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Base Pairs Season 2

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Cold Spring Harbor Laboratory’s award-winning podcast, Base Pairs, tells stories that convey the power of genetic information—past and present.

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Episode 13: A lesson in class

No, we’re not talking about high society or your biology class! In this episode, we share three distinct stories about classification in the life sciences and how genetic information is changing how we define important categories.

BS: Hey everyone. My name is Brian.

AA: And I’m Andrea.

BS: And this is Base Pairs, the podcast about the power of genetic information.

BS: Today, as promised, is our season finale, and for it, we’re going to talk about classification. That is, the part of the life sciences that puts everything into the neat little categories that the birders, librarians, and text-book authors of the world love oh so much…

AA: Sounds like you’re classifying the classifiers as boring people! You may think Brian paints a pretty drab picture of this topic, but in reality, scientific classification has never been so simple OR mundane. Here’s what I mean:
[Music change}
In order for any category to be useful, it has to mean something – and that’s a problem that all kinds of experts in the life sciences have been arguing over and struggling with for a very long time. [pause] What we want to talk about in this episode is a couple of different ways in which our ability to understand the messages in genes is revolutionizing our ability to classify things in nature – whether different species of animals, our own human ancestors, or even cells in the human brain!

AA: So Brian, take the category of “human” for example. What does it mean to be a human, like you or me? — in a scientific sense, not a waxing philosophical sense.

BS: Ok, I’ll bite. It means that we’re part of the modern human species, Homo sapiens.

AA: Well, you may recall from episode 3, “Non-Modern Family,” that category isn’t as bulletproof as a lot of people think it is. Remember this?

AS: We don’t really know what a species is.

BS: Oh yea! That’s Professor Adam Siepel, Chair of the Simons Center for Quantitative Biology. He’s spent a lot of time looking through the genomes of not only modern humans like us, but also ancient humans like Neanderthals.

AA: And Neanderthals are considered to be a different species, Homo neanderthalensis. But what’s really different between Neanderthals and modern humans? What makes us different species?

AS: Historically, species was used for groups of individuals that could no longer interbreed and have fertile offspring. But then the concept was extended when people began to dig up fossils of ancient individuals and they were called different species because they looked different from the modern humans that we know — And by implication that suggests that they couldn’t interbreed, [pause] but now we know that they could interbreed.

BS: Then why are they still considered different species?!?

AS: Well, that’s still hotly debated in the scientific community. Today, the argument is that Neanderthals and modern humans are different species because they did not interbreed—have kids together, in other words—very often. In general, modern humans mated with modern humans, and Neanderthals with Neanderthals. And scientists like Adam know this from studying the genomes of modern humans and Neanderthals.

BS: Because breeding mixes the DNA of both parents together in the child. So, since modern humans and Neanderthals only interbred occasionally, these groups still have distinct genomes.

AA: Yes, the differences in their genomes provides a concrete reason to classify modern humans and Neanderthals as different species. In fact, by using this approach, Adam’s team even found an entirely new subspecies of ancient human that once lived around the Denisova Cave in Siberia.

AS: This Denisovan individual we’ve identified as a whole new subspecies on the basis of one pinky bone. I mean, that’s just unthinkable by the standards of anthropology in previous decades and centuries. So that to me is really fascinating—the idea that we can get at these ancient stories just by analyzing the DNA sequences.

BS: Wow, that is powerful. They couldn’t tell that it was a new subspecies just by looking at this tiny bone fragment, but they could look deeper, into its DNA, to figure out its real identity.

BS: That’s so VASTLY different than how classification used to be done. I remember as a kid, wanting to be a paleontologist – but not the kind who dug up bones. I wanted to sit in quiet museum archives somewhere piecing together the bones of some ancient dinosaur like an epic erector set – then giving it a name and species, and determining who it was related to just by squinting at skeletal structure and the fossil record alone. For a long time, that was how even MODERN species were classified [pause] BUT clearly, in this age of genomics, things have… evolved.

A: (groans) I’m going to just ignore that wordplay…

E: I extracted samples and I was DUMBFOUNDED when I looked at the DNA sequences.

B: That’s Evon Hekkala, a Fordham professor and research associate at the American Museum of Natural History. She first told her story for the museum’s Shelf Life YouTube series, and it describes I at least think is a super fascinating complication for this whole classification endeavor.

EH: I was doing my dissertation research on crocodiles, and as I was collecting data I started to realize that there were a lot of places where you couldn’t get samples anymore because crocodiles had gone extinct at those sites. And so I thought “maybe I can use museum specimens to fill in some of these gaps…” I found that here was this expedition to the Congo from 1909 – 1915 by the American Museum of Natural history. And those explorers had collected crocodile specimens.

AA: Ah. So Evon benefited from the passionate naturalists of the past. The ones who really helped the modern biologists decide what the term “species” was going to mean.

BS: Yea, but when she took a look at these specimens on a genetic level, what she discovered is the kind of species that those historied naturalists never would have seen.

EH: So this site right here, Feraage (sp?) is where they collected two specimens of crocodile on either side of this little river. And it turned out that one specimen has one DNA sequence and another specimen has another DNA sequence and they were COMPLETELY DIFFERENT! And I started thinking… “there must be a cryptic species here!”

AA: Cryptic species… I think I’ve heard of this before, and it’s a pretty crazy concept! It’s essentially what we call species that are very genetically different, but they look nearly exactly the same.

EH: It turned out that one species there represents the Nile crocodile that we all know and love from the Nile. And the other represents a completely separate species of crocodile. In fact, they are so distinct that they’re not even each other’s closest relatives.

BS: Here’s what’s amazing. Those two crocodile neighbors, living right across from one another on the banks of a river – and therefore thought by old-school naturalists to have been members of the same species – had, in reality, been part of groups that…

EH: had not exchanged genes in millions of years.

AA: Oh wow!

BS: Yea. According to our friends at the American Museum of Natural History, modern genetic sequencing is revealing cryptic species in virtually every animal group out there, showing that even after a couple centuries of species-seeking, there is still so much we don’t know about where to draw the lines between species.

AA: But… our story doesn’t just stop with a pair of crocodiles.

BS: It doesn’t?

AA: Of course not! We’ve talked about WHAT a species is, and how comparing entire genomes of individuals is helping us better understand and – in some cases – even expand upon that definition. But what about in other aspects of biology? Can the information packed into the genome tell us more about the incredible diversity of cells that all of us are made of? To answer that question, I talked with someone who studies arguably the most complex organ of all: the brain. (dramatic sound effect)

AP: The problem with the brain is, unlike other organs there are all this different cell types all mixed together in one organ. Essentially, it’s like multiple organs, just a big rat’s nest, everything’s put together.

AA: That’s my friend Anirban Paul – a postdoctoral researcher here at CSHL – and he’s describing how the brain, in a certain way, is like Dr. Hekkala’s Congo riverside. It’s populated by lots of individuals – neurons in the case of the brain – and while we know that MANY of these cells look the same – just like those crocodiles – and others look different… what we don’t know is whether this actually means anything.

{city sounds fade in}

AP: the way I tell this story is let’s say first time you walk into Manhattan, you see people of all race, color, age, everything. And then you are overwhelmed. But, then if you want to say how do I distinguish one from the other, you really can’t unless you select certain populations and look deeper. Like where they came from, what they do, and so on and so forth.

AA: As things stand, most brain cells are classified by how they look and how we think they function. For instance, the lab of Professor Josh Huang at CSHL, likes to look at chandelier cells – these beautiful cells in the cortex of mammals like us, to which many other neurons connect. The way this brain cell branches makes it look like it should be hanging over an elegant dining room table. When Sir Francis Crick saw it soon after its discovery about 50 years ago, he proposed that it was a cell with “veto power” – this single, well-connected cell could inhibit the signals coming from hundreds of other cells in its vicinity.

BS: So, chandelier cells are an example of one basic kind of brain cell – it is inhibitory. And inhibitory neurons are like circuit breakers within large networks composed of other neurons. The trouble is, inhibitory neurons are a pretty diverse group! Like those two similar-looking crocodiles living on opposite banks of a river in the Congo, all neurons with many branching connections that inhibit other neurons may seem the same – but they’re not. It’s well known that chandelier cells are not the same as, say, basket cells, which also have many branches and are also inhibitory. But how exactly they are different from one another and other varieties of inhibitory neurons is something that still befuddles neuroscientists!

AA: I get it – so this is why Anirban and his colleagues want a much more rigorous way to classify these things. Neuroscientists have made some progress since the days of, “Oh! and this one looks like a lighting fixture!” but they still have a way to go.

AP: My question was what is cell identity? How do we know that this cell is different from another cell? So, if you can imagine 10 clones of me, but all of them are wearing different hats, are they different people? Or do they just look different?

AA: As you can tell, Anriban likes metaphors. I don’t know if that totally makes sense, but you can understand his goal. Much like with taxonomy, neuroscientists would benefit greatly if they could use the information packed into the genome to help classify brain cells. So that’s what Huang lab set out to do!

AP: So, what we did was we went into the nuts and bolts of what keeps a cell ticking, and we asked, “Okay, between these cell types, which are the one feature that would predict what this is?”

BS: The tricky part about brain cells is, in an individual, every cell has the same genome. So how can genetic information help us tell them apart?

AA: Right. What the Huang lab did was look at how that genetic information is expressed differently as a way of categorizing cell types.

BS: Ok. Time for a refresher course. Genetic expression is all about when and why certain genes activate within a given cell’s genome. Need a specific protein? The genetic information that codes for it – a lot like a blueprint – is copied into a message for the cell to follow, in order to manufacture that protein. In some ways, gene expression can work almost like a record of any cell’s behavior and development. BUT, a TON of that behavior isn’t exactly noteworthy. Going back to Anirban’s city metaphor, if we’re trying to break that dizzying number of New Yorkers into manageable groups, “people who eat” probably won’t be distinguishing enough.

AP: So, there are genes that are involved in replication, there are genes involved in transcription, there’s genes involved in oxidative stress management and so on. For neurons, we went through a whole bunch of these gene lists and said, “Oh, if I use this gene list, can I distinguish these cells?”

AA: Amazingly, Anirban told me that he and Professor Josh Huang spent countless mornings sifting through these gene sets, looking for any groups of significance. In all, he and Huang looked at more than 600 groups.

AP: You have a huge spreadsheet of that and from there our job was to first teach a machine learning algorithm to say, “Hey this is cell type A, this is cell type, B, C, D, and E. And these are the ingredients that made up cell type A, and those are the ingredients that made up cell type B. And now, tell me if I give you a subset of these ingredients, is it good enough to tell A and B apart?” The algorithm comes back and says, “Nope. This is no good. And yep, this is fantastic and so on.” The process repeats itself over and over again, until we get to a very high confidence list of genes.

AA: Incredibly, all that work revealed that only about 8% of those 600-plus gene families were distinct enough to show differences between cell types. But of course, that’s not enough.

BS: Right! Even if we use a bunch of expressing genes to distinguish different cells, that alone would be JUST as arbitrary as sticking neurons into categories based solely on how they look.

AA: So what they still had to determine was meaning. They had to ask, “well, what do these important genes do – in those 8% of gene families that are expressing in such a distinct way from cell-to-cell.

AP: Then we figured out that yes, these gene families are all related to the input function. These are all related to the signal transduction function, and then these are related to the output function of the cell.

BS: Hmm ok. So for those of us without a neuroscience degree, this means?…

AA: Essentially, it all has to do with how the cells were developing their cell membrane, because it’s THERE that different brain cells determine how and who they’re talking to.

AP: that’s where a lot of interesting things are happening. They are receiving signals, they’re sending out signals, they’re integrating signals and that’s where all the cell communication and connectivity molecules are expressed. So, to distinguish yourself, the cell needs to literally make changes on the proteins that are expressed in the cell membrane. They’re all so far, that we have looked into, point to the single quintessential function of cell to cell communication, synaptic communication.

AA: and if you think about it, this makes sense! If I wanted to get a sense of someone’s distinct personality, I might want to observe who they talk to and how they talk to them!

BS: Oh man! In fact, this is totally reminding me of targeted advertising, where experts are using our communications and behaviors on social media to group us into different consumer demographics… or different “species” of buyers, if you will.

AA: [laughs] It seems like a really common-sense perspective, right? But it was a hidden distinguisher until Huang lab started looking at what the genes are doing. And Anirban tells me that now he and Huang have had this eureka moment, they’re just beginning to tease out the whos and hows behind all the different cells.

BS: It’s all very exciting when you think about it that way. It’s like… thanks to genetics, SO MANY of these fields in life-sciences are standing at the edge of a whole new pool of discovery, and right now, they’re JUST beginning to test the waters. But the question is, will we learn how to swim efficiently? And… why should we bother?

AA: That’s easy. We bother because at the end of the day, this is about so much more than just discovery. Like we’ve explained before in Base Pairs, basic scientific discovery – this mission to further our understanding of everything – is just a means to an end. How else do you fix a car, if not by understanding – and yes, even classifying – its parts?! THAT’S why this is so important. It may seem arbitrary now, but by identifying new species, we can learn which groups are most affected by problems like poaching, urban development, or climate change! By tracing human evolution, we can also trace the origins of genetic disorders and disease! And by comprehensively labeling the components of the brain, we can effectively share ideas and research in the fight against threats like schizophrenia or Alzheimer’s!

BS: I joked at the top of the show that classification is a boring subject for boring poindextors or obsessive collectors… but in reality, like arguably all of scientific discovery, classification serves everyone. All that’s left is learning how to use it – and ever-improve it.

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Episode 12.5: Big decisions

Following up on the last Base Pairs episode, “Good genes, bad science,” we hear from David Micklos, executive director at CSHL’s DNA Learning Center, and Miriam Rich, CSHL Archives Sydney Brenner Research Scholar, on some big ethical questions.

BS: Hey, everybody. I’m Brian.

AA: And I’m Andrea.

BS: This is our fourth chat episode—fifth maybe? I don’t know. But regardless, it is about a really cool episode we just had about eugenics. So what is eugenics, Andrea?

AA: Eugenics is basically the idea of good breeding, or good genes. And that might sound like a good thing, but it turned out to be a very, very destructive thing.

BS: And you say “turned” because this is actually history. This is American history, and not too long ago either.

AA: Right, we’re talking about, you know, the early 20th century. Especially—the American eugenics movement really peaked around the 1920s, and that’s when laws that made it legal to force people to undergo these surgeries that prevented them from being able to have children started going on. And it was all in the name of improving the gene pool in the country and making sure “defective” genes did not get out into our society, basically.

BS: And now, in this modern age, we’ve got a means to improve gene pools, again, very efficiently and most importantly, accurately.

AA: Right, for those of you who may not know, there’s this totally revolutionary genome editing tool called CRISPR that makes it possible to make very precise changes to DNA. But the issues that people are really talking about with using CRISPR, in human embryos in particular, is what does it mean to be able to have this precise control over whether your baby is going to have the gene for a particular disease? Or, if we get to the point where we can pinpoint certain genes for, say, intelligence, what if we can make sure that an embryo has those? And that sounds like completely new territory. And that’s really how I was thinking of it before I talked to Dave.

BS: That’s Dave Micklos, executive director of CSHL’s DNA Learning Center.

AA: Yes, and he knows a lot about eugenics because he was the creator of the online eugenics image archive, which you can go check out at But that, as you can imagine, has really changed how he looks at a lot of things, having all of this historical knowledge. And even things that we’ve come to kind of take for granted in our society right now, like, you know, in vitro fertilization—it’s a pretty common practice—he really changed the way that I think about it.

(in clip) AA: Hearing all of these ethical discussions about using CRISPR in human embryos, what goes through your mind?

DM: Oh, everybody’s going to do it. Whatever technology becomes available for parents to do better for their children, parents will do. 100%, it’s been that way forever. Didn’t your parents want to give you certain kinds of lessons and help you be good at piano or voice or dancing or whatever?

AA: Oh, yeah.

DM: Yeah. They did whatever they could to give you a better life and they would buy you anything. How about if they had the opportunity to buy you slightly better genes, and they had the money? Do you think your parents would have done that?

AA: Yeah, probably.

DM: Yeah, forget about the whole difficulty of it and …

AA: Oh, yeah, of course but if … breast cancers runs in my family, if my mom could have gone to the doctor and said make sure my daughter doesn’t have the BRCA gene …

DM: And she wouldn’t care if it was gene editing or hocus pocus, she would do it because she was a good mother, and that’s what parents do, because they take care of their kids. So, of course, if their technology that could make your kid suffer less or prosper more, any parent will do that. So to say that people aren’t going to make use of genetic technology is a lie. Great example of … we have lots and lots of people now delaying child birth, and because of that, more reproductive problems. Lots and lots of people doing in vitro fertilization. Well, when you fertilize a bunch of eggs in a test tube, you can of course check for diseases that might be in your family that can be readily tested for, but soon you’ll be able to test for things that might have something to do with intelligence or athletic ability.

So let’s just take the case where you’re fertilizing these eggs and you can know anything about one egg over the other. So let’s say that there’s six fertilized eggs there, you come from a family that might have a history of breast cancer. You’re certainly not going to take any of those fertilized eggs that the data suggests might carry breast cancer. You’d be a fool to take any of those, right? And of course, you wouldn’t. How about if you could know just a little more information about any one of those six eggs? Like there’s a combination of genes in this egg, egg #1, that have to do with developing a nervous system, and we’re not sure exactly how that works, but they could make your nervous system go together better, develop better, function better. Maybe give you a smarter person.
Would you, knowing that egg #1 had that better combination of genes that just might give your kid an advantage but not cause harm, would you just ignore that information and just say, “No, I’ll just take a random selection, just close my eyes, and I’ll select one,”? No, of course, you’d have to as a parent choose … So to think that anyone’s not going to use genetic technology when it becomes available, there may be laws initially and people will have these moral problems about it, but the only real moral problem about having a better child is when does the technology become so expensive that it becomes one more way of disadvantaging people?

BS: Others have raised moral problems besides this one, for sure, but I can see why this one really stands out for Dave. People who don’t have a lot of money already have a hard enough time catching up with wealthier people. If CRISPRing your kid becomes an option that only the wealthy can afford, that will give them a whole new competitive edge over poor people.

AA: And there’s even more to this issue of disadvantaging people than just wealth. The big question for me is, who should get to decide which traits are desirable and which are not? Like we talked about in the full episode, science can’t exactly tell us which traits are good or bad, because these are subjective and very personal judgments. I spoke about the dangers of labeling certain traits as desirable and others as undesirable with Miriam Rich, the CSHL Archives Sydney Brenner Research Scholar who spent a lot of time in our eugenics archive for her doctoral research.

MR: I think any conversation that is predicated or trading in this idea of identifying some traits as desirable and others as not should really be extra aware of this history, and sort of have a heightened awareness of the potential for those designations to entrench existing prejudice.

AA: Right, I think about a lot the example of deaf people. And, you know, a lot of people who are not so familiar with the deaf community might say, if we can fix deafness with CRISPR, for some people at least, people who have, you know, genetic conditions that lead to deafness, then that’s great! We should do that. But a lot of people in the deaf community would not argue that their deafness is an impairment at all, and in fact would say that it’s something that enhanced their lives.

MR: Yeah, I think that’s a really powerful example, and certainly there have been critiques from a variety of disability communities about just that issue of certain types of disabilities being labeled as “impairments” or something in need of correcting by certain discourse, and not recognizing them as in fact sort of human variants that can be accommodated and in fact enrich a society that is dedicated to inclusion and diversity as opposed to correcting what it sees as undesirable traits.

AA: Would you say that ultimately it has to be a personal decision when it comes to deciding how to use a new technology that affects reproduction, or is it more complicated than that?

MR: I think it’s probably more complicated, just because even if, sort of, the use of reproductive technologies are personal choices, sort of, the conversation around them and the assumptions people make can contribute to a climate in society or to a prevailing vision or perspective in society that affects how people living with, for instance, disabilities are treated. Even if, sort of, the widespread use of reproductive technologies is something that’s framed as individual choice, it’s still affecting a society that everyone lives in.

So I think that certainly personal choice is an important aspect of this conversation. I think everyone would be uncomfortable with the idea of this being an imposed or mandatory technology to use but I think it doesn’t by itself solve or address all the potential problems or critiques that people might have.

Even if it’s an individual choice, just recognizing that we all live in—again, live in a society that is shaped by social prejudices and inequalities—individual choice can be shaped by that. If we live in a future or in a present in some cases where certain traits can be selected against because they’re seen as undesirable in the context of a social discriminatory society, are we using this technology to further entrench that social prejudice in those cases? I think those are very hard questions to answer, and part of the reason that there needs to be such robust and reflective conversation around these kinds of issues.

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Episode 12: Good genes, bad science

In the early 1900s, American science took a wrong turn toward eugenics. In this episode, we talk with experts in both science and history about what we can learn from this dark period in today’s age of unprecedented control over the genome.

BS: Hey there! Brian Stallard here.

AA: With me, Andrea Alfano.

BS: What are we talking about today, Andrea?

AA: Good genes. And why science can’t tell us what they are.

BS: Science has helped us learn a lot about genes, though.

AA: That is something science can do. With tools like CRISPR (spell out) gene editing, scientists are able to gather this knowledge even more quickly.

BS: We talked about gene editing in plants a few episodes back, in “CRISPR vs. Climate Change.” CRISPR is a new tool that allows scientists to make precise changes to DNA. A plant scientist here used it to find genes in tomatoes that can be mutated to give them the ability to grow in new regions, which would come in handy if climate change causes their geographical range to shift.

AA: Just a little over a month after we released that episode, in August, the New York Times published a story with the headline, “In Breakthrough, Scientists Edit a Dangerous Mutation from Genes in Human Embryo.”

BS: I remember that story. Scientists claimed that they were able to use CRISPR to edit out a mutation from the human genome that causes a heart condition that can trigger sudden death later in life. Most people would probably not consider that to be a good gene.

AA: But importantly, like you said, the judgement of good versus bad comes from people—in other words, society—but not the science itself.

BS: Of course! How could it not? Science is a process—the scientific method of hypothesize, experiment, analyze, and repeat. When done properly, it gives us reproducible results and valuable knowledge that can help us make more informed decisions. But people still have to make decisions about how to use the knowledge that scientific experiments generate.

AA: That New York Times article about human gene editing has one line that really jumped out at me, because it gets at the big question of how to use scientific knowledge. It reads: “Some experts have warned that unregulated genetic engineering may lead to a new form of eugenics, in which people with means to pay have children with enhanced traits even as those with disabilities are devalued.”

BS: Eugenics was an idea in which issues of science and society got mixed up in horrific ways. I can see why the author mentioned that history as a warning.

AA: Until relatively recently, I honestly had no idea that there was a eugenics movement in the United States early in the 1900s, much less that as a result of this movement, the government forced thousands of people to undergo surgery that destroyed their ability to have children. I was hardly even familiar with the word eugenics, and I had only heard it used in the context of Nazi Germany when I did come across it.

DM: It was just taboo, nobody mentioned it.

AA: That’s David Micklos, executive director of CSHL’s DNA Learning Center, whose science education programs are aimed at preparing students in grades 5 through 12 for life in the genome age. It’s largely thanks to Dave that I now do know that there was a very prominent eugenics movement in the U.S. His effort to inform as many people as possible about this dark but important history started in 1995, earlier in his career at Cold Spring Harbor Laboratory.

DM: Well, I was poking around the archives a long time ago, and I pulled up a couple of tracks and brochures from the eugenics time — I was writing a little history of the Lab for the 100th anniversary, and so I put one paragraph on eugenics in it, and I think I said it was misguided at the very least, but it was pretty pabulum. But, that was the first word in a published synopsis of the Lab that eugenics had been mentioned since the Second World War.

BS: Those archives are here because the institution now known as CSHL was once a division of the Carnegie Institution of Washington. It was also home to the Eugenics Record Office. Dave Micklos was the leader of an effort to make those archives available online in the 1990s, which was still the early days of the web. You can check them out yourself at CSHL has always considered this part of its history a really important “teachable moment” for people in the present day.

AA: The Eugenics Records Office was part of the Department of Genetics here during the early 1900s.

BS: The word eugenics is derived from the Greek “eu,” meaning “good,” and “genos,” which gave rise to the English word “gene,” right?

AA: Yes. But eugenics as it was employed in the early 1900s most closely translated to “good breeding”—which hints at how this “misguided at the very least” movement got its start through science. That’s a big part of what I wanted to find out from Dave: how did something that started out as a legitimate pursuit of scientific knowledge about genetics turn into a scientifically bankrupt, yet popular social movement?

DM: If you look at the people who were in the early American eugenics movement, a large number of them had come from backgrounds in plant and animal breeding. They thought they had some pretty good ideas about how things worked when you bred two parents and got an offspring, say corn plants, or pigs, or cattle, or horses. They thought they knew some of the principles behind how those genetic components from the parents came out in an offspring. So, if we had these ideas about how we could make a better pig or a faster racehorse or a bigger corn plant, why not use those principles in making human beings better?

BS: I could see the appeal of that idea. Studies in those other organisms did reveal evidence that inbreeding increases the risk of many genetic diseases, for example. In those days, it still wasn’t terribly uncommon to marry your cousin.

AA: That was actually one of the (quote) “chief activities” (unquote) of the Eugenics Record Office, according to a 1918 report from its director, Dr. Charles Davenport: “to advise concerning the eugenical fitness of proposed marriages,” particularly, “contemplated cousin matings.”

BS: People in Iceland are doing a high-tech version of that right now through a dating app called Bump that uses genealogical data to warn potential couples about incest. Since the population is so small in Iceland and last names aren’t that revealing of family history there, the chance of accidentally dating your cousin is actually pretty significant.

AA: Yeah, that’s one of Davenport’s ideas that’s still makes sense to a lot people today. In fact, despite having been a leader of the American eugenics movement, Davenport was a trained geneticist and, before coming to CSHL, a professor at Harvard.

DM: He also had some insight, more than a lot of people, that when genes went wrong, they could lead to certain kinds of diseases. For example, Davenport — worked out the classic formula that basically brown eyes are dominant over blue eyes, that genetic bit that everyone learns in high school.

BS: Wait, he was the one who figured out that brown eyes are dominant over blue eyes?!

AA: He was! So, he did start out doing legitimate, solid science, like that eye color paper from 1907. But let’s check in again ten years later, in 1917. Davenport listed a few of the (quote) “principal advances” (unquote) of the Department of Experimental Evolution at Cold Spring Harbor, which he also directed and which spawned the Eugenics Record Office. Let me know when you hear something suspicious:

The analysis of a new method of selecting the best egg-laying poultry.
The production of a “pure” highly abnormal race of beans.
The analysis of the juvenile traits and hereditary characteristics of successful naval men.
BS: Naval men? As in, men who are in the navy?

AA: That’s right.

DM: Davenport even published a study of sailors and of great naval captains and so forth, and thought that they had inherited a couple of genes basically in a linked fashion. And one of them, was called thalassophilia, love of the sea. Another one of them was fearlessness. Well, do you get the love of the sea cause it’s in a gene you inherit or is it because your father liked boats and your grandfather liked boats and you had one in the background and you lived next to the sea? But the eugenicists said, “Well, looks like it’s genetic.”

BS: Looking back, it’s easy to recognize that that’s just not science. There’s no scientific reason to think that family members’ shared love of the sea must have a genetic basis. Mistaking correlation for causation is such a basic error.

AA: Exactly. That’s a relatively harmless example of the non-science of eugenics. Unfortunately, not all of them are so humorous.

DM: A perfect example is the eugenicists and a lot of intelligent people around the world and in the US were really worried about one disease in the early 1900s, and it was called feeble-mindedness. Well, you haven’t ever heard of that disease because it doesn’t exist as a disease.

BS: What did they think feeble-mindedness was?

AA: Here’s how a doctor defined feeble-mindedness in 1912 in the prestigious New England Journal of Medicine: it is “the synonym of human inefficiency and one of the great sources of human wretchedness and degradation.”

BS: That definition isn’t scientific, it’s just mean!

AA: It is mean. And when that kind of unscientific approach gets applied to social issues, it becomes even more problematic. Davenport wrote in 1911 that, “anyone acquainted with rural poorhouses, particularly in the South, will appreciate that the people housed in them are mostly mentally inferior.” He also became involved in issues of immigration to the U.S., and specifically, curtailing immigrants’ introduction of what he described as “defective alien germplasm.”

BS: And feeble-mindedness was one of those “defects”?

AA: To eugenicists, yeah. By attributing supposedly scientific causes, like feeble-mindedness, to social phenomena, like poverty, people like Davenport lent scientific legitimacy to eugenic ideas—even though there wasn’t any. And already-marginalized people, like immigrants and the poor, were harmed as a result.

BS: I think I see where this is going. If Davenport thought that love of the sea was genetic, he surely thought that feeble-mindedness was, too.

AA: He did. And he wasn’t the only one. Many people were convinced that this unscientifically-defined trait of feeble-mindedness had a genetic basis, and they took action to prevent these “defective” or “inadequate” genes, as they were called, from spreading through the population.

DM: So, you could segregate them, and hope that they didn’t get out and reproduce, or you could just sterilize them, which was a surer solution to what they thought was a eugenic problem. It was on the strength of this sort of fear of feeble-mindedness that the law that allowed eugenic sterilization passed the United States Supreme Court.

BS: I know about this. Dave’s talking about the infamous Buck vs. Bell case. Eugenicists decided that a young woman named Carrie Buck from Virginia was so feeble-minded that she should be sterilized—meaning that her ability to have children would be surgically destroyed—and in 1927, the U.S. Supreme Court agreed, 8 to 1.

AA: One of the things I found really striking about the American eugenics movement is that it was very mainstream. That Supreme Court decision really shows that eugenics was not some fringe movement.

BS: I remember from a post you wrote for our LabDish blog that in the early 1900s, a family might for example go to the state fair and enter a “fitter families” competition in which they were basically judged on how good their breeding appeared to be. There are photos of grinning parents, children, and grandparents being judged like livestock at these competitions and it’s… unsettling to say they least – but if you’re interested in checking them out, and I hope you are, you can find them at

AA: It really shows how widespread eugenic ideas were at this time, even among the general public. I was also amazed to see that on the Google Books Ngram viewer, which shows the prevalence of words in books over time, the word “eugenics” is actually far more prevalent than the word “genetics” from 1900 until around 1930.

BS: That make some sense, actually. These were the earliest days of genetics! Mendel’s famous laws, which gave rise to the field, only came to light around the turn of the 20th century. So, then what happened after 1930?

AA: There’s a decline in the usage of “eugenics,” as it became thoroughly discredited within the scientific community, while “genetics” steadily became more prevalent.

BS: And eugenics just disappeared? Usage of the word could still go up, even after most people have rejected what it stands for. It’s part of learning from history, just like what we’re doing now.

AA: Well, just before 1990, the use of the word “eugenics” really picks up again, for the kinds of reasons you’re getting at. Quiz time, Brian: As a CSHL employee (hint, hint) does that timing, around 1990, seem curious to you?

BS: Hmmm, the Human Genome Project started in 1990. That was the initiative to write out every DNA “letter” in the human genome, so it seems like it could be a good time to revisit the history of eugenics.

AA: Correct! CSHL’s director at the time, James Watson, was also a leader of the project. Here’s Dave Micklos again.

DM: When Watson became a first director of the Human Genome Project, he got it written into the operations of the genome project that 3% of the research budget should go to the consideration of ethical, legal, and social implications of genome research. Well, that had never been done before.

BS: I can’t believe that wasn’t already standard practice!

AA: Neither could I, but I’m glad they helped get that ball rolling. Dave got a grant from the National Institutes of Health, or NIH, to put materials from the Eugenics Record Office and other eugenics archives on a website.

DM: People said, “Yeah, there’s obviously lessons to be learned from our first involvement with human genetics and our current involvement with genomics.”

BS: So, Watson’s point was, how would we protect citizens’ genetic information—information that could be used to discriminate against them—in a future where the human genome could be “read”?

AA: Yes, and that’s the work that we still need to do today. How do we let people know what they’re in for as scientists gain the ability not only to “read” the human genome, but to edit it?

MR: It’s not, sort of, the kind of issue where there’s going to be a conversation that reaches closure and we’ve addressed all the ethical issues and there’s nothing more to talk about. There really needs to be a commitment to ongoing discussion around those issues.

AA: That’s Miriam Rich, a doctoral student at Harvard who’s studying the history of science, particularly the social and cultural history of medicine in the U.S. as it relates to gender and race.

BS: I learned about Miriam’s work because she’s researching the history of eugenics with support from the Sydney Brenner Research Scholarship from CSHL’s Library & Archives.

AA: I wanted to know what goes through her mind as she reads the latest CRISPR gene editing news.

MR: I think conversations around the value and uses of gene editing technology should really be careful to avoid this trap of expecting that a new genetic technology, as promising as it may be for, you know, for many applications, but not expect that it can serve as a catchall cure or replacement for addressing social, political, and environmental problems. I think that was really an issue with eugenics—that rigid commitment to not being able to imagine that there were problems that were better addressed through social and political and environmental change, as well as through thinking about genetics and heredity.

BS: That’s a great point. As much as we believe in the power of genetic information—it is what this podcast is about, after all—it’s not all-powerful.

AA: Davenport definitely fell into that trap. In 1913, in an article in the magazine Popular Science, he wrote: “The recognition of the part that heredity plays in determining human behavior … leads us to recognize the true worth and the real limitations of education, religion and other good influences, and leads us to conclude that the greatest advance that humanity can make is to secure an increasing proportion of fit marriages producing the largest number of effective, socially good offspring to carry on the world’s work.”

BS: So, how do we avoid this trap?

AA: Well, when Jennifer Doudna, a professor at UC Berkeley and co-discoverer of the CRISPR gene editing technology, was recently here at CSHL for a scientific meeting, she talked about how she looks to history for guidance. In contrast to the cautionary example of eugenics, she described an inspirational one.

JD: I think a great example of this is actually looking back to the 1970s when molecular—what we call molecular cloning—was getting started. And that just means being able to make copies of desired genes, typically by putting them into the DNA of bacteria. And the bacteria that scientists were using for those experiments were bacteria that can grow in the human gut. And so, people realized, gee, this could be a problem! (laughter) Potentially. So, that led to conversations that were convened in Asilomar, California by scientists who wanted to get a conversation going about the responsible use of molecular cloning. And that became known as the Asilomar Meeting and led to some initial restrictions on molecular cloning until it could be shown to be safe.

BS: This was really cool. About 15% of the participants at Asilomar were from the media, which helped keep the public well informed about the deliberations, including all of the initial indecisiveness and arguing as well as the consensus that eventually came out of them.

JD: We’re trying to take that same approach now with CRISPR technology, and really try to get people interested in learning about this, people who are not scientists. It’s one of the reasons it’s great you’re doing this podcast. But to have people understand the beauty and power of this technology and the kinds of things it’s enabling, but also to appreciate that it has real potential to be misused as well. And so, we need to be very actively discussing appropriate ways to proceed. So, we had a great talk the first night of this meeting (BS: the recent CSHL gene editing meeting, that is) by Richard Hynes from MIT, who has been—was the co-chair of a committee that reviewed the application of CRISPR technology in a particular setting, in what’s called the human germline. That means being able to make changes to DNA in human embryos or human eggs or sperm that we would heritable. So, they’d become transmitted to future generations. Very—something that cuts right to the core with eugenics, right?

BS: That’s for sure. Eugenics and genome editing of the germline are both issues of controlling reproduction. I know that Dr. Doudna herself has called for a worldwide moratorium on using CRISPR to make these heritable changes to the human genome, and many other scientists have joined her.

AA: Right now, in the United States, the use of federal funds for research for creating heritable modifications in human embryos is prohibited.

BS: But some of the research in that study we talked about at the beginning of this episode—the one where scientists edited out a mutation for a potentially deadly heart condition from a human embryo—some of that work was done in the US. Somehow, they got around the federal funding barrier.

AA: There are clearly mixed feelings about this kind of work even within the US, let alone around the world. Earlier this year, the National Academy of Sciences and the National Academy of Medicine got together to discuss the science, ethics, and regulation of human genome editing. Perhaps the most important line in their report is this: “Given both the technical and societal concerns, the committee concludes there is a need for caution in any move toward germline editing, but that caution does not mean prohibition.” Even though Dr. Doudna has called for at least temporary prohibition, she seems to agree with the Academies about the appeal of human germline editing.

JD: It has the power to possibly relieve families of mutations that might lead to cancer and to other very disabling diseases. And so, this is something that everyone now is grappling with. How do we proceed? There are no easy answers, but I think one thing that’s happening which is good is that there are a lot of people engaging in that discussion.

AA: Again, science alone can’t give us the answers here. It can’t tell us how we should and should not use technologies like CRISPR in our lives. But Miriam Rich did offer some insights into what needs to be considered and who needs to be included in those discussions.

MR: Whenever you’re dealing with a science of human reproduction or a question that’s about managing human reproduction, you know obviously, the science itself is pivotal but it’s never going to just be about science. — It’s really important to have input and voices of many different people and communities, particularly those who may be most vulnerable to potential harm and certainly the historical example of eugenics demonstrates how communities most vulnerable to harm are, again, those who are already marginalized in society.

AA: The report from the National Academies echoes this sentiment, urging that “public education and engagement are crucial in the process of assessing and applying societal values to the risks and benefits of genome editing technologies.”

BS: Absolutely. That’s why we put this episode together. Where do you draw the line between ethical and unethical uses of human genome editing? Deadly diseases? Disabling diseases? What about enhancing human traits? Hopefully you listeners out there will help, too, by talking to the people in your daily life about these issues. It may seem small, but these little conversations can add up to make a big difference.

AA: I hope so too. Science shows what is possible to do. It’s up to all of us, scientists and non-scientists of all backgrounds, to use that knowledge to figure out what is right to do in our very nuanced society.

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Episode 11.5: What Silicon Valley and biology research share

A few favorite moments from our talk with theoretical physicist and quantitative biologist, Associate Professor Gurinder “Mickey” Atwal, that touch on topics ranging from his stint in medical school to the job market in the age of big data to Schrödinger’s cat.

BS: Okay okay. Hi guys, I’m Brian.

AA: And I’m Andrea.

BS: And this is one of those Base Pairs chat episodes that you are beginning to hear about. This is our third one, right?

AA: Yes, our third one, following up with Mickey Atwal, who we heard about in our biology behind the screens episode in August.

BS: I had a lot of fun with that one. In that very punny episode…

AA: Moving on.

BS: In that episode, we talked a lot about little known or little appreciated side of biology, which is quantitative biology. It’s super crazy important to biology, and it’s been that way for a long time. It played a big part in molecular biology, and these days it’s playing a big part because we have too much data and we need people to help us sift through the noise, see what’s important so we can keep experiments going.

AA: Yeah, too much data for humans to go through, manually at least.

BS: Yeah absolutely. What’s cool about all of that is that the folks who do that kind of work, they don’t do biology in the sense we’re used to. They’re not behind a microscope. I talked to Mickey a little bit about that.

When was the last time you actually needed to look through a microscope?

MA: Oh, it’s been a long time. Probably I would say a good 20 years ago.

BS: Was that when you were still a student?

MA: Yeah I was actually, yeah for all my students, and not many people may know this, I was actually a medical student back in the day, straight out of high school. In England, there is no pre-med, you go straight from being a spotty 17 year old or 18 year old and go straight to medical school and chopping up dead bodies. I just really hated it, medical science, as it was just a lot of memorizing and lugging around huge textbooks, breaking my back. I didn’t have good memory, I was more of a math geek, more of a numbers guy.

BS: You were a problem solving guy.

MA: Yeah, I loved challenges, problems and math and physics. Things I would read on the spare, so two years of medical school and I was out.

AA: I had no idea that anybody went into medical school right out of high school. That seems, in high school pretty much you’re at the level of dissecting frogs, then to go from that straight into …

BS: Cadavers.

AA: Cadavers, that’s quite a leap.

BS: I got to talk to him a little more about that, and it’s actually a very interesting past. As you could tell, he grew up in England, his parents were actually immigrants from India, one was a farmer and the other was a factory worker. But the interesting thing about Mickey’s past was that from day one, everybody called him Mickey, just as we’re doing now.

AA: Right. He also as I know from going on the website…

BS: His faculty page.

AA: His faculty page, yes I know that his given name was Gurinder, am I saying that right?

BS: Yeah Gurinder, I think that’s … the thing is, Mickey’s not even sure if you’re saying it right and we’ll explain.

So they call you Mickey, but your other name is Gurinder?

MA: So the name on my passports and my birth certificates is Gurinder. Yes, I think that is the correct pronunciation. I’m not entirely sure if that’s correct.

BS: You’re not entirely sure? So how long have you been going by Mickey?

MA: Since day one. It’s a nickname that my mom gave me and it stuck.

BS: Was she a Disney fan or did she just like the name Mickey?

MA: Good question, you’d think I would know the answer to that one. No, I think she had heard of the name being used as a nickname by somebody else and she liked it. I don’t think she was very familiar with Disney and the movies back then.

BS: So you know, not the biggest Disney fans, or not yet anyways.

AA: There’s still time, it’s never too late. Disney isn’t paying us by the way.

BS: Another really interesting subject Mickey and I got to talk about a little bit was the idea that here we are, we’re talking about quantitative biology, we’re talking about this really specific skill set.

AA: And desirable skill set.

BS: Very desirable skill set, and Andrea why is that skill set desirable?

AA: I think if you went over to Silicon Valley, it would be pretty apparent that …

BS: Wall street too.

AA: Yeah, Wall Street. That’s true, even closer to home for us. I wonder what our world could be like if some of those people were using their skills to change biology instead of to revolutionize the way we communicate through social media and things like that.

MA: These are the same skill sets that are used by people on the West Coast and Silicon Valley, and here close to us on Wall Street. I would have students or post doctoral candidates interviewing for me and would have competing job offers at places like Facebook. They would do very similar research, except trying to predict how does a tumor evolve, they may be trying to predict how does the stock price change, sometime in the future. It’s surprisingly very similar, the kind of mathematics. I don’t think there is enough awareness of machine learning and big data technology as compared to the advertising industry and the financial sectors.

BS: So people with these skill sets just immediately assume they’re going to be going off to Silicon Valley or Wall Street.

MA: Yeah, I can understand it’s quite lucrative and there’s a steady pathway from traditional undergraduate majors and electrical engineering and data sites to these jobs. Perhaps the transition into biological science isn’t so well paved out. It would be great if more people were aware of how machine learning is really making great inroads to solving really fundamental problems to molecular biology.

AA: We talked about in the full episode that even though it’s kind of the minority of people with this skill set who apply it to biology, there is a pretty long history of this happening famously as we mentioned. The double helix paper from Austin and Crick was really a quantitative biology theory paper at its core. There was no experiment that led them to discover the double helix.

BS: Right, right, it was basically just equations and putting together a model and saying does this work, does this work, et cetera. Interestingly enough, in that paper, they credit somebody named Irwin Schröedinger. I’m sure you all know him pretty darn well.

AA: Especially if we mention the word cat, that might help.

MA: Erwin Schröedinger? Him of the famous unfortunate cat experiment. Don’t know why he had to choose cats.

BS: He doesn’t really like cats.

MA: I guess so. After his multiple contributions in quantum physics and relativity theory, he was interested in problems in biology. Back then big problems in the 40’s were, how did you inherit information, and how do cells do it? He wrote a famous book for the public, I think it’s called “What is Life”. He made some amazing predictions back then. One of his predictions was, all the information you’d need to convey life in a cell is carried in a molecule. I think he called it, what is it, an a-periodic crystal. Basically it’s a long molecule which doesn’t repeat itself, it has lots of different elements. That’s what we now know as DNA.

BS: Yes, yes.

MA: So interesting enough, Frances Crick and James Watson both credit Irwin Schröedinger and his book for inspiring them to work on understanding the double helix structure of DNA.

BS: So I’ve got an amazing prediction of my own, which is that everybody is going to really enjoy our next podcast episode.

AA: Look at you with the transitions.

BS: Andrea wound up doing a lot of really good reporting for it, and what’s it about Andrea?

AA: It is about very important but I would say little known period in American history. Some of you might be familiar with the word eugenics, you probably associated it with Germany. But that is a period in American history as well and I think it’s a good time for us to talk about that history because of the advances that are being made in our ability to hold the human genome which is really what eugenics is all about.


AA: CRISPR, exactly.

BS: Alright, so stay tuned for that because it’s going to be a good one.

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Episode 11: Biology, behind the screens

A “behind the screens” look at how biology is addressing its “most wonderful problem”—too much data. Associate Professor Gurinder S. “Mickey” Atwal joins us to explain the essential enigma that is quantitative biology.

(Chatter sounds trickle in, growing steadily louder)

BS: Hey guys… I’m Brian

AA: And I’m Andrea…

BS: And we’re needing to almost shout here because well… this noise. This raucous crowd you’re hearing behind us… that’s hundreds of high schoolers.

AA: 312 high school students to be exact.

BS: And despite this happening at the cusp of summer, this isn’t a clip from day camp. What you’re hearing is a scientific poster session where these high schoolers – many of them freshmen – got to present their own experimental findings. These are ambitious kids, so I expected to be impressed. But what really blew me away wasn’t the amount of work they did—it was how little it resembled the kind of biology I learned in high school.

BS: So what do we have going on here? What am I looking at?

GP: For me… scientifically… I had to learn how to code in Python for that which was REALLY INTERESTING to say the least. But also how to analyze the data we obtained. Which wasn’t just simple graphs. We had thousands and thousands of sequences that we had to go through!

BS: That was Giovanna Prucia, a 17-year-old Junior from Connetquot High School, and the project she and Chris Paciello showed me was SUPER different from what you’d see at your average grade-school science fair.

AA: Yea! I’ve heard of Python before… and that’s a programming code, isn’t it? That’s not exactly something you normally learn in highschool, right?

BS: I definitely didn’t. And Victoria DeAmbrosia, a science teacher from William Floyd High School, was also pretty shocked about what she’s got kids learning these days.

VD: And a lot of the students go to the next level. Those who did barcoding last year, they got to do microbiomes this year, in which they’re doing these really complex statistical analyses – both types of projects get to use bioinformatics tools…

AA: This is crazy! Brian, not too long ago, I too was an aspiring biologist… and computer coding… statistical analyses?! These were NOT the kinds of things I focused on.

BS: Well… biology is changing! It’s looking that more and more scientists are going to spend as much time behind a computer as at a lab bench. And that’s for a REALLY good reason…

FC: “We’re all STRUGGLING with the wonderful problem of having too much data. Big Data, as it’s featured on the cover of Nature magazine. Big Data as we talk about around the table at institute director meetings on Thursday mornings. Big Data as I am even now being asked by people in the White House ‘what are you going to do about this?’ as now everybody recognizes that we are in a circumstance about needing to be very thoughtful and creative about how we handle the very large quantities of biological data that are pouring out of many different approaches… toward understanding how life works and how disease occurs.”

BS: That’s Francis Collins –the man who has been directing the National Institutes of Health for nearly a decade. The clip I just played was from 2012, when he was serving under President Obama, but Collins’ goals and concerns have hardly changed since.

AA: I can understand why. Collins was also the head of the Human Genome Project – that massive scientific undertaking that, once accomplished, left the world with a WHOLE lot of data and very little idea of what it all meant. I mean, we just wrapped up a two-part series that was all about how we’re still sifting through the sequenced human genome, slowly but surely making sense of it all. One could even hazard the guess that Collins feels responsible for all the new work that needs to be done!

BS: Sure! But the other big issue is that for centuries, traditional biologists have been able to get by on their own – mostly. In this way, the cycle of observe-hypothesize-experiment-observe has been a closed system. And that’s not just for biology, but for lots of sciences! Here’s Kafui Dzirasa of the NIH’s BRAIN Initiative really bringing that point home while chatting with Collins at a meeting called “Faster Cures” held last year.

K: “Big data has gotten bigger right? So 500 years ago big data was staring out at the galaxy and mapping out the planets and how they were orbiting around the Sun. So then there was a role of an individual investigator sitting and observing and framing things. The problems today are SO complex that one person CAN’T handle all of that at all!”

AA: Ok. I can see that. For last year’s season finale of Base Pairs, we talked about how the problem of mapping the brain is so complex that it can’t be done by hand –

BS: Or by eye, er– microscopy, so to speak

AA: Right, so instead Neuroscientist Tony Zador is recruiting RNA sequencing to map the brain computationally, and THEN neuroscientists can pick specific neurons and circuits to investigate more traditionally.

BS: It’s an elegant solution. But what they have yet to really work out is how to identify which neurons are significant for any one problem. Likewise in genomics, biologists have countless genes to choose from when investigating biological function or disease

AA: – Thanks to the Human Genome project –

BS: but they struggle to select key targets for study… And why is this? CSHL Associate Professor Mickey Atwal suggest that it may just have to do with the fact that people are really bad at making predictions.

MA: In a way I feel like we’re almost hard-wired to get things wrong. There’s one example I can remember. Where, I went to a roulette table. And the most common thing to do at a roulette table is to bet either red or black and it’s roughly 50% (except for the one or 2 green ones)…

And these roulette table managers are smart. So what they figured out is if you show the customers what other players have bet in the past, that’s gonna offset how people think about random. Meaning, that if a person sees that there were 6 reds played in the past, there is a compulsion, within them, to bet that the next one is gonna be black!

And you know, there is almost a primitive part of me that felt that urge! “of course it’s gonna be black, there have been 6 reds in a row!” but if you’re grounded in understanding probability theory you understand that it makes no difference. Each one is an individual instance! And yet, I saw this time and time again. So, we’re really bad at understanding whether something is a statistical fluke or a real signal.

BS: What’s wild is that even in this roulette example, the data we’re dealing with is very small. Just 36 numbers, 3 colors, and some results. And YET, even Mickey – who is a trained physicist and quantitative biologist – even he feels the urge to bet irrationally – to feel that those results actually influence the next outcome – even when he KNOWS that in reality, they are what academics call statistical noise. It’s no wonder we can’t make heads-or-tails of Big Data!

AA: But Brian. Isn’t that what quantitative biologists DO? Help biologists filter out that noise from big data sets?

BS: In part. Yeah.

(interview clip) BS: So what IS quantitative biology?

MA: Yeah…. Really good question (laughter) so I think there are as many answers to that question as there are quantitative biologists. It’s not really answered to anyone’s satisfaction. And I think there’s a really good reason for that!

In most areas of science—chemistry, geography) you are defined by your object of study. And this is especially true in biology. So neuroscience is defined by the neural system. And plant biology is studying plants, right? Quantitative biology isn’t. The role of a quantitative biologist is to ask certain kind of questions and to ask for certain kinds of solutions… so what that means is that our domain of study can cut across many fields of biology.

And the kind of questions we ask… are different form the usual question a biologist would ask. Can we simplify what we see into something abstract so that we can make a predictive model of that? Can we make a model of the phenomenon we observe? And can we test those predictions? And to do this you really have to formulate the problem differently than how a traditional biologist would.

(interview clip) BS: would this fall in the lines of say, Punnet squares?

BS: You might remember these little charts from high school biology called Punnet Squares, and even today, students use them to predict the outcome of a basic genetic cross.

MA: So that’s a really good example! I think that’s arguably the first time most biologists experience an equation… And that’s a really simple example because it gives you a prediction of what is the expected observation given a set of hypotheses.

BS: You see, Andrea. Quantitative biologists are often the reinforcements that traditional biologists need in this age of big data. They’re essentially that outside help that Dr. Dzirasa was talking about in his discussion with Director Collins.

AA: So, they provide a new perspective, allowing predictions and observations to be made on a concrete statistical level. That way biologists can then formulate new hypotheses and experiments based on what is learned.

BS: Right! Right now, Mickey is working in collaboration with a number of specialists in trying to better understand breast cancer, and his lab here at CSHL is bringing that essential QB perspective to the table.

MA: Now, immuno-therapy is a buzzword and you may have read about this in popular press, and there’s been some really exciting developments in the treatment of lung cancer and skin cancer, melanoma, but it hasn’t fared so well in breast cancer. So one of the things that keeps me up at nighttime is trying to understand why not? Why aren’t the immune cells, which we know are found in breast cancers, why aren’t they doing their job and killing the cancer cells? What is it about the cancer cells that somehow tricks the immune cells into not attacking them?

So, the research team that we’ve built and grouped together is really focused on understanding the communication between the different kinds of cells that you find in a growing tumor. So we have actual biopsies from patients in a clinic based in Los Angeles, actually shipped here to Cold Spring Harbor. And with our DNA sequencing facilities, we are able to measure the activity of thousands of genes in individual cells.

AA: Oh my. THAT’S a lot of data. And how each cell expresses those genes can differ wildly. One could even think of the environment around a tumor as a neighborhood. You’ve got your behaving cells expressing their genes in one way – they’re good citizens. And then there’s cancer cells acting badly. But there’s also lots of other cell “personalities,” if you will, who also might act strangely.

BS: That chatter alone creates a lot of statistical noise

AA: Right, and when everyone is talking with everyone…

MA: it’s a bit like a needle-in-a-haystack problem. So we have to develop algorithms that can sift through mountains of data and try to find out which genes are really important, and more importantly for this project, which genes are really important for the cells to bypass the immune system and actually allow the cancer cells to grow without the immune system killing them off.

BS: Essentially, breast cancer cells are really good at conning their neighborhood. Those “good-citizen” cells Andrea mentioned can’t tell that their nasty neighbors are ruining the neighborhood and are happy to communicate with them. And because the cancer cells are acting so darn “neighborly,” the immune system – or the local police in this metaphor – don’t realize that they’re criminals.

AA: But if Mickey and his collaborators are successful, the hope is that they can identify ways to quiet those problematic cell-to-cell conversations, putting a stop to cancer’s neighborly act.

BS: Mickey’s project is one of MANY so-called “Big Science” collabs – this is one funded by the group “Stand Up to Cancer” – and it shows the power of various scientific disciplines all aiming their efforts at one objective. However, Mickey argues that for these projects to truly move science forward in this age of Big Data, everyone needs to become a little more familiar with QB.

MA: You certainly don’t want to be in a position where you’re shuttling off your data to somebody else and you’re treating them like a black box. They somehow perform their magic. And they say “these are probably the targets for your disease.” Right? You want to have some sort of conversation. You want to be more intelligent than that.

Even if you’re not going to do the experiments themselves, I still think it’s really important for the experimentalists and the classical biologist to at least be able to understand what are the state-of-the-art techniques that are required to sift through mountains of statistical data.

I really do think that it’s going to be the next generation of biologists – undergraduates, graduates, and postdocs – all need to be trained in computational and quantitative skills.

AA: Hmm, well… there is good news. Here at Cold Spring Harbor Laboratory, the students of our Watson School of Biological Sciences

BS: – that’s our Ph.D. Program –

AA: every student admitted to the program is required to take what can be best described as a computational “boot camp” where they learn PYTHON – that premiere programming language for MANY important scientific databases.

BS: And amazingly, it’s mostly being taught to students who have only ever known text books and a lab bench.

MA: We say “hey! This a computer. This is what a computer does. This is what it doesn’t do! This is how we can write code to perform basic commands. And by the second day they’re actually analyzing next generation sequencing data by themselves!

AA: Mickey teaches this boot camp and as you might expect, he (and his subject) are not exactly popular with new students.

BS: Can you blame them? They came here to do science… and instead Mickey’s got them sitting behind a computer! Doing code!

AA: And yet… we know that this is exactly how lots of science gets done.

MA: I’m sure there’s a whole bunch of them who hate me here when they first arrive… (laughter)

MA: And what’s interesting is that, because it’s such a new skillset, such a new concept, and it’s so immersive on the first day that by the end of the first day they usually end up… dreaming… well, thinking about Python obsessively. And you can get to this state where you can just spend hours in front of a computer coding away! It can become quite addictive.

BS: According to Mickey, it’s rare to have a true convert – a student who actually leaves their well-paved bio-science path to wade into the unknown of quantitative biology. However, he did explain that by the end, the idea that you can frame a theoretical scientific question mathematically becomes pretty popular among the students.

AA: So popular in fact, that for three years now, Mickey has been elected to receive the Winnship Herr Teaching Award by the Watson School’s freshman class.

BS: It’s basically a teacher popularity contest, and each year, Mickey acts like he has no idea why he’s won it.

(graduation ceremony clip) MA: I don’t know how and who decides these awards uhh… but whoever you are… Russian hackers included… your check is in the mail (laughter).

AA: (laughing) I spoke with Mickey about this for a story on our LabDish blog, but it’s easy to see why his course is actually popular. While other instructors are simply reinforcing old skillsets and scientific methods, Mickey is teaching these students something fresh! It’s practically a new way to think for many of these young scientists.

BS: And that’s what I actually found most surprising during my chat with Mickey. While this strategy – this way of approaching theoretical problems seems rather new to many scientists – it’s actually been around for decades.

MA: What’s not appreciated enough in biology I think is the Watson and Crick paper, their famous paper, THAT’S A THEORY PAPER! There’s no new data that’s reported. It’s basically a theoretical conjecture on solving some equations based off crystallography.

BS: And yet, in that paper – in the 1953 Nature paper in which Watson and Crick proposed that the DNA molecule was shaped like a double-helix – there is a single line that many scientists can recite.

AA: “It has not escaped our notice,” it begins, “that the specific pairing we have postulated immediately suggests a possible copying mechanism for the genetic material.”

BS: This bon mot is famous probably as much for its coyness and understatement as for the significance of its prediction… and that’s a good embodiment of what quantitative biology really is. It’s not a field of a study, but a strategy and even a way of thinking (pause) with predictive prowess that are too-often underappreciated.

AA: Mickey is but one of our scientists employing quantitative biology in a quest to answer some really important questions, so like always, this won’t be the last you hear of this subject.

BS: Cancer, autism, neuroscience, the evolution of humanity, and SO much more – all are subjects that employ QB, and all are things we have or will talk about in episodes of Base Pairs.

AA: So stay with us! And as always… “more science stories soon!”

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Episode 10.5: Tomato baby and its family

Plant scientist Zachary Lippman tells stories from the field of bizarre tomatoes, intensely hot peppers, and giant pumpkins.

BS: Hey, everybody. I’m Brian.

AA: And I’m Andrea.

BS: This is our second chat episode of Base Pairs. We kind of make these episodes so you can get sort of a backstage pass into what’s going on here at Cold Spring Harbor Laboratory, and a little bit of off the cuff discussions that happened in our previous episode. Last episode was CRISPR versus Climate Change, and Andrea had talked to associate professor Zach Lippman. He’s a plant scientist here at Cold Spring Harbor Laboratory. Andrea, what did you guys talk about?

AA: Yeah. What we talked about in the episode was mostly what Zach does in the lab. He is using techniques like CRISPR, this new genome editing tool to make precise changes in the genomes of tomatoes. The plant that he focuses. But I also wants to talk to him about the other big part of his work, which is going out in the field, and growing tomatoes basically the same way a farmer would. I wanted to know about what kind of the weirdest things he’s found out there have been.

ZL: Yeah. What’s wonderful about genetics is that you see crazy stuff all the time. We’ve seen tomato plants that instead of making clusters of flowers, we’ll make the equivalent of cauliflower. It’ll just massively over proliferate what are called meristems. This is where stem cells are in plants, and you’ll got to the plant, and you won’t see during the peak of flowering, you won’t see one yellow flower. All you’ll see are these giant clusters of branched cauliflower. That’s one really crazy mutant that we worked on in the past, and as you might imagine the gene that was no longer working in that plant, or was mutated was responsible for making flowers. This is why you end up with this cauliflower type trait because it’s not able to make flowers.

We’ve seen plants that will instead of making nice round fruits, we’ll make these crazy shapes of fruits, which of course many different people who’ve grown tomato before. Heirloom tomatoes will have seen these types of shapes, but we’re sometimes finding even crazier shapes. Things that we look at and were quite clear in our minds that it would have no business being grown for consumption because it looks so weird. Sometimes we get fruits that have appendages, and it’s not because of any weird laboratory based experiments that we’re doing, this happens naturally. I mean you can see this in many different plants, and many different types of fruit bearing plants where you’ll have a tomato that will have what looks like a nose coming out of it, or arms and legs. In fact last year we had one that looked like a little baby. Two arms, two legs, and a belly. This happens sometimes.

AA: Did anybody eat it?

ZL: No, but they drew a face on it, and a bellybutton, and we took a nice picture of it, and sometimes we show it in presentations.

AA: I want to see that picture.

ZL: Yeah. I can show it to you sometime. It’s really funny. We see all sorts of crazy things when you do genetics. I think what’s most exciting is that not so much the weirdness, but what the weirdness is going to tell you once you start to understand why it’s weird, and this is really the secrets of genetics.

BS: Wait, so did Zach deliver on this promise that he made? Do we have the photos of tomato baby? Now you’ve piqued my interest.

AA: He did indeed. He delivered on the tomato baby photo, and on other baby photos. Specifically Zach Lippman baby photos. You should definitely also check out, and it is posted on our lab dish blog for all of you to see. In one of those photos you’ll see baby Zach in his little overalls with a pumpkin, which I found out also has a lot of significance to him. He had said in the last episode. I was surprised to learn that even though he studies tomatoes, he really strongly disliked tomatoes growing up.

BS: I think the word was despised.

AA: Yes. But he felt very differently about pumpkins, and he’ll tell you a little more about that in this clip.

ZL: We often grow a few crops on the side, and one of the most special ones to my heart has been growing giant pumpkins, which I have been doing for many years, and the idea is to get it as big as we can every year, and we do not too bad. We’re not near the top where some of the largest pumpkins have broken 2000 pounds, but we get up there in the several hundred.

BS: Aha! Now everything makes sense. All over our campus every October season, suddenly massive pumpkins pop up, and I kind of never knew how they got there.

AA: Yeah. Pretty massive. I took a photo once. The pumpkins were on campus for Instagram, and I felt that I needed to put a small child in the photo for scale, so you could tell that this pumpkin was several times larger than this toddler. That’s really just a fun project that Lippman Lab tends to while they’re in the fields for the summer growing their tomatoes. But they also have another side project that is a little bit more relevant because tomatoes are part of a family of plants that has some members that you’re already are familiar with like potatoes, eggplants.

BS: Stop. Explain to me how a potato is related to a tomato?

AA: Not only are potatoes are related to tomatoes, but tobacco is in that family.

BS: What? Wait, what is the family?

AA: It’s called the Nightshade family.

BS: The Nightshade family.

AA: Also known as Solanaceae.

BS: This is nightshade. You make poison from nightshade? The infamous nightshade?

AA: Yes. Indeed.

BS: Oh wow. The things we learn in Base Pairs.

AA: Yeah.

BS: Okay. What is this other mysterious plant?

AA: The other plant in this family that Zach’s lab is really interested in is peppers. They’re interested because they’re related to tomatoes, but what they’re also interested in is that some of those peppers are very, very spicy.

ZL: The side project is that we work on pepper. Pepper is a very closely related relative of tomato in the Solanaceae family. There are many attributes of pepper that are similar to tomato, and we have a very large project to study flower production in pepper because unlike tomato where every cluster of flowers will be anywhere from 7 to 15 flowers. That translates to 7 to 15 fruits on the tomatoes on the vine. Pepper plants typically will make one flower in every “cluster”. We’re very interested in the few wild species of pepper, wild relatives of pepper that will make a few more flowers. Sometimes three to four flowers in each cluster. We have a large project. Now, the reason that sort of somewhat of a hobby on the side is that a lot of these peppers are extraordinarily spicy, and people in the lab every summer will collect from the spiciest varieties, and there’ll be taunting in the lab, and competitions about who’s willing to pop one of those peppers, and maintain a straight face. At least for a minute or two, yeah.

I’ve heard that people have taken some of the hottest peppers. The Reaper for example, or the Ghost Pepper, and made at home these extraordinarily hot sauces. These salsa type sauces that will last in the lab for up to a year because you only need a drop or two in order to spice up food.

AA: Oh my.

ZL: Yeah. The pepper project is a fun one that has real, real value to. Actually, our entire research program.

AA: I heard around campus that … We have a bar on campus, and I had heard that at the end of the summer, Lippman lab would all go down to the bar with a bunch of jars of different kinds of peppers, and they would play Russian Roulette with tasting the peppers, and you would have to try to withstand it for as long as you can, and they would make this kind of drinking game out of it.

BS: I don’t know. I think I can handle this. I got to go find Zach and get in on this game here.

AA: We’ll see.

BS: Very cool. That’s it. That’s everything that we have?

AA: Yeah, that does it for this time. Definitely make sure that you go to our Lab Dish blog. See all the great photos of bizarre tomatoes, and baby Zach, and giant pumpkins, and all the fun things that go on in Lippman Lab.

BS: Right. Next month we’ve got another full story episode, so we’ll dive right back into the science that goes on here, and the implications in real life, and the power of genetic information as this podcast is all about. Thanks for tuning in guys.

AA: Thanks. We look forward to talking to you next time.

BS: Yeah. Bye everybody.

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Episode 10: CRISPR vs. climate change

CRISPR is a tool that makes it easier than ever to edit the “letters” of the genetic code. In this episode, we talk with a plant scientist about how this advance could help agriculture deal with climate change.

BS: Hey everyone! I’m Brian.

AA: I’m Andrea, and this is Base Pairs.

BS: Exactly one year ago, we launched this show about the power of genetic information. And now, NBC might be making a show about the power of genetic information, too.

AA: Except theirs would be a TV show instead of a podcast. Oh, and instead of being produced by Brian, the NBC show would be produced by Jennifer Lopez.

(Short clip of “I’m Real” by J. Lo chorus)

BS: Yes, that Jennifer Lopez. The pop star. This show that NBC’s considering would be called C.R.I.S.P.R., a name that comes from a real scientific tool that few scientists would dispute is the biggest thing that’s happened in biology in the last few years. CRISPR makes it easier than ever to edit the genetic “letters” of DNA.

AA: I’m going to read a description The Hollywood Reporter’s description of the show: “In the same vein of Castle, romance will blossom between the scientist and the FBI agent as they team to bring down a diabolical genius with a twisted God complex: her former boss. The drama will see mentor and protege battle for control over the human genome in a game of cat and mouse in which the future of our species may rest and all disease could one day be eradicated.”

BS: It sounds pretty farfetched for the sake of drama. But, if done very thoughtfully, who knows—it could be a good way to get more people thinking about this new technology.

AA: And CRISPR is dramatically changing biological research. Quite a few scientists at CSHL and many more around the world are using CRISPR for their experiments, for example finding new ways to kill cancer.

BS: Eradicating diseases is probably the most obvious use of CRISPR, and scientists have been quick to adopt it in their research toward that goal. Of course, disease isn’t the only big obstacle that humanity faces.

ZL: With the change in climate that’s happening, whether you believe it’s human-created or not, there is a change that’s going on, you now have to start to consider whether we’re gonna need to expand even further the range of where we’re able to grow our crops. — Now we have a tool to match that urgency because of how quick and powerful the gene-editing tool that comes from CRISPR is.

BS: That’s Professor Zach Lippman. He’s a plant scientist who’s using CRISPR in a way that could help us overcome the challenges that climate change poses to crops.

AA: NASA is actually doing a lot of work to help better understand those challenges, using their satellites and other technologies to gather information from all over the world. Cynthia Rosenzweig, a senior research scientist at NASA, explains in an educational video that climate change will affect different places in very different ways.

VIDEO: Vulnerability to climate is uneven across the world. Agricultural studies show that in the mid and high latitudes, the agriculture there should actually be ok for at least a while, before the really big temperature changes set in. But in the low latitudes, where it’s hot already and where there are more arid areas, climate change will affect those agricultural systems negatively right from the beginning.

BS: So, we need to plant more crops up north, where the climate’s too cool for a lot of crops right now, but it’s getting warmer with climate change

AA: Exactly.

ZL: You can imagine a scenario in the future where areas where we currently grown our major crops, for example in the corn belt, could become too hot and too dry as temperatures rise and those high temperatures move further north during the peak of growing seasons. So in areas like Canada, where you have northern latitudes, you would have an opportunity to grow crops in areas now where the temperatures are more moderate—similar to the temperatures we have right now for example in the middle of the country.

AA: I talked to Zach about his lab’s recent discovery in tomatoes, and how it shows CRISPR’s incredible potential to help keep these climate shifts from harming our food supply. Zach mostly works with tomatoes for his research, and while his love for agriculture was clear early on, this is a pretty strange turn for his life to have taken.

ZL: So, I grew up on the coast of Connecticut and worked on a vegetable farm, only job I could get when I was 13 years old. Got paid cash under the table every two weeks and was obviously around a lot of different plants, crops. And ironically the one that I despised was tomato. And the reason that I didn’t like it was that you would have to harvest it from staked plants, and you would see this beautiful red tomato on the front and you’d go to the back and you’d grab it and it would be rotten and it’d go squish.

BS: Despised, wow, that’s a strong word. He must have found some redeeming quality that helped him get past the squish issue.

AA: I was surprised too. But then he explained that there’s something special about the way tomatoes produce flowers.

ZL: I was still very interested in the plant itself, because it was one of those few plants that continued to put out new flowers and fruits throughout the course of its growth and during the season.

AA: It wasn’t the tomatoes themselves that captured Zach’s interests, it was the flowers: these beautiful, delicate structures that we so heavily depend on for our food supply.

BS: Yeah, flower power isn’t just a catchy anti-war slogan. Flowers have a huge influence on our lives because they’re essential to so many of the fruits and vegetables we eat.

ZL: The reason we focus on tomato is because it’s one of those plant systems, those plants that we call model systems that are representative of many other crops. — It’s a representative of pepper and eggplant and soybean—so all these crops that produce flowers and then bear fruits.

AA: While Zach was telling me about how much our food depends on flowers, I thought about how a few years ago, my family wanted to go apple picking, like we do every year, but when we called the orchard they said they hardly had any apples. In the spring, a late frost wiped out almost all of the flowers on the apple trees, which meant no apples in the fall.

BS: It’s amazing that farmers are able to produce crops so consistently, considering how delicate flowers are.

AA: It is. Plant breeders have worked for decades to create crops that can pretty reliably withstand the weather in a particular place. The weather has always changed from day to day, but you could expect the same general patterns from year to year.

ZL: With climate change, all of that — “stability” — for a particular environment that is quote-unquote “not changing very much” over the last century very much, but now is, now gets thrown up in the air.

BS: Stability for a particular environment used to be enough, but now that the climate is changing, we need flexibility so that we can move crops to new environments.

AA: Right, and to achieve that flexibility, scientists like Zach first need to understand the constraints on where crops can grow successfully. Have you ever wondered how plants know when to bloom? For a lot of plants, the number of hours of light in a day is a critical cue.

BS: So for a lot of plants, you can’t just expect them to flower properly when you move them far away because days are different lengths in different parts of the world.

AA: Right. In the case of the tomato…

ZL: Wild tomato originated in Central and South America, where it’s near the equator, so it’s not exactly a short day, not exactly a long day, but it turns out that many of the wild tomato species, the wild tomato relatives, flower best under shorter day conditions.

AA: If you try to plant one of those wild tomato species much farther north, where the summer days are longer than in places near the equator, they flower really late in the season and don’t make many tomatoes.

BS: Some tomatoes grow just fine all the way up here in New York, though. My family would grow them in our garden all the time.

AA: That’s the thing. Unlike those wild tomatoes from equatorial regions, the domesticated tomatoes that we usually grow and eat here in the U.S. went through a genetic change that allowed them to grow far beyond the geographic range they were first adapted to.

ZL: This change caused the tomato plant to no longer care about day length and it essentially became day-neutral. — This is the reason that we can grow tomatoes in much higher northern latitudes.

AA: Zach really wanted to find out what that change was.

BS: But if we already have tomatoes that don’t care about day length any more, why bother?

AA: That was enough to make tomatoes grow well here in the United States, but with a changing climate and a growing population, we need even more flexibility.

ZL: Now the question is, can we develop varieties that can grow at even further northern latitudes where you have two things working against you. One is you have an even longer summer day length and the total number of days in the summer is now shorter, so you have to put out your flowers and your fruits and your yield under a very long summer day, in terms of hours of light, and under a very short window of time.

BS: Long days and a short summer. So even if the tomato plants can flower with long days, they’ll have fewer days to go through the full process of developing their fruits. They need a head start.

AA: Right now, it’s like the tomato’s genetic control dial for flower production is on the middle setting. All the way on one side of the dial is the original flowering setting: flower on relatively short days throughout a long equatorial summer. One the other side is the maximum flowering setting: don’t pay attention to day length and just flower as soon as possible

BS: So Zach wants to turn that genetic dial. That sounds like a job for CRISPR—I think. What exactly is CRISPR, anyway?

AA: Scientists like Zach call what CRISPR does “gene editing,” because it makes it possible to create genetic changes in genes. And it allows them to make those changes much more precisely than ever before.

BS: Initially, plant breeders just had to wait until they got lucky, and nature happened to create the genetic mutations they were looking for. Then, scientists figured out how get “nature’s genetic engineer”—a common species of soil bacterium—to work for them. But the bacteria still had their own agenda, so scientists didn’t have full control over the changes they made.

AA: Now, the big difference with CRISPR is that the plant scientists are the engineers and can control exactly which letters they want to change.

ZL: Before gene editing came along, we were looking for needles in a haystack when we were trying to create mutations in genes that would affect a trait of our interest—in this case flower production. — Gene editing comes along, and now all of a sudden it’s possible to say, “Ah, this gene that I really wish I had a mutation in over the last 10, 20, 30 years and nothing ever came of all my hard work — Now you could pinpoint that gene and say, “I want to mutate it.”

BS: Zach isn’t exaggerating the amount of time it takes to do this work using what people think of as natural or conventional breeding. Remember Dave Jackson from episode 4, “The People Problem”? He was looking for a mutation in a gene that would lead to a big increase in corn’s yield. And it took a while.

DJ: Almost 20 years I’m a little embarrassed to say… but sometimes these things go on for a long time…

BS: Dave is very modest, but finding that yield-boosting mutation even after 20 years was a huge accomplishment. It took an incredible amount of work, and quite a bit of luck.

AA: But like Zach, Dave started using CRISPR in his research once it became available because it makes this process way, way faster.

ZL: Within 8 months you would be able to induce a mutation in that gene and then have the ability to ask how it affected that plant.

BS: 20 years to 8 months. And it’s that easy? I must be missing something. How does CRISPR know where to make a mutation? I’ve heard it described as “molecular scissors” before, but there has to be something guiding the scissors to the right spot.

AA: There is. CRISPR is really a two-part system. The “molecular scissors,” which is really a specialized protein, is one part. The other part is a piece of RNA, an essential molecule in cells that’s very similar to DNA and can bind to particular pieces of DNA through base pairing.

BS: Like how the As and Ts or Cs and Gs in DNA pair with each other. That’s how the two strands of the double helix stay together—they have complementary “letters,” or bases, that attract each other.

AA: Right. RNA can do essentially the same thing. A piece of RNA will bind to a piece of DNA with the complementary sequence. The protein “scissors” use a piece of RNA that’s complementary to the DNA of interest to guide it to the right spot.

BS: Ah, because that RNA will be naturally attracted to that exact piece of DNA. That still sounds too simple.

AA: Ok, then maybe hearing from one of the CRISPR co-creators herself will help convince you. UC Berkeley Professor Jennifer Doudna was here at CSHL for a big meeting in 2015 and she sat down for an interview with former Banbury Center Director Jan Witkowski. It was the summer, so they took advantage of the warm weather and did the interview at a gazebo on campus that overlooks the harbor.

JD: This protein will actually find its RNA out of all the RNAs in the cell, will bind to its guide, and then use that for recognition of DNA and making the cut.

JW: It all sounds very straightforward. Is it as straightforward as you’re making it out…

JD: This is the amazing thing, it really is. You know, I mean in my lab some of the early experiments that we did testing this in mammalian cells were done by a first-year graduate student.

BS: Wow, I’ve never heard genetic engineering sound so easygoing. The birds chirping definitely add to the effect, but the fact that a novice scientist was able to do this work shows that it’s relatively easy to learn how to use CRISPR.

AA: All of a sudden Zach basically had the tool of his dreams available to adjust the genetic control dial for flowering, which he’s been interested in since he was a kid.

BS: And scientists had already made some progress on figuring out what those dials are. It was just so laborious to test that idea out using older tools—to turn the dial the way you wanted.

AA: Zach knew from previous research that there are these two proteins that have opposite effects on flowering. One tells the plant “it’s time to flower” and the other says “don’t flower.”

ZL: The plant has this — yin-yang relationship between these hormone proteins.

BS: Hmmm, kind of like a dial.

AA: Sure enough, when Zach compared the genomes of wild and domesticated tomato species, he found some very intriguing differences in a gene that controls the production of the anti-flowering protein. And the wild plants made even more of the anti-flowering protein when exposed to long days than they did for short days.

BS: Which suggests that the amount of this anti-flowering protein the plant produces has something to do with its sensitivity to day length, since the wild tomatoes pay attention to it and the domesticated ones don’t.

AA: And now that CRISPR is available, Zach could precisely target the gene that seemed to be behind that difference.

ZL: A lot of what we found is that the system is tunable, so that you can tune the relative yin versus the yang.

AA: Even the domesticated tomatoes were still making a little bit of this anti-flowering protein, so Zach used CRISPR to make a mutation in the gene that would turn this anti-flowering force down even further. He tried it in cherry and roma tomatoes, and with this small change…

ZL: Now they’re putting out their flowers, fruits, and yield much faster (AA: Two weeks faster!) and so the possibility of expanding cultivation to northern latitudes for example in Canada, where it’s very difficult to grow many of the modern elite hybrids that dominate the tomato production industry, now we can start to think about modifying the genes — to grow them in regions like Canada where you have very long days and very short summers.

BS: That’s amazing! It’s like, instead of trying to precisely turn a tiny dial using a cumbersome 30-foot pole, scientists can just reach right out and grab it.

AA: Right, he’s working on making changes to some of the same genes that breeders have been changing through conventional breeding for a very long time, but CRISPR is greatly speeding up the process.

BS: Plus, like Zach was saying earlier, tomatoes are a representative of a huge variety of plants that flower and bear fruits. So maybe he can turn this same genetic dial in other crops.

ZL: It will be an interesting question in the future, how tunable the system will be, not only in tomato but in other crops where again we have conservation of genes between many different plants, the same flowering genes, the flower-promoting genes and the flower-repressing genes that exist in tomato also exist in rice and corn in the same gene families, many of them do the same functions.

AA: The hope is that this will help provide growers and breeders with a genetic toolkit to tweak the flowering time of a crop in a single generation, instead of the many, many generations that breeders had to go through before.

BS: There is an elephant in the room, though. Are these early flowering and fruiting tomatoes GMOs?

AA: Bizarrely, even though CRISPR technology itself is relatively straightforward, this question of whether the final products—like Zach’s early tomatoes—are GMO is a little more complicated.

ZL: From a technical standpoint, they are no longer GMO and they don’t carry foreign DNA.

BS: That seems pretty clear—a commonly used definition of GMOs is that they are organisms that have been engineered to contain genes that you wouldn’t normally find there.

AA: Exactly. That’s why the tomatoes that Zach tweaked using CRISPR are technically not GMO. But…

ZL: They did go through a GMO process in order to achieve the desired outcome.

BS: How is that possible??

AA: To get CRISPR into the plants, scientists have to borrow part of the older genetic engineering process, the one that this definition of GMO is based on. That process involves using a common species of soil bacteria, called agrobacterium, which inserts foreign DNA into the plant.

ZL: The beauty though is that after you target your gene using CRISPR, to create mutations or to change the DNA in interesting ways and powerful ways, you can then immediately remove, — through genetic crosses that are done through natural breeding processes, you can remove the foreign DNA that was brought in by agrobacterium. And you are left simply with a plant that no longer has the — foreign DNA that was introduced, and all you’re left with is the remaining mutation, or the scar, in the gene that you were targeting. So this is an active discussion of whether this is considered GMO or not, and I think it’s gonna be an interesting discussion to see, how it plays out worldwide, whether such and such gene-edited plants and crops are considered GMO.

BS: These are the kinds of questions that individuals need to ask themselves, and why it’s so important that even non-scientists have an idea of what CRISPR can do. I’ve seen criticism from scientists about the idea for that C.R.I.S.P.R. TV show we talked about at the beginning of the episode, because they worry it won’t actually give people the knowledge they need to make informed decisions.

AA: Jennifer Doudna, one of the co-creators of CRISPR the gene editing tool who we heard from earlier, said it well in a statement to Motherboard about the TV show: “CRISPR is powerful and profound technology that can help us positively impact human life. It is important to introduce it to the public and characterize it correctly but we must remember that this show is dramatized science fiction.”

BS: Hopefully our little show about the power of genetic information is doing its part to properly introduce CRISPR to the public.

AA: And we hope you’ll help us, J. Lo.

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Episode 9.5: Redefining biologists, redefining genes

Set aside your notions of how biologists are born, or what the word “gene” means as you listen to our first chat episode. We talk with Assistant Professor Molly Hammell, a genome biologist who started out as an astrophysicist. She tells us what it’s like to peer deep into space using a high-tech telescope. We also speak with Professor Tom Gingeras about whether it’s time to redefine the gene.

BS: Okay, hey everyone I’m Brian.

AA: I’m Andrea.

BS: And this Base Pairs but-

AA: A little bit different from the Base Pairs that you’re used to.

BS: Ah, yes, just a tad. This is going to be a mini-episode, is what we’re calling it.

AA: Yeah, because these are just a couple little tidbits from the interviews that we did in the previous two episodes. Those were our Dark Matter of the Genome series.

BS: Part one and two.

AA: Yes. And even though we had two episodes all about that, we still had parts of these interviews, as we do every time, that we really enjoyed but just didn’t make the cut. And we wanted a way to share those with you anyway.

BS: Right, right. Some of these moments are going to be, they describe more about our guest’s backgrounds, their history, some really cool tidbits like that.

AA: Yeah, sometimes that’s takes the form of a tangent about their philosophy about what they study. Or sometimes it could just be an anecdote about what got them into science as a youngster. All those little nice moments.

BS: And surprisingly, scientists usually don’t like to talk about themselves, so when we say that these are gems that we want to share with you, they really are. They’re rare moments. Along those lines, I know that you were talking to Assistant Professor Molly Hammell for episode eight, part one of our two part premier. What did you guys get into talking about that didn’t make the cut?

AA: One of the things that I had to ask her about was the fact that she started her career in science as, not a biologist, but an astrophysicist. And that is something that I personally do not know very much about. My science background is all biology, and I wanted to know what it’s like to be a professional astrophysicist, and to use a really fancy telescope.

When you were doing astrophysics, what kind of things were you doing? I’m so curious just such a unique background.

MH: No, yeah, sure. I used to go, so how I spent my time is probably the easiest way to do it. I used to go a couple times a year up to a telescope and I would be alone of a mountaintop, sleeping during the day, staying up all night taking pictures of the sky. And what we were really doing at the time is we were looking for the oldest galaxies in the universe, right. Because we knew, that if we knew how older galaxies looked compared to the modern ones like the one we live in, then we might have a better idea of how our universe formed, and what, how our galaxies derived as compared to the early ones that first formed. That particular property is really determined by the amount of matter in the universe. So the dark matter content has a huge impact because it interacts gravitationally with, okay, this is getting too detailed. I’m going to stop. Okay, let’s start this over again.

AA: And what kind of telescopes were you looking through?

MH: These are professional telescopes. These were, the one I was working with was about three feet in diameter, and then there was another one that was nine feet in diameter. There’s no eyepiece to in the back of the telescope. The telescope sits in its own room, and I would sit in the control room next door and control it from there. Basically just open and close the shutter as many times as possible to cram every image that I could into the night.

AA: So Brian, you talked to professor Tom Gingeras and it turns out, and I did not know this, but he had a pretty strange path to science too.

BS: Yeah, a little bit different than Molly in the fact that he didn’t stick with this for long, but when he was in college he originally was an economics major, and he was pretty far down that path when he sat in on a few biology classes and that was the moment that he realized that he needed to change everything he was doing.

TG: When I was in college, I found myself with some spare time and I sat in on a freshman biology course. Mainly because in high school I never had a biology, and I wondered what that was all about. And it was a such a novel experience, and things I never imagined that we knew about. Needless to say, I spent the next three years making up for the things that I missed as an economics major. Then from then on, it was very clear that doing molecular biology, which was the emerging field at the time, was all that I wanted to do.

BS: Back to Molly though, because I know there’s a lot more of that interview where you asked her some personal questions that tie back to the lab.

AA: Right, things that are actually about biology, which is what we do here at Cold Spring Harbor Laboratory. Yeah, so now that she studies biology, Molly focuses on these strange little zombies of the genome called transposons-

BS: Which you can learn more about in our first premier episode.

AA: Yes, in episode eight, Dark Matter of the Genome part one, and these things were actually discovered right here at Cold Spring Harbor Laboratory by a scientist named Barbara McClintock So I just wanted to get a sense of what that means to Molly, to be able to work at the same place where these things she’s studying every day were first discovered. And to realize how far we’ve come in all these decades.

MH: Wow, so Barbara McClintock, she was an amazing scientist who received a Nobel prize for her research for this discovery. That there are these sort of selfish elements within our genome that are capable of moving around. It was amazing what she did in the time when we had far fewer tools to look at these things than we do now.

Fortunately for me, I have a lot of tools to look at these things that makes them completely visible. Now, we can sequence a genome. We can sequence the genes that are being used at any time, in a given cell. And we can just look and count them up and do a bit of math and statistics on that. At the time when Barbary McClintock was working, she was really inferring this huge, vast existence of these transposon sequences without a picture of what the genome itself actually looked like. She had sort of a rough map, but she you know, for the most part, had no idea what was in between the genes she was following. Her ability to infer that these things were present, without being able to actually see them, it’s amazing right. I feel like the work that we do in my lab, where they’re plain as day, out there and its just a matter of counting them up and doing the math. I have a much easier job.

AA: You make it sound so easy!

As we talked about in episode eight, transposons are not exactly genes. But what even is a gene? That’s something that I know Tom has thought about a lot, and has apparently some very interesting thoughts about.

BS: Yeah right. When I was talking to Tom, this was actually something we spent a great deal of time talking about, and I will not able to show you guys the whole conversation today, but we’ll get to the core of his main points. Which is really that, when the term gene was first developed, it was in a time where nobody even knew what DNA was. Now that that term is being reapplied in the genomics age, it’s kind of being misused in Tom’s opinion. He wanted to elaborate a little bit upon that, and you can hear what he has to say for yourself.

TG: Well there are many phenomenon in classical genetics, which while they’ve been explained partially, have never been satisfactorily fully explained. One of these phenomenon is called penetrants. You can look at a mutation in a gene, and that mutation can exist in multiple people. But the effect of that mutation, that variation on a phenotype can be different. You can have a mutation, which in one individual is lethal, and in another individual virtually has no phenotype whatsoever. Now why is that the case?

It’s because, in many cases, is that there are other mitigating factors that control the effect of that mutation on that gene. Those other factors are other genes. They could be protein coding, they can be non-protein coding. That mitigating factor now brings together this idea, in a very solid manner, that a gene, the gene responsible for this is not just one structural unit. It’s the RNA made from that gene plus all of the mitigating genes that have an influence contributing to this phenotype.

BS: Right, right. What would you call a gene?

TG: A gene is a higher order concept. If you think about, in a subatomic fashion, that the element inside of the atom are many subatomic particles, the total of which constitutes an atom. The atom is the gene. The subatomic particles are the transcripts that contribute to the characteristics of that atom.

BS: So that’s it for today guys. Thanks for tuning in. Hearing a little bit more on what we didn’t get to include in our season premier episodes, Dark Matter of the Genome part one and two.

AA: Yeah, and we’ll be back in June with a new full episode. So make sure to listen in then.

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Episode 9: Dark matter of the genome, part 2

One scientist’s junk is apparently everyone’s treasure! They just haven’t realized it yet…  In this episode of Base Pairs, we question the mythos that is “junk DNA” and explore how and why scientists are becoming enthralled by the mysterious non-coding portions of the genome.

BS: Hey all! I’m Brian

AA: And I’m Andrea

BS: And welcome to season two of Base Pairs!

AA: This episode is actually the second half of a two-part season premiere, so if you’re interested in hearing the whole story, we highly recommend you check out our episode from March of 2017. It’s titled Dark Matter of the Genome, Part 1.

BS: And in that episode, we talked to CSHL Assistant Professor Molly Hamell – who coincidently used to be an astrophysicist – about the “Dark Matter” of the genome. The chunk of the genome—

AA: About 98% actually!

BS: —the HUGE chunk that in fact does not code for proteins.

BS: Now before we go any further, I wanted to invite our listeners to join me for a step back into the past – when I was just an awkward high school student trying to pass his biology class.

(classroom chatter)

AA: Oh, my. I’m not sure you’re going to keep an audience for this one, Brian. Are we going to have to hear all about your high school angst?

BS: No… no, no. Nothing like that. But like most of our listeners, I loved science, even then… even if I was sleeping through some of the lectures. And a favorite wacky science fact my teachers – and even the textbooks! – tended to repeat was that more than 90% of the genome was… junk. “Junk DNA,” is what everyone called it. And it stuck. I remembered that. Even when I turned my attention away from biology to space science, and animal science, and climate change, and medical reporting… that crazy statistic stuck with me.

AA: Well, that’s why we prefer the term “Genomic dark matter” so much more. Instead of seeing “junk,” the world is finally learning to look the non-coding part of the genome – the part that doesn’t contain the recipe for proteins — as the exciting unknown, an area worth investigating.

BS: Right, right… but imagine being a scientist interested in that unknown back when I was in high school. When everyone, even your esteemed colleagues, also pushed the “junk DNA” concept. At the time, people researching that ignored part of the genome must have looked a little like… well… garbage pickers, or maybe trivia freaks.

TG: There was sort of a negative connotation associated with any region of the genome that was not engaged in making proteins. And, it acquired a label of Junk DNA, in the literature, and therefore, this pejorative concept really stayed with us and focused the attention of most people on these protein coding regions, without the need for studying these other regions.

BS: That’s Tom Gingeras, a CSHL professor who can be found carefully scrutinizing genomes at the aptly named Genome Research Center.

TG: Even when I was an undergraduate, one of the major topics that was being pursued by a lot of different labs, and this will sound somewhat strange given where we are today, was that where were genes in DNA? Obviously, we had an understanding that DNA was the genetic molecule that’s passed from one cell type to another, and from one generation to another. But we didn’t realize that a unit called a gene … What was it? How was its structure identifiable in gene, in a genome? How was its expression, how was its information turned on at any one particular time, in one cell type versus another? These are questions that continue to be pursued in science. But, in the days when I was a student, we knew virtually nothing about it. That’s been sort of a probing question for me for many, many years.

AA: Oh wow. I can see why he’d want to be a part of that. It’s the one drive A LOT of scientists share: a desire to break new ground in the search for information about… everything!

BS: That’s it, and to make those new discoveries, Tom found himself leading projects were he and his lab wadded and sifted through the genome’s so-called junk, one nucleotide at a time. It was all part of the ENCODE project-

AA: That’s E-N-C-O-D-E – an international project consortium first established by the U.S. government in 2003 to examine the recently decoded human genome sequence in greater depth.

BS: Yup. And they were spending most of their time studying the areas occupied by what’s considered “genes” – that 2% of the genome that leads the production of proteins.

TG: So, we… looked at two chromosomes. Chromosomes 21 and 22. And we walked along the genome roughly every five bases. Is there an RNA that contains that base as encoded in the genome? And then you’d walked to the next five and ask, “Is there an RNA coming from there?”

AA: To remind our listeners: RNA is the short-lived cousin of DNA. Scientists first learned about RNA because it carries the instructions for making proteins from the DNA to the cell’s protein factories.

BS: Right, and with that understanding, most scientists looked for the presence of functioning RNA as a sign of activity coming from the protein-coding parts of a genome. In this way, many hoped to figure out where exactly each gene is on a chromosome, and what it’s up to. Tom figured that since only 2 percent of the genome was genes, only about 2 percent of each chromosome would be written in an RNA—or transcribed, as scientists say.

TG: My post-doc at the time, Phil Kapranov, came back with a result, which seemed to me entirely wrong because it went against the very simple principle that the only place that we probably should be seeing things are where known genes are… Now, you might see new known genes, and so, all right, so you would increase the number of spots that would be functional in that fashion. But, instead, we saw almost a totality of those two chromosomes being transcribed. So, I got very upset with Phil, because he obviously did the wrong experiment and what he did was wrong. I asked him, “Please, go back and do this again.”

BS: So. Phil did it again, and again, and again – each time with the same result.

TG: The exact same result…

AA: Ok. So NOW I’ve got to know. What’s going on here?

BS: You know? That’s the thing. Tom had no idea. As far as the scientific community was concerned, Tom’s lab had been sifting through junk, looking for treasures. But now it seemed that EVERYTHING was treasure! The genome in those 2 chromosomes was expressing massive numbers of RNA messages, or transcripts, as they are called by scientists.

TG: To add to the complexity… this incredibly rich output of RNA from every region of the genome indicated that there was a lot of energy being “spent” by cells being put into making these RNAs, which apparently had no function since many of them– most of them– were well outside the 2% of the genome that encodes protein.

AA: To blow so much energy on making useless RNA… that doesn’t sound like the efficiency we’ve come to associate with cells. Nature, as many experts will tell you, generally has a “waste not” kind of attitude.

BS: Exactly. After seeing examples of this phenomena again and again, Tom and his team decided to change how they perceived the genome. Almost overnight, they became those so-called “garbage picking” scientists I mentioned earlier. And in doing so, they discovered something that really abolishes the “junk DNA” mythos.

TG: What we determined is that roughly 80% of the genome is transcribed… Not every cell makes 80% of its genome, but if you look at a totality of many, many different cell types, what is capable of being transcribed is about 80% of the genome. Only 2% of the genome is actually embedded within a protein coding region. So, that meant that a majority of the genome was transcribed and that most of it was making RNAs that were not intended to make a protein.

AA: 80%… Wow. So… we know today that there’s around 20,000 protein-coding gene regions. Scientists even today are still trying to identify what each gene does. Tom’s work is exciting stuff – don’t get me wrong – but can’t we just… I don’t know… shelve it until we get the protein coding parts figured out?

BS: (laughs) Well…Initially, that’s exactly what happened. A lot of scientists simply didn’t accept Tom’s results, saying that Tom, Phil, and rest must have been mistaken.

TG: ‘…either your technology doesn’t work, or B, it doesn’t make any difference because it’s all noise anyway because it’s not a perfect system.’

BS: And then, even among the people who did believe it, they argued that – like you said – it’s just too much. They preferred to focus on what the Human Genome Project had made known, and suggested saving the unknown for a rainy day.

AA: But then… something happened, didn’t it?

TG: Slowly but surely, what we saw was that these RNAs were seen to be important regions, that if they were mutated, deleted, you would see an effect. A phenotypic effect.

BS: By “phenotypic effect,” Tom means, simply, a physical manifestation in living creatures – things that made them look different, or in some cases, made them sick. Our first sense of the scope of these changes came about 5 years ago, when teams from 32 institutes in five countries – all contributing to the ENCODE project – released 30 papers at once.

AA: Not exactly light reading.

BS: Hehe. Well, it was important stuff! Previously, it had always been assumed the only way to affect the physical expression of traits was to mess with a gene, or – as we described in the previous episode – inhibit the regulation of transposable elements. But a lot of the ENCODE data showed that even if you messed with only the non-protein coding parts of the genome, it could affect cells, and whole organisms, in a big way.

AA: Oh wow… that is important. I take it the scientific community is a bit more amenable to Tom’s results now, right?

BS: Well…

TG: I’ll answer that with a personal vignette. So, I would go to meetings and we would present our data. That almost invariably ignited a discussion, no matter how large the audience was. I’ve been in places where there’ve been more than a thousand people, and then people would have no problem jumping up and saying, “This is all nonsense. And even if it is all true, we are totally swamped with just learning about the things we know about, instead of dealing with all this other nonsense.” You would have this back and forth. I would go back home feeling very upset. Feeling, “why can’t they see? Why can’t they understand?” And I would say, “We’re not incompetent. So why is that we’re having this discussion?” And I would get very personally worked up. Until one day I honestly had what might be called, in sort of a religious sense, this enlightenment. Seriously. Sitting in my office. Which, basically, led me to understand that you need to let them discover it…

I’m sure that people will do these experiments in their own way in their own systems. And, if they see the same thing then perhaps you’ll understand that there’s a lot of work to be done. And, that the things we thought were solved, in fact, are not solved, and they offer an opportunity to learn even more.

DS: … Yes, 7SK. Yeah. That kind of started our interest and then it just expanded from there. Now it’s pretty much the main focus of my entire lab. We do very little imaging at this point. Mostly we’re doing RNAseq and try to figure out the function of these long non-coding RNA’s.

AA: That’s Professor David Spector – and he’ll explain “7SK” in a minute….

BS: David was once one of “them.” Those doubting scientists Tom was talking about. Not necessarily a critic of ENCODE’s work. Just a scientist so focused on his own work that he didn’t pay much attention to the non-coding part of the genome.

AA: You see, David is the Director of Research here at CSHL, so we know a lot about him…

BS: And we know he’s REALLY adamant about speckles.

(Clip from the holiday party) (laughter fades)

DS: My lab is probably best known for the early work that we did on nuclear organization and function. I started that work probably back in 1981. We were very intrigued by how the nucleus might be organized, given the fact there are no membrane-bound structures in the nucleus. Yet if you stain cells with either dyes or with antibodies there are clearly concentrations of specific proteins in different places in the nucleus… So, I got really interested in studying these structures and spent a significant amount of my scientific research career on a particular nuclear structure called nuclear speckles…

…in fact, some people call them Spector speckles as a joke. We spent a lot of time working on them. We purified them biochemically. Did proteomic analysis, identified 146 proteins in them. We did live cell imaging of them and just an enormous amount of work.

BS: So much work. Back then, the majority of David’s lab was dedicated to this subject, but that started to change when he had his own run-in with the unknown.

DS: “7SK. It was a known RNA at the time”

BS: Ok. So not THAT unknown. But it was still a non-coding RNA, and the fact that it was jumbled in there – hiding in Spector’s speckles – that caught his attention.

DS: that kind of tipped the bucket in a way from proteins to RNA because we were intrigued by the fact that there was such a high concentration of this non-coding RNA in nuclear speckles.

AA: I see. Here’s this important region of the cell, and David found himself wondering, “why is it wasting energy making so much of this supposedly useless RNA?”

BS: That’s the ticket. But David’s foray into the Dark Matter of the genome didn’t stop with just one RNA.

DS: One day we got a call in the lab from a student in a lab in France

BS: — her name is Delphine Bernard —

DS: She was doing a study in neurons and… She came upon a long non-coding RNA and her adviser was telling her to drop it and forget about it and focus on what his lab was interested in. She persisted and she was curious about it and because my lab had been working on long non-coding RNA’s she decided to call us and see what do we think? So, she started to tell me about this RNA on the phone and it sounded really exciting so we told her absolutely don’t drop it. We started a collaboration with her and then we ended up having a paper together in EMBO Journal. Her PI bought into it very strongly, so he was a convert. (laughter) Anyway, so that kind of got us interested. The RNA happened to be MALAT1.

AA: Ok. That sounds VERY familiar. MALAT 1 is a puzzle, even among genomic dark matters.

DS: MALAT 1 in essence breaks the rules for all long non-coating RNA’s. First rule, most long non-coding RNA’s are present in very few copies per cell. MALAT 1 is widely abundant in cells. In fact, in many cell culture lines it rivals… one of the most highly expressed transcript in tissue culture cells

AA: And that… that would indicate that MALAT 1 is important.

DS: It’s got to have a really amazing function.

AA: VERY important.

BS: And yet, when they studied mice that couldn’t produce MALAT 1…

DS: At the end of the day, the mouse was perfectly happy without MALAT 1.

AA: What?!

BS: Yeah. Perfectly healthy. David’s lab even sent a number of tissue samples to folks over at Yale.

DS: They looked at all the tissues, couldn’t find anything abnormal about them. The mice have been in my lab now breeding perfectly well for probably close to seven years.

AA: Somehow, I doubt this was a complete bust. It seems highly unlikely that cells mass-produce MALAT1 for fun.

BS: that’s what David thought too. He figured that MALAT1’s function may in-fact be more important than he and his lab presumed – SO important that healthy cells have back-up systems in place if the RNA’s production fails in one part of the genome.

DS: Given that, we said “okay we need to take a different approach…”

AA: So, David and his team needed to study cells that were omnivorous — hungry for all things good for them… (Pause) that sounds like…

BS: Yup. Cancer. Aggressive tumor cells are like regular cells gone rogue, multiplying rapidly and sapping up important resources in the otherwise organized world of a living thing. Tumor cells that travel from one place to another – such as breast cancers that invade the lung – are called metastatic – and you can often blame their bad behavior, at least in part, on a mangled genome.

AA: So mangled that the failsafe in place of MALAT1 might not work. I see. Take MALAT1 away from a tumor, and something might happen.

BS: Something dramatic.

CBSNY: “A possible breakthrough tonight in the war on Breast cancer…” CG: “It was a eureka moment when a new drug he and colleagues invented, chewed up and destroyed aggressive metastic breast cancer cells.” DS: “The effect was so dramatic that it was not something I could have actually predicted…”

AA: That was David talking to Carolyn Gusoff of CBS2 New York just last year – and his words… they’re not the kind that scientists say lightly. The effect REALLY was dramatic. So much so, that David has microscopy photos of the experiment framed on his desk.

(in interview) AA: so, I’m looking at this picture that’s right behind you. So that kind of captures the difference that you saw between– So can you describe that a little bit, like what it looks like? What you saw that was so different about the chamber without MALAT 1?

DS: When we looked at the tumors in this mouse model that had MALAT 1, the tumors were very aggressive tumors which means that the tumor was just filled with cancer cells.

BS: I think the best way to describe this is to imagine a white sponge, except… there are LOTS of wide holes in this sponge and each of them is PACKED full of this pink… stuff.

AA: Those are the cancer cells. The pink stuff.

DS: When we got rid of MALAT 1, the tumor totally changed. A lot of the cancer cells died and were released and the tumor changed its whole gene expression pattern and it started to form these cystic structures which were formed because cells died, leaving these cysts.

BS: Interestingly, these large cavities, once rife with aggressive pink cancer cells, they’re now full of something much more benign: Milk.

DS: these cysts are filled with liquid – milk proteins and so what does that mean? If you think about it, this is a tumor in a mammary gland and at a particular stage a mammary gland can produce milk. What we’ve done is by taking away MALAT 1 we’ve changed that tumor from being this aggressive tumor, to …

AA: To one that has switched its focus to milk production. You can see these images for yourself at our LabDish blog to really feel that “wow factor” for yourself. And David and his colleague think it’s safe to assume that if they turn off MALAT1 in tumors in other parts of the body, the cancer cells will be replaced with other types on harmless proteins.

BS: The coolest thing about all of this is that MALAT1 is just one of over 17,000 known non-coding RNAs. Few of these are as prevalent as MALAT1, and even fewer are seemingly as crucial, but there is an awful lot about non-coding RNAs that we still don’t know.

AA: And that 17,000 is just the ones recorded so far. (pause) According to David, by targeting MALAT1 and parts of the genome like it, experts might be able to open up new avenues for personalized treatment options in cancer and possibly other illnesses.

DS: The long-term goal of this over the next ten years, let’s say, is to develop a precision medicine based approach whereby we could get a small piece of the patient’s tumor. We could put it through a battery of tests… and screen them for these non-coding RNAs and identify which patients would benefit most from knocking down these three RNAs versus another three. That’s kind of what we hope to do because every patient’s tumor will be different.

BS: Since David’s work has taken off, MALAT1 has really become a poster child for the importance of what was once thought of as “junk DNA.” And according to Tom Gingeras, the opinion of the scientific community is changing too.

TG: Most of the scientific community, at least I come in contact with, have an appreciation for the fact that these regions we thought were relatively inactive, that is to say, nonfunctional, probably contain some proportion of things which are of biological note. There’s an argument about how much that is, and then there’s an argument exactly how important. But, there is, I think, a general appreciation that it’s not something we just slide under the carpet.

AA: So… that’s it! While research into the non-coding part of the genome is just getting started, this is where our story is going to have to stop.

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Episode 8: Dark matter of the genome, part 1

Most of the genome is not genes, but another form of genetic information that has come to be known as the genome’s “dark matter.” In this episode, we explore how studying this unfamiliar territory could help scientists understand diseases such as ALS.

BS: Welcome to season two of Base Pairs! We took a little break for the holidays, but we’re back with a two-part series for you all.

AA: And we need two episodes for this because—well, there’s a solid 98 percent of the genome that we haven’t even mentioned yet. And that’s what we want to tell you about.

BS: If you’re thinking, “That makes sense—there are thousands of genes, so of course they haven’t covered most of them yet,” you’re right. But that’s not what we mean.

AA: We’re talking about the part of the genome that’s not made up of genes at all: The “dark matter” of the genome. Because scientists are realizing that this strange, mostly uncharted genomic territory within all of our cells may lead us to new insights and possibly treatments for devastating diseases like Alzheimer’s, breast cancer, and Lou Gehrig’s disease—that’s the one we’re going focus on today. You may also know it as ALS.

BS: But we should back up a little—back to when scientists spelled out, or sequenced, the full human genome for the first time, an effort known as the Human Genome Project. They expected to find lots and lots of genes – the lowest estimates were around 100,000. Instead, what they found was a measly twenty thousand or so. And lots of what appeared to be genetic junk. Some scientists actually called it that, and kind of dismissed it.

AA: But they actually just didn’t understand what they were looking at.

MH: I think, with the sequencing and assembly of the human genome, we really changed our idea of what genes are, what we’re made of, and all of the things out there that we had no idea about—how little we actually knew about something we thought we knew a good deal about.

BS: That’s CSHL assistant professor Molly Hammell, and like other genome scientists, she no longer thinks about this mysterious majority of the genome as junk. Actually, a lot of scientists really object to the term “junk DNA” now.

AA: I can see why. In labs like Molly’s, the non-gene parts of the genome—which, again, make up about 98 percent of the genome—those are the focus, not some “junk” that gets in the way. She and other scientists have come to prefer looking at it as the “dark matter of the genome.” I talked to Molly to learn more about why that is.

BS: And she should know, after all, since before she began studying the genome, she worked in the field from which biologists borrowed the term “dark matter”: astrophysics.

MH: I used to go a couple of times a year up to a telescope, and I would be alone on a mountaintop, sleeping during the day, staying up all night, taking pictures of the sky.

AA: At first, when you hear Molly talk about what she studied as an astrophysicist, it sounds about as far away as you can get from genome biology.

MH: So I spent my nights on the mountaintop at the telescope, looking for the oldest clusters of galaxies, trying to figure out how they formed and if they could tell us how the universe was going to end—whether it was going to be this big bang where everything would come back to a point again or whether it would just expand forever into some cold dark world. And dark matter has a big role in that, in determining whether the universe is going to come back again or whether it’s going to expand forever.

BS: Wow, yeah, the scale of what she was thinking about as an astrophysicist is so big, but the entire genome is contained within each tiny cell in our body.

AA: Exactly. But when Molly starts talking about the discovery of dark matter, you can begin to see the analogy to her current work in biology.

MH: At the time when dark matter and now dark energy where discovered, we thought we had a good understanding of what the universe was made of, what our role in it was, and, you know, what the basic constituents of the universe were, right. And then these discoveries came about, showing us that not only were there these—all of these different types of particles that we had no idea about but also that they actually constitute more of our universe than the part we did know about.

BS: Ah, so, kind of like the way we look at the genome nowadays.

AA: Molly finished her Ph.D. in 2003—the same year that the Human Genome Project was completed. And as she was getting her professional scientific career started as an astrophysicist, biologists were learning all of this shocking stuff about the human genome

MH: What we figured out was that most of the genome is actually not genes—not in the way we think about them. In fact, only 2 percent of the genome was genes and 98 percent of this was this other stuff, and we didn’t know what it did, if it exerted its influence on the genes that we have, and this was really similar. And I found this idea fascinating.

BS: And that was it? Then she just decided to leave that telescope on a mountaintop for a microscope at a lab bench? How many biologists do we know who have done research using the Hubble Space Telescope?!

AA: Yeah, pretty amazing.

BS: How was she able to make such a huge leap?

AA: Well, the dark matters of universe and of the genome have something else in common, too. Scientists can use a lot of the same mathematics to analyze data about them.

BS: I guess that makes sense when you think about how there are billions of stars in a galaxy, and billions of base pairs in a genome. Looking for patterns in such huge datasets like that is a skill that doesn’t change very much even when you switch from galaxies to genomes.

AA: Yeah, that’s a good way to think about it. Now, Molly’s research is focused on a particular kind of genomic dark matter known as transposons. In the human genome, most transposons are the remains of ancient viruses—they’re fossil viruses, essentially.

MH: So a transposon itself is very, very similar to, like, a viral sequence. So these viruses, they come in, they infect the cell, some of them actually insert themselves into our genome in order to take over the cell and start using it for the purpose of the virus. — So half our genomes—fifty percent—are these transposon sequences

BS: Fifty percent?! We’re half virus graveyard?

AA: Yes, fifty percent of our genome is basically an ancient graveyard for viruses and other transposons, millions of them. They’ve inserted themselves into the genomes of our ancestors, gotten passed on from generation to generation, and most of them are truly dead after all of this time—but there are a few zombies out there.

MH: 99 percent, almost all of them, are nonfunctional, because they’ve accumulated mutations or for some other reason they don’t work anymore, right? But there’s one percent that are still capable of being active and doing damage. And because that one percent is one percent of millions, it’s actually thousands of these things.

BS: Aren’t these the things that Barbara McClintock discovered? Back in the 1940s. I’ve been here at the Laboratory long enough now to know that about transposons.

AA: She did discover transposons, and so much more that we won’t have time to get into today. And she made the Nobel Prize-winning discovery of transposons during the 50 years she spent here at Cold Spring Harbor Laboratory, so she’s a particularly big name around campus. Part of what made this discovery so remarkable is that back when she was starting out in biology, next to nothing was known about the human genome.

BS: What’s next to nothing?

AA: I’ll let Barbara give you an idea. For reference, she was born in 1902.

BM: Well between, say 1875 and 1900, there was a burst, one of those wonderful periods in biology when so much was learned. We learned about the nucleus. I say we because I just am so enthused about what—I just feel that I’m in on it! We discovered chromosomes. We discovered how the chromosomes divided. We discovered the numbers of chromosomes. We discovered what happened with the chromosomes to make the gametes. We knew what happened when fertilization occurred.

BS: So this is really the basic, fundamental stuff in biology—what kids learn about in high school or maybe even middle school biology now.

AA: Pretty much. No one was even certain that genes were contained within chromosomes until McClintock proved it more than thirty years later. There was a lot she didn’t know, but she was incredibly astute in her observations of the corn plants that she bred. She was still pretty modest about this discovery, though. Here’s what she said in an essay for the Nobel Prize committee. She wrote, “I doubt if this could have been anticipated before the 1944 experiment. It had to be discovered accidentally.”

BS: What did she mean by that? I’ve seen the corn with all of the colorful, streaky kernels in a library exhibit here. I know that had something to do with it…

AA: Yes! We’ll put a photo of this corn cob up on our LabDish blog, but say a little more about what you remember that corn looking like.

BS: There are some kernels that are a dark bluish color, and some that are more of a red or a burgundy, and some that are more of a normal light yellow color. But then, some of those yellow kernels have these blue streaky splotches, and some have red ones.

AA: So those streaks and splotches are caused by transposons, which are also known as “jumping genes.” Even though they’re not exactly genes, it’s helpful to think of them this way. And I should mention that most of the transposons in corn and other plants didn’t come from viruses. They’re a bit different from human transposons in that way, but the important part is that transposons do this “jumping” thing, whether they’re in plants or in people.

BS: Ok, just to recap a little, most of the transposons in people are basically these fossils of viruses. They’re viruses that came along thousands or even millions of years ago, infected our ancestors by inserting their own viral genome into the human genome, and 99 percent basically died there in the human genome…

AA: …which leaves one percent of transposons that still have a little bit of life in them. Those are the jumping genes—the “zombies” we talked about earlier.

MH: One of the things that they can do is that they can cut themselves out of the particular piece of the genome they inserted into, and then insert themselves somewhere else. And if they do, they’ll probably break the gene next door to wherever they inserted, right?

AA: In the case of McClintock’s corn kernels, transposons were jumping around and “breaking” the genes for the colorful pigments that make the kernels look red or blue. By “breaking,” I mean interrupting and disturbing their function. Since the transposons are breaking those genes kind of haphazardly, there are patches and streaks where the genes are left intact—they’re still able to produce the red or blue pigment. That’s the only way that McClintock could think of what would explain these bizarre patterns.

BS: So McClintock discovered this whole phenomenon of transposons because she was trying to explain this weird coloration in corn.

AA: Right. And this where the connection to diseases like ALS comes in. Basically, the idea is: What if some of the symptoms of ALS are caused by transposons that have been jumping around and breaking important genes? Molly started to really consider this idea after talking with a CSHL colleague named Josh Dubnau, who has recently moved to Stony Brook University. Josh was studying a protein called TDP-43.

MH: The thing about this protein was that we knew that if it wasn’t functional, that if this protein wasn’t working properly, that it actually causes specific a neurodegenerative disease called ALS, right? So one of the things that had happened is that Josh got a hint that TDP-43 might actually be binding to and regulating transposons.

BS: Wait, what is TDP-43 doing to transposons?

AA: It’s fighting the zombies. That dangerous one percent of transposons—the ones that are STILL able to jump around the genome—need to be kept under control. Our bodies actually devote a lot of resources to preventing a kind of zombie apocalypse from happening in our cells. And TDP-43 might be part of that effort.

MH: We think it’s possible that when it’s now not regulating these transposon sequences, those things could be escaping and wreaking havoc in our genomes. We started a collaboration together to look and see if this could be possible—that this ALS-related protein might also be moonlighting in regulating transposons, and that possibly that could be related to the disease.

BS: What causes ALS, anyway?

AA: That’s the thing. No one really knows yet exactly how ALS starts in the very beginning. I also asked this question when I was talking to Molly, and she told me about the bits and pieces scientists havelearned from studying patients with the disease.

MH: We do know that patients develop these clumps of TDP-43. We know that if TDP-43 doesn’t function in a mouse model of this disease (AA: those are mice are genetically engineered such they can’t produce working TDP-43) that the mice will get motor neuron defects and neurodegenerative disease just like the patients do. When the neurons start to lose function because of TDP-43 not doing its job, then the muscles themselves waste away because they don’t get used. It’s a really fast-progressing disease. The time from symptom onset to sort of the end stage of the disease is, in general, about two years. It’s really—it’s quite sad.

BS: What an awful disease. It takes away a person’s ability to walk, talk, breathe, swallow—anything that we voluntarily control with our muscles. I met someone who lost her mother to the disease over the summer. She was actually a grad student here, named Lisa Krug, and she worked with Molly and Josh to figure out whether transposons might play a role in this disease that took her mother. She wrote about her experiences and research for our LabDish blog.

AA: Molly told me that since she started doing this research, a lot of people she already knew started telling her about loved ones they had lost to ALS. Suddenly, it felt like ALS was everywhere—it was just hard to realize before because these people are prisoners of their bodies. Leaving the house is incredibly difficult, even with help, and so ALS patients become kind of invisible.

MH: We think of this as kind of rare but I think this is much more common than we realize and that people are finally really paying attention to ALS and realizing that we really need more research to understand it better so that we can have a hope of some kind of treatment for these patients, which right now, there’s nothing, there’s nothing that can be done—it’s awful.

BS: The Ice Bucket Challenge that happened a few years ago definitely helped a lot with awareness. Remember that?


AA: The Ice Bucket Challenge really did raise the profile of ALS. And, as silly as it seems, it helped research a lot, too. The campaign raised over $115 million for ALS research and development of new treatments, and may help support Molly’s future research. Like she said, right now there are no treatments for ALS. Researchers have already looked through the genes of ALS patients and so far have discovered no obvious avenues for treatment. That’s what makes it so exciting that this largely unknown world of transposons might be involved in ALS. There’s hope that this new territory will offer some solutions that would have otherwise seemed ridiculous—like treating ALS with antivirals.

BS: You mean the kinds of drugs that we’re given to treat, say, the flu?

AA: Yes. Because, remember, many transposons were once viruses. That dangerous one percent of transposons that can still jump around the genome, they’re acting as if they were still normal viruses.

MH: They haven’t figured out that they’re not really viruses any more, they’re now these pro-viral sequences that exist in our genome, but they’re still trying to act like they are, right? And if we can block them, if we can slow them down, and if that has an impact on patients’ lives, that would be fantastic. We have an idea about how this could lead to a potential therapy, in the sense that some of these transposon sequences are still similar enough to viral sequences that the antiviral drugs we have are actually effective in slowing them down and inhibiting their activity.

BS: That’s amazing! That would mean that if someone has non-functional TDP-43, leaving transposons to run amok as Molly and her team suspect, then it may still be possible to stop those transposons from causing ALS by simply giving them an antiviral drug.

AA: That’s the idea!

BS: How close is this idea to becoming a treatment that’s ready to give to patients?

AA: It’s a work in progress, for sure. This is still such a new idea, and so little is known about how transposons effect our health in general, much less in the specific context of ALS. Right now, Molly and her team are working on building up the knowledge needed to take that next step of developing a new treatment. One way that they’re doing this is by looking at the genetic sequences of people with and without ALS.

MH:  We get samples from patients with ALS disease and samples from patients who definitely don’t have any kind of neurodegenerative disease, and we’re usually just cross-comparing what’s different, right. Do we see the transposons coming up only in the patients and never in the controls?

BS: Ah, because if the transposons are only active in the ALS patients, that’s a clue that they could be involved in causing the disease.

AA: Right. Molly uses algorithms and other mathematical tricks from her astrophysics days to uncover those clues within vast datasets filled with genetic information. Once she finds a solid clue, the next step is to find out whether there’s any causation behind that correlation by doing experiments on cells very similar to neurons that can be grown in a dish. That’s where they are for the moment: uncovering little clues about how TDP-43 might work to keep transposons under control, and how symptoms of ALS emerge when that control system goes haywire.

BS: This really shows the importance of sharing knowledge between different scientific disciplines—that the mathematics that astrophysicists and computer scientists use can help biologists explore a new avenue for treatment of a deadly disease. And we know about transposons in the first place because of work done in plants!

AA: True! Barbara McClintock in particular always liked to remind people of the contributions that plant science has made to biology.

BM: The plants are just as significant as animals when it comes to genomes, and the operation of the genomes—the operation of the genome is just like that in animals. The plants really offer very special conditions for studying genetic phenomena.

AA: When McClintock first discovered transposons in 1944, relatively few took notice. She didn’t even get her Nobel Prize until nearly 40 years later, in 1983. But as knowledge and technology advanced, the importance of her discovery became more apparent. And that realization is still going on today, now that we can easily sequence the genome and the many transposons within it.

MH: You know, at the time when Barbara McClintock was working, she was really inferring this huge, vast existence of these transposon sequences without a picture of what the genome itself actually looked like, right. Now that we have the tools to look at these things, we can really go out and see how many human diseases could be potentially related to these things becoming unregulated and escaping. This is the tip of the iceberg.

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