botstein developed. This argument outside
10-250 with Botstein and trying to develop
the principles for polygenic diseases, and
just the totally, totally unreasonable nature that we
could ever possibly get there. Efforts of a lot of
people over 13 years to get a sequence
of the human genome. Realization that what
we need even more than that, maps of the genome. Even further, polymorphisms
and other things. But eventually, enough
tools got in place and it was possible
to tease apart genes for complex diseases. And in the last
three or four years, it’s been possible to work out
the biology underlying these. And I think it’s
just getting going. So I think the point to the many
young people in the audience here is science has this
just complex character. Any given day, you’re incredibly
frustrated at how slow it’s going. Things are failing, you’re
not making progress. Any week, you’re
not making progress. And even across a
couple of months, you feel like you’re stuck. When you can get enough
perspective on things, though, over the course of years
and decades, it’s stunning. Nothing in the
world moves faster. And for me, this
is so much faster than I could have ever imagined. If you put a gun to my head
in the mid-1980s and said, how far do you think we
could get in your career? I’d have been off by a couple
orders of magnitude, at least. And I think that’s what’s
so special about science, and that’s what’s special about
doing it in a place like MIT, where one not only experiences
it as people in the world will experience, but experiences
it at the center of the driving force of those ideas. So for this second
part of the talk, I just want to put
up acknowledgments of the people whose work
I’m referring to here. And of course, there’s
a few thousand names left off that slide. And I’m putting
up these consortia to indicate what an amazing
community it is, because I want to turn, in my closing remarks,
to the third part of the talk. Having given you
the adventure story, and it has been an
adventure story. And it’s not done yet. We don’t even know how the
story comes out at the end yet, although we’re
beginning to get a hint. Finally, I owe
you a trip report. You know, when you
go away, you’re supposed to report
on what did you do. And so, I have a picture here
of an American Airlines plane. All of us know these
planes out of Logan. So I want to just very
briefly, in my closing part of this talk, report
on this sojourn I have taken to Washington
for the past eight years on science and
technology policy. Getting to co-chair the
President’s Council of Advisors on Science &
Technology, which has been an amazing opportunity. And you would think, well,
this is Washington, what does it have to do with MIT? Well, MIT’s fingerprints
are all over it. Let me start by explaining this
President’s Council of Advisors on Science and Technology. It is co-chaired by one John
Holdren, the president’s science advisor. MIT class of ’65, of course. A loyal MIT alumnus here. And he was my co-chair. So let me explain how this
President’s Council works. The President’s
Council has about 20, 21, 22, depending, leading
non-governmental scientists, technologists, and innovators. And the job of the Council is
to provide independent advice and policy recommendations–
and I underscore independent– to the president, and
to the executive office of the president, and to the
executive branch on matters of national importance,
where science, technology, and innovation is
key to strengthening our national security,
economy, or health. It’s a pretty broad remit. We tend to take on the things
that cut across departments. I got a phone call from
President Obama’s office Thanksgiving weekend
of 2008, asking if I would meet with
the president-elect. I had not met him
before, had not played any role in the campaign. But we met, and the
result of the meeting was asking me to
co-chair this group. The group has been
historically co-chaired by the White House
Science Advisor and an external,
non-federal scientist. It was created, by the
way, rather poignantly, six weeks after the
launch of Sputnik, when President
Eisenhower decided they needed to have a
much stronger connection to the external
science community. He did this, together
with his science advisor, who was the first true science
advisor to the President of the United States, in 1957. That person was
James R. Killian. He created this job– the job of a science
advisor and PCAST. It was then called PSAC– President’s Science
Advisory Committee. But there is some
wonderful resonance in this part of the
talk, too, that Killian is responsible for
all of this stuff. And as best I can tell,
because he was president of MIT from 1948 to 1959, and was
science advisor from 1957 to 1959, he held both of
those jobs concurrently for three years. It was a different era,
when you could do that, but it is a remarkable thing. And MIT is just all
over this thing. So in any case,
every president has had one, although they’ve
treated it differently. It’s worked in different ways. And when President Obama
came into office in 2009, he said, in a line that I think
was resonant for all of us, “We will restore science
to its rightful place.” That science had not
gotten enough attention, and President Obama
wanted very much that his administration
should be a science-based administration. He was the first
president to designate his co-chairs of PCAST. Harold Varmus was
also designated as co-chair of PCAST. He stayed for about
a year and a half before becoming the head of
the National Cancer Institute. And on January 1, in the
middle of a snowstorm, on the whiteboard in my
office over at the Broad, we came up with a proposed
list of members for PCAST. And remarkably, we put in a list
of members to the White House for who should serve on this
PCAST, every name was accepted. Just stunning. Nothing was added,
nothing was subtracted. The feeling was, hey,
let the scientists decide what’s the right thing there. It was just quite remarkable. And at the National Academy
of Sciences, in April of 2009, we met first with the president. This group has
had only 25 people over the course of eight years. It has been remarkably stable. People have left for
such frivolous reasons as becoming the head of the
National Cancer Institute, becoming the Secretary of
Energy, things like that. One became ill and
eventually died. This has been an
incredibly stable group of amazing servants
to the public. And I will note,
by putting boxes around six people well known
to this community, all of whom have MIT ties of being either
alumni or former faculty, and members of the Corporation– just amazing people. And it’s been wonderful to see
that a quarter of all of PCAST has been composed of MIT folks. We’ve met with the
president frequently. And it was an incredibly
interesting experience to engage with someone so
smart, and so thoughtful, and probing with questions. We got to tour all
sorts of rooms. This is our most common meeting
place, the Roosevelt Room, which is just outside
the Oval Office. We’ve met in the Map Room here,
State Dining Room sometimes. That was good fun. And John and I would
go brief the president in advance of the
meeting, giving him an agenda and chatting
with him, outside the Oval. And from time to time,
in a non-PCAST fashion, I would get called in for
meetings periodically. And my graduate
students teased me mercilessly about
having to cancel a thesis committee for
this, or a meeting with them for that, to go down for this. It was really interesting. This is actually
the conversation that led to the Precision
Medicine Initiative here. But mostly what we did for the
president was we wrote reports. This was a group that rolled up
its sleeves and wrote reports, and I cannot tell you how
impressed I am at watching scientists in public policy. I had occasion to serve on
some non-scientific committees. I served on the Jobs Council,
which was very different. It was a very impressive thing. It consisted of 26 CEOs of
major companies, and myself, and Laura D’Andrea Tyson. They didn’t do the writing. They didn’t do the
original research. PCAST worked its tail off. We had Nobel Laureates,
university presidents, many others, Eric
Schmidt from Google. They worked their tails
off writing these reports. And in the end, we produced
38 reports, two classified, to the president on a
wide range of subjects. They went anywhere from
one at 192 pages to one at eight pages. We wrote whatever was needed. Total of about 440
recommendations, and a pretty good
fraction of them got taken, quite remarkably. Over the course of
time, we had about 48 stated, formal public
meetings, 406 phone calls of the co-chairs–
but who’s counting? And it was a
remarkable experience. And I’ll just mention a
few of the things that emerged from this. Advanced manufacturing–
there was an amazing effort that the administration
wanted to put into advanced manufacturing. PCAST wrote a
report recommending things we could do to restore
advanced manufacturing in this country. And Susan Hockfield co-lead
that effort that came out of that initial report. We had the easy job. We wrote the report
suggesting it should be done. Susan and her co-chair actually
implemented the Advanced Manufacturing Initiative
in the United States, and it has a huge impact. You can look across the country
at these advanced manufacturing centers that have been started. And I think, if we are serious
about bringing manufacturing jobs, and keeping
manufacturing jobs, here, it’s going to be
through the high end stuff, not the cheap labor stuff. And that’s just one example. And I want to credit so
much to Susan’s leadership in doing that. And that is something
that I think will have persistent impact. The United States has
had a quadrennial defense review that it did, but it
never had a quadrennial energy review. It never had any
persistent energy policy. And we wrote a
report that called for the creation of a
quadrennial energy review to go on. And this was a case of
real extreme leadership by a PCAST member. The person who headed up
that working group for PCAST was Ernie Moniz. And he felt so strongly
about this recommendation that he went on to become
the Secretary of Energy, so he could implement
that recommendation. And he did, and
did an amazing job. You know, we did
reports on spectrum– how to allocate the
electromagnetic spectrum and said that, if we could share
spectrum, like you share Wi-Fi, instead of giving it out
in little slices that are permanently owned, you could
increase the amount of spectrum by maybe about a
hundred thousandfold, and maybe increase,
ultimately, GDP by about a trillion dollars,
if you could do that right. And that’s become the
policy of the United States. We wrote a report on
something as granular as, why do hearing aids cost
$5,000 a pair, when, in fact, their
technology is nothing compared to an iPhone
that’s 10 times less? And the outcome of
that year-long report is now the FDA has
changed its policies, and we will have
over-the-counter hearing aids coming out. They’ve already waived
the audiologist’s exam. We’ve taken on
antibiotics, all sorts– biosecurity– all sorts of
crazy, different things. It’s been an amazing opportunity
to serve with scientists and technologists, and see what
scientists and technologists can do in government, when
they’re given the opportunity to do it. We had free reign. It had to be a request
from the president, but half the time, the
request from the president came when we said, would
you like a report on x? And he said, yeah. That’s a request from the
president, by the way. And you may, then,
call people up and say, the president
would like a report on x. And then, they’ll come
and do a lot of things. It’s really cool. And so, we did that. You know, it was a good
back and forth there. And he was an amazing client,
and we learned so much from doing it. And so, I just
come back to that– “We will restore science
to its rightful place.” MIT has played such a major
role over the course of decades in ensuring that science has
its rightful place in society, from early science advising
to subsequent science advising, Jerry Wiesner,
to all these people who have been involved. I know people are
concerned, well, where is science going now? What’s going to happen in
the new administration? And the answer is,
we don’t know yet. It wasn’t actually
a campaign issue, with the exception of
climate change, which is very worrisome. For the most part, I’m prepared
to wait and see a little bit, and see where that’s
all going to go. But I will say
very clearly here, while MIT does not
have politics– we don’t sign up as
Republicans or Democrats– we do have values. This place runs on
a set of values. And these values include the
power of knowledge and truth, and there is such
a thing as truth, and the power of
diverse communities. That is what has
powered science. And quite apart from
any passing issues of this political party or
that, this great Institution has contributed so much
to those principles of the power of knowledge and
the power of communities, which have largely driven the
economic growth of this country, the security of this country,
the health of this country. And I have no doubt that, in
the years ahead, we will do so, because those values
outlast anything. So it is an amazing opportunity
to come, and amazing honor to be given the title
of Killian Lecturer. I could not imagine a more
extraordinary community to be part of, from
the bold mentors who were willing to take a bet
on a crazy young person, to the colleagues
with whom I’ve taught, which has been such a big
part of my life, the students that I’ve had the
pleasure to work with, the colleagues with whom
we’ve started and sustained the Broad Institute. And you just turn a
corner around this place, and you’re just amazed at the
energy, the amazing people, the amazing ideas,
and the notion that the future can be
so much better, that in measurable times– not this week, not next week– but in measurable times,
unbelievable things can happen. And so all of this is to
say, my love letter to MIT, my adventure story,
my trip report are all just ways of
saying infinite thanks to the home of the Infinite
Corridor, and to MIT. Thank you very much. [APPLAUSE] Thank you. Thank you so much, Eric. Eric will take a few questions–
a couple of questions. Please, lineup at
one of the aisle mics if you’d like
to ask a question. And as people are
lining up, let me just say that, after
questions, everyone is invited to a reception
downstairs in Lobby 13. So are there questions? And if there are, please come
to one of the two microphones. There must be questions. All right. Hi– oh, it is on. Cool. Hi. So I’m Course 18,
and my question is, I’m wondering how your
background in mathematics, which you touched on
a little bit here, has contributed to the way you
approach work and teaching now? So in work in science, I think
the biggest transition that’s occurred in biology is,
back in the mid-1980s, biology had no
mathematics, no data, in the sense we would use data. Data was what you wrote down
in pencil in your lab notebook. When David Baltimore built
the Whitehead Institute, he made no provision,
originally, for a computer room at all. The thought that
computers would matter. What’s happened
over this period is biology has totally become
an information science. There’s so much information. And there’s no paper. I write that doesn’t
depend on tons of data generated by other people. So in a sense,
you could say, I’m still being a
mathematician, but I’m being a mathematician
getting to apply it to a problem I love so much. So in that sense,
computer science is driving more
and more, and you don’t have to necessarily
even be the data generator to make amazing contributions. I guess the other way
in which computers are driving the other
things I do is teaching. I think this notion of
sharing over the internet is just a brilliant idea. We’re still at the early
baby days of these MOOCs. Who knows where
it’s going to go? But there will come a
time that we look back and we say, MIT is able
to project, through both the internet and through
computer problems, and virtual reality,
experiments in labs, and who knows where this will go
in the next couple of decades, we’ll be able to project
to the whole world. And so in that sense,
I’m still a mathematician and a computational scientist. Just doing something I love. Let’s take one from this side. Yeah? Hello, Professor Lander. Hey, ya! I took your course last fall. Yay! Yeah. I just– like, since you’ve been
working on biology and genetics for a lot longer than
I’ve been alive– [LAUGHTER] –I just had a question about,
how you deal with the times when it feels like your
research isn’t getting anywhere? And how do you persevere
for, like, however many decades to make
great discoveries? [LAUGHTER] Well, it’s not like there’s
no positive feedback over the course of decades. That would be hard. I think I would find
trouble with that. Look, it’s a question
of a balanced life here. I mean, the single best
answer is my wife and my kids. Because you come home and you
realize, there’s a lot in life. And yeah, you didn’t do
anything particularly brilliant that day, and you’re
stuck on a problem, but family makes
a huge difference. Having somebody you can share
the frustration with, or just forget about it, or take
pleasure in your kids. And then, frankly,
there’s 7.012. You know? You can come in and do a
really good job teaching, even if that day you didn’t
succeed on something. This is actually something
my undergraduate thesis advisor at Princeton told me, is
he taught because he knew that, whether or not anything
was going well, he could do the teaching well,
and that was part of the job and really important. And I get enormous
pleasure out of that, because when I tell
you and other students about how remarkable biology is
each year, I re-inspire myself. You need to re-inspire yourself,
because stuff doesn’t always work really well. And then, you remember,
why am I doing this? At least you should work on
problems which, if god forbid, you succeed, it would
make a difference. Right? There’s no point in taking
on problems which, even if you succeed, don’t matter. That’s the best
advice I can give you. But when you take on problems
like that, you will fail a lot. That’s OK. You have good friends. You have family. You have students. And somehow, although the
market goes up and down and has a lot of fluctuation,
it’s pretty clear which direction it’s all going. One last question from the side. Hey, ya! Hi. I remember once, after class,
I had asked about the Human Genome Project, and
how it was decided how the work would be divided up. And I guess, at that
time, you basically said it would be good to talk
over a beer to get that answer. But I was wondering
if I could ask you a bit more about how
it was organized, that the work would be– How it was organized? The amazing strength
of science is shown in how the Human
Genome Project was organized. Nobody was actually in charge. That was the really
amazing thing. It was done by six
different countries. They didn’t report
to each other. Right? They worked it out. In the United States, there
were at least two major funding agencies– the Department
of Energy and the NIH. Neither reported to the other. They worked it out. The NIH funded a handful
of major centers. We didn’t report to them. They sent us checks. [LAUGHTER] If we wanted more checks, we
would pay a lot of attention to their good advice. And Francis Collins, who was
the head of the National Human Genome Research Institute and
was a brilliant colleague, we took his opinions
very, very seriously. But they were grants,
not contracts. And we were explicitly told to
do what we thought was best. It was the amazing thing of a
scientific community meeting together, resolving things. We didn’t match it– we
didn’t coordinate everything perfectly. We had deliberate overlaps
and non-deliberate overlaps. All of that was
part of the picture. We had, for a period of about
nine years, the phone call. The phone call was
Friday at 11:00. It’s still the case,
Friday at 11:00, some neurons go
off thinking, I’ve got to get back
on the phone call. It was the G5 phone
call– genome 5 for the five major centers. And we had phone calls,
and sometimes they were exasperating. But we agreed to get back on
the phone again the next week. And we had meetings and
we worked things out, and it was worked out on
an evidence-based basis. We sent around quality
control things and find out, were you really doing a good
job, and we hated doing that, because we found out we
weren’t doing as good a job as we thought. But we all believed in
data and openness, and all. And we kept revising plans. It’s just a model of how
science is, as a way of working. Had it been done in some
top-down bureaucratic, here’s the organization,
everybody’s assigned their piece, it
would have never worked. So it is incredibly
inspiring to watch what a scientific community can do. It didn’t look
pretty at all times, but it beat every
possible alternative. Thank you. Thank you. Thank you very much. Please join me in
thanking Eric again. [APPLAUSE] And please join us downstairs
in Lobby 13 for a reception.

9 thoughts on “2017 Killian Lecture: Eric Lander, “Secrets of the Human Genome”

  1. Thanks Eric, I did the Introductory Biology MOOC just a couple of years ago, it began an interest in molecular biology that has become absorbing. All the best to you and MIT.

  2. there are serious reports that today's college age men produce half the testosterone college age men produced 25 or so years ago. here is more proof

  3. I learned how life works from this man! That's no small matter. I'm grateful to his and MIT's extraordinary generosity and educational talents. Eric Lander is my favorite teacher!

  4. 2019 anyone?

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