How Ancient DNA Revealed Accelerating Selection in the Bronze Age, and a New Model of Who the Neanderthals Were

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Overview

For decades, the mainstream view in human evolution held that natural selection has been largely quiet in our species for the past several hundred thousand years. Geneticist David Reich of Harvard, speaking with Dwarkesh Patel, argues that this view is wrong, at least for Europe and the Middle East over the last 18,000 years. A new preprint led by Ali Akbari, a staff scientist in Reich's lab, uses ancient DNA from about 16,000 individuals to show that selection has been pervasive. By their analysis it intensified sharply during the Bronze Age, between roughly 5,000 and 2,000 years ago. The conversation covers what the study found, how it found it, why some of the results run against common intuitions, and a speculative model Reich has been developing about the relationship between Neanderthals and modern humans.

37 min read

Why ancient DNA had not delivered on biology

Reich says the ancient DNA field, now more than 16 or 17 years old, started with two hopes. One was to learn about human history. The other was to learn how human biology changed over time. The first hope has been realized. The field has shown that people in a given place often do not descend from earlier inhabitants of that place, that population mixture is common, and that sex-biased processes are common, and many of these findings were not expected from archaeology. The biological hope, in Reich's account, has largely gone unfulfilled.

He attributes the gap mainly to sample size. A single genome is extremely informative about history because it is really a record of many people: two parents, four grandparents, eight great-grandparents, and eventually tens of thousands of ancestors. A single Neanderthal genome lets researchers position that individual precisely relative to others. But tracking how one genetic variant changes in frequency over time is a different problem. The variant might affect skin pigmentation, adult milk digestion, or a behavioral trait, and each individual supplies at most two samples of it, one from the mother and one from the father. Detecting shifts of a few percent or 10 percent requires very large numbers of people, and those numbers have only become available in the last few years.

Frequency change matters because it lets researchers use history as a natural experiment. People adopted agriculture, began living close to domesticated animals, and moved between cold and warm places or low and high ones. Each change should put pressure on a population to adapt. That pressure would show up as variants moving systematically in one direction, too consistently to be chance.

The old consensus: selection was quiescent

Reich lays out why the field believed selection had gone quiet. Europeans and East Asians descend from a common population that left Africa and the Middle East 40,000–50,000 years ago. That is roughly 1,500–2,000 generations, which should be plenty of time for a strongly favored mutation, say one for digesting alcohol or milk, to reach very high frequency in one group and not the other. Yet almost no variants show anything like a 100 percent frequency difference between the two groups, and the extremes are no greater than chance would predict. The inference was that the ancestral population reached some kind of optimum a few hundred thousand years ago. On that view, selection since then has mostly removed the bad mutations that constantly arise, with little directional selection pushing populations toward new adaptive set points.

The new study partitions the frequency changes across roughly 10 million variable positions in the genome. By its estimate, about 98 percent of the change comes from factors other than directional selection, overwhelmingly migration, population structure, and genetic drift. Adaptive signals are therefore a tiny fraction of the total and hard to detect. Reich's claim is that selection is nonetheless "rampant" in the genome.

Patel asked why population replacement shouldn't itself count as selection, since one group replacing another could partly reflect genetic differences. Reich granted that it could count, and "probably should count in some respects." A replacement might instead be driven by cultural factors such as technology, though some mutations might contribute. The study, however, looks for individual positions that behave differently from the rest of the genome. Periods of migration are statistically the worst times to detect selection, because every frequency fluctuates wildly. Reich gives the example of Europe 4,500 years ago. The steppe migration from north of the Black and Caspian Seas made 40–80 percent of the DNA derive from Yamnaya pastoralists, and nearly all frequencies shifted because those pastoralists had evolved elsewhere, not because of selection.

The best windows are the stretches of a few hundred years without major migration. The study treats Europe and the Middle East as "an archipelago of little populations in space and time": a pocket of people in Britain isolated for a few centuries, another in Hungary, another in Italy. In each pocket it asks whether a given variant rose slightly. As Reich puts it, "if all the arrows point in the same direction, we win."

How the method works

Patel moved the methodology discussion to the end of the episode, but it is useful to explain it here.

Reich describes years of disappointment before this study. In 2015, work with Iain Mathieson analyzed about 200 ancient Europeans and Middle Easterners. It compared them with modern Europeans and found 12 positions whose frequencies were too different to be chance. The team hoped more samples would bring many more discoveries. That did not happen. The largest comparable study, from a Copenhagen group in 2024, used much better data and found only 21 positions. Reich calls that result exciting but also disappointing, because it suggested the approach might be hitting an asymptote. Perhaps selection really was quiescent.

Akbari's study changed two things. The first was data. It reports new data from about 10,000 individuals, roughly a 14-fold increase, for a total of about 16,000 ancient people spread over 18,000 years, or 22,000 including modern people. All of it comes from Europe and the Middle East. Reich stresses that this region is not more important than others. For historical reasons, it simply accounts for perhaps 70–80 percent of the ancient DNA published so far. He calls comparative studies elsewhere "super important and interesting" but says this study is about this one region.

The second was a new statistical approach, adapted from methods for finding disease risk factors in medical studies. For each of the 10 million positions, the model predicts each person's genotype from their pattern of relatedness to all 22,000 others. That relatedness matrix absorbs the genome-wide effects of drift, bottlenecks, and admixture. The model then asks whether adding a single constant selection coefficient, selection pushing in the same direction everywhere and at all times, predicts the data better. Reich calls the constant-selection assumption "dumb," since selection surely varied, but says it is the simplest possible question. Patel summarized it back as a whole-genome relatedness term plus a position-specific selection term, and Reich agreed.

The result was many hundreds of positions changing too much and too consistently to be chance. Because the signals are densely packed and interfere with one another, the team counted only one per region. On that basis they found at least 479 independent positions at 99 percent confidence. In the methodology discussion Reich cited about 3,800 positions at more than 50 percent confidence. Earlier in the conversation he gave the figure as about 7,200 positions at 50 percent confidence, of which half, about 3,600, would be real, without knowing which ones. Previous scans had yielded at most a couple of dozen hits. Reich says the team assumed something was wrong and "spent the next couple of years trying to make the results go away, but they just kept getting stronger."

Validating the signals with medical genetics

The independent check, which Reich credits as "a brilliant idea that Ali had," uses genome-wide association studies. In the UK Biobank, about 500,000 people have been measured for hundreds of traits and fully sequenced. About 15 percent of the 10 million positions, roughly 1.5 million, are predictive of at least one trait. The team then raised the selection statistic threshold step by step: one, two, three, four, five. The selection statistic is roughly the number of standard deviations the selection estimate lies from zero. As the threshold rose, the share of positions affecting some trait climbed. Above about five, it reached 60–70 percent, around a five-fold enrichment, and then plateaued.

Reich interprets the plateau as the point where essentially all signals are real, and says computer simulations supported this reading. The plateau also yields calibrated probabilities. A threshold that is halfway to the plateau in enrichment corresponds to about 50 percent of hits being real, three-quarters of the way corresponds to 75 percent, and so on.

The main worry was background selection, the removal of newly arising harmful mutations. Background selection is concentrated in genes, and genes are also where trait associations concentrate, so a third factor could produce both signals. The team repeated the enrichment analysis within slices of the genome that were equally affected by background selection and got the same pattern. They also repeated it using only mutations of matched frequency, because detection power varies with frequency, and again saw the plateau above about five.

Reich adds that selection is not confined to the confident hits. At a 25 percent probability cutoff there are tens of thousands of candidates, many of them real. Other analyses suggest "the genome is vibrating with natural selection," with nearly every position correlated to some nearby position being dragged by selection. Even though selection accounts for only about 2 percent of frequency change, it is "tugging the positions in one direction or the other everywhere."

Which traits are under selection, and why behavior looks deceptively quiet

The team checked roughly 100 traits with GWAS data covering immunity, autoimmunity, behavior, metabolism, and more. The strongest selection signals were enriched about four- to five-fold for immune traits. They were also strongly enriched for metabolic traits such as obesity, fat distribution, and type 2 diabetes, with almost no detectable enrichment for behavioral or psychiatric traits.

Reich warns that concluding behavior was not selected would be "a wrong conclusion," and says the team can prove it. Immune traits tend to be governed by relatively few genes of strong effect, so the strongest individual signals capture them well. Behavioral traits are governed by very many genes of weak effect, below the power of single-position tests. Immune traits may still be the most selected category, but other analyses show clear selection on behavioral traits too. Across the more than 500 traits examined, about 100 complex traits showed significant systematic movement over this period.

Reich also reconciles the new findings with the old ones. Hundreds of positions are rising with selection coefficients of 1 percent or more, which means a doubling over a few dozen generations. So why aren't there many fixed differences between Europeans and East Asians? He says at least two factors explain it, and the one he dwells on is acceleration. When the team compared the last 5,000 years (the Bronze Age onward) with the previous 5,000, the concentration of selection on immune and metabolic traits had intensified. Selection has not run at a constant rate. It increased across the study period, and plausibly the whole period is elevated compared with earlier times.

The Bronze Age as an inflection point

Reich's explanation is a shock to the way of life. Nearly everyone in the dataset was a farmer or food producer. Farming began in the Middle East 11,000–12,000 years ago and spread across Europe after 8,500 years ago. The Bronze Age brought much higher population densities and people living ever closer to their animals, swapping diseases with them and with each other. He invokes evolutionary mismatch: variants that evolved in hunter-gatherers were placed into farmers, pastoralists, and urban dwellers. What the data may show, he offers as a hypothesis, is the genome reacting to being moved into an agricultural, high-density, Bronze Age environment only 10,000 years after its ancestors were hunter-gatherers.

Most signals fit constant selection, but a handful show reversals. Many of those fall between 5,000 and 2,000 years ago, during the Bronze and Iron Ages. The team built a public tool, the AGES browser, for inspecting trajectories at each position. Examples discussed include:

  • TYK2, a major risk variant for severe tuberculosis, which Reich calls the leading infectious killer today. It rose from around 8,000–6,000 years ago to perhaps 9–10 percent in this region, then fell sharply in the last 3,000 years, with clear evidence of selection in both directions. A possible explanation is that tuberculosis became endemic 2,000–3,000 years ago. That timing is potentially consistent with pathogen sequence data, and the variant may have protected against something else before then. Reich labels this speculative. Asked whether that something was another disease, he said only "maybe."
  • A multiple sclerosis risk variant, which increased before the Bronze Age and reversed 2,000–3,000 years ago. The reversal was very strong in Northern Europe and weak in Southern Europe.
  • Hemochromatosis, pathogenic iron buildup, which also reversed around this period.
  • Lactase persistence, which Patel noted fits the period, since cattle came to be used for milk and other secondary products.
  • Pigmentation. Europeans lightened over the last 10,000 years, most strongly between about 4,000 and 2,000 years ago and much less afterward. Reich calls this the strongest selection signal on a complex trait in the dataset.

Patel raised FADS1, which helps convert plant fatty acids into the long-chain fatty acids the body needs and seems relevant from the dawn of farming, yet showed especially strong selection 5,000–3,000 years ago. Reich noted that the FADS1/2 variant, a vegetarian-versus-meat-eating adaptation, was already identified as strongly selected in the 2015 work and is actually ancient, with copies present in archaic humans. Similarly, the B blood group rose to about 10 percent at A's expense, yet A and B both predate the common ancestor of humans and gibbons. Some variants have been oscillating over long periods.

Reich's overall reading is that the transition into the Bronze Age may have been "qualitatively greater" than the initial transition to growing plants. That surprised him, because "our cartoon picture is that the big transition is farming." The biological readout, he says, shows the genome reacting much more strongly to events of around 5,000 years ago.

Patel brought up Reich's 2014 work with Bhatia and colleagues on about 30,000 African Americans. That study found no genomic region deviating significantly from the average of roughly 80 percent West African ancestry, despite the enormous environmental upheaval of slavery. Reich suggests the period is simply too short. It spans perhaps five generations, so even 2 percent selection per generation compounds to only about 10 percent. The Bronze Age lasted 3,000 years, and compounding over that span produces detectable effects.

The genetic predictor of cognitive performance

The most provocative result concerns a polygenic score that predicts performance on intelligence tests in white British people today. That score is highly correlated with the genetic predictors of years of schooling and household wealth. Reich notes that these are "crazy traits in the past," since there were no tests, no schools, and no wealth in the modern sense. Still, the modern predictor moved systematically upward by about one standard deviation on the scale of modern variation over roughly 10,000 years. The standard deviation here refers to movement of the score within a population held constant in ancestry.

To find when this happened, the team slid a 2,000-year window through the data and reran the whole analysis in each window. Selection on this score peaked in the Bronze Age, between 5,000 and 2,000 years ago. Averaged over the stretch from about 4,000 to 2,000 years ago, it was about two standard deviations in strength. In the last 2,000 years there was essentially no evidence of selection at all. Reich admits his own bias would have been to expect the strongest signal in the most recent period, perhaps with industrialization.

Patel observed that one standard deviation would move the median person to about the 85th percentile. He then pointed out how large migration effects must be if selection is only 2 percent of frequency change. Reich agreed that the migration effects are huge. The predicted score for European hunter-gatherers sits about three standard deviations below the modern mean. Early farmers sit at the mean, and steppe pastoralists are lower. Those jumps reflect different set points in groups that evolved separately, not selection. The method's job is to detect a consistent push on top of those fluctuations.

Patel raised the "collective intelligence" hypothesis. It holds that growing specialization reduced the demand on individual minds, so the ancients were smarter and selection has since run downward. He also cited Joseph Henrich's point about how much knowledge hunter-gatherers had to carry. The data point the other way, with selection upward and strongest as complex societies emerged. Reich guessed that Henrich would not have made a strong prediction beforehand but might have expected hunter-gatherers to score high and complex societies to select against the trait. "It's the power of data. It's not what you expect."

What the "intelligence" predictor may really be measuring

Reich stresses that this score is confusing. The genetic predictor of years of schooling, which is measured better, is correlated with the age at which women have their first child, and controlling for that makes the schooling signal disappear. It also correlates with obesity, BMI, walking pace, and household wealth. A 2017 Icelandic study found an estimated 0.1 standard deviation decrease in the schooling predictor within a single century, which Reich calls an absolutely huge effect for so short a time. He corrected himself mid-conversation to stress that this was the schooling predictor, not intelligence.

His "hand-wavy" suggestion is that what is under selection might be some general trait, perhaps executive function or a propensity to defer gratification. Such a trait would push all these correlated outcomes together and be favored at some times and disfavored at others.

The team doubted the signal at first and tested it. They took effect sizes for years of schooling measured in Chinese people in China, a population essentially disconnected from Europeans over this period, and compared them with the European trajectories. The correlation came out at five to six standard deviations, as strong as when European effect sizes were used. Reich says they "could not see a way this could happen by chance" and became convinced that selection had favored the variants that today predict more years of schooling. Patel's restatement, that this rules out an artifact of how European GWAS were done, was confirmed as correct.

Why didn't evolution max out intelligence?

Patel pressed the obvious puzzle. If intelligence seems robustly useful, how could hunter-gatherers be three standard deviations lower on the predictor, and why was the trait not already maxed out? Reich answered by framing himself as no authority and his answers as speculative.

First, he suggested, modern society's intense valuation of test scores and schooling is historically unusual. The Hebrew and Christian Bible barely values intelligence. It prizes strength, courage, and religiosity. Homer and other religious texts prize beauty and other qualities. Patel noted the irony that the Old Testament was written exactly when selection on this predictor was apparently at its peak. He also suggested that test-style intelligence may not track the kind of practical competence Henrich emphasizes.

Second, Reich pointed to the shared genetic basis of obesity, schooling, walking pace, test performance, and wealth. One interpretation of the Icelandic decline is a toggle between reproductive strategies. One end is having many children and investing less in each, which may pay off in times of plenty such as 20th-century Iceland. The other is deferring reproduction, accumulating resources, and investing heavily in fewer children. He compared this to mammals versus fish that spawn huge numbers of offspring. The balance could swing back and forth with conditions.

Third, for schizophrenia and bipolar disorder, he speculated that subclinical versions such as anxiety, imagination, or neuroticism might have been advantageous in shamanistic or religious traditions that value visions. Patel mentioned Julian Jaynes's bicameral mind theory, and Reich said he doesn't know. He added that for these disorders, most risk mutations do appear disadvantageous, since they tend to be low-frequency and of small effect. His broad sense is that complex traits have not moved in one direction because both ends of the spectrum carry advantages and the effects are multidimensional.

Selection against body fat

The team also found selection of about one standard deviation, over 10,000 years, against the combination of variants raising risk for obesity, high BMI, fat mass, waist-to-hip ratio, and type 2 diabetes. Reich invokes the "thrifty gene" hypothesis. Once hunter-gatherers moved into farming with more constant food stores, building up fat reserves became less advantageous. He notes Europeans are relatively better protected genetically against type 2 diabetes than some populations, such as African Americans and Native Americans, that have perhaps not been exposed to agriculture as long.

Patel objected that the common story holds that hunter-gatherers had more stable diets and that farmers faced famines. Reich answered with timescale. He says he is no anthropologist, but hunters often gorge after a kill and then go days without meat. That is a boom-and-bust rhythm that fat storage helps with. Farmers may suffer a famine every three or five years, and their bones show more stress in some communities. But a fat store from the last meal won't carry anyone through a famine three years later, so selection on fat storage responds to a different tempo.

Standing variation, mutation supply, and why time matters more than population size

Patel asked whether the dominance of immune and other traits over intelligence means there is "more room at the top," a question he linked to AI systems trained purely for intelligence. Reich said there is more room at the top for many traits. Height or any complex trait could be pushed much further, though probably with strong trade-offs.

He argued that the human gene pool is like "the clay that's needed to make almost any trait." Setting every height-increasing variant to its tall form would produce someone "as tall as a tall building," though that will never happen. For polygenic traits the needed variation already exists, so a population can move to a new set point within hundreds or thousands of years. A few traits, like lactase persistence or sickle-cell protection, depend on a single key mutation that must first arise. In a population of 10,000 that might take dozens or hundreds of generations. With eight billion people and about 30 new mutations per person per generation, there are 240 billion new point mutations per generation against about three billion bases. By Reich's count, every possible mutation occurs about 100 times each generation.

Patel proposed that the Bronze Age mattered because populations finally got big enough, around 50 million by 3000 BC, for weakly favored variants to become visible to selection. Reich thought this unlikely. Once populations reach around a million, every possible mutation arises within a few generations, which was true well before the Bronze Age. Drift in a population of 1,000 moves frequencies by about one in 1,000 per generation, so only coefficients below 0.1 percent are swamped. The coefficients in this study are about half a percent or more and work fine even in populations of 1,000 or 10,000. Coefficients small enough to require huge populations, on the order of 1 in 10,000 or 1 in 100,000, would take hundreds of thousands or millions of years to act. Past a threshold, he agreed, time span rather than population size is the dominant factor, a point he says is "not widely understood."

No sweeps behind "behavioral modernity"

Patel raised a 2016 paper by Swapan Mallick and colleagues. It searched the genome for regions where nearly all living people share a common ancestor 100,000–200,000 years ago, the signature of a sweep during the period when art, bead necklaces, and faster tool innovation appear. They found nothing more recent than 400,000–500,000 years ago. Reich calls this "a crazy result." Biological adaptation in that period may have happened, but if so it was polygenic, with no single key change sweeping through everyone.

The population ancestral to West Africans, most East Africans, and all non-Africans lived 100,000–50,000 years ago. Groups such as Khoisan southern Africans and Central African rainforest hunter-gatherers carry substantial ancestry from lineages that diverged around 200,000 years ago. Reich emphasizes that "all of these groups today are able to go to college and do everything everybody else does." He says there is no evidence of a key mutation that some groups lack.

Why no farming before the Ice Age ended?

If the genetic ingredients were in place 50,000 years ago, Patel asked, why no farming until 11,000–12,000 years ago? Reich calls it "an outstanding mystery of human history." The descendants of that common ancestral population spread to the Americas, New Guinea, East Asia, Europe, and West Africa, and many independently or semi-independently developed farming, but only in the Holocene. Climate scientists and archaeologists tell him the Holocene is highly unusual on a two-million-year scale, not just warm but stable. Lake-bottom isotope records show far less fluctuation year to year, decade to decade, and century to century. He finds it hard to believe that we live in such a special time, "but my colleagues tell me it's true."

Patel found the climate explanation surprising given how different the farming environments were, maize in the New World and cereals in the Old. Reich agreed that it is very surprising and something most people simply accept. He described it as a "very long fuse": 40,000–60,000 years of delay after the common population split, or perhaps 300,000 years if the relevant capacities were already in place when Neanderthals and the deepest living lineages diverged.

Patel suggested that early farmers might have existed and vanished without leaving a trace. Reich said we would see their archaeology, and pointed to the Americas, where achievements like Teotihuacán, which he visited at 20 and found as impressive as ancient Egypt, were built without metal, draft animals, or wheels. Those builders separated from East Asians' ancestors at least 20,000 years ago and from West Eurasians' ancestors 40,000 years ago.

On timing more broadly, Reich said "this is actively what I'm thinking about all the time right now." He described a major cultural transformation 300,000–400,000 years ago: Levallois technology, prepared-core stone toolmaking. This is known as the Middle Stone Age in Africa and the Middle Paleolithic in Eurasia. It is shared by Neanderthals and modern humans but absent in East and South Asia, and it presumably involved a cognitive change. The later transition, 100,000–50,000 years ago, he considers less revolutionary. It is "not obvious," he says, that the behavioral and genetic toolkit was not already in place 200,000–300,000 years ago, possibly even in Neanderthals. "I just don't know."

The Neanderthal puzzle

Reich says he remains very confused about how archaic and modern humans relate. Genome-wide, Denisovans and Neanderthals are sisters, descending from a common population 500,000–600,000 years ago that split from modern humans' ancestors 700,000–800,000 years ago. There is now also a skull shown to be Denisovan. Yet Neanderthals and modern humans share much that Denisovans do not: Levallois technology, and closely related mitochondrial DNA and Y chromosomes. The standard explanation is that about 5 percent of Neanderthal DNA came from a modern-human-related interbreeding event 200,000–300,000 years ago. That event introduced mitochondrial DNA and a Y chromosome that then rose to 100 percent frequency.

Reich finds this "a crazy claim." He estimates the chance of both uniparental lineages fixing from a 5 percent contribution at maybe 5 percent times 5 percent. He says it has "accreted" into accepted belief. Still, the pattern appears to be real. At Sima de los Huesos in Spain, a site 300,000–400,000 years old, the nuclear genome looks mostly Neanderthal-like while the mitochondrial DNA and Y chromosome are Denisovan-like. It looks as if a modern-human-related population later displaced those lineages while leaving the rest of the genome.

Along the way, Reich noted that the divergence between Neanderthals and our lineage falls within human variation. The two copies of a chromosome a person inherits typically share a common ancestor one to two million years ago. So in many places in the genome a person is more closely related to a Neanderthal than to the other parent's copy, much as siblings share some genomic segments but not others.

Reich's whiteboard model: Neanderthals as "swamped" modern humans

After the recording ended, Reich sketched an alternative on a whiteboard, which Patel captured on a phone. Reich repeatedly said it is "probably wrong."

In this model, a population somewhere around the Caucasus, the Middle East, or Northeast Africa invents Middle Stone Age / Levallois technology 300,000–400,000 years ago. Reich places the earliest known use of the technique in places like Georgia or in East Africa. That population then expands outward. In Europe it meets local archaic humans. Simulations and studies of expanding mammals and birds show that even modest interbreeding at a moving wave front leads to massive introgression of local genes, so the pioneers end up mostly local by the time they cross the continent. The result would be a population roughly 95 percent archaic genetically but modern in culture, and that is what the 5 percent signal would reflect.

If the expanding group were matrilineal, with toolmaking transmitted from mother to child and outside males absorbed into the mothers' culture, it would retain its mitochondrial DNA. A patrilineal group would retain its Y chromosome. Reich notes that patrilineality or matrilineality is the rule rather than the exception in human communities, usually patrilineality. That explains one lineage but not both. The other would require natural selection or social selection. Reich pointed out that male reproductive success is highly variable in traditional societies and female mate choice matters. Children of archaic fathers might fare worse in competition for mates, and he recalled, hedging on his memory, that Central African rainforest hunter-gatherers treat boys and girls differently depending on which group each parent belongs to. When Patel pressed on why people carrying archaic mitochondrial DNA would not persist, Reich offered lower biological fitness or social discrimination, and called this "the weakest link in this argument."

The same expansion also went into Africa. Several studies of modern DNA, at least three and perhaps four or five that Reich knows of, find that modern humans descend from lineages that split more than a million years ago and came back together a few hundred thousand years ago. One such model gives roughly 80 percent early modern ancestry and 20 percent from an archaic African group about 1.5 million years diverged. In Reich's model the 80 percent comes from the Levallois-inventing population. In Africa it was only about 20 percent swamped rather than 95 percent, which he attributes to greater divergence. Incompatibilities rise steeply with separation, "probably as the square of the separation distance" because they involve pairs of interacting genes, so a lineage 1.2 million years removed would be near the edge of reproductive compatibility. By contrast, Khoisan and Bantu-speaking groups separated by nearly 200,000 years, such as those that mixed to form the Xhosa, show no problems. Europeans and West Africans, about 70,000 years apart, show none either, as the Bhatia study indicated.

Reich argues that a small percentage should not be dismissed. He compared it with Yamnaya ancestry. That ancestry was diluted as it moved through the Corded Ware, back across Central Asia, and through the Hindu Kush, and it is now at most 10–20 percent in India, with most people under 10 or 5 percent. Yet it acts as a "tracer dye" for Indo-European languages and shared culture. On this view, Neanderthals and people alive today would both derive from one revolutionary event, linked by three threads: a shared toolkit, shared mitochondrial and Y lineages, and the same timing of formation by mixture. That event is contemporaneous with the breakup of the deepest African lineages. It also coincides with the appearance of anatomically modern skeletons and recognizable Neanderthals. Reich notes this is also roughly the time depth at which fixed differences shared by all modern humans begin to appear. He raised the possibility that genetic changes arising in the source population might have been partly retained by selection even as it was swamped. After that, he says, modern humans made Levallois tools for about 200,000 years without being obviously more impressive than Neanderthals. The later quickening of behavior could be genetic or not.

The alternative, Patel noted, is that Neanderthals independently invented the same technology. Reich said that is not inconceivable, likening it to farming arising independently in multiple places, which did happen.

Epicycles, and what would make the model hard to accept

Reich compared the current standard model to Ptolemaic astronomy. The baseline, Neanderthals and Denisovans as sisters, gets patched with extra mixture events: modern humans into Neanderthals, a super-divergent lineage into Denisovans, and the improbable fixation of the uniparental lineages explained by invoking selection. He likened these patches to epicycles and said his model is "not as fantastic" as heliocentrism but "much simpler" and explains more. "To me, this is much more plausible than the model we currently write down. It's probably wrong, but it's much more plausible."

Patel asked what the analogue might be of Aristarchus's heliocentrism, which was rejected because it implied the stars were impossibly far away. What implausible implication does this model carry? Reich said nobody is currently thinking about the model. It requires assuming a linkage between cultural transformations in Africa and Eurasia at that time. It also requires combining two literatures that have never been joined, modern-DNA studies of African substructure and ancient-DNA studies of archaic–modern relationships. Put together, he says, their timings line up, which seems parsimonious to him. It also implies that different lineages were close enough genetically that once one group developed the technology, others could learn it.

Reich framed all of this against his own track record. When he helped analyze the Neanderthal genome, he believed non-Africans were a simple subset of African variation with no archaic interbreeding. The evidence for Neanderthal ancestry in non-Africans seemed like a mistake, and he spent years trying to make it go away before accepting it. The selection study repeated the pattern. He says he has been "almost traumatized" by how consistently the data have overturned his expectations. That history is why he presents the Neanderthal model as an open question rather than a conclusion. In his words, "we don't really know the world we live in."