Manolis Kellis is a professor at MIT and head of the MIT Computational Biology Group. He is interested in understanding the human genome from a computational, evolutionary, biological, and other cross-disciplinary perspectives.

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EPISODE LINKS:
Manolis Website: http://web.mit.edu/manoli/
Manolis Twitter: https://twitter.com/manoliskellis
Manolis Wikipedia: https://en.wikipedia.org/wiki/Manolis_Kellis

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OUTLINE:
0:00 - Introduction
3:54 - Human genome
17:47 - Sources of knowledge
29:15 - Free will
33:26 - Simulation
35:17 - Biological and computing
50:10 - Genome-wide evolutionary signatures
56:54 - Evolution of COVID-19
1:02:59 - Are viruses intelligent?
1:12:08 - Humans vs viruses
1:19:39 - Engineered pandemics
1:23:23 - Immune system
1:33:22 - Placebo effect
1:35:39 - Human genome source code
1:44:40 - Mutation
1:51:46 - Deep learning
1:58:08 - Neuralink
2:07:07 - Language
2:15:19 - Meaning of life

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The following is a conversation with Manolis Kellis.

He's a professor at MIT and head of the MIT Computational Biology Group.

He's interested in understanding the human genome from a computational, evolutionary, biological, and other cross-disciplinary perspectives.

He has more big, impactful papers and awards than I can list, but most importantly, he's a kind, curious, brilliant human being and just someone I really enjoy talking to.

His passion for science and life in general is contagious.

The hours honestly flew by, and I'm sure we'll talk again on this podcast soon.

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And now, here's my conversation with Manolis Kellis.

What to you is the most beautiful aspect of the human genome?

The first answer is that the beauty of genomes transcends humanity.

Genomes in general are amazingly beautiful.

So In my view, the way that I like to introduce the human genome and the way that I like to introduce genomics to my class is by telling them, you know, we're not the inventors of the first digital computer.

We are the descendants of the first digital computer.

Basically, life is digital and that's absolutely beautiful about life.

The fact that at every replication step, you don't lose any information because that information is digital.

If it was analog, if it was just brought in concentrations, you'd lose it after a few generations.

And that's what the ancients didn't understand about inheritance.

The first person to understand digital inheritance was Mendel, of course.

And his theory, in fact, stayed in a bookshelf for like 50 years while Darwin was getting famous about natural selection.

But the missing component was this digital inheritance, the mechanism of evolution that Mendel had discovered.

So that aspect, in my view, is the most beautiful aspect, but it transcends all of life.

And Can you elaborate maybe the inheritance part?

What was the key thing that the ancients didn't understand?

the very theory of inheritance as discrete units, throughout the life of Mendel and well after his writing, people thought that his pea experiments were just a little fluke, that they were just a little exception that would normally not even apply to humans.

That basically what they saw is this continuum of eye color, this continuum of skin color, this continuum of hair color, this continuum of height.

And all of these continuums did not fit with the discrete type of inheritance that Mendel was describing.

But what's unique about genomics and what's unique about the genome is really that there are 2 copies and that you get a combination of these, but for every trait, there are dozens of contributing variables.

And it was only Ronald Fisher in the 20th century that basically recognized that even 5 Mendelian traits would add up to a continuum-like inheritance pattern.

And he wrote a series of papers that still are very relevant today about sort of this Mendelian inheritance of continuum-like traits.

And I think that was the missing step in inheritance.

So well before the discovery of the structure of DNA, which is again another amazingly beautiful aspect, the double helix, what I like to call the most noble molecule of our time, is, you know, holds within it the secret of that discrete inheritance, but the conceptualization of discrete, you know, elements is something that precedes that.

So even though it's discrete, when it materializes itself into actual traits that we see, it can be continuous, it can basically arbitrarily rich and complex.

So if you have 5 genes that contribute to human height, and there aren't 5, there's a thousand.

If there's only 5 genes and you inherit some combination of them and everyone makes you 2 inches taller or 2 inches shorter, it'll look like a continuous trait.

But instead of 5, there are thousands and every 1 of them contributes to less than 1 millimeter.

We change in height more during the day than each of these genetic variants contributes.

So by the evening, you're shorter than you were, you woke up with.

Isn't that weird then that we're not more different than we are?

Why are we all so similar if there's so much possibility to be different?

Yeah, so there are selective advantages to being medium.

If you're extremely tall or extremely short, you run into selective disadvantages.

So you have trouble breathing, you have trouble running, you have trouble sitting if you're too tall.

If you're too short, you might, I don't know, have other selective pressures acting against that.

If you look at natural history of human population, there's actually selection for height in Northern Europe and selection against height in Southern Europe.

So there might actually be advantages to actually being not super tall.

And if you look across the entire human population, you know, for many, many traits, there's a lot of push towards the middle.

Balancing selection is the usual term for selection that sort of seeks to not be extreme and to sort of have a combination of alleles that sort of keep recombining.

And if you look at mate selection, super, super tall people will not tend to sort of marry super, super tall people.

Very often you see these couples that are kind of compensating for each other, and the best predictor of the kid's age is very often just take the average of the 2 parents and then adjust for sex and boom, you get it.

Let me ask, you kind of took a step back to the genome outside of just humans, but is there something that you find beautiful about the human genome specifically?

So I think the genome, if more people understood the beauty of the human genome, there would be so many fewer wars, so much less anger in the world.

I mean, what's really beautiful about the human genome is really the variation that teaches us both about individuality and about similarity.

So any 2 people on the planet are 99.9% identical.

How can you fight with someone who's 99.9% identical to you, it's just counterintuitive.

And yet, any 2 siblings of the same parent differ in millions of locations.

So every 1 of them is basically 2 to the million unique from any pair of parents, let alone any 2 random parents on the planet.

So that's, I think, something that teaches us about sort of the nature of humanity in many ways, that every 1 of us is as unique as any star and way more unique in actually many ways.

Yeah, just like stars, most of it is just fusion reaction.

Yeah, you only have a few parameters to describe stars.

Mass, size, initial size, and stage of life.

Whereas for humans, it's thousands of parameters scattered across our genome.

So the other thing that makes humans unique, the other things that makes inheritance unique in humans is that most species inherit things vertically.

Basically, instinct is a huge part of their behavior.

The way that, you know, I mean, with my kids, we've been watching this nest of birds with 2 little eggs, you know, outside our window for the last few months, for the last few weeks as they've been growing.

And there's so much behavior that's hard-coded.

Like a bird that's born in Boston will be the same as a bird that's born in California.

So there's not as much inheritance of ideas, of customs.

A lot of it is hard-coded in their genome.

What's really beautiful about the human genome is that if you take a person from today and you place them back in ancient Egypt, or if you take a person from ancient Egypt and you place them here today, they will grow up to be completely normal.

This is the other type of inheritance in humans.

So on 1 hand, we have genetic inheritance, which is vertical, from your parents down.

On the other hand, we have horizontal inheritance, which is the ideas that are built up at every generation are horizontally transmitted.

And the huge amount of time that we spend in educating ourselves, a concept known as neoteny.

Neo for newborn and then teny for holding.

So if you look at humans, I mean the little birds that were eggs 2 weeks ago, and now 1 of them has already flown off, the other one's ready to fly off.

In 2 weeks, they're ready to just fend for themselves.

So that's so fascinating, this picture of a vertical and the horizontal.

When you talk about the horizontal, is it in the realm of ideas?

Okay, so it's the actual social interactions.

So basically the concept of neoteny is that you spend acquiring characteristics from your environment in an extremely malleable state of your brain and the wiring of your brain for a long period of your life.

You take any primate at 7 weeks and any human at 7 weeks, we lose the battle.

But at 18 years, you know, all better off.

Like we basically, our brain continues to develop in an extremely malleable form till very late.

This is what allows the person from Egypt to do extremely well now.

And the reason for that is that the wiring of our brain and the development of that wiring is actually delayed.

So, you know, the longer you delay that, the more opportunity you have to pass on knowledge, to pass on concepts, ideals, ideas, from the parents to the child.

And what's really absolutely beautiful about humans today is that that lateral transfer of ideas and culture is not just from uncles and aunts and teachers at school, but it's from Wikipedia and review articles on the web and thousands of journals that are sort of putting out information for free and podcasts and video casts and all of that stuff, where you can basically learn about any topic, pretty much everything that would be in any super advanced textbook in a matter of days, instead of having to go to the library of Alexandria and sail there to read 3 books and then sail for another few days to get to Athens and et cetera, et cetera, et cetera.

So the democratization of knowledge and the spread, the speed of spread of knowledge is what defines, I think, the human inheritance pattern.

Are you also a little bit afraid or are you more excited by the power of this kind of distributed spread of information.

So you put it very kindly that most people are kind of using the internet, and looking Wikipedia, reading articles, reading papers and so on, but if we're honest, most people online, especially when they're younger, probably looking at 5 second clips on TikTok or whatever the new social network is, are you, given this power of horizontal inheritance, are you optimistic or a little bit pessimistic about this new effect of the internet and democratization of knowledge on our, what would you call this?

This genome, like would you use the term genome by the way

Yeah, yeah, I think, you know, we use the genome to talk about DNA, but very often we say, you know, I mean, I'm Greek, so people ask me, hey, what's in the Greek genome?

And I'm like, well, yeah, what's in the Greek genome is both our genes and also our ideas and our ideals and our culture, So.

So I think that there's a beauty to the democratization of knowledge.

The fact that you can reach as many people as any other person on the planet, and it's not who you are, it's really your ideas that matter, is a beautiful aspect of the internet.

I think there's of course a danger of my ignorance is as important as your expertise.

The fact that with this democratization comes the abolishment of respecting expertise.

Just because you've spent 10,000 hours of your life studying, I don't know, human brain circuitry, Why should I trust you?

I'm just gonna make up my own theories and they'll be just as good as yours.

Is an attitude that sort of counteracts the beauty of the democratization.

And I think that within our educational system and within the upbringing of our children, we have to not only teach them knowledge, but we have to teach them the means to get to knowledge.

And that, you know, it's very similar to sort of you fish, you catch a fish for a man for 1 day, you fed them for 1 day, you teach them how to fish, you fed them for the rest of their life.

So instead of just gathering the knowledge they need for any 1 task, we can just tell them, all right, here's how you Google it.

Here's how to figure out what's real and what's not.

Here's how you form a basic opinion for yourself.

And I think that inquisitive nature is paramount to being able to sort through this huge wealth of knowledge.

So you need a basic educational foundation based on which you can then add on the sort of domain specific knowledge.

But that basic educational foundation should not just be knowledge, but it should also be epistemology, the way to acquire knowledge.

I'm not sure any of us know how to do that in this modern day.

1 of the big surprising thing to me about the coronavirus, for example, is that Twitter has been 1 of the best sources of information.

Basically, like building your own network of experts, as opposed to the traditional centralized expertise of the WHO and the CDC, or maybe any 1 particular respectable person at the top of a department or some kind of institution, you instead look at 10, 20, hundreds of people, some of whom are young kids that are incredibly good at aggregating data and plotting and visualizing that data.

I don't know how that matures into something stable.

You know, I don't know if you have ideas.

Like if you were to try to explain to your kids of where should you go to learn about coronavirus?

And I think the current pandemic and the speed at which the scientific community has moved in the current pandemic, I think exemplifies this horizontal transfer and the speed of horizontal transfer of information.

The fact that, you know, the genome was first sequenced in early January.

The first sample was obtained December 29, 2019, a week after the publication of the first genome sequence.

Moderna had already finalized its vaccine design and was moving to production.

I mean, This is phenomenal, the fact that we go from not knowing what the heck is killing people in Wuhan to, wow, it's SARS-CoV-2 and here's the set of genes, here's the genome, here's the sequence, here are the polymorphisms, et cetera, in the matter of weeks is phenomenal.

In that incredible pace of transfer of knowledge, there have been many mistakes.

So, you know, some of those mistakes may have been politically motivated, or other mistakes may have just been innocuous errors.

Others may have been misleading the public for the greater good, such as don't wear masks because we don't want the mask to run out.

I mean, that was very silly in my view and a very big mistake.

But the spread of knowledge from the scientific community was phenomenal.

And some people will point out to bogus articles that snuck in and made the front page.

Yeah, they did, but within 24 hours, they were debunked and went out of the front page.

And I think that's the beauty of science today.

The fact that it's not, oh, knowledge is fixed.

It's the ability to embrace that nothing is permanent when it comes to knowledge, that everything is the current best hypothesis and the current best model that best fits the current data and the willingness to be wrong.

The expectation that we're gonna be wrong and the celebration of success based on how long was I not proven wrong for rather than, wow, I was exactly right.

Because no 1 is gonna be exactly right with partial knowledge, but the arc towards perfection, I think is so much more important than how far you are in your first step.

And I think that's what sort of the current pandemic has taught us, the fact that, yeah, no, of course, we're gonna make mistakes, but at least we're gonna learn from those mistakes and become better and learn better and spread information better.

So if I were to answer the question of where would you go to learn about coronavirus?

Just open up a chapter on virology and how coronaviruses work.

Then some basic epidemiology and sort of how pandemics have worked in the past.

What are the basic principles surrounding these first wave, second wave?

Then understanding about growth, understanding about the R naught and R T at various time points, and then understanding the means of spread, how it spreads from person to person, then how does it get into your cells from when it gets into the cells, what are the paths that it takes?

What are the cell types that express the particular ACE2 receptor?

How is your immune system interacting with the virus?

And once your immune system launches a defense, how is that helping or actually hurting your health?

Why are the comorbidities and these risk factors even applying?

What makes obese people respond more or elderly people respond more to the virus while kids are completely, you know, you know, very often not even aware that they're spreading it.

So, you know, I think there's some basic questions that you would start from, and then, I'm sorry to say, but Wikipedia is pretty awesome.

it used to be a time maybe 5 years ago, I forget when, but people kind of made fun of Wikipedia for being an unreliable source.

I thought from the early days it was pretty reliable or better than a lot of the alternatives.

But at this point, it's kind of like a solid, accessible survey paper on every subject ever.

There's an ascertainment bias and a writing bias.

So I think this is related to sort of people saying, oh, so many nature papers are wrong.

And they're like, why would you publish in nature?

And just because more of them are being proven wrong than in other articles is actually evidence that they're actually better papers overall because they're being scrutinized at a rate much higher than any other journal.

So if you basically judge Wikipedia by not the initial content, but by the number of revisions, then of course it's gonna be the best source of knowledge eventually.

You then have to go into the review papers, et cetera, et cetera, et cetera.

But I mean, for most scientific topics, it's extremely superficial.

But it is quite authoritative because it is the place that everybody likes to criticize as being wrong.

On a lot of topics that I've studied a lot of, I find it, I don't know if superficial is the right word.

Because superficial kind of implies that it's not correct.

No, no, I don't mean any implication of it not being correct.

It's basically only scratching the surface.

For depth, you don't go to Wikipedia, you go to the review articles.

But it can be profound in the way that articles rarely, 1 of the frustrating things to me about like certain computer science, like in the machine learning world, articles, they don't as often take the bigger picture view.

You know, there's a kind of data set and you show that it works and you kind of show that here's an architectural thing that creates an improvement and so on and so forth, but you don't say, well, what does this mean for the nature of intelligence for future data sets we haven't even thought about, or if you were trying to implement this, like if we took this data set of 100,000 examples and scaled it to 100 billion examples, would this method, like look at the bigger picture, which is what a Wikipedia article would actually try to do, which is like, what does this mean in the context of the broad field of computer vision or something like that.

And- No, I agree with you completely, but it depends on the topic.

I mean, for some topics, there's been a huge amount of work.

Well, yeah, actually, the, which we'll talk on, genomics was not great.

Yeah, every time I criticize something, I should feel partly responsible.

Basically, if more people from my community went there and edited, it would not be shallow.

It's just that there's different modes of communication in different fields.

And in some fields, the experts have embraced Wikipedia.

And perhaps the reason is that if it was any better to start with, people would invest more time.

But if it's not great to start with, then you need a few initial pioneers who will basically go in and say, ah, enough, we're just gonna fix that.

And then I think it'll catch on much more.

So if it's okay, before we go on to genomics, can we linger a little bit longer on the beauty of the human genome?

What else do you find beautiful about the human genome?

So the last aspect of what makes the human genome unique, in addition to the similarity and the differences and the individuality, is that, so very early on, people would basically say, oh, you don't do that experiment in human, you have to learn about that in fly, or you have to learn about that in yeast first, or in mouse first, or in a primate first.

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Manolis Kellis: Human Genome and Evolutionary Dynamics | Lex Fridman Podcast #113