The Most Controversial Idea in Biology

[00:00] If you want to know if someone really understands  evolution, just ask them this one weird question. Oh, gosh. Trash-

[00:13] Because of the chemicals? Yeah. Well, that's a different question  entirely. Do you think it objectively smells bad?

[00:25] How do you think it smells to flies? Animals love stinky things. Poop smells good to flies because  poop is full of nutrients.

[00:39] But it's also full of bacteria that  can be life-threatening to humans. if anyone ever thought it smelled good,

[00:51] they would probably get really sick,  die, and not pass on their genes. But survival of the fittest what? as being about the survival of  the fittest individual animal.

[01:06] Animal. Okay, so it's like an individual. I mean, individuals best adapted to their  environment have increased odds of survival, So it follows that each individual should do  everything it can to survive and reproduce.

[01:24] But if that's true, then how do you explain this? Worker bees will sting  predators to protect the hive, Female worker ants are sterile,

[01:40] but regardless, they work for the colony  for their entire lives until they die. Monkeys adopt orphans, wolves bring  meat to non-hunting members of the pack,

[01:52] and squirrels can let out alarm calls  to warn others about nearby predators. why do we observe so much altruism in nature?

[02:05] I think generally the species. But survival of the fittest species or  the fittest group also doesn't work.

[02:17] I mean, think about what you need  for natural selection to occur. You need something that replicates  itself many times over, creating copies, whereby some of those copies get eliminated and  some thrive to go on and create more copies.

[02:33] The problem with groups or species is that  they don’t typically make copies of themselves. other copies of groups to  see which groups win out.

[02:45] So if it's not survival of the fittest individual  and it's not survival of the fittest group, Well, to explain that, I want  to take you on a little journey, all the way back to the beginnings of the Earth.

[03:06] Well, not really nothing, but nothing interesting. This one might be a carbon dioxide  molecule, or it might be cyanide.

[03:19] but we do know that these  compounds are very simple. So for now, they'll just be  blobs floating around our void. In fact, much of what we'll encounter  along our journey here are just hypotheses.

[03:31] so keep that in mind. maybe from a ray of UV light  or a nearby hot source. This is the first major upgrade  to our void, excess energy,

[03:46] And most of the time, this  interaction leads to nothing, but sometimes these blobs can combine  into more complicated compounds.  Here's a simple simulated example,  where we only have four red blobs.

[04:01] Right now, they are all individual particles,  but each time step we move forward, let's say there's a 10% chance that all  four combine into one red mega-blob. For every time step it's alive,

[04:16] it has a 95% chance of falling apart  back into the four smaller blobs. If we add more of these red blobs into the mix,  you'll notice that they rarely ever come together. On average, a mega-blob only  exists around 10% of the time.

[04:31] But if we were to reduce the chances of  the mega-blobs dissolving to only 1%, the void would suddenly be filled with them. the law of stability.

[04:45] Unstable blobs fall apart and  vanish. Stable ones endure. maybe a couple of years per second,  maybe even a couple million.

[04:58] so they combine with others to  form more complex compounds. by pure chance,

[05:11] you get a compound that is more  stable than the blobs it's made of. This doesn't happen because the blobs  want to build more complex structures. It's just because these new configurations  happen to be more favorable in the environment.

[05:24] And now when these complicated  compounds become abundant enough, making our void increasingly complex. this causes an extremely unique shape to form,

[05:39] See, the blobs it's made of just happen to attract  similar blobs from the surrounding environment. and this purple blob always attracts yellow ones,

[05:53] until their counterparts suddenly snap  into position next to the original shape. Its green blobs attract red ones

[06:05] and yellow ones attract the purple until  another shape yet again snaps into position. What just happened fully  spontaneously is replication.

[06:19] This marks the birth of the first replicator. It might've been a single standalone molecule   There's a lot of debate on this today,

[06:35] How about this one here? Keep in mind it's still just a lifeless  molecule, one without any intent or purpose.

[06:48] Now, you might think that the chances for the  replicator to form were extremely unlikely, but in our void, where we have hundreds  of millions of years to play with, what might seem impossible to  us becomes virtually inevitable.

[07:00] And the thing is, the replicator  only has to arise once. it can take the simpler compounds available in the  environment to copy itself at a much faster pace. until it entirely fills our void.

[07:16] but there is a flaw in the process. one of its copies makes a mistake. Perhaps a stray ray of UV light hits  it during the replication process,

[07:31] or the replicator uses a building  block it wasn't supposed to. which is slightly different from its parent, and so its properties might  be slightly different too.

[07:44] For example, it might make the copy less stable. It could be beneficial, making  the copy better at replicating, not changing the replicator in any meaningful way.

[07:56] mutation. and what they do is they replicate themselves. and so our void turns into a battleground.

[08:13] So which replicator will win? What  kind of properties will the void favor? Well, let's try to simulate what happens. or need a place to run your own code

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[09:49] Thanks to Hostinger for sponsoring this part  of the video, and now back to our simulation. let's assign simplified traits to each of  the replicators, starting with the first one.

[10:01] since it's the only one that can form  spontaneously from smaller building blocks. so let's set the chance of  formation to 1% per time step.

[10:15] Just keep in mind we're just making these numbers  up. The simulation is purely illustrative. let's say it's governed by three key traits. the chance of it falling apart or  being destroyed with each time step.

[10:29] Second, a replication rate, Let's say 4%. the chance a copy comes out mutated.

[10:41] If it's 4%, roughly one in  25 copies will be a mutation. it will inherit the replication death  and mutation stats from its parent,

[10:53] Notice that we won't give any of these  secondary replicators a spawn rate. So if all of their copies die  out, they'll be gone for good.

[11:06] Our setup was inspired by his amazing  in-depth simulations on evolutionary biology. Okay, let's run it.

[11:18] and this box on the left will  show a slice of the void, You can see how the first replicator  appears and then immediately disappears,

[11:31] because it just happened to die  before it got the chance to replicate. The original replicator can be created from  smaller blobs, so it'll come back at some point. You can also see that it spawns some  mutations, but they're struggling to keep up.

[11:48] Eventually, though, superior mutations pop up  and start to replicate faster than the original. But you can see almost all of them are  growing exponentially, which is unrealistic. limited resources.

[12:03] We can simulate this effect by introducing a sort   This factor should depend on the total  number of replicators in the void, N,

[12:16] which will also divide with an  arbitrary crowding factor, C. C lets us define the maximum number of  replicators we'll allow into the void. Then once there are 10,000 replicators,

[12:29] the two terms cancel out and drive  the replication rate down to zero, meaning none of the replicators will be able to  make copies until the population drops again.  So let's see how this changes our simulation.

[12:41] after which it's quickly  taken over by its mutations, but this time, most of these mutation  populations start to decline.

[12:54] the lime one, After that, a few more mutations pop  up, even more powerful than the lime.

[13:06] occupying around 9,000 of  the 10,000 available spaces. It goes without saying that the environment  plays a massive role in which replicator wins.

[13:21] But let's look at the stats of the  replicator that came out on top this time. compared to the 17% average  across all populations.

[13:36] Its death rate is below average. And finally, it has a 1% mutation  rate, compared to the average of 3.73%.

[13:50] for any single species, If we rerun the simulation, you'll notice  the outcomes are always slightly different,

[14:04] but the winning species consistently have high  replication and low death and mutation rates. Instead of just tweaking these three stats, the replicators would have to mutate all  sorts of different ways to gain an advantage.

[14:19] For example, one replicator might mutate a  trait that lets it destroy other individuals and then use their building blocks  to make more copies of itself. but it's really just chemistry  that gets copied over and over  

[14:32] Naturally, a risk of offense would  likely favor mutations that result in defense. it form protective barriers from nearby materials,

[14:46] These barriers would also help protect the  fragile replicators from environmental damage, This marks an important threshold. determining the properties  of the molecules themselves.

[15:01] So by chance, the replicators inevitably mutate in  ways that build scaffolding around   They stumble upon ways of making  structures to propel themselves around.

[15:16] They even mix, exchange, and  steal traits from each other. Through billions of years of trial and error,  this scaffolding gets more and more complex,

[15:28] the replicator's interactions with  the void become exceedingly indirect. machines whose sole purpose is to  protect the replicators inside.

[15:42] These machines became such experts at surviving, They are the bacteria, Everything alive,

[15:56] was built as a survival  vessel for these replicators. Now we just call them genes.

[16:08] strands of DNA made from the sequences  of A, T, G, and C nucleotides. earliest replicators were actually  something closer to RNA molecules,

[16:22] this must have evolved into a more  stable system of storing information, They are the code that shapes our traits. We’re taught that these traits are  here solely to help ensure our survival

[16:35] But do we have this the wrong way around? Okay, yeah. These tiny replicators are still fighting the  same battle that started billions of years ago,

[16:51] The traits just become more convoluted. Replicators that produce traits poorly suited  to their environment tend to become less common, while those that produce advantageous traits  become more numerous in the population.

[17:04] it's fundamentally about the  survival of the fittest genes. They are the core unit of natural selection. Why not something smaller or something bigger?

[17:21] it needs to have three characteristics. Second, it needs to exhibit traits that affect  its interaction with the environment which,

[17:33] third, affect the probability of survival  and reproduction of the replicator. Something small like a single  nucleotide doesn't work, because, it doesn't exhibit a trait  that could be selected for.

[17:47] Well, each chromosome affects  potentially thousands of traits   sections of chromosomes get swapped around.

[17:59] So a chromosome doesn't stay together  as a cohesive replicating unit, But a gene is somewhere in the middle. It's a long enough stretch of DNA that  it can independently influence a trait,

[18:12] but it's also short and stable enough to be  faithfully copied over into future generations. This is why the gene is the  unit of natural selection. This perspective led to one of the most powerful  and controversial ways of seeing evolution,

[18:25] one popularized by Richard Dawkins  in his book The Selfish Gene. And as a response against the, then very popular, Dawkins argued that just about every trait,

[18:39] is a strategy that helps their  genes survive and replicate. even if they do so at the expense of others.

[18:52] we are survival machines, robot vehicles blindly programmed to preserve  the selfish molecules known as genes. Now, you might think this framework  isn't all that groundbreaking.

[19:06] They hesitate to jump into the water until  they are sure there are no seals around. So what kind of genes could help a  penguin survive in this environment?

[19:18] the penguin might stay back until  someone braver tests the water. and has a better chance to survive,  reproduce and pass on its ‘timid’ genes.

[19:32] Here, you can think about this either  as ‘the timid genes help the penguin’ Either way works. So is there any real benefit to viewing  things from the gene's perspective?

[19:44] Well, look at what happens when you use these  two frameworks to explain altruistic behavior, Take California ground squirrels for example. like a fox or a hawk,

[19:58] to warn other nearby squirrels, even  though this puts her survival at risk. The genes influencing this behavior  surely don’t help the squirrel. I think this is a bit more  clear if you think about the  

[20:12] fact that most living things reproduce sexually. So a squirrel will get half its DNA  from its mom and half from its dad. But also, any child that it has,

[20:26] it's also going to share half of its genes  with the child, but also any siblings. But then if you take a step out to an uncle or up  to a grandparent, then it's sharing one-quarter, All to say, you share a lot of  genes with your immediate family.

[20:43] And California ground squirrels, females  in particular, they live around family. So if a squirrel has a set of genes that  make her call out when it spots a predator, also carry those genes.

[20:57] let's say the squirrel attracts a predator  her way, and it ends up getting eaten. to any future offspring of that squirrel.

[21:10] But, if the warning call saved  at least 2 copies of those genes well then, in total, these  2 squirrels have a better chance of passing on the genes through their  offspring than the single squirrel did.

[21:23] From the gene's perspective,  this could be a good trade-off. only that as many copies as possible survive. This principle, that altruistically helping your  close relatives helps preserve your own genes,

[21:38] And the payoff behind any altruistic  gesture under kin selection depends heavily on how related you  are to the individuals you're helping, the smaller the chances that you will share  that particular gene with another individual.

[21:54] Male squirrels that don't live near relatives  almost never give out warning calls. Now, there is a big question this  gene-centric view still has to address.

[22:08] then why would sex ever evolve  as a means of replication, Most animals reproduce sexually. get to pass on all of their genes  through asexual reproduction?

[22:26] From a gene's perspective, this  seems like a much better deal. When it comes to sexual  reproduction, people like to say, "Okay. Well, it mixes up the genes.  It's like shuffling a deck of cards,

[22:38] and isn't that better for creating more  variation? And clearly, that's advantageous." Another way this has been explained  is if the genes that regulate sexual   reproduction benefit from replicating sexually,

[22:51] Even if it's a net negative to  all the other genes in the genome. So if it benefits them,  they'll keep pushing for it. So are there any problems with how The  Selfish Gene explains natural selection?

[23:06] Well, yes. I mean, it turns out the  framework comes with a lot of controversy. One of the biggest criticisms against The  Selfish Gene is that it leaves little to chance.

[23:18] It implies that every gene present in the genome  is there because it actively got selected for, But many genes are actually  invisible to natural selection, because they don't really exhibit  meaningful traits in the population.

[23:33] Imagine 20 blind cave fish, we’ll assume that their eye color traits  make no difference to their survival

[23:45] Now, to form the next generation, If you repeat this 20 times,  you get a 2nd generation. By chance alone, one color will probably  appear more often than the other.

[23:59] And if you repeat this  process over many generations, Not because it’s better, This shift in the frequency of gene  variants is called genetic drift.

[24:13] traits that aren't pruned  for by natural selection. But it doesn’t only apply to silent genes. there is a chance that genetic  drift overrides natural selection,

[24:27] and a less fit gene will spread  through the population just by chance. If we run our simulation enough times, sometimes the winning gene won’t be the one  with the traits that maximize its own survival.

[24:39] Here, you can see that the winning population  actually has a higher than average mutation rate, And the average mutation rate is  also higher than the starting value. about how much of evolution was  actually due to natural selection

[24:56] Another major criticism of  The Selfish Gene is about the   It seems to imply that genes have agency, like they know what they're doing  and they understand the consequences,

[25:11] just as portraying them as characters was a  way for us to make the story more engaging. They don't decide to replicate or  conspire to out-compete others.

[25:25] So what may look like intention is just simple chemistry that  happens to work well and propagates. But perhaps the most obvious and  easiest to understand criticism is  

[25:38] Genes are much more complicated than we thought. One gene can influence many traits, and  one trait can be influenced by many genes.

[25:51] There are genes that inhibit or activate others, the so-called non-coding DNA.

[26:03] Not to mention that the environment itself, also affects how different genes get expressed. So you might think that a single gene  would rarely have a large enough effect  

[26:20] but it doesn't matter how  convoluted the pathway is. it will be subject to some  amount of natural selection.

[26:34] And surely, the whole theory is a simplification,  but any theory or framework of nature is. And what we're covering in this video is an  even more simplified picture of that framework, but that doesn't take away the fact  that viewing the world through this  

[26:48] lens has an incredible power to help  us understand the process of evolution. It helps us understand why we see such a  range of different behaviors in our world those traits tend to cause the increasing  prevalence of the genes they are associated with.

[27:03] It's like the whole point  is figure out what's true. And this, to me, is the  baseline truth of evolution. is that we get to sort of  unpack and dig under the hood.

[27:21] And it's what I loved about  reading The Selfish Gene book, Previously, I'd always just probably  thought at the level of the individual, but it makes more sense to  think at the level of the gene.

[27:35] The feeling that you and every other  living organism is being driven by some   molecules deep in every cell  is fundamentally unsettling, and seems to remove agency from you as  an acting, thinking being in the world.

[27:52] But whether or not you agree with the fact that   we might be controlled by our genes  and we're simply their flesh robots, I think it's kind of unreasonable  and unrealistic to go through life  

[28:07] It doesn't really do you any good, So I think it's very beneficial to see  yourself as your own thing, as your own unit.

[28:25] I want to give a big shout-out to Joe Hanson  from BeSmart for helping us out with this video, and another shout-out to Primer for letting us  adapt his simulation on the first replicators. so please check them out.

[28:38] Thank you for watching.