Session 2: Theory Behind Evolution II

Transcript of Part 2: African Genomics: Human Evolution

00:00:07.10	Hi, I'm Sarah Tishkoff.
00:00:08.23	I'm a professor at the University of Pennsylvania
00:00:11.02	in the Departments of Biology and Genetics,
00:00:13.24	and today I'm gonna tell you about my research
00:00:15.18	on African integrative genomics,
00:00:17.29	and implications for human origins and disease.
00:00:21.17	So in Part 1, I'm gonna tell you a bit about
00:00:23.24	human evolutionary history,
00:00:25.24	and what the implications are of that
00:00:27.20	on the patterns of genomic variation
00:00:29.18	that we see in populations today.
00:00:34.05	So I want to start by talking about some of the
00:00:35.26	key challenges in human genomics research.
00:00:38.19	And the first one is to characterize
00:00:40.27	the immense array of genomic and phenotypic diversity
00:00:44.29	across ethnically diverse human populations.
00:00:48.14	Secondly, to understand what the evolutionary processes are
00:00:51.16	that are generating and maintaining that variation.
00:00:54.14	And third, to better understand how
00:00:56.04	gene-gene, gene-protein, and gene-environment interactions
00:00:58.28	contribute to phenotypic variability.
00:01:01.27	So first let's start with the evolutionary history
00:01:05.00	of the hominin lineage
00:01:06.26	that's leading to modern humans,
00:01:10.13	which begins around the time that we
00:01:12.03	diverged from our closest genetic relative
00:01:14.04	the Chimpanzee,
00:01:15.18	sometime between 5-7 million years ago.
00:01:18.14	So shown here are some of the fossils
00:01:20.07	from the different species
00:01:22.17	preceding anatomically modern humans.
00:01:25.16	In blue are shown fossils from the oldest lineages,
00:01:30.06	and in fact one of the oldest is Sahelanthropus,
00:01:34.10	which has been dated to at least 7 million years ago,
00:01:37.29	and there's some debate about whether it even
00:01:39.14	belongs on the hominid lineage
00:01:41.09	or if it actually preceded the Chimpanzee and human divergence.
00:01:45.26	After that, in green,
00:01:47.14	we see the Australopithecus genus.
00:01:50.14	In yellow, we see Paranthropus genus.
00:01:54.09	In orange, we have the genus Homo
00:01:56.24	and the species proceeding anatomically modern humans
00:02:01.13	is Homo erectus, dated to about 2 million years ago.
00:02:06.14	And then we have the origins of
00:02:08.15	Homo neanderthalensis
00:02:11.02	and of anatomically modern humans.
00:02:13.24	Neanderthals are thought to have originated
00:02:16.00	somewhere between 300,000-400,000 years ago,
00:02:19.12	and modern humans originated
00:02:20.27	approximately 200,000 years ago.
00:02:24.03	Here's one of the best examples
00:02:26.11	of Australopithecus afarensis.
00:02:29.07	This was a set of fossils that was
00:02:31.24	discovered in the 1970's by Johanson and Gray,
00:02:36.02	named Lucy,
00:02:38.00	and Lucy was about...
00:02:41.04	she lived about 3.2 million years ago.
00:02:43.29	She was very small, only about 3 feet tall,
00:02:46.13	she had a very small brain,
00:02:48.07	and she was bipedal.
00:02:49.27	And being bipedal, in fact,
00:02:51.07	is one of the characteristics of the hominin lineage.
00:02:57.12	And, interestingly,
00:02:59.17	there have been some fossilized footprints
00:03:01.21	identified in Tanzania,
00:03:03.24	and we can see from these that there
00:03:06.08	appears to have been a mother,
00:03:08.27	from the species Australopithecus afarensis,
00:03:12.08	and she was holding the hands of her child.
00:03:14.29	And they must have been walking
00:03:16.15	in ash from recent volcanic activity,
00:03:20.06	and then that ash hardened and preserved these footprints
00:03:23.06	so that we can see them today,
00:03:24.21	and we can clearly see that they were bipedal.
00:03:29.08	So the species preceding modern humans
00:03:31.28	is called Homo erectus.
00:03:33.24	Homo erectus evolved around 2 million years ago,
00:03:39.02	and then after the origin of Homo erectus in Africa,
00:03:42.24	Homo erectus spread across Eurasia
00:03:47.17	and, indeed, shown here are some of the
00:03:49.21	oldest fossils of Homo erectus,
00:03:52.18	dated to as early as 1.9 million years ago (MYA) in Indonesia.
00:04:00.15	And this species was very successful,
00:04:03.14	lasting to as recently as 25,000 years ago
00:04:06.17	in Southeast Asia.
00:04:09.08	A very interesting recent finding was
00:04:11.20	a set of fossils identified on the island of Flores,
00:04:14.26	which is within Indonesia,
00:04:17.25	and these fossils actually show some characteristics
00:04:21.22	that look very similar to Homo erectus,
00:04:24.19	and for that reason it was proposed that
00:04:27.09	this species may have directly evolved
00:04:30.23	from a Homo erectus ancestor
00:04:33.20	that arrived on that island
00:04:36.07	about 1 million years ago
00:04:37.28	and then evolved in isolation.
00:04:39.25	And two of the very unique features of this species
00:04:42.17	is that they were very short, so again,
00:04:46.01	about the same size as Lucy, around 3 feet tall,
00:04:50.15	and secondly, that they had tiny brains.
00:04:53.14	And there's been a lot of debate about
00:04:55.01	whether this is an adaptation or in fact a pathology,
00:04:58.09	and there's still a lot of research being done,
00:05:01.03	but what was clear is that there were multiple species
00:05:04.01	outside of Africa
00:05:05.29	within the past 2 million years.
00:05:08.20	So now let's move on to the origins of
00:05:10.15	Homo neanderthalensis and Homo sapiens.
00:05:13.12	There's some question about the species preceding
00:05:16.28	Neanderthal and Homo sapiens.
00:05:19.17	Some say that it was heidelbergensis,
00:05:22.04	but there's debate about that.
00:05:24.15	However, what is clear is that the Neanderthals species
00:05:28.10	arose somewhere within the past 300,000-400,000 years,
00:05:32.15	and Homo sapiens arose within the past 200,000 years.
00:05:38.04	And this is a fossil from Neanderthals,
00:05:40.29	we can see a few features such as
00:05:44.02	the double arched and very wide brow ridges,
00:05:47.08	a broad nose,
00:05:48.28	a very large brain size,
00:05:50.27	and a retromolar space,
00:05:52.21	and in fact these species were very robust.
00:05:55.16	The males would have been over 6 feet tall,
00:05:57.15	they had very big bones,
00:05:59.19	and they had rather big brains.
00:06:02.20	In fact, here are some reconstructions of Neanderthal.
00:06:06.28	We have the old reconstruction
00:06:09.03	and then the more recent one as well.
00:06:12.11	So, anatomically modern humans, Homo sapiens sapiens,
00:06:16.06	arose approximately 200,000 years ago.
00:06:19.02	In fact, here these red dots
00:06:21.09	are representing locations where fossils have been found
00:06:24.11	of anatomically modern humans,
00:06:26.27	and the oldest fossil is
00:06:28.22	dated to around 150,000-195,000 years ago,
00:06:32.19	in Southern Ethiopia.
00:06:36.23	We also see evidence of early modern human behavior
00:06:40.10	dated to 70,000 years ago,
00:06:42.11	or even as old as 120,000 years ago,
00:06:45.16	in caves in south Africa
00:06:47.13	and also some from east Africa as well.
00:06:51.05	So after modern humans arose in Africa within the past 200,000 years,
00:06:55.08	one or a few small groups of individuals
00:06:57.25	migrated across the rest of the globe
00:07:00.11	within the past 50,000-100,000 years.
00:07:03.23	Indeed, we think that Europeans...
00:07:07.15	there were no people in Europe, actually,
00:07:09.06	until about 40,000 years ago,
00:07:11.13	and then modern humans crossed the Bering Straits
00:07:14.15	and went into the Americas
00:07:16.28	within the past 30,000 years.
00:07:19.05	The earliest migration event was actually into Australo-Melanesia,
00:07:23.11	dated to about 40,000-60,000 years ago.
00:07:26.14	And then we have much more recent migration events,
00:07:29.03	such as into the Pacific Islands,
00:07:31.12	within the past few thousand years.
00:07:34.11	Now, interestingly,
00:07:36.16	when modern humans migrated out of Africa
00:07:39.08	within the past 50,000-100,000 years,
00:07:42.05	they would have run into Neanderthals,
00:07:44.10	in fact they overlapped in their distribution.
00:07:47.08	So shown here is the distribution of Neanderthals,
00:07:50.22	and the modern humans who lived at that time
00:07:52.25	were referred to as Cro-Magnon,
00:07:55.17	and in fact we did not see anatomically modern humans
00:07:59.09	in this region, in Europe, until about 40,000 years ago.
00:08:03.03	They would have been in the Middle East a little bit earlier,
00:08:05.23	but it appears they overlapped
00:08:08.18	for about at least 10,000 years with Neanderthals.
00:08:12.13	And as we'll discuss later,
00:08:13.27	there is some evidence that there could have been actual admixture
00:08:17.05	between Neanderthal and anatomically modern humans
00:08:20.18	during that time.
00:08:22.26	So now I want to discuss the evolutionary forces
00:08:25.27	that influence the patterns of genetic variation
00:08:28.08	that we see today.
00:08:30.04	And these include mutation,
00:08:32.14	genetic drift,
00:08:33.29	migration,
00:08:35.09	and natural selection.
00:08:37.16	So let's first introduce some terminology.
00:08:40.05	The gene pool refers to the set of all genomes
00:08:42.25	in a specified population,
00:08:44.10	and here we have an example from a population of warthogs.
00:08:47.22	So where we have at a single genetic locus
00:08:51.03	two alleles, big B or little b,
00:08:54.17	and here's an example of an individual
00:08:56.11	who is homozygous for the big B allele,
00:08:59.07	and an individual homozygous for the little b allele,
00:09:02.12	and here's an individual who is heterozygous
00:09:05.08	for big B and little b.
00:09:07.12	And together, the set of alleles in that population
00:09:10.19	represents the gene pool.
00:09:13.28	So when we are doing population genetics analyses,
00:09:16.25	we can't actually go out and look at every genotype
00:09:21.00	for every individual in the population,
00:09:23.14	that would be unfeasible.
00:09:25.13	So what we typically do is to
00:09:26.23	infer frequencies by estimating them
00:09:30.10	from a random sample.
00:09:32.25	So in population genetics
00:09:35.01	generation, each new individual
00:09:37.16	is viewed as drawing from a set of gametes
00:09:39.20	with alternative alleles,
00:09:41.08	so let's use an example here
00:09:43.01	in which we have a set of marbles in a bowl.
00:09:46.05	And initially, we have a distribution of
00:09:51.26	60 of the white marbles
00:09:54.13	relative to 40 of the green marbles,
00:09:56.27	and these, the white and the green,
00:09:58.08	are representing different alleles.
00:10:00.14	So let's say that we're gonna pick...
00:10:02.04	we're gonna reach into this bag
00:10:04.04	and we're gonna randomly draw out
00:10:06.09	another hundred of these marbles.
00:10:09.01	And now in the next generation
00:10:10.26	we have 80 of the white and we have 20 of the green.
00:10:15.02	We're gonna reach back in,
00:10:16.01	we're gonna grab another set of a hundred,
00:10:18.09	and now in the next generation
00:10:20.15	we have 100 of the white alleles and 0 of the green.
00:10:26.08	And this is a demonstration of
00:10:27.15	how we get changes in allele frequency over time.
00:10:31.25	Allele frequencies will also change over time
00:10:34.23	due to genetic drift,
00:10:36.21	which is defined as random fluctuations
00:10:39.01	of allele frequencies from generation to generation,
00:10:42.03	simply due to chance.
00:10:44.19	So as we see, sometimes things could happen,
00:10:47.16	like these bugs are getting squashed,
00:10:50.00	and that's gonna change, perhaps,
00:10:52.07	the allele frequency in the next generation.
00:10:55.19	Here's another example from some lady bugs,
00:10:58.23	and we can see that, perhaps,
00:11:01.03	in the next generation, just by chance,
00:11:03.10	we're gonna see more of these ladybugs
00:11:04.29	with the dark colors,
00:11:06.12	or we might see more that are with the medium colors and dots.
00:11:10.16	And the fact is that drift is just an inevitable fact of life.
00:11:16.15	I also want to define what we mean by neutral evolution.
00:11:20.08	So we define a selectively neutral allele
00:11:22.10	as one that does not affect reproductive fitness of individuals
00:11:25.20	who carry that allele,
00:11:27.20	so it's frequency in the population
00:11:29.25	changes by chance or genetic drift alone.
00:11:32.18	And here we have an example:
00:11:35.04	this is just a substitution
00:11:37.22	in the third position of the codon,
00:11:41.02	and when we have substitutions
00:11:44.09	of nucleotides in the third position,
00:11:46.20	very typically they result in a silent or synonymous change.
00:11:51.05	So here there's been a substitution,
00:11:53.00	but there's no change in the amino acid;
00:11:55.02	it remains as valine.
00:11:57.26	So the rate at which genetic drift occurs
00:12:00.01	is going to inversely proportional to the population size, N,
00:12:03.23	and it's going to be very fast in small populations.
00:12:06.27	And here's an example that we can look at
00:12:08.23	based on computer simulation.
00:12:11.20	So let's assume here that we're looking at a single locus
00:12:15.15	and it has two alleles
00:12:18.06	that are at 50% frequency each,
00:12:21.25	as we can see here.
00:12:23.22	We have a sample size of 25,
00:12:27.06	and we're going to do the simulation
00:12:29.03	over 80 generations.
00:12:31.14	Now, each of these lines here
00:12:34.03	represents a different simulation,
00:12:36.27	and what we can see is that
00:12:38.23	over time alleles are either going to
00:12:44.02	be lost from the population
00:12:46.08	or they're going to reach fixation,
00:12:48.17	which means that they go to 100% frequency.
00:12:52.10	And the rate at which this occurs
00:12:54.00	is going to depend on the sample size.
00:12:56.09	So in a small sample it's gonna be very rapid,
00:12:59.19	but in this example where we have a larger sample, now N=300,
00:13:03.26	you can see that it just takes more time.
00:13:05.23	There's not as much genetic drift occurring.
00:13:08.19	Now, the end result is gonna be the same,
00:13:10.15	it just takes more time.
00:13:14.09	The change in allele frequency also is going to depend
00:13:17.27	on the initial allele frequencies.
00:13:19.20	So in this particular case,
00:13:21.05	we've now changed the starting frequency:
00:13:23.20	it's not 50%, it's now 10%.
00:13:27.06	And you can see that there's much more
00:13:29.28	probability of loss of the allele in this case,
00:13:34.11	and here we have just one of the alleles reaching fixation.
00:13:42.08	So again, in this particular case,
00:13:44.05	about 1 out of 10 will eventually become fixed,
00:13:47.14	or reach 100% frequency.
00:13:51.09	Now here's an example from a large population.
00:13:54.01	It'll take longer for this to occur,
00:13:56.02	but the proportion of alleles are gonna be
00:13:58.12	roughly the same,
00:13:59.29	so again roughly 1 out of 10 will go to fixation,
00:14:03.06	it's just gonna take longer.
00:14:05.16	Other important terms in population genetics
00:14:07.26	are bottleneck and founder effects,
00:14:10.08	and this is because genetic drift
00:14:11.23	has a large effect on allele frequencies
00:14:14.10	when a population originates
00:14:16.05	via a small number of people from a larger population.
00:14:19.16	So here we have an example of a bottleneck,
00:14:22.10	and what a bottleneck means is that
00:14:24.01	there's been a decrease in population size
00:14:26.21	at some time in the past.
00:14:28.14	So you can think of it as a population crash.
00:14:31.10	And what happens when the population is very small,
00:14:34.28	you're going to have a higher rate of genetic drift,
00:14:37.12	and we can see here that these alleles,
00:14:39.20	which are represented by the different colors,
00:14:42.00	have shifted from what we're seeing
00:14:44.18	back at this earlier time.
00:14:46.25	Now we go through the bottleneck,
00:14:48.19	and now we're seeing predominantly
00:14:50.07	these white and black alleles.
00:14:53.09	Another example we can look at is a founder event,
00:14:57.20	which is sort of a special case of a bottleneck event.
00:15:00.11	And in this case it's where a population, a small population,
00:15:05.03	breaks off from the larger population,
00:15:07.25	and again there's going to be increased genetic drift
00:15:10.26	in this initially small population
00:15:13.12	and here, by chance,
00:15:15.05	we just happened to see more of these dark blue
00:15:18.12	and light blue alleles.
00:15:21.09	The pattern of variation that we see
00:15:22.23	in the human genome
00:15:24.09	is also dependent on the effective population size,
00:15:27.17	which we distinguish as capital N sub e.
00:15:32.10	And the definition of the effective population size
00:15:35.10	is the number of breeding individuals in a population.
00:15:38.19	So estimates of Ne
00:15:40.17	are most strongly influenced by population sizes
00:15:43.07	when they're at their smallest,
00:15:45.10	and it could take many generations
00:15:47.02	to recover from a bottleneck event.
00:15:49.11	So estimates of Ne in modern populations
00:15:51.21	reflect the size of the population
00:15:53.20	prior to population expansion.
00:15:56.22	Pretty consistently, studies of nuclear sequence diversity in humans
00:16:00.24	have estimated an effective population size
00:16:03.15	of about 10,000.
00:16:05.19	Now, by contrast, if we look at Chimpanzees,
00:16:08.29	the estimate is closer to 35,000.
00:16:12.14	And so what that means is that
00:16:14.01	humans have undergone a bottleneck
00:16:16.18	sometime during their evolutionary history.
00:16:19.22	So the pattern of genomic variation
00:16:21.25	that we see in modern populations today
00:16:24.00	is a reflection of our evolutionary and demographic history.
00:16:27.14	So how much do we differ?
00:16:29.17	Well, identical twins
00:16:31.27	have no differences at the nucleotide level.
00:16:35.06	If we compare unrelated humans,
00:16:36.29	we differ at about 1 out of 1,000 nucleotide sites.
00:16:41.12	And if we compare humans to our closest genetic relative, the Chimpanzee,
00:16:45.02	we differ at about 1 out of 100 sites.
00:16:47.29	So, as a whole, our species is very similar,
00:16:50.27	and that simply reflects our recent common ancestry
00:16:54.05	from Africa within the past 100,000 years.
00:16:57.06	But when you consider that there are
00:16:58.27	over 3 billion DNA bases in the genome,
00:17:02.02	that results in 3 million differences
00:17:04.16	between each pair of genomes,
00:17:06.05	more than enough to generate the diversity
00:17:08.29	that will make each of us unique.
00:17:12.02	Now I want to introduce a statistic
00:17:14.13	that we typically use to look at how much variation
00:17:17.06	there is among populations,
00:17:20.01	and this is referred to as an Fst statistic.
00:17:24.00	And it's simply looking at the proportion of genetic variation
00:17:27.03	that is within populations,
00:17:29.06	relative to that which is between populations.
00:17:32.18	Fst can be measured based upon heterozygosity,
00:17:37.20	and heterozygosity is simply a measure of genetic variation,
00:17:41.26	which is very simply calculated as
00:17:44.15	1 minus the sum of the allele frequencies squared.
00:17:49.09	And so once we calculate
00:17:51.26	the heterozygosity for each locus,
00:17:53.29	we can look at the average,
00:17:55.23	and we can look at the average within a subpopulation,
00:17:58.03	or in the total combined population.
00:18:00.29	Now, just as an example,
00:18:03.15	if we were to see here that
00:18:06.22	in the case of Fst = 1,
00:18:09.12	it means that there is no overlap at all in the allele frequencies.
00:18:13.15	So we can see that in population 1 they have all A's,
00:18:16.13	and in population 2 they have all B's.
00:18:19.15	And in the case of Fst = 0,
00:18:22.18	there is complete similarity,
00:18:26.08	so here we see exactly the same number
00:18:28.13	of A alleles and exactly the same number of B alleles.
00:18:32.01	And then here's an intermediate case
00:18:33.29	where we have about 0.11, 11%,
00:18:39.07	showing that there's just a small amount of differentiation
00:18:43.04	between these two populations.
00:18:46.09	So what do we see in humans?
00:18:47.29	Well, the average Fst between human populations
00:18:51.04	is about 15%,
00:18:53.15	and what that means is that the majority of genetic variation
00:18:56.04	is found within a population,
00:18:59.07	and only about 15% of the genetic diversity
00:19:02.08	differs between populations.
00:19:04.23	Again, this is reflecting our recent common ancestry in Africa,
00:19:09.00	within the past 50,000-100,000 years.
00:19:14.13	Now, interestingly,
00:19:16.09	if we were to do this calculation from Chimpanzee populations,
00:19:19.08	we see that the value is around 32%,
00:19:22.15	so there's actually a lot more differentiation
00:19:25.04	among Chimpanzee populations
00:19:27.07	than among human populations,
00:19:29.18	again reflecting our overall close genetic similarity to each other.
00:19:36.19	So I now want to talk about the
00:19:38.04	different sources of DNA that we use
00:19:40.04	to reconstruct human evolutionary history.
00:19:43.01	One source of DNA is
00:19:45.29	that which is present in the nuclear genome
00:19:48.06	that's located in the nucleus of the cell.
00:19:51.03	And there's another type of genome
00:19:53.20	which is present in the mitochondria of the cell,
00:19:56.15	and the mitochondria is the energy-producing organelle.
00:20:02.13	So what is the difference between these different genomes?
00:20:06.03	Well, the nuclear genome
00:20:08.09	consists of 22 autosomal pairs of chromosomes
00:20:12.26	and then the sex chromosomes,
00:20:14.15	XX for females and XY for males.
00:20:17.27	The nuclear genome is about 3.4 billion bases in size,
00:20:22.02	and it consists of about 20,000 coding genes.
00:20:25.10	It's inherited from both parents,
00:20:27.21	but it also undergoes extensive recombination each generation.
00:20:32.07	But, one of the reasons it's useful is that there's
00:20:34.18	so many different locations where we can study variation,
00:20:38.08	given that there are 3 billion nucleotides,
00:20:41.02	it's just a little bit more difficult to trace them back
00:20:43.29	to a single common ancestor.
00:20:46.20	By contrast, the mitochondria DNA genome
00:20:50.21	is very small, it's only about 16,000 nucleotides in size,
00:20:55.14	and it's circular,
00:20:57.17	and it's passed on only through the maternal lineage.
00:21:00.19	There's also no recombination
00:21:02.17	and it has a very high mutation rate.
00:21:05.00	All of these features make it very useful
00:21:07.01	for tracing evolutionary history.
00:21:09.27	So let me give you another example of what I'm referring to.
00:21:13.12	The mitochondrial DNA is inherited through the maternal lineage,
00:21:17.05	whereas the nuclear DNA is inherited from both parents.
00:21:22.08	So if we were to trace back from a present day individual,
00:21:25.26	they will have inherited their nuclear genome
00:21:28.20	from their parents,
00:21:30.17	their parents would have inherited from their set of parents,
00:21:33.28	and then their set of parents, and so on.
00:21:36.15	So we can trace it back to a large number of ancestors.
00:21:39.16	But by contrast, if we're tracing back mitochondrial DNA lineages,
00:21:44.00	we can see that they're only passed on
00:21:46.25	through the maternal lineage,
00:21:49.10	so they're essentially inherited from a single lineage.
00:21:52.03	We can trace them back to a single common female ancestor,
00:21:56.01	and that's why they're been very useful
00:21:57.29	for human evolutionary genetics studies.
00:22:00.21	So for example, if we were to consider
00:22:02.26	these dots to be mitochondrial DNA lineages,
00:22:06.20	and let's start at generation 11 at the bottom,
00:22:10.12	shown by the red dots,
00:22:12.06	and imagine those are different mitochondrial DNA sequences
00:22:15.00	from different individuals.
00:22:17.10	At some time in the past, these two individuals, for example,
00:22:22.06	coalesced back to a common ancestor,
00:22:24.26	and then this group coalesces back to a common ancestor here,
00:22:29.29	and ultimately they all coalesce back
00:22:32.20	to a single common ancestor.
00:22:35.03	Now, in the popular literature,
00:22:36.22	the single common ancestor for mitochondrial DNA
00:22:39.04	is often referred to as "mitochondrial Eve",
00:22:42.21	but one thing to remember is that
00:22:45.17	Eve was not alone, she lived within a population,
00:22:49.06	as we can see here by the other colors.
00:22:51.22	But those lineages just never made it
00:22:54.22	down to the present day.
00:22:57.25	So this is a phylogenetic tree
00:23:00.11	constructed by sequencing mitochondrial DNA
00:23:03.10	whole genome lineages
00:23:05.02	from ethnically diverse individuals.
00:23:07.19	So each individual actually represents
00:23:10.29	a branch on this tree,
00:23:13.02	and if two individuals are very closely related to each other,
00:23:16.05	they'll be very close to each other
00:23:19.01	in the tree.
00:23:21.03	So one of the first things you can see
00:23:22.19	using Chimpanzee as an outgroup
00:23:25.01	is that all modern human lineages
00:23:27.25	coalesce at about 170,000 years ago,
00:23:31.12	and so that corresponds very well with the
00:23:33.05	time of origin of anatomically modern humans.
00:23:36.23	So another thing that we can see is that
00:23:39.25	all of the oldest genetic lineages
00:23:42.26	are from African individuals.
00:23:45.22	We can also see that
00:23:48.12	the very oldest lineages
00:23:50.15	are from the San and the Mbuti pygmy hunter-gatherers,
00:23:54.28	and then the more recent lineages
00:23:57.13	are from non-African populations.
00:24:00.01	And that is a pattern that's very consistent
00:24:02.17	with the model of a recent African origin
00:24:05.12	of modern humans.
00:24:07.23	Now, another way that we can compare mitochondrial DNA sequences
00:24:11.21	is to simply count up the number of sites
00:24:14.04	at which they differ when we compare any pair of sequences.
00:24:17.23	And when we do this,
00:24:19.09	we observe that
00:24:22.11	any two African lineages will differ from each other
00:24:25.03	at many more sites than any two non-African lineages.
00:24:29.06	And again, that means that there has been more time
00:24:32.02	for variation to accumulate in Africa,
00:24:34.16	and is consistent with an African origin
00:24:37.08	of modern humans.
00:24:39.20	When we sequence the mitochondrial DNA lineages,
00:24:42.21	we can classify them as haplotypes,
00:24:45.10	and those haplotypes belong to
00:24:47.16	larger subsets of haplogroups.
00:24:50.01	You can think of a haplotype as simply
00:24:52.14	the arrangement of genetic variants along a chromosome,
00:24:55.19	or in the case of the mitochondrial DNA
00:24:57.22	there's just a single genome,
00:24:59.14	so it's really just the different nucleotide differences
00:25:02.27	amongst different mitochondrial DNA lineages.
00:25:06.24	And one of the first things that you can note is that
00:25:09.26	there are different haplogroups
00:25:11.29	in different regions of the world.
00:25:13.19	So here are some that seem to be pretty specific to Africa,
00:25:16.20	but are also present in some regions
00:25:18.20	where there may have been some gene flow
00:25:20.20	from Africa.
00:25:22.21	Then we have others that may be more common in Europe,
00:25:25.12	or in east Asia,
00:25:28.18	or in the Americas.
00:25:30.19	And for that reason,
00:25:32.11	mitochondrial DNA can be very useful for
00:25:34.11	tracing recent human migration events.
00:25:38.13	Now, by contrast,
00:25:40.02	the Y chromosome is also inherited with no recombination,
00:25:45.14	and so it can also be very useful for tracing back
00:25:48.01	through the male lineages.
00:25:50.16	And here is a phylogeny constructed from Y chromosome variation,
00:25:55.07	and as with the mitochondrial DNA,
00:25:58.08	what we see is that the oldest lineages
00:26:01.19	are specific to Africans,
00:26:04.02	and the more recent lineages
00:26:06.05	are found predominantly in Non-Africans,
00:26:08.13	although we do see some in Africans as well.
00:26:11.25	Again, this is consistent with the recent African origin of modern humans.
00:26:18.14	We can also look at Y chromosome haplogroups,
00:26:22.09	and one of the things that's a little bit different
00:26:24.04	is you can see that they're a bit more differentiated
00:26:26.16	between geographic regions.
00:26:29.03	So for example,
00:26:30.24	here we just see haplogroups that are in blue,
00:26:34.04	and we see very distinct haplogroups
00:26:36.20	in the Americas, shown in purple.
00:26:39.26	And one of the reasons for that may have to do with
00:26:43.08	sex-biased migration,
00:26:46.01	that you may have, for example,
00:26:47.16	one male traveling long distances.
00:26:50.06	And it may also have to do with patterns of mating structure.
00:26:54.20	So for example, in some populations or ethnic groups,
00:26:57.23	you may have one male who has many different wives,
00:27:01.05	and because of that the effective population size of the Y chromosome
00:27:07.01	is actually smaller than the mitochondrial DNA,
00:27:09.28	and we tend to get more genetic differentiation
00:27:12.27	around the world.
00:27:15.07	So now I want to talk about analyses of ancient DNA,
00:27:18.27	for example, in this case from Neanderthal,
00:27:22.12	and these are some images of scientists
00:27:25.20	working on a Neanderthal fossil.
00:27:29.10	And this type of analysis is very challenging
00:27:32.01	for a number of reasons.
00:27:33.25	One is that DNA which is that old,
00:27:38.04	on the order of say 30,000 years old
00:27:40.10	to even 100,000 years old,
00:27:42.06	is going to be highly degraded,
00:27:44.24	and if there's any contamination
00:27:46.25	with modern human DNA,
00:27:49.02	that is much more likely to amplify
00:27:51.19	than the old degraded DNA
00:27:54.01	from the archaic species,
00:27:56.21	so one has to be extremely careful when analyzing this DNA.
00:28:01.03	Now, more recently,
00:28:02.24	there was a pinky finger bone
00:28:05.07	identified in a cave in Siberia
00:28:07.22	from a region called Denisova,
00:28:10.11	so it's referred to as the Denisova
00:28:13.21	or Denisovan genome.
00:28:16.11	Here I'm presenting a phylogenetic tree
00:28:18.29	based on mitochondrial DNA variation
00:28:21.24	comparing modern humans, shown in blue here,
00:28:26.09	to Neanderthals shown in red,
00:28:29.01	and the Denisova individual shown in yellow.
00:28:32.23	And what we can see is that the
00:28:34.17	time to most recent common ancestry in humans,
00:28:37.08	as we've already discussed,
00:28:39.00	is about 200,000 years ago.
00:28:41.13	The time to most recent common ancestry
00:28:43.14	between humans and Neanderthals
00:28:46.01	is about 500,000 years ago,
00:28:48.13	for the mitochondrial DNA lineages.
00:28:51.03	And the time to most recent common ancestry
00:28:53.20	with the Denisova mitochondrial lineages
00:28:57.08	is about 1 million years ago.
00:29:00.05	So this is demonstrating a couple of things.
00:29:02.20	From the mitochondrial DNA perspective,
00:29:05.07	there's no evidence of any admixture
00:29:07.13	with anatomically modern humans.
00:29:10.02	The Neanderthal sequences are clearly
00:29:12.18	very distinct from modern humans.
00:29:14.28	It's also showing you that there was another species, Denisova,
00:29:18.15	that appears to be distinct from the Neanderthals,
00:29:21.07	and they diverge even earlier than Neanderthals
00:29:24.09	from modern humans.
00:29:26.21	So if we were to compare pairwise nucleotide diversity,
00:29:31.01	for example,
00:29:33.02	among anatomically modern humans shown in blue,
00:29:35.24	you can see that there's not a lot of diversity,
00:29:38.15	as expected considering that
00:29:40.13	we all have a very recent common ancestry.
00:29:43.04	If you compare the modern human mitochondrial genomes to Neanderthal,
00:29:48.03	you can see that they're more divergent,
00:29:50.07	as expected, given that the mitochondrial DNA lineage
00:29:54.04	diverged about 500,000 years ago.
00:29:57.02	If we compare to the
00:29:59.03	Denisovan mitochondrial DNA lineage,
00:30:01.10	they're even more divergent.
00:30:04.04	And then if we compare to Chimpanzee,
00:30:06.14	of course as expected,
00:30:08.11	given that they diverged at least 5 million years ago,
00:30:11.14	they are the most different in terms of sequence variation.
00:30:15.13	Now, several years ago
00:30:18.13	there was a draft sequence produced of
00:30:21.20	the Neanderthal genome using next-generation sequencing technology.
00:30:25.25	And this was an absolutely amazing feat,
00:30:28.17	but at the time they had very low coverage,
00:30:31.07	meaning that any particular region of the genome
00:30:33.19	was sequenced only about once or twice.
00:30:36.20	Now, more recently,
00:30:38.07	as the technology has improved,
00:30:40.05	they've gotten much better coverage of the Neanderthal sequence,
00:30:43.04	and quite recently they now have a 30-fold coverage,
00:30:46.22	meaning that on average most sites
00:30:49.03	will have sequenced 30 times.
00:30:51.22	And so you'll have a much better accuracy
00:30:54.23	when determining nucleotide variation.
00:31:01.07	So, when the Neanderthal genome
00:31:03.25	was compared to the human genome,
00:31:06.11	what you can do is first
00:31:08.10	look at how much divergence has occurred
00:31:11.02	since modern humans differentiated from Chimpanzees
00:31:15.10	within the past 6.5 million years.
00:31:18.12	And you can look at the divergence
00:31:20.24	that has occurred specifically in the human lineage
00:31:24.06	since they diverged from Neanderthal,
00:31:26.21	and they've only accumulated
00:31:29.07	about 8% of this total divergence.
00:31:34.08	And so the estimate of the time of population divergence
00:31:38.06	between humans and Neanderthals
00:31:40.15	is about 400,000 years ago.
00:31:43.09	Furthermore, it has been estimated that
00:31:45.24	there may have been a small amount of admixture
00:31:48.16	between Neanderthals and anatomically modern humans,
00:31:52.01	as shown by this red arrow here.
00:31:54.18	So the estimated amount of admixture is about 1-2%,
00:32:00.15	of the modern human genome,
00:32:02.17	may be of Neanderthal ancestry.
00:32:05.03	But what is of interest is to note that
00:32:07.24	this is only present in Non-Africans.
00:32:10.13	It is not present in African genomes.
00:32:13.05	And so what we can infer from that is
00:32:15.16	that this admixture event probably occurred
00:32:18.25	before modern humans spread across the globe.
00:32:22.01	It may have occurred, for example, in the Middle East,
00:32:24.28	and that's why we're seeing it present in all Non-Africans,
00:32:29.18	and we don't see it at all in Africans.
00:32:32.15	Now, more recently, there has been
00:32:34.22	whole genome sequencing of the Denisovan individual,
00:32:39.20	and what that has shown is that
00:32:42.09	the Denisovan species, or this individual,
00:32:45.15	appears to have diverged from modern day humans
00:32:48.13	around 800,000 years ago,
00:32:51.09	consistent with what we saw from the mitochondrial DNA.
00:32:55.21	They also observed low levels of heterozygosity in Denisova,
00:32:59.21	suggesting that they may have had
00:33:01.19	a small population size.
00:33:04.06	Additionally, when a phylogenetic tree
00:33:07.24	was constructed from the nuclear DNA variation,
00:33:11.13	they could see that the modern humans
00:33:15.11	tend to cluster together,
00:33:17.09	and as we expect they're divergent
00:33:19.01	from the Denisova and the Neanderthals.
00:33:21.29	The Neanderthals tend to cluster together,
00:33:24.06	so they're clearly divergent from Denisova.
00:33:27.03	But what's interesting is if you look at how much
00:33:31.01	variation there is amongst the modern humans,
00:33:34.11	as indicated by the length of these lineages,
00:33:38.06	and then you compare that to Neanderthals,
00:33:40.14	which have very short branches.
00:33:43.06	What that suggests is
00:33:44.28	that there was not a lot of genetic variation
00:33:47.09	amongst the Neanderthals,
00:33:49.23	and therefore they may have undergone a bottleneck,
00:33:52.11	so they might have undergone a population crash
00:33:54.20	at some point in the past.
00:33:57.07	So in summary,
00:33:59.04	what we can see is that
00:34:01.23	Homo erectus left Africa
00:34:04.05	within the past 2 million years,
00:34:06.28	and spread throughout Eurasia,
00:34:09.09	giving rise, possibly,
00:34:11.09	to species like Homo floresiensis,
00:34:14.17	and surviving until quite recently,
00:34:17.12	as recently as around 25,000 years ago.
00:34:20.28	Then we have other species like Neanderthal and Denisovans,
00:34:27.02	who may have originated from a different species,
00:34:30.07	such as heidelbergensis,
00:34:33.10	and they differentiated sometime
00:34:36.12	around 600,000 or 700,000 years ago in the case of Denisova,
00:34:39.29	or in Neanderthals around 400,000 years ago.
00:34:43.05	And then we have the modern human lineage,
00:34:46.11	Homo sapiens,
00:34:49.00	which arose around 200,000 years ago
00:34:51.07	and spread out of Africa.
00:34:53.21	And when they did so,
00:34:55.02	they would have encountered these other species,
00:34:57.09	and there may have then been low levels of gene flow.
00:35:01.20	And in fact for the case of the Denisovan genome,
00:35:03.23	it appears that the gene flow
00:35:05.26	was predominantly with populations from Oceania,
00:35:10.01	implying that this admixture
00:35:12.17	may have occurred in a different location and a different time.
00:35:16.00	Now, we still don't know exactly
00:35:18.05	how much admixture there may have been
00:35:20.12	between archaic species
00:35:22.23	and modern humans in Africa,
00:35:25.01	but there's some preliminary data suggesting that
00:35:27.10	this has occurred there as well.
00:35:29.14	The problem is that the fossils don't preserve as well in Africa,
00:35:32.19	so we don't have any DNA sequences
00:35:34.26	from archaic lineages in Africa at this point.
00:35:40.01	So in conclusion,
00:35:41.18	Africa has the most genetic diversity in the world.
00:35:44.15	Human dispersions out of Africa
00:35:46.11	populated the entire world,
00:35:48.15	and we are the last of a series of hominin dispersal events
00:35:51.14	out of Africa.