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0:01
Good afternoon, and welcome to the 47th annual James R. Killian, Jr. Faculty Achievement Award lecture. I'm Susan Silbey, chair of the MIT faculty. Before we begin, I will ask that you please silence your electronic devices. And also, I invite, though I don't see too many, those at the edge of the room-- there aren't many seats left to move to the middle, just in case few stragglers come in, and we can accommodate them. The James R. Killian, Jr. Faculty Achievement Award
0:42
was established in the spring of 1971 as a permanent tribute to Dr. James R. Killian, Jr., president of MIT from 1948 to 1959 and chairman of the corporation from '59 to '71. The purpose of the Killian Award is to recognize and celebrate extraordinary 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 a colleague.
1:24
It is our privilege today to be addressed by Gerald Fink, Margaret and Herman Sokol professor in biomedical research, American Cancer Society professor of genetics, and a member of the Whitehead Institute for Biomedical Research. As noted by our colleagues on the Killian Award Committee, which was chaired by Professor Michael Strano, Professor Fink is among the very few scientists who can be singularly credited with fundamentally changing the way we approach biomedical problems.
2:01
He has made numerous seminal contributions to understanding the fundamentals of all nucleated life on the planet, significantly advancing our knowledge of many cellular processes critical to life systems and human diseases. His research, which includes understanding infectious disease, how cells divide, and how genes are controlled, has proved critical to modern biology. Professor Fink's overarching scientific achievement has been the development of baker's or brewer's yeast
2:39
into the premier model for understanding the biology of eukaryotes, that is, organisms whose cells have a nuclei, which includes all known animals and plants. Yeast transformation advanced the field of biology by making it possible to do gene editing and targeting in yeast similar to contemporary CRISPR, but-- an importantly but-- approximately 40 years earlier. The ability to gene edit yeast spurred many scientists to take a yeast molecular biology course that Professor Fink taught for 17 years
3:19
at Cold Spring Harbor Laboratory. Former students in that course include three Nobel laureates and 28 members of the National Academy of Sciences. Professor Fink's discovery of transposable elements in yeast laid the groundwork for future studies of transposable elements. A later discovery of filamentation in yeast uncovered a genetic mechanism by which disease-causing fungi switch from a benign to an infectious form and invade human tissues. This has led to a better understanding
3:58
of how Candida albicans, a persistent human pathogen, can overpower the immune system, offering clues that may lead to the development of life-saving antifungal drugs. Professor Fink joined the MIT faculty and the Whitehead Institute in 1982. He served as director of the Whitehead Institute from 1990 to 2001, establishing during this time the Whitehead MIT Genome Center, which in 2003 became the cornerstone facility of the newly launched Broad Institute.
4:37
MIT's premier place in the world of biological research is due in no small part to Professor Fink's selfless, tireless, and generally unheralded work in creating and nurturing these institutions. Professor Fink's scientific accomplishments have been heralded and recognized by many awards, including the National Academy of Sciences Award in Molecular Biology, the George W. Beadle Award from the Genetics Society of America, and the Gruber International Prize in Genetics.
5:15
He has served as president of both the American Association for the Advancement of Science and the Genetics Society of America, and he is an elected member, or fellow, of the National Academy of Sciences, the American Academy of Arts and Sciences, the Institute of Medicine, and the American Philosophical Society. He chaired a National Research Council committee that produced a highly influential report entitled Biotechnology Research in an Age of Terrorism: Confronting the Dual Use Dilemma.
5:48
This report recommended policies and practices that would allow the continuation of legitimate research while preventing the destructive use of biotechnology. In addition, throughout this time, Professor Fink mentored more than 100 graduate students and postdoctoral fellows and is approaching the publication of his 300th paper. This is an extraordinary career. Jerry, will you join me up here, please?
6:21
[APPLAUSE]
6:44
Gerald Fink, it is my privilege to represent the MIT faculty in honoring you with James R. Killian, Jr. Faculty Achievement Award. We recognize your pioneering contributions to the genetics and engineering of eukaryote systems and your scientific and educational leadership in the biological sciences. Congratulations. [APPLAUSE]
7:31
Thank you, Professor Silbey, for your generous introduction and the committee for choosing me as the Killian lecturer. I consider it a tremendous honor, especially because it's an award coming from my peers, family, rather than from outsiders, who often know your achievements, but don't know your contribution to your institution and colleagues. As I look out on this audience, I realize what an amazing group of talented scientists we have here at MIT and how fortunate
8:14
I am to be a member of this community.
8:20
I'd also like to thank the institute affairs office for saturating the campus with posters of me. [LAUGHTER]
8:31
As I walk along Main Street, strangers now stare at me as if I were someone they must have seen before, but can't quite recognize. [LAUGHTER]
8:44
Now, I'm a real American.
8:49
On my father's side, my grandfather came from Scotland. And on my mother's side, my grandfather came to America from Lithuania through Brazil.
9:05
I grew up in Freeport, New York, a complacent suburb on the south shore of Long Island, notable only for its easy access to New York City and for its access to Jones Beach State Park. The high school was sleepy and uninspiring. Its heroes were the athletes and their admiring cheerleaders. The successful launching of the Russian satellite Sputnik in October 1957 awakened this sleepy town, electrified the nation, and changed the course of American science and my future.
9:50
And I can still remember the thrill one dark fall evening in 1957 when I went out in our backyard and was hypnotized by the new star in the sky as Sputnik slowly raced towards the horizon. Overnight, science became a national priority energized by the dread of Soviet technology and technological superiority. Local engineers from Grumman and Republic Aviation came to our high school and taught math courses pro bono.
10:33
Not only did this improve my science education, but perhaps, equally important for a teenager, the cheerleaders suddenly took an interest in the smart kids. [LAUGHTER]
10:53
I came to MIT in 1982 after 15 years as a professor at Cornell as the first appointed professor at the Whitehead Institute. Now, probably, looking out here, most of you probably cannot recall, but the idea of an independent Whitehead Institute associated with MIT was considered a radical experiment at the time. MIT was not sure it wanted to take the leap. Concern among the faculty spawned articles in The New York Times.
11:44
The third and perhaps last time the faculty in Massachusetts will convene to try to resolve one of the most divisive conflicts-- I think there's a bit of hyperbole here. [LAUGHTER]
11:59
But it was a difficult time. Now, while still at Cornell, I was on the visiting committee for the biology department when the faculty was debating the wisdom of having this separate institute. Now, as you know, the visiting committees here at MIT are taken extremely seriously. At the committee meeting, we sat around in a circle with the faculty, and there was heated discussion, pro and con, about the possibility of the Whitehead. I was fortuitously sitting next to the president of MIT, Howard
12:48
Johnson, who whispered to me, do you think this would be a good thing? I whispered back, absolutely wonderful opportunity. Two weeks later, after I had this whispering exchange with President Johnson, MIT agreed to the Whitehead, and I was immediately offered a position at the new Whitehead Institute. [LAUGHTER] Let me assure you there was no collusion. [LAUGHTER]
13:33
As we now know, MIT made the right decision. Whitehead turned out to be a successful pioneer, a pioneer experiment that led, in my opinion, to the blossoming of the Kendall Square area. And we should not forget that Whitehead was the home of the Human Genome Project and the model for the many other institutes that have grown up here now at MIT.
14:01
Moreover, three previous Killian awardees were Whitehead faculty.
14:08
I came to MIT with some trepidation. I was told by the chairman of the biology department not to go across Main Street after dark. It was too dangerous. Well, there was really nothing on this side of Main Street, either, except MIT.
14:31
So this is what it looked like when the Whitehead was being constructed. Here's Main Street. No Novartis. Back here, I think, was a building that store popcorn and beer for Fenway Park. OK. [LAUGHTER]
14:53
There was only one restaurant, the F&T Diner.
15:00
I didn't know-- oh, yes.
15:06
This was construction of the Whitehead. This was the first director, David Baltimore. This is Jack Whitehead, who engendered this New York Times article. And you may not believe it, but that's me. [LAUGHTER]
15:33
I didn't know what it would be like to leave the rustic, pastoral countryside of Ithaca to come to the big city, but my confidence was buoyed, as it has always been, by my family, my wife, Rosalie, and my two daughters, Julia and Jennifer. But MIT turned out to be much better than I had imagined. It's a real community of scholars, and I was welcomed into this community. Perhaps no better indication of what I mean by a community of scholars is to note the wonderful people with whom
16:10
I have collaborated in research and published papers over the years.
16:18
They were not only from biology, this group on the left, but also from a number of other departments. Alex van Oudenaarden when he was in physics, Greg Stephanopoulos and Bob Langer in chemical engineering, and David Gifford from EECS, all co-authors of papers with me since I've been here. This is unique to many institutions.
16:48
Furthermore, it wasn't just in research. Another sense of community is the number of compelling colleagues who taught courses together with me. This group on the left taught undergraduate courses with me. And the group on the right taught graduate seminars together with me and some graduate courses.
17:14
Bob Horvitz probably doesn't remember that we taught a course a number of years ago.
17:23
So in this lecture, I would like to address the question that has intrigued me and geneticists throughout my career-- what is a gene? In the lecture, I hope to live up to a charge given to the speaker for the Killian lecture. According to the terms of the award, I quote, "these lectures are intended to be at a level that will make them understandable to a majority of the faculty and students at MIT."
18:02
So you may ask, why waste time on this question when the gene, what it is, is common knowledge? You hear it all the time. It should be a simple task. It's integrated into our daily language. Everybody seems to know what it is. A book has been written about it. And PBS is planning a special on the gene.
18:26
The author of this book won a Pulitzer Prize for this book, which many you may have read, The Emperor of All Maladies, where they get most things right.
18:42
They also wrote a book called The Gene, where much is incorrect. [LAUGHTER]
18:55
And after reading it-- it's 600 pages long.
19:00
Not a real page turner. [LAUGHTER]
19:08
I was completely confused about what the gene was. [LAUGHTER]
19:17
But you can't avoid it. Gene talk is everywhere. I hear workers behind the counter in Starbucks talking about their genes, no doubt because companies like 23andMe or AncestryDNA-- I'm not partisan here-- look at your DNA and promise to provide you not only with your ancestry, but your potential health or why don't you feel chipper every morning.
19:56
A little saliva is all it takes. You spit into a tube, and you send it off to them. Well, I was teaching 703, and I kind of poopooed this 23andMe. And several undergraduates walked up to me and said, did I do it?
20:16
They said, you're a geneticist. Aren't you interested? So I did it.
20:23
And I got back this email. Here, Gerald Fink. [LAUGHTER]
20:38
Our laboratory attempted analysis of your saliva. I don't have any DNA in my-- I have no DNA. But I don't need to worry. [LAUGHTER]
20:55
I spit again. It worked. It worked the second time. Now, geneticists have struggled with the definition of a gene since genetics began as a science at the dawn of the 20th century. It's a young science. And it may seem strange that in his Nobel talk, one of the great geneticists, T.H. Morgan, said, what are genes? Now that we locate them in the chromosomes, are we justified in regarding them as material units, as chemical bodies of a higher order than molecules? And here's the kicker.
21:36
Frankly, these are questions with which the working geneticist has not much to concern himself, except now and then to speculate as to the nature of the postulated elements.
21:53
The discovery that DNA is the genetic chemical body of heredity, coupled with the ability to sequence the DNA of whole genomes, requires the definition of a gene for reasons that T.H. Morgan could not have anticipated.
22:12
The DNA sequence of a genome yields a string of billions of nuclear bases that are incomprehensible without the aid of a computer. But the computer, shown here, is helpless in its search for genes within this vast sea of nucleobases without an explicit definition of a gene.
22:40
You can't tell the computer, I don't have a definition of the gene. If you try, the computer says, hey, you just fed me three billion base pairs and want to know how many genes are in the genome. How about a definition? So 20th century scientists must have a definition of the gene that is computer compatible. And arriving at a computer compatible definition of the gene took an enormous amount of work and resulted in four Nobel prizes. A current definition of the gene used to program the computer
23:18
is the sequence of bases in DNA sufficient to encode a single polypeptide. This comes from the central dogma that I think they teach now in grade school. DNA makes RNA makes protein.
23:42
And so what does a gene look like to the computer? There's a string of bases. And what the computer sees is, oh, there's an ATG. That's like a capital letter in a sentence. And then, it reads along in frames of three these bases until it sees the period in the sentence.
24:07
In the decoding process, each successive triplet code specifies the next amino acid to be added to the polypeptide chain. So what about the code? Well, you can read it right off this table.
24:28
So if you look at AUG, methionine, that would be the beginning of the protein that it specified. And you go along this whole chain by threes until you get to one of these stop words, the period.
24:48
So for the computer, a gene is defined as this segment of DNA that's translated into proteins starting with a triplet, ATG, and ending with a period.
25:04
So what does the genome of protein coding genes look like to the computer? You can see the smile on its face. It's happy. Here's gene one. Makes an RNA. Then, RNA translated into a protein. Gene two. Gene three. Gene four.
25:26
So when you read in the newspaper that humans have about 20,000 genes and the yeast genome has about 5,500, that's what they're talking about, these protein coding genes.
25:46
Now, the question of what is a gene became more pressing for me in my own lab when we discovered how to transform yeast with DNA because the ability to transform yeast meant we could insert any gene into yeast and express the protein.
26:05
So what protein?
26:10
Well, it could be whatever your favorite gene was, but you had to know what the code was for that gene. Let's say you wanted to express insulin, for example. You had to know what the code for insulin was. You could get that gene from human tissue, put it into yeast, and now, yeast would decode it and make human insulin. Indeed, half of all human insulin is now made in yeast.
26:49
Knowing what a gene is in terms of the protein coding gene is really important. In fact, all of these proteins are made now commercially in yeast.
27:11
Hepatitis B, which is eliminating hepatitis B in mainland China-- the vaccine is made. Gardasil against human cervical cancer. I mentioned insulin and all the rest of these. So it spawned an industry that continues today. Yeast is easy to grow not only to make beer and wine, but to make all of these medicinal products.
27:48
But I think that what may have the most profound effect on economics and society in general is what I read in New York Times on Tuesday. And that is "Behold the Beefless Impossible Whopper."
28:18
Burger King is introducing a Whopper made with a vegetarian patty from the start up Impossible Foods. I have no stock in Impossible Foods. [LAUGHTER]
28:32
So this is a-- you should know the background to this, which is that a highly respected scientist at Stanford University, Pat Brown-- me and my colleagues know. Very imaginative guy. Got tired of academia. He's a vegan. But he was forced to taste a hamburger and realized as much as he liked veggie burgers, they don't taste the same. I've tried. If you put enough ketchup on, they taste like ketchup. [LAUGHTER]
29:19
And so he started-- he left Stanford and started a company, Impossible Foods. And he then did taste tests. What is it that makes a hamburger taste like a hamburger? And it turns out that it is the hemoglobin in the blood of the meat that you're eating from cattle.
29:48
It's this iron containing protein.
29:57
This is a true story.
30:01
So what gave hamburgers their distinctive taste was the cow's blood, specifically hemoglobin protein. Now, it turns out that soybeans have a heme protein that mimics the taste of hemoglobin in the cow. Legumes make like hemoglobin. So what did he do? He cloned the like hemoglobin gene into yeast and produced tons of it and made hamburger patties without any cows.
30:46
The head of tasting at Burger King said, quote, "employees were not able to tell the difference between the old meaty Whopper and the new one. People on my team who know the Whopper inside and out-- and I'm sure they do--
31:03
they try it, and they struggle to differentiate which one is which."
31:09
I think this is fundamentally going to change agriculture and farming and many other things. I will point out a farm of 3,000 cattle produces the amount of manure of a city of 500,000. That's Sacramento or Atlanta.
31:33
This is game-changing.
31:40
Now, also, Professor Silbey mentioned that I like yeast, which I do.
31:55
I want to point out that when you're pumping gas in your car, 40% of the corn that's grown in the United States goes to feed yeast to make ethanol.
32:09
Right Greg? And so this is not to feed livestock, but to feed yeast.
32:28
So, together with Greg Stephanopoulos, we've used gene editing, whose modern incarnation is CRISPR, to modify the yeast genome. And we tried to make any little improvement you make when you're dealing with-- the US is aiming for 15 billion gallons of ethanol per year made by this process. Any little bit that you change is, of course, transformative. So having a definition of the gene has clearly been a benefit for both basic research and human health. And you might want to know not about yeast.
33:16
How does a human genome look to the computer? If you look at four people's genomes--
33:32
these are past presidents. This is the current president, in case you didn't recognize it.
33:42
The important thing to note is how conservative evolution is. They all have the same genes in the same order. Evolution is very conservative with the protein coding genes. Now, this little gene over here shows that there might be spelling changes between Abraham Lincoln's genes and [INAUDIBLE] genes. Lincoln was thought to have Marfan syndrome, so he might have a coding difference because that gene encodes a protein, fibrillin-1. And if he did, that might account
34:33
for his description of him as tall and thin with long arms and legs. But the genes are all in the same order. there's no change in that. In fact, the remarkable thing to me as a geneticist is how conservative evolution is. If you look at these protein coding genes in humans and the mouse, much of the gene order is the same, even though they had a common ancestor 75 million years ago. Why didn't it all get scrambled up? Something is keeping these things in the order.
35:13
So these are two chromosomes, and this is the alignment of genes on those two chromosomes that have been saved over the millennia. It's quite remarkable.
35:30
It accounts for the fact that if you don't-- why is a mouse such a popular organism to work on? Well, if you don't know what a gene does in humans and you figure it out in the mouse and you know where it is on the human chromosome, there's a pretty good chance it has a similar function in the mouse.
35:54
So the definition of a gene as a DNA sequence that codes for a protein coupled with the sequencing of the human genome I think has-- everybody does-- revolutionized molecular medicine. It's been a remarkable milestone. Genome sequencing, along with computational power to compare and analyze genomes, has led to important insights into basic science and disease. As an example, we know the genetic basis for literally thousands of inherited diseases caused
36:32
by those spelling changes I showed for Abe Lincoln in protein coding genes.
36:45
Sickle cell disease, which afflicts about 100,000 Americans roughly, it's one of the earliest molecular diseases identified where a component of hemoglobin normally has the codeword CAG.
37:10
Gluten codes for this-- amino acid glutamate, you have a normal red blood cell. In sickle cells, there's been a change in the code to make valine instead of glutamic acid, and so red cells sickle.
37:33
These sickling cells cause periodic episodes of pain called crises. And pain develops when the sickle red blood cells block blood flow through the tiny vessels to the chest, abdomen, and joints. Now, when I used this example of a molecular disease to teach 703, an MIT undergraduate came up to me at the end and said, oh, just reverse the arrow. Then, you can cure the disease.
38:11
It's easy in PowerPoint. Very easy in PowerPoint. Unfortunately, the student asked the question about reversal more than 10 years ago at a time we didn't know enough about how red blood cells differentiate from bone marrow stem cells, and we didn't know enough about stem cells. And there was no CRISPR to edit the gene and reverse the arrow. But now, armed with CRISPR and really deep knowledge about stem cells, it seems feasible to make the correction in patient's own stem cells
38:51
use a gene editing by CRISPR, coupled with knowledge about the bone marrow. Normally, in a bone marrow transplant recipient, you have to get rid of their stem cells, get stem cells from someone who's a compatible donor, and then, hopefully, they'll take home in the patient and regenerate good red blood cells. But often, there are immunological problems because the two people are not the same person. But with this new technology, you could reverse the sickle cell trait in the bone marrow
39:37
stem cells of this person and populate them with their own cells, not donor cells.
39:51
This is not the germline editing of embryos to make genetically modified children, for which scientists have called a moratorium. This is similar to bone marrow transplants used widely today to treat hematopoietic diseases, and not the germline. You'd be your own donor, populating your bone marrow with your own genetically modified cells, but your eggs and sperm would be unchanged.
40:25
The protein coding gene makes cures just around the corner is my title. And there are articles popping up in The New York Times frequently because I think it is true. We are close.
40:41
I predict this type of gene therapy will be one of the great successes of modern medicine in the 21st century and is a wonderful benefit of science achieved in our time, not only the sequencing of the genomes, but the definition of a gene as encoding for a protein.
41:02
Now, with this evangelical prediction, if this were a TED Talk, which [INAUDIBLE] calls God talks, I could end the lecture here. As a recent TED speaker ended her talk, my talk should get your testosterone up and get your cortisol down.
41:32
However, the sobering fact is that these protein coding genes constitute only 2% of all the DNA in your cells.
41:43
What does your DNA really look like to the computer?
41:50
Well, here are the genes we've been talking about. But 98% of it is outside of these genes.
42:00
And the computer is frowning because they are invisible to the computer.
42:09
The computer doesn't like this. Now, what do you do when you have a good definition that the computer likes and gives you results, but can't explain 98% of the data? Do you know what happens? I don't care what field you're in. It happens in all fields. You could ignore it, or you could given a name that defies a definition. Geneticists could call it dark matter. [LAUGHTER]
42:45
But that name is already taken. [LAUGHTER]
42:50
You could call it garbage or junk DNA. Well, it ended up being called junk DNA.
43:00
According to Sydney Brenner, you need to distinguish between garbage and junk. Garbage, you throw out. Junk, you keep. [LAUGHTER]
43:16
Right after I arrived at MIT, my lab obtained results suggesting the junk DNA was not just an uninteresting, inert wasteland. We found that yeast had jumping genes, genes that leapt from one place on the chromosome to another by a process of retrotransposition. And where did they end up? In the supposed junk DNA.
43:48
So here, gene one, gene two. Here is the supposed junk. But these jumping genes would jump around.
44:04
And if you look at the DNA now, not of the conserved protein coding genes, but in this interstellar space in between them-- Rafael has one here. Susan has one here. President Obama has one here. Abe had one there. They're all in different places. And furthermore, instead of DNA, RNA, protein, they just went DNA, RNA. They didn't make protein. And furthermore, if they tended to land near one of the protein coding genes, as shown here for Abe, they affected the expression of that gene.
44:58
So here, we have a real conundrum, which is they didn't have the classical DNA, RNA, protein, just DNA, RNA, but they had a function. And they landed all in this wild world of junk DNA.
45:20
This alerted me and many others to the fact that lots of junk DNA might be making RNA, but not proteins. What was needed was a technique, a very sensitive technique, to assess the total RNA output of the genome from protein and non-protein coding DNA. And a very sensitive method was devised, not by me, to sequence all the RNAs in a cell, called RNA-seq. And when you looked at the total RNA output of the genome, you saw an amazing collection of RNAs,
45:56
not only those that made proteins, but those that had no protein coding capacity. That is, they want DNA to RNA, but no protein.
46:13
No ATG and no open reading frame. No capital letter and no open reading frame. When I discussed this initially with a computer biologist--
46:30
a computational biologist. Excuse me. He's a well-known one here on campus. He told me, don't worry. These RNAs from the junk DNA are noise.
46:46
But they turned out not to be noise because these RNAs have functions. And you know they have some functions because they now have names. [LAUGHTER] MicroRNAs. LncRNAs. Long non-coding RNAs is the acronym. RAN RNAs. And the list can go on. So these are, in other words, what's coming from interstellar space here, is lots of non-protein coding RNAs. And are they noise? No. OK, they're not noise because over the last 15 years or so, it turns out these microRNAs are
47:38
critical for controlling gene expression of those protein coding genes. And the long non-coding RNAs are critical, as well. These are so wild, I won't discuss them. And they're antisense RNAs.
48:03
So what is the function of these RNAs? The image is just emerging.
48:11
But, of course, they're invisible to the computer because we don't have an algorithm to identify them in the DNA or what they do. They're in this vast genome interstate.
48:31
So while many scientists sleep at night and sleep well at night without a definition of the gene that includes DNA that codes for these non-protein coding RNAs, which constitute a huge percentage [INAUDIBLE],, more than the protein coding, that we call genes, geneticists sleep like a baby. They wake up every two hours crying. [LAUGHTER]
49:08
But these RNAs are not just recreational or noise. They're regulatory, like these microRNAs and lncRNAs depicted here, turning on or off the protein coding genes. And only now are we beginning to visualize the importance of this formerly invisible part of the genome. As an example, I'll focus on the best known of one of these lnc, or non-coding, RNAs, which has an important role in silencing genes, but only in females. As you know, females have two X chromosomes,
49:48
one they got from mom, one they got from dad. And this lncRNA actually codes one of the two X chromosomes, either the one from mom or the one from dad randomly, and shuts it off. That's weird.
50:13
Men are uninteresting. They get only their X chromosome from their mother. And so that's quite different from females, who have two. Now, why would you have this mechanism? Well, there's a dosage problem. If women get two X chromosomes, they should have twice as much of all those protein coding gene products as the men.
50:47
But they don't. They have exactly the same amount.
50:52
It turns out that this lncRNA shuts down most of the genes on one of the two X chromosomes.
51:08
Remember, she got one of her X chromosomes-- all you ladies got one of your X chromosomes from your mother and the other from your father, here shown as pink and green.
51:24
This RNA shuts off one or the other, and it does it early in development. So men, for any cell that you look at, all of their genes come from one X chromosome, and they're all one color. You can imagine color blindness, for example.
51:52
They'd be all one color. They would see or not see, depending what gene they got from their mother. But women are much more interesting. They have this polka dot pattern because one of their X chromosomes, the one they got from their father, from their dad, is shut off and is now expressing only the genes from the mother, or the other is only expressing the one in the father. Now, if you look at this in a mouse in a real experiment-- and what we're looking at here, this
52:33
was an experiment done at Johns Hopkins in the laboratory of Jeremy Nathans. We're looking at individual neurons in the brain of the mouse. And you see for individual neurons, some are expressing mom's, and some are expressing-- I don't know whether you call mice mom and dad. One is expressing mom, and one is expressing dad.
53:01
And even to me, more remarkably, this left-right asymmetry in some of the neurons-- some neurons on the left side of the brain are expressing one X chromosome, and some, the other. And so this left-right asymmetry is not seen in males. They're either red or green.
53:27
This is all due to this long non-coding RNA, again, which would be invisible to the computer.
53:37
This is, to me, remarkable results and, I think, to people in the field, suggests that X chromosome mosaicism in the human central nervous system caused by one of these strange lncRNAs could generate female-specific functional diversity that does not exist in males. And the similarities in early brain development across mammals suggests that the observations made in the mouse may apply to humans. In fact, there's already data suggesting inhomogeneities in human female X chromosome mosaicism.
54:15
And a question that might arise in your mind is, does this variability caused by this non-coding lncRNA lead to behavioral differences, even among genetically identical individuals?
54:32
So these lncRNAs have an important function, so important they now have their own blog, and journals are now full of what used to be called junk. I like the other side here-- extremely volatile. Because they're much more evolutionarily mutable than the protein coding genes. They've even got their own blog, lncRNA blog.
55:10
They do everything. Long intergenic non-coding RNA promotes colorectal cancer, HIV infection, [INAUDIBLE] kidney cancer. The literature is flooded with that used to be noise.
55:32
So I've been referring to non-protein coding RNAs that don't make proteins. There's even junk in protein coding genes that confuses the computer. Many protein coding genes are discontinuous genes. That is, you go along. There's an ATG. You see some coding. And then, there's some junk, which is called an intron, in the middle of the gene. And then, the gene again. And then, this is spliced out, as shown by Phil Sharpe in his Nobel Prize-winning work. These genes are mosaics, small pieces
56:16
of coding sequences interrupted by non-coding sequences here. The computer doesn't recognize. It can't tell when they come. These junk genes here, which would be very nice to recognize because then, you'd say, oh, there's an interrupted gene-- but the computer can't-- they're not consistent enough for the computer to recognize them. People here have worked trying to find those signals, but can't find them.
56:57
What's even worse-- some of these genes-- the intervening sequences, the junk, is bigger than the gene itself, the protein coding, or there are many small coding sequences camouflaged by introns. So the computer goes along and then suddenly has to start. It can't find one of these genes. So I point out, what happened to this junk? It's supposed to be discarded, chewed up. Well, it turns out the intron is not junk. Oh, my god. So together with Dave Bartell, we just published a paper
57:52
showing that excised linear introns regulate growth in yeast. Namely, this piece of non-coding RNA now has a function.
58:25
These have no obvious sequence conservation. They do have some size constraints. I just want to emphasize again that your genome is full of these protein coding genes that were thought to be junk, but this paper shows they have valuable information. Now, this paper reincarnating the intron as genetic information with function generally received a rather complimentary, though I have to say, surprised response from the readers of the paper.
59:08
There are those that cannot deal with this continued attack on the definition of the gene. It made them very anxious. Soon after publication, I received this email from a highly regarded biochemistry professor at Berkeley. "Just wild. Now, I have to pay more attention to all that splicing crap." OK. [LAUGHTER]
59:49
So, as [INAUDIBLE] explained, the current definition of a gene used to program the computer, the sequence of bases and DNA sufficient to code a single polypeptide, is inadequate to embrace all the different informational units of the genome.
1:00:16
The existence of these diverse classes of RNAs, microRNAs, lncRNAs, antisense RNAs, enhancer RNAs, intron RNAs, and many others that are cropping up that don't encode proteins but are transcribed from distinct sequences of DNA are evidence that there is no single physical and functional unit heredity that we can call the gene.
1:00:46
Rather, the genome contains many different categories of informational units, each of which may be considered a gene. And the definition I think that is compatible with current knowledge is a DNA sequence that's transcribed into an RNA molecule with a function. This RNA centric definition would permit a number of categories of gene, each one denoted by an adjective that describes the transcription unit. So there would not only be protein coding genes, but lncRNA, intron, et cetera.
1:01:21
Really, this is not radical. The terminology is already becoming part of the vernacular. It's part of the literature. The majority of these RNA only units would currently be invisible to a computer program to uncover only genes that encode proteins. But progress is being made. For some RNA only genes, like transfer RNA and ribosomal RNA, they're so evolutionarily conserved, the computer can easily spot those signature sequences in the DNA. For micro RNAs, progress is being
1:01:59
made in identifying secondary RNA folding structures that conserve signatures for microRNAs. But so far, the lncRNAs and other non-protein coding RNAs have not identified unified identifying signatures that enable the computer to see all of them in the vast sea of nucleotides. But I believe that the importance of these genes for non-coding RNAs and the flurry of activity around them-- definitions that will work for the computer will emerge.
1:02:40
And I think as this attempt to identify definition for these genes, the computer will work together and be an indispensable ally of the lab bench scientists trying to figure out function.
1:03:01
So in genetics, we've lost a simple definition of a gene, a definition that lasted over 50 years.
1:03:14
But loss of the definition has spawned whole new fields trying to understand the unknown, information in non-protein coding junk DNA, which is, after all, 98% of the information. As scientists witnessing the unknown creates that intense moment of exhilaration as a new vista unfolds, whether it's, in your field, discovering a new planet or unraveling the role of unanticipated RNAs, it evokes an emotion that I have personally found difficult to express in words.
1:03:56
Perhaps, it's best expressed in music.
1:04:03
[MUSIC PLAYING] To go where no one has gone before and to see what no one has seen before, this lure of these unexpected voyages is what drew us all to science in the first place. I look forward to enjoying these voyages with you. Thank you. [APPLAUSE]
1:04:48
Will you take questions? If you want me to. [APPLAUSE]
1:05:05
Thank you, Jerry. At this time, Professor Fink will answer one or two, maybe three, questions about his work or the lecture. And so I will ask those who want to pose the questions, as you're forming the queue and thinking about your questions, to let you also know that afterward, I invite you all to a reception downstairs in the lobby of building 13. Do we have any questions? I was about to ask one, but the microphone is quite far away. OK. [INAUDIBLE] speak loudly. Go ahead. Jerry. Hi.
1:05:40
Truly, truly congratulations. This is such a well-deserved award. I've known you since I was very small, and you've been always such a wonderful mentor to all of us, all of your students, and extended groups. So thank you very much, and congratulations. I want to go to that last point that you made that maybe our computers will be our friends one day and sort of be happy about the signal. And I want to challenge that a little bit because I work on the computer.
1:06:10
And we've looked a lot for these signals, and they're simply not there. I mean, basically, it's not that we haven't looked for a code for these non-coding RNAs. Coding genes have a code. [INAUDIBLE] they have codons, et cetera. If you look evolutionarily, you look transcriptionally, if you look at [INAUDIBLE],, if you look in all kinds of ways, there doesn't seem to be a single code. So my question to you is, what do you mean by that statement?
1:06:39
Do you mean that we simply haven't found the code yet, or is it that we have to think about it differently in some way?
1:06:52
Is Dave Bartel here? [LAUGHTER] He should really answer. Because-- [LAUGHTER]
1:07:03
He should answer it because for the microRNAs, there are signatures of the microRNAs, which he has-- And we've worked together with Dave [INAUDIBLE] [LAUGHTER] So why are you asking me? [LAUGHTER]
1:07:22
My question's about the lncRNAs and-- The lncRNA.
1:07:28
I don't have an answer to that, although there are some lncRNAs that are conserved.
1:07:38
[INAUDIBLE] You're younger than I am. You should solve this problem. [LAUGHTER] I was hoping you were going to guide me. You've been doing that my whole career.
1:07:54
I have a simple question. Why do the microbiologists go to sleep at night, and they sleep right through the night because the DNA going to RNA going to protein holds? It's only in the eukaryotic cells with nuclei that you have the problem or the-- how should I say it-- the joy of searching for these RNAs.
1:08:23
Actually, bacteria have them. They don't. They don't have them. They have some small RNAs. Yeah. If you take a bacterium like E. coli, 99% of it is either coding or ribosomes or tRNA. And then, there's a small smattering of small RNAs. Now, there's no such thing as lncs or microRNAs that our equivalent. So there is something going on in the eukaryotic cell, the cell that you study, that is totally different than what's going on in bacteria. And the question is, why? [LAUGHTER]
1:09:19
I don't know. [LAUGHTER] End it now? That's it. Again.
1:09:28
Would you all please thank Professor Fink? [APPLAUSE]
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