A high-coverage genome from a 200,000-year-old Denisovan

A high-coverage genome from a 200,000-year-old Denisovan | bioRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-M677548'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results A high-coverage genome from a 200,000-year-old Denisovan View ORCID Profile Stéphane Peyrégne , Diyendo Massilani , Yaniv Swiel , Michael James Boyle , Leonardo N. M. Iasi , Arev P. Sümer , Alba Bossoms Mesa , Cesare de Filippo , Bence Viola , Elena Essel , Sarah Nagel , Julia Richter , Antje Weihmann , Barbara Schellbach , Hugo Zeberg , Johann Visagie , Maxim B. Kozlikin , Michael V. Shunkov , Anatoly P. Derevianko , Kay Prüfer , View ORCID Profile Benjamin M. Peter , View ORCID Profile Matthias Meyer , Svante Pääbo , View ORCID Profile Janet Kelso doi: https://doi.org/10.1101/2025.10.20.683404 Stéphane Peyrégne 1 Max Planck Institute for Evolutionary Anthropology , Leipzig, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Stéphane Peyrégne For correspondence: stephanepeyregne{at}gmail.com kelso{at}eva.mpg.de Diyendo Massilani 1 Max Planck Institute for Evolutionary Anthropology , Leipzig, Germany 2 Department of Genetics, Yale School of Medicine , New Haven, CT, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Yaniv Swiel 1 Max Planck Institute for Evolutionary Anthropology , Leipzig, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Michael James Boyle 1 Max Planck Institute for Evolutionary Anthropology , Leipzig, Germany 2 Department of Genetics, Yale School of Medicine , New Haven, CT, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Leonardo N. M. Iasi 1 Max Planck Institute for Evolutionary Anthropology , Leipzig, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Arev P. Sümer 1 Max Planck Institute for Evolutionary Anthropology , Leipzig, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Alba Bossoms Mesa 1 Max Planck Institute for Evolutionary Anthropology , Leipzig, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Cesare de Filippo 1 Max Planck Institute for Evolutionary Anthropology , Leipzig, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Bence Viola 3 Department of Anthropology, University of Toronto , Toronto, Ontario, Canada Find this author on Google Scholar Find this author on PubMed Search for this author on this site Elena Essel 1 Max Planck Institute for Evolutionary Anthropology , Leipzig, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Sarah Nagel 1 Max Planck Institute for Evolutionary Anthropology , Leipzig, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Julia Richter 1 Max Planck Institute for Evolutionary Anthropology , Leipzig, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Antje Weihmann 1 Max Planck Institute for Evolutionary Anthropology , Leipzig, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Barbara Schellbach 1 Max Planck Institute for Evolutionary Anthropology , Leipzig, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Hugo Zeberg 1 Max Planck Institute for Evolutionary Anthropology , Leipzig, Germany 4 Department of Physiology and Pharmacology, Karolinska Institutet , Stockholm, Sweden Find this author on Google Scholar Find this author on PubMed Search for this author on this site Johann Visagie 1 Max Planck Institute for Evolutionary Anthropology , Leipzig, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Maxim B. Kozlikin 5 Institute of Archaeology and Ethnography, Siberian Branch, Russian Academy of Sciences , Novosibirsk, Russia Find this author on Google Scholar Find this author on PubMed Search for this author on this site Michael V. Shunkov 5 Institute of Archaeology and Ethnography, Siberian Branch, Russian Academy of Sciences , Novosibirsk, Russia Find this author on Google Scholar Find this author on PubMed Search for this author on this site Anatoly P. Derevianko 5 Institute of Archaeology and Ethnography, Siberian Branch, Russian Academy of Sciences , Novosibirsk, Russia Find this author on Google Scholar Find this author on PubMed Search for this author on this site Kay Prüfer 1 Max Planck Institute for Evolutionary Anthropology , Leipzig, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Benjamin M. Peter 1 Max Planck Institute for Evolutionary Anthropology , Leipzig, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Benjamin M. Peter Matthias Meyer 1 Max Planck Institute for Evolutionary Anthropology , Leipzig, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Matthias Meyer Svante Pääbo 1 Max Planck Institute for Evolutionary Anthropology , Leipzig, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site Janet Kelso 1 Max Planck Institute for Evolutionary Anthropology , Leipzig, Germany Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Janet Kelso For correspondence: stephanepeyregne{at}gmail.com kelso{at}eva.mpg.de Abstract Full Text Info/History Metrics Supplementary material Preview PDF Abstract Denisovans, an extinct sister group of Neandertals who lived in Eastern Eurasia during the Middle and Late Pleistocene, are known only from a handful of skeletal remains and limited genetic data, including the high-coverage genome of a woman who lived ∼65,000 years ago. Here, we present a second high-quality Denisovan genome, reconstructed from a molar found at Denisova Cave. It belonged to a man who lived ∼200,000 years ago in a small Denisovan group. This group mixed with early Neandertals and was then replaced by Denisovans who had mixed with later Neandertals. We show that in addition Denisovans received gene flow from hominins that diverged before the split of the ancestors of Denisovans and modern humans. The two Denisovan genomes allow us to disentangle Denisovan ancestry in present-day humans revealing contributions from at least three distinct Denisovan groups. In particular, Oceanians and South Asians independently inherited DNA from a deeply diverged Denisovan population which was likely isolated in South Asia. This supports an early migration of the ancestors of Oceanians through South Asia followed by the later arrival of the ancestors of present-day South Asians. East Asians do not share this Denisovan component in their genomes, suggesting that their ancestors arrived independently, perhaps by a northerly route. Finally, the two high-quality Denisovan genomes allow us to refine the catalogue of genetic changes that arose on the Denisovan lineage, some of which were contributed to present-day humans. Main text Denisovans, an extinct human group, were first identified based on ancient DNA extracted from Denisova 3 , a finger phalanx discovered at Denisova Cave in the Altai Mountains of Siberia in 2008 1 , 2 . Analysis of the nuclear genome from this individual revealed that Denisovans were a sister group to Neandertals 2 , another group of now extinct humans who lived in Western Eurasia in the middle and late Pleistocene. While twelve fragmentary remains and one cranium have since been attributed to Denisovans based on DNA or protein analysis 1 - 12 , only Denisova 3 has yielded a high-quality genome (∼30-fold genomic coverage) 13 . The Denisovan genomic data available from Denisova Cave, which also includes three partial nuclear genomes, seven mitochondrial genomes, and Denisovan DNA recovered from sediment samples, indicate recurrent Denisovan presence in the Altai region between 200 and 50 thousand years ago (ka) 8 , 14 , 15 , interspersed with periods of Neandertal occupation. The identification of a child of a Neandertal mother and a Denisovan father shows that these groups sometimes overlapped and interbred 4 . However, Denisovans remained genetically distinct from Neandertals, perhaps because these events were limited to a few contact zones. Mitochondrial DNA analyses at Denisova Cave and Baishiya Karst Cave on the Tibetan Plateau 16 suggest that different Denisovan populations at these locations at times replaced each other. Comparisons of the genomes of Denisova 3 and modern humans revealed that interbreeding between Denisovans and the ancestors of present-day people took place in Asia and possibly Oceania 2 , 13 , 17 - 20 . Evidence of multiple Denisovan components with different relationships to the sequenced Denisovan in the genomes of present-day people indicates mixture with genetically distinct Denisovan populations 20 - 25 , about whom we know very little. Additional Denisovan genomes would be helpful to better understand Denisovan population history, the relationships among Denisovan ancestry components in present-day people, and the biology of this now-extinct human group. A new Denisovan genome sequence In 2020, a complete left upper molar was found in layer 17, one of the lowest cultural layers of the South Chamber of Denisova Cave, dated to 200-170ka by optically stimulated luminescence 15 . Designated as Denisova 25 , this molar is similar in size to the other molars discovered at Denisova Cave, Denisova 4 and Denisova 8 2 , 3 , and larger than those of Neandertals as well as most other Middle Pleistocene and later hominins ( Supplementary Note 1, Figures S3 and S4 ), suggesting that it potentially belonged to a Denisovan. Yet, Denisova 25 shows a simpler morphology than Denisova 4 and Denisova 8 , with only three main cusps and lacking the very robust and strongly diverging roots seen in Denisova 4 . Its outline is most similar to that of an upper molar preserved in the Harbin cranium from northeastern China, dated to at least 146ka 26 . Two samples of 2.7 mg and 8.9 mg were removed by drilling one hole at the cemento-enamel junction of the tooth, and twelve subsamples, ranging from 4.5 mg to 20.2 mg, were obtained by gently scratching the outer layer of one of the roots with a dentistry drill ( Supplementary Note 2 ). After DNA extraction and library preparation, we identified two samples with exceptional ancient DNA preservation. Notably, 20 to 47% of DNA sequences generated mapped to the human genome and less than ∼3% of these sequences stemmed from present-day human DNA contamination ( Figure 1 ). We sequenced these libraries more deeply and reconstructed a 23.6-fold coverage of the genome of this individual ( Supplementary Note 3 ). As the coverage of the X and Y chromosomes is half that of the autosomes, we concluded that the tooth belonged to a male individual ( Figure 1 ; Supplementary Note 3 ). Download figure Open in new tab Figure 1. Origin of Denisova 25 and available genetic data. ( A ) Map of Asia showing the locations of Denisova Cave, Baishiya Cave, the Harbin cranium and Penghu mandible discoveries, and other sites with potential Denisovan remains 27 - 29 . ( B ) Stratigraphic profile of the South Chamber in Denisova Cave, illustrating the approximate origins of Denisova 25 and other Denisovan remains (specimen numbers circled in the corresponding layers). A composite section (modified from 15 ) to the left of the profile displays modelled start and end ages (in ka) for sedimentary layers (95% highest posterior probability). Circles denote previously described sediment sample locations, coloured by detected hominin mitochondrial DNA: red (Denisovan), blue (Neandertal), grey (unidentified ancient hominin), and white (no ancient hominins detected). Triangles indicate sediment samples assigned to a specific Denisovan mitochondrial lineage. Distal and occlusal views of Denisova 25 are shown. ( C ) Genomic coverage and proportion of present-day human DNA contamination for Denisova 25 . Molecular dating The mitochondrial genome and Y chromosome of Denisova 25 are of the Denisovan type ( Figures 2B and 2C ; Supplementary Notes 4 and 5 ) and are more closely related to the mitochondrial genome and Y chromosome of Denisova 8 , a Denisovan previously dated to 136-106ka, than those of Denisova 4 dated to 84-55ka 30 . Molecular dating using a Bayesian analysis 31 of the mitochondrial genome and the Y chromosome (restricted to regions that facilitate accurate dating 32 ) results in age estimates for the Denisova 25 individual of 219ka (95% Highest Posterior Density Interval, HPDI: 275-159ka) and 232ka (95% HPDI: 288-177ka), respectively. Given that the mitochondrial lineage of Denisova 8 is longer than that of Denisova 25 by at most two mutations, we estimate that the Denisova 8 individual lived approximately 215ka (95% HPDI: 273-158ka), which is consistent with the assignment of Denisova 8 to a deeper layer (dated to ∼190ka) in a recent re-evaluation of the stratigraphy of Denisova Cave 15 . The number of missing mutations in the nuclear genome of Denisova 25 relative to present-day humans yields a molecular date of 205ka (215ka-195ka, 2 s.d.; Supplementary Note 6 ). The mitochondrial, Y chromosome and nuclear estimates are thus consistent with the age of layer 17 where the molar was found. Denisova 25 is therefore about 140,000 years older than the previously sequenced Denisova 3 (75-55ka, 2 s.d.; Supplementary Note 6 ). Download figure Open in new tab Figure 2. Relationships of Denisova 25 to archaic and modern humans. ( A ) Tree representing average population relationships inferred from nuclear genomes. Arrows indicate gene flow between populations, with darker arrows denoting those identified or examined in this study. Age estimates for high-coverage genomes are inferred from branch shortening (i.e., missing mutations in archaic genomes), with intervals corresponding to two standard deviations from the estimate as computed with a block jackknife. Population split time estimates are indicated by dotted lines. The split between the populations of Denisova 3 and Denisova 25 is estimated at 15,000 years (±2,000 years) before Denisova 25 lived, adjusted for the uncertainty in the age of Denisova 25 . Neandertal-Denisovan and modern-archaic split times correspond to the range of estimates obtained with calibrations of the divergence in genomic regions that presumably evolve neutrally. The split between the population of the Denisova 5 Neandertal and other Neandertals was previously estimated 33 . The tree is not to scale. ( B ) Bayesian phylogenetic tree of mitochondrial genomes of 7 Denisovans, 27 Neandertals, 64 modern humans and a hominin from Sima de los Huesos. The numbers at the nodes correspond to the posterior probabilities of the depicted branching orders. The Denisovan mitochondrial sequence of Denisova 19 is not included because it is identical to that of Denisova 21 8 . ( C ) Bayesian phylogenetic tree of the Y chromosomes of 3 Denisovans, 2 Neandertals, and 32 modern humans. The Y chromosomes of Denisova 4 and Denisova 8 were excluded from the analysis due to the lower coverage available, but positioned on the tree based on the sharing of derived alleles with the Y chromosome of Denisova 25 . The length of the branches for Denisova 4 and Denisova 8 is inferred from the age of these individuals on the mitochondrial tree. The scale for the mitochondrial and Y chromosome phylogenies is indicated. Throughout the figure, Denisovans, Neandertals and modern humans are highlighted in light red, light blue, and light yellow, respectively. Relationships to other hominins We next compared the derived allele sharing between the high-quality genomes of Denisova 25 , the Denisova 3 Denisovan and three Neandertals, as well as the lower-quality genomes from four additional Denisovans ( Supplementary Note 8 ). These comparisons show that Denisova 25 is more closely related to Denisova 3 than to Neandertals, indicating that he belonged to an early Denisovan population ( Figure 2A ). Furthermore, Denisova 8 shares more derived alleles with Denisova 25 than with Denisova 3 , whereas Denisova 4 and Denisova 11 share more alleles with Denisova 3 ( Supplementary Note 8 ). This is consistent with the mitochondrial and Y chromosome relationships and supports a temporal transition between two distinct Denisovan populations at Denisova Cave. The partial genome of Denisova 2 , a deciduous molar found in the deepest layer of the Main Chamber, is equally related to Denisova 3 and Denisova 25 , which could suggest the existence of a third population, but the high level of present-day human DNA contamination in the Denisova 2 genome may obscure the relationships. Denisova 25 shares more alleles with Neandertals than Denisova 3 does ( Supplementary Note 8 ), suggesting that Denisova 25 received more Neandertal gene flow than Denisova 3 , who has been estimated to carry approximately 0.5% DNA from Neandertals more closely related to the 120,000-year-old Neandertal Denisova 5 than later Neandertals 33 , 34 . In addition, the Neandertal Denisova 5 shares more alleles with both Denisova 3 and Denisova 25 than the Vindija 33 . 19 and Chagyrskaya 8 Neandertals do, who appear equally related to Denisovans ( Supplementary Note 8 ). This difference between Denisova 5 and the other Neandertals in their relationship to Denisova 25 cannot be due to gene flow from the Neandertal Denisova 5 population to the Denisova 25 population as Denisova 25 predates the existence of the Denisova 5 population, which splits from the other Neandertal populations around 140ka 33 , 34 . The explanation must therefore be gene flow from Denisovans to the ancestors of the Neandertal population to which Denisova 5 belonged. Recurrent Neandertal gene flow into Denisovans Using a method 35 that leverages reference genomes to identify local ancestry along the Denisovan genomes, we estimated that Denisova 25 and Denisova 3 carry 3.6-5.2% and 1.8-2.5% Neandertal ancestry, respectively, and identified between 56Mb and 166Mb of Neandertal segments in Denisova 25 , and between 34Mb and 87Mb in Denisova 3 , depending on the parameters used for calling segments ( Figure 3 ; Supplementary Note 9 ). While the Neandertal ancestry of Denisova 3 is more closely related to the Denisova 5 Neandertal than to the two other Neandertals, the Neandertal ancestry of Denisova 25 is equally related to all three Neandertal genomes. Given the age of Denisova 25 , this suggests that his Neandertal ancestry comes from a yet undescribed Neandertal population that split over 200,000 years ago from the Neandertal populations for which we have genomes. Moreover, the length distribution of their Neandertal segments fits better to a mixture of exponential distributions than a single exponential decay ( Figure 3 ), suggesting that both Denisovans inherited their Neandertal ancestry from multiple gen flow events. We estimated that the most recent Neandertal ancestors of Denisova 25 predate him by an average of 13,000-7,000 years, and that his ancestors may also have mixed with even earlier Neandertal ( Supplementary Note 9 ). Similarly, the ancestors of Denisova 3 mixed with Neandertals on multipl occasions, with both recent gene flow 16,000 to 12,000 years before she lived, as well as older gene flow. This indicates repeated contacts between Neandertals and Denisovans throughout their history ( Supplementary Note 9 ). Despite this recurrent mixing, distinct Neandertal and Denisovan groups can b identified at Denisova Cave from around 200,000 years ago until around 70,000 years ago. This suggests that mixed individuals did not contribute much to the gene pool of later individuals, which is consistent with archaic population turnovers in the Denisova Cave region. It is possible that mixing between Neandertals and Denisovans occurred locally in the region of Denisova Cave at the edges of their respective geographical ranges without spreading further. Recurrent migrations from elsewhere then replaced these mixed groups with Denisovans and Neandertals with less mixed ancestry. Download figure Open in new tab Figure 3. Distribution of Neandertal ancestry in Denisovan genomes. Colours indicate the inferred local ancestry along the two copies of each chromosome (or the single X chromosome of Denisova 25 ). Neandertal DNA segments of at least 0.05cM are shown. Pie charts depict the total proportion of Neandertal DNA identified in each genome. The length distribution of Neandertal DNA segments (in centimorgans, cM) is presented for each genome as histograms, alongside fitted distributions modeling one or two pulses of admixture with Neandertals. The two-pulse model provides a significantly better fit than the one-pulse model for both genomes (likelihood ratio test p-values: <10 -6 for Denisova 3 and <10 -23 for Denisova 25 ). Revised population split times The amount of Neandertal DNA in these Denisovan genomes could affect population split time estimates. We show with simulations that a previously used statistic ( F(A | B) , which measures the extent to which individuals share genetic polymorphisms 13 , 34 , 36 , is highly sensitive to gene flow, and likely under-estimates the true split times, while split time estimates based on sequence divergence are less biased ( Supplementary Note 8 ). In addition, background selection has a large effect on demographic inferences 37 - 39 . To account for this, we masked regions exhibiting a reduced genetic diversity in present-day humans, a signal indicative of selective constraints 40 . When restricting the analysis to neutrally evolving regions and using sequence divergence, a statistic less sensitive to gene flow, we estimate that modern and archaic humans separated 825-694ka, while Neandertals and Denisovans separated 585-504ka. These dates are substantially older than previous estimates (630-520ka and 440-390ka, respectively 33 ) and consistent with the time to the most recent common ancestor between Denisovan and modern human mitochondrial genome and Y chromosome ( Figure 2B and 2C ). The revised dates are also consistent with estimates based on dental evolutionary rates 41 and the presence of derived Neandertal dental and mandibular traits in the early Neandertals from Sima de los Huesos 42 - 44 . Finally, we estimate that the ancestors of Denisova 25 and Denisova 3 separated 15,000 (±2,000) years before Denisova 25 lived. Considering the uncertainty in the age of Denisova 25 , this results in a split time of 231-204ka ( Supplementary Note 8 ). We caution that the split time estimates, particularly those between archaic and modern humans, remain approximate; in particular, gene flow from more divergent groups into modern humans 45 , 46 or Denisovans 33 , 34 could inflate our estimates by tens, but not hundreds, of thousands of years ( Supplementary Figure S45 ; Supplementary Note 8 ). Genetic diversity and population sizes of early and late Denisovans As Denisova 25 lived about fifteen thousand years after the divergence from the ancestral population with Denisova 3 , we investigated the demographic history of the Denisova 25 population (Supplementary Note S7). Using the Pairwise Sequential Markovian Coalescent model, we detected a decline in population size approximately 220,000 years ago, following the split with the ancestors of Denisova 3 ( Figure 4A ). Additionally, about 15.8% of the Denisova 25 genome are present in homozygous regions longer than 2.5cM, indicating a history of consanguinity among the ancestors of Denisova 25 ( Figure 4B ). In particular, the fraction of the Denisova 25 genome covered by homozygous regions longer than 10cM (8.9%) is similar to that in the Denisova 5 (13%) and Chagyrskaya 8 (8.3%) Neandertal genomes, compatible with various scenarios of recent consanguinity, including parents that were double first cousins to half-siblings 34 . Despite these long runs of homozygosity, Denisova 25 exhibits higher heterozygosity than other archaic genomes. However, if the regions derived from Neandertals are excluded in the Denisova 3 and Denisova 25 genomes, their heterozygosity becomes similar to the Neandertal genomes, showing that the apparent differences in heterozygosity stem from the presence of Neandertal ancestry in the Denisovans ( Figure 4C ). Download figure Open in new tab Figure 4. Population size, runs of homozygosity, and heterozygosity of Denisova 25 . ( A ) Population size estimates over time based on the Pairwise Sequential Markovian Coalescent model, calculated for presumably neutrally evolving genomic regions (B-score 40 ≥0.9). ( B ) Percentage of the genome in runs of homozygosity (ROH) of at least 2.5cM in high-coverage archaic genomes, assuming a uniform recombination rate of 1.3cM/Mb. Black bars indicate the proportion of the genome in ROH of at least 10cM, suggesting close parental relatedness. ( C ) Heterozygosity estimates in high-coverage archaic human genomes. For comparison, Neandertal segments (identified with admixfrog , Supplementary Note 9 ) were masked in the Denisovan genomes. Each dot represents the heterozygosity for a chromosome, while diamonds denote the average across all autosomes. Using an approach which estimates group size from the length and number of runs of homozygosity 47 , we estimated that the Denisova 25 lived in a group of 50-60 individuals, with approximately one migrant per generation, similar to the estimates for the 80,000-year-old Chagyrskaya 8 Neandertal genome and about twice that of the 120,000-year-old Denisova 5 Neandertal genome ( Supplementary Note 7 ). In contrast, the 60,000-year-old Denisova 3 Denisovan and the 50,000-year-old Vindija 33 . 19 Neandertal likely lived in larger groups (>100 individuals), suggesting that group sizes were not inherently different between Neandertals and Denisovans. The small size of the early groups and the population turnovers suggest that conditions may not have allowed large groups to persist during earl periods in Southern Siberia, potentially contributing to the disappearance of the Denisova 5 Neandertal and Denisova 25 populations. Evidence of “Super-Archaic” ancestry in Denisovans The availability of a second Denisovan genome provides an opportunity to investigate a previous hypothesis that Denisovans have ancestry from archaic humans who diverged from the modern human lineage earlier than Denisovan ancestors did (“Super-archaic” humans) 33 , 34 , 48 . This was suggested because Neandertals share more derived alleles with present-day Africans than Denisovans do, particularly at positions with derived alleles fixed in present-day Africans 34 , a result we replicate with Denisova 25 ( Figure 5A ; Supplementary Note 10 ). Given more recent evidence for early gene flow from the ancestors or relatives of modern humans to Neandertals 48 - 54 , the presence of any such gene flow into Denisovans may not be necessary anymore to account for this observation. Download figure Open in new tab Figure 5. Evidence of “Super-Archaic” ancestry in Denisovans. ( A ) Stratified D-statistics of the form D(Neandertal, Denisovan, African, outgroup) (left) and D( Denisova 3, Denisova 25 , African, outgroup) (right), binned by allele frequency i SGDP Sub-Saharan Africans (in intervals of 10%, and for fixed derived alleles). The outgroup allele was determined from four great ape reference genomes ( Supplementary Note 8 ). Only transversion polymorphisms were used to avoid biases observe with transitions ( Supplementary Note 8 ), likely due to recurrent mutations. Whiskers indicate ±2 standard errors estimated with a block jackknife in 5Mb windows. ( B ) Decay of genotype covariance between sites carrying alleles potentially inherited from a “Super-Archaic” hominin (fixed derived in Africans, ancestral in one pseudohaploid archaic genome, and shared with Africans in the other). Points show mean covariance for site pairs binned by distance (kb); curves are exponential fits. Colours indicate genome pairs. Observed data (top left) are compared to coalescent simulations with 10% gene flow from a “Super-Archaic” hominin to Denisovans (top) or from modern humans to Neandertals (bottom) (see Supplementary Note 10 for more details). We first analysed the relationship of Denisova 3 and Denisova 25 to present-day Africans b comparing their derived allele sharing stratified by the allele frequency in present-day Africans and found no significant differences across the allele frequency spectrum ( Figure 5A ; Figure S65 ). This suggest that if Denisovans received any gene flow from a more divergent archaic group, it is likely to have occurred over 200,000 years ago, i.e., before the Denisova 3 and Denisova 25 populations split. As Denisova 25 is much older than Denisova 3 and therefore closer in time to any potential contact with a divergent archaic group, any DNA segments contributed by such a group should be longer in the Denisova 25 genome than in the Denisova 3 genome. By examining the decay of linkage disequilibrium between alleles potentially inherited from such a hominin (i.e. at positions where derived alleles are fixed in present-day Africans but where a Neandertal or Denisovan genome carries the ancestral allele), we found a stronger decay in Denisova 3 than in Denisova 25 , but no differences among Neandertals ( Figure 5B ). Simulations exploring the effect of deeply divergent and modern human DNA contributions shows that the difference in decay among Denisovans can be explained by gene flow from a deeply diverged hominin in Denisovans but not by only early modern human gene flow in Neandertals. This shows that, in addition to modern human ancestry in Neandertals, an unknown “Super-Archaic” hominin contributed DNA to the ancestors of Denisovans. Using a method that infers introgressed DNA segments from a divergent population based on an elevated density of single nucleotide variants 55 , we identified 46 and 70 candidate segments for “Super-Archaic” ancestry in Denisova 3 and Denisova 25 , respectively, with 33% of Denisova 3 segments overlapping those reported in a previous study 48 . The higher number of candidate segments in Denisova 25 may reflect the closer temporal proximity of this individual to the admixture event, facilitating the detection of “Super-Archaic” DNA segments. Notably, such DNA segments were detected also in the Neandertal genomes (44, 45, and 37 candidate segments in Denisova 5, Chagyrskaya 8 , and Vindija 33 . 19 , respectively). Since Neandertals should have little or no “Super-Archaic” ancestry, this suggests a high rate of false positives, currently making it difficult to identify “Super-Archaic” DNA segments in Denisovans, perhaps because admixture was ancient enough for segments to be short. However, in Denisovans, unlike in Neandertals, several candidate regions exhibit extreme heterozygosity as well as unusually high divergence both from Neandertals and between the two Denisovan genomes, consistent with retention of ancestry from a deeply divergent lineage ( Extended Figure 1 ). Download figure Open in new tab Extended Figure 1. Example of a genomic region in Denisova 25 with a candidate “Super-Archaic” segment (shaded region), showing high heterozygosity (dashed line) and high divergence from Denisova 3 (solid line). The region overlaps TSPEAR and keratin genes (shown on top) and lies near the end of chromosome 21 (red frame on the ideogram). Denisovan ancestry in present-day humans As genetic contributions from distinct Denisovan populations have been detected in the genomes of present-day humans 20 - 25 , we next compared how these components relate to the Denisova 3 and Denisova 25 genomes. We used a published map of Denisovan ancestry in the 1,000 Genomes Project dataset 21 as well as new maps we reconstructed for genomes from the SGDP dataset 56 using a method that relies on the high quality archaic genomes to detect introgressed archaic segments (“reference-based” method) 35 and a method that infers archaic introgressed segments based on an increase in the density of single nucleotide variants (“reference-free” method) 55 ( Supplementary Note 11 ). We present the results using the reference-based method, which are qualitatively consistent with the results from the reference-free approaches ( Supplementary Note 11 ). On average, 1.8-fold more Denisovan-like segments are identified in non-Africans when adding the Denisova 25 genome ( Figure 6A ; Figures S83 and S85 ). The lowest levels are found in Europeans (average 0.4 Mb) and the highest levels in Oceanians (average 31 Mb) ( Extended Data Table 1 ; Table S66 ). Download figure Open in new tab Figure 6. Characterisation of Denisovan ancestry in present-day human genomes. ( A ) Average Denisovan ancestry coverage across genomes from different geographical groups, using one or both Denisovan genomes as references. More details are provided in Extended Data Table 1 . (B ) Proportion of Denisovan-like segments, grouped by population (columns), sharing a breakpoint with those from other populations (rows). ( C ) Match rate of Denisovan-like segments in present-day human genomes to Denisova 3 (x-axis) and Denisova 25 (y-axis), by counting the proportion of derived alleles in each segment that are share with the Denisovan genome, after excluding alleles shared with Africans. Each dot represents a different segment and contours show their density. Counts of segments above and below the diagonal are indicated. Roughly expected match rates for each of the three identified Denisovan ancestry components are shown with different colours (as shown in D). ( D ) Tentative geographical distribution of the three Denisovan ancestry components detected in present-day populations, with their relationship depicted in the tree. Diamonds represent the geographical origin of analysed genomes. ( E ) Distributions of match rates to Denisova 3 at sites where Denisova 3 has a derived allele absent in an African genome. The fit of a beta-binomial distribution to the match rate of Denisova 25 to Denisova 3 within the same genomic segments identified as Denisovan-like in present-day humans is shown (black line). A mixture of two beta-binomial distributions including a more distant component is shown (yellow line) when this mixture provides a better fit to the match rate of Denisovan-like segments in present-day humans (histogram). The distributions were fitted using an Expectation-Maximization algorithm and the reported p-values were computed using a likelihood ratio test. ( A-E ) Segments used in all panels were identified with admixfrog using both Denisovan genomes as references. For overlapping segments within a geographical group, one segment is randomly chosen. The Denisovan-like segments match Denisova 3 more frequently than Denisova 25 ( Figure 6C ), a pattern that persists even after masking Neandertal-like segments in both Denisovan genomes, indicating that potential mis-assignment of the Neandertal segments in modern humans, which is more closely related to the Neandertal ancestry in Denisova 3 , does not explain the observation. Thus, all non-Africans inherited at least part of their Denisovan ancestry from Denisovans who were more closely related to Denisova 3 than to Denisova 25 . Consistent with previous findings 21 , we observed an additional Denisovan component that is even closer to Denisova 3 in the genomes of present-day East Asians, Central Asians, Siberians, Native Americans, and some Europeans (e.g. Finnish). In South Asians and Oceanians, the match rate between Denisovan-like segments and the Denisovan genomes is lower than the Denisova 3 - Denisova 25 match rate in the same genomic regions, providing evidence for a different Denisovan component that diverged earlier from the common ancestral population of Denisova 3 and Denisova 25 ( Figure 6D and 6E ). This divergent Denisovan component is not found in populations other than South Asians and Oceanians. Therefore, we detect at least three distinct Denisovan components in present-day humans that are differently distributed across populations today. To test whether South Asians and Oceanians inherited the most divergent Denisovan DNA component through separate events we compared the breakpoints of Denisovan-like segments among non-Africans, assuming that segments inherited from a common introgression would share breakpoints from past recombination events ( Figure 6B ). However, we found that segments identified in Oceanians almost never share breakpoints with segments in other populations, including South Asians, while th segments identified in other populations share breakpoints broadly across all non-Africans. This suggests that ancestors of Oceanians inherited their Denisovan ancestry independently from other modern humans. It further implies that although the deeply diverged Denisovan component is seen in both South Asians and Oceanians, South Asians must have inherited it in a separate event from Oceanians. These observations support the hypothesis that Oceanians descend from an early wave of modern humans that reached Oceania via a route through South Asia 57 . The observation that East Asians do not carry the deeply diverged Denisovan component, but do have a component most closely related to Denisova 3 , suggests that their ancestors migrated into East Asia via a more Northern route. Notably, Neandertal-like DNA segments are shared among all populations 58 ( Supplementary Note 11, Figure S114 ), including Oceanians, consistent with a single out-of-Africa event, but independent Denisovan gene flows suggest multiple migrations into Asia ( Extended Figure 2 ). Download figure Open in new tab Extended Figure 2. Potential admixture history between Denisovans and modern humans. The phylogeny illustrates the relationship between Denisovans, with colours corresponding to their hypothesised geographical distribution shown on the map. Molecular evidence from Denisova and Baishiya caves (locations indicated) suggests a northern distribution of Denisova 3 -like Denisovans 16 . Denisovans most divergent from Denisova 3 were likely in South Asia, given the distribution of this ancestry today. The hypothesised distribution of other Denisovans (orange) is based on morphological evidence 59 but could have been instead further west, e.g. in the Middle East. Arrows represent the minimum number of migrations required (for this geographical distribution of Denisovans), with colours illustrating their order. Assuming this distribution of Denisovans, the later migration from Southeast Asia into East and South Asia (grey arrows) is necessary to explain the wide distribution of the orange Denisovan ancestry. However, this migration would not be necessary if these Denisovans were found further to the West. View this table: View inline View popup Download powerpoint Extended Table 1. Average Denisovan ancestry coverage breadth (in Mb). Statistics were computed from putative Denisovan segments of at least 0.05cM. Segments identified with hmmix exhibit a posterior probability of at least 0.8 and are assigned as Denisovan based on a majority of alleles shared with a Denisovan genome compared to Neandertal genomes. For the segments identified with admixfrog , we report the results using the reference that only includes Denisova 3 and the reference that includes both Denisova 3 and Denisova 25 . Dating Denisovan gene flows into modern humans Assuming that the same Denisovan population mixed with the ancestors of present-day Oceanians and South Asians, the geographic distribution of this ancestry makes South Asia a likely contact zone where Denisovans different from those identified in Denisova Cave mixed first with the ancestors of Oceanians, and later with those of South Asians. To test whether we can distinguish these admixture events, we estimated Denisovan admixture times using the exponential decay of the linkage disequilibrium between alleles inherited from Denisovans in present-day individuals. We replicated a previous estimate that admixture between the ancestors of Oceanians and Denisovans occurred about 10% more recently than Neandertal admixture 60 ( Extended Figure 3 ; Supplementary Note 11 ). Although uncertainties in recombination rates prevent an absolute time estimate for Oceanians 60 , population-specific recombination maps available for other populations 61 allowed us to estimate Denisovan admixture times of 50-39ka in South Asians and 44-35ka in East Asians, approximately 20% and 29% more recent than Neandertal admixture time estimates in these populations (62-49ka – the range of estimates obtained for Eurasians), respectively ( Extended Figure 3 ; Supplementary Note 11 ). Therefore, the difference in Denisovan admixture times between Oceanians and other populations supports that Oceanians descend from an early wave of modern humans that encountered Denisovans before other non-Africans did. Europeans are likely to have acquired Denisovan ancestry indirectly through contact with Asian populations as there is no evidence of Denisovan DNA contributions in early modern humans in Europe 62 . East Asians are the most likely contributors of this ancestry, as Europeans share more Denisovan-like segment breakpoints with East Asians than with other Asians ( Figure 6B ). The date of the Denisovan DNA fragments in Europeans (46-34ka) is consistent with that estimated for East Asians. We could not further deconvolute the timing of introgression for the different Denisovan ancestry components due to limitations in accurately determining the length of Denisovan segments, which w show is sensitive to the choice of methods and parameters ( Supplementary Note 11 ). It may in future be possible to get more precise dates for the Denisovan admixtures using ancient genomes, as has been recently shown for Neandertal admixture 58 , 62 . Download figure Open in new tab Extended Figure 3. Estimation of Denisovan and Neandertal admixture dates. ( A ) Admixture dates in present-day Oceanians (SGDP dataset 56 ), inferred from linkage disequilibrium (Lewontin’s D) decay between putative Neandertal (reference: Denisova 5 ) or Denisovan introgressed alleles (references: Denisova 3 , left; Denisova 25 , right). Genetic distances were calculated using the African-American recombination map 63 . ( B ) Admixture dates in other present-day populations (1,00 Genomes dataset 64 , inferred from the linkage disequilibrium decay between putative Neandertal (reference: Denisova 5 ) or Denisovan introgressed alleles (reference: Denisova 3 , closest to most Denisovan ancestry). Genetic distances were calculated using population-specific recombination maps 61 . For both panels, average linkage disequilibrium in bins of 0.001 cM is shown with fitted exponential decay curves. Estimates in other populations are provided in Supplementary Note 11 ). The estimate of the Neandertal admixture in Native Americans is inconsistent with estimates for all other groups. This seems to be driven by over-estimates of the recombination rates in the population-specific recombination maps perhaps due to the complex admixture history of Native Americans. Local adaptation through Denisovan introgression Denisovans inhabited much of Asia for hundreds of thousands of years and likely adapted to diverse local environments. These adaptations may in turn have benefited incoming modern humans when genetic variants were passed on to them from Denisovans. Previous studies identified Denisovan-like DNA segments at high frequency in modern humans 20 , 22 , 65 - 71 , potentially due to adaptive introgression, but had limited ability to identify the contributing Denisovan population when only one Denisovan genome was available. Leveraging the increased power to detect Denisovan DNA segments using both Denisova 3 and Denisova 25 , we scanned the genomes of 236 present-day non-Africans from six geographic regions for candidates of adaptive introgression and compared each segment’s relationship to the two Denisovan genomes ( Supplementary Note 12 ). We defined candidates as segments in the extreme upper tail of the frequency distribution (Z-score ≥ 4.5) in the genomic regions where at least one individual carries Denisovan ancestry. We identified a total of 38 candidate regions, with the highest number (27) identified in Oceanians, who have the highest levels of Denisovan ancestry in our study ( Supplementary Note 11 ), the majority of which were not identified in a previous scan of the same genomes 60 . Interestingly, most candidates were unique to single geographic groups, with only two candidates shared by more than one group, suggesting that selection on introgressed Denisovan DNA differed between geographic regions and contributed primarily to local adaptation. In Oceania and South Asia, segments that are more divergent from Denisova 3 than Denisova 25 are significantly more frequent among candidates than expected from the genome-wide composition of Denisovan-like DNA segments. By contrast, in Native Americans, East Asians, and West Eurasians, most candidate segments are closer to Denisova 3 than Denisova 25 is, significantly more frequently than expected from Denisovan-like segments genome-wide. These patterns are consistent with local adaptation with northern, Denisova 3 -like Denisovans contributing most to adaptation in northern populations, and the more divergent, likely more southern Denisovans contributing most to adaptation in Oceanians and South Asians. Finally, we investigated the potential functional roles of candidates. Functional enrichment analysis of the set of adaptive introgression candidates yields only a single significant association: in South Asia two of the four candidate regions overlap genes, ATP6V0A4 and COL4A3 , and both genes are associated with sensory perception of sound and mechanical stimulus ( Table S69 ). The introgressed Denisovan segments do not modify the protein coding sequences of either gene, suggesting that any functional impacts could be related to differences in gene expression. Notably, there are four potentially regulatory variants on the introgressed haplotype in ATP6V0A4 , including a variant in the 5’ UTR of the canonical transcript. The adaptive advantage of these candidates is unclear; as mutations in both ATP6V0A4 and COL4A3 also cause renal diseases 72 - 74 any advantage may also be related to kidney function. An updated catalogue of Denisovan-derived variants Little phenotypic information is available for Denisovans, as they are known from only a few skeletal remains. However, their genomes have the potential to provide insights into their biology and its similarities and differences with modern humans 75 - 78 . A previous analysis of the Denisova 3 genome identified 692,818 single nucleotide changes that may be Denisovan-derived 13 , though many of these likely represent variants specific to that individual. Using the newly available high-coverage Denisovan genome and three high-coverage Neandertal genomes, we identified 237,112 single nucleotide variants shared between both Denisovan genomes (allowing a missing genotype in one), thereby refining the set of variants that likely arose on the Denisovan lineage ( Supplementary Note 13 ). Of these, 1,307 result in amino acid substitutions in 1,142 protein-coding genes. Variants at evolutionary conserved sites are likely to have the largest functional effects. Using a deep learning approach that integrates nucleotide conservation across 236 primate species with protein 3D structure information 79 , we identified ten missense changes predicted to have the strongest effects (PrimateAI-3D score between 0.8 and 1). Five of these genes, COPB1, KIF14, PIGG, PLCE1 and VWA8 have been linked to morphological traits 80 , several of which show changes in Denisovan fossils. In particular, COPB1, KIF14 , and PIGG influence cranial size, head circumference, and orbital size, all of which have been described to be large in the Denisovan cranium from Harbin 11 , 12 , 26 . Furthermore, COPB1 and PIGG are also associated with finger breadth, which is potentially relevant given that the Denisova 3 phalanx is more gracile than that of Neandertals 81 , while KIF14 and PIGG are associated with projection of the lower jaw, and KIF14 with a sloping forehead, which are also described in the Harbin cranium 26 . These genes are therefore promising candidates for understanding the distinct cranio-facial morphology of Denisovans. Changes that influence gene regulation may also have an important impact on phenotypes. Although many regulatory variants occur within non-coding regions where their target genes are difficult to determine, those located in promoter-proximal regions typically allow for a more direct link to gene expression. We identified 1,126 changes in promoter-proximal regions potentially impacting transcription initiation of 1,052 genes. Those with changes at highly conserved positions, inferred from 447 mammalian genomes 82 , are significantly enriched in the gene ontology terms central nervous system development (GO:0007417), brain development (GO:0007420), and neuron projection membrane (GO:0032589) (family-wise error rates ≤ 0.05) ( Table S67 ). The change at the most conserved position (phyloP score 8.097) lies 395 base pairs upstream the FOXP2 transcription start site, within an “ultra-conserved” 22-base-pair region identical across 235 mammalian genomes 83 . The Denisovan allele likely disrupted binding of the transcription factor ISL1 that is predicted to bind strongly to the ancestral allele ( Supplementary Note 13 ), and thereby potentially modified the expression of FOXP2 . This gene encodes forkhead box protein P2, a transcription factor expressed in many tissues. In the brain, it is involved in cerebral cortex development (GO:0021987), as well as speech and language development 84 , 85 . The effects of introgressed Denisovan alleles on modern human phenotypes may also provide some hints into Denisovan biology. Using alleles that have been associated with phenotypes in modern humans 86 , we identified 16 associations with 11 Denisovan alleles ( Table S75 ), including height, blood pressure, monocyte count, and levels of cholesterol, haemoglobin and C-reactive protein. We also identified 305 expression quantitative trait loci (QTL) and 117 alternative splicing QTL affecting gene expression in modern humans across nineteen tissues, the strongest effects include eQTLs in thyroid, arterial tibial, testis and muscle ( Figure S125 ). These molecular effects can be leveraged to explore further phenotypes not preserved in the fossil record, and this updated catalogue provides a more reliable basis for exploring Denisovan traits, adaptations, and disease susceptibilities, some of which may have been contributed to present-day humans through admixture. Future perspectives Using this second Denisovan genome has shown that there was recurrent mixing between Neandertals and Denisovans in the Altai region, but that these mixed populations were replaced by Denisovans from elsewhere, supporting the idea that Denisovans were widespread and that the Altai may have been at the edge of their geographic range. The Denisovan ancestry in modern humans provides a glimpse into the diversity of Denisovans, and suggests that Denisovans may have lived in populations that were geographically isolated from one another over an extended time. This isolation may simply reflect the large distances over which Denisovans were distributed or be due to more substantial geographic barriers. The presence of deeply divergent Denisovan ancestry in both Oceanians and South Asians makes it plausible that the Denisovans that contributed ancestry to these groups were isolated in South Asia by the Himalayas. Retrieving genetic data from these deeply diverged Denisovans will be critical to fully understand the origins and diversity of Denisovans, including their relationship to Neandertals and to the more deeply diverged hominin that contributed DNA to Denisovans. Data availability The sequences and genotypes from this study will be deposited in the European Nucleotide Archive. The FASTA file of the reconstructed mitochondrial genome will be deposited in GenBank. Author contributions S.Pe. and J.K. designed the study. D.M., E.E., S.N. and J.R. performed ancient DNA lab work. A.W., B.S., H.Z., J.V., S.Pe. and J.K. performed DNA sequencing and raw data processing. M.B.K., M.V.S. and A.P.D. provided and analysed archaeological material. B.V. performed the morphological analyses. S.Pe., Y.S., M.J.B., L.N.M.I., A.P.S., A.B.M., C.d.F. and K.P. performed or aided the genetic analyses. J.K., S.Pä., B.M.P. and M.M. supervised the study. J.K. S.Pe and J.K. wrote the manuscript with input from all co-authors. Ethics declarations Competing interests The authors declare no competing interests. Supplementary information This file contains Supplementary Notes 1-13 including figures, tables and references. See contents page of the Supplementary Information file for more details. Acknowledgment This project was funded by the Max Planck Society and the European Research Council (grant agreement no. 694707). Archaeological research at Denisova Cave by M.V.S. and M.B.K. was supported by the Russian Science Foundation, grant number 24-18-00069. We acknowledge support from the National Genomics Infrastructure in Stockholm funded by Science for Life Laboratory, the Knut and Alice Wallenberg Foundation and the Swedish Research Council, and SNIC/Uppsala Multidisciplinary Center for Advanced Computational Science for assistance with massively parallel sequencing and access to the UPPMAX computational infrastructure. We thank Isabel Pineda Yupanqui for helping prepare Figures 2 and 6 . Funder Information Declared Max Planck Society, https://ror.org/01hhn8329 European Research Council , 694707 Russian Science Foundation , 24-18-00069 References 1. ↵ Krause J , Fu Q , Good JM , et al. The complete mitochondrial DNA genome of an unknown hominin from southern Siberia . Nature . Apr 8 2010 ; 464 ( 7290 ): 894 – 7 . doi: 10.1038/nature08976 OpenUrl CrossRef GeoRef PubMed Web of Science 2. ↵ Reich D , Green RE , Kircher M , et al. Genetic history of an archaic hominin group from Denisova Cave in Siberia . Nature . Dec 23 2010 ; 468 ( 7327 ): 1053 – 60 . doi: 10.1038/nature09710 OpenUrl CrossRef GeoRef PubMed Web of Science 3. ↵ Sawyer S , Renaud G , Viola B , et al. Nuclear and mitochondrial DNA sequences from two Denisovan individuals . Proc Natl Acad Sci U S A . Dec 22 2015 ; 112 ( 51 ): 15696 – 700 . doi: 10.1073/pnas.1519905112 OpenUrl Abstract / FREE Full Text 4. ↵ Slon V , Mafessoni F , Vernot B , et al. The genome of the offspring of a Neanderthal mother and a Denisovan father . Nature . Sep 2018 ; 561 ( 7721 ): 113 – 116 . doi: 10.1038/s41586-018-0455-x OpenUrl CrossRef PubMed 5. Slon V , Viola B , Renaud G , et al. A fourth Denisovan individual . Sci Adv . Jul 2017 ; 3 ( 7 ): e1700186 . doi: 10.1126/sciadv.1700186 OpenUrl FREE Full Text 6. Chen F , Welker F , Shen CC , et al. A late Middle Pleistocene Denisovan mandible from the Tibetan Plateau . Nature . May 2019 ; 569 ( 7756 ): 409 – 412 . doi: 10.1038/s41586-019-1139-x OpenUrl CrossRef PubMed 7. Viola BT , Gunz P , Neubauer S , et al. A parietal fragment from Denisova cave . American Journal of Physical Anthropology . 2019 ; 168 ( S68 ): 1 – 283 . doi: 10.1002/ajpa.23802 OpenUrl CrossRef 8. ↵ Brown S , Massilani D , Kozlikin MB , et al. The earliest Denisovans and their cultural adaptation . Nat Ecol Evol . Jan 2022 ; 6 ( 1 ): 28 – 35 . doi: 10.1038/s41559-021-01581-2 OpenUrl CrossRef 9. Xia H , Zhang D , Wang J , et al. Middle and Late Pleistocene Denisovan subsistence at Baishiya Karst Cave . Nature . Aug 2024 ; 632 ( 8023 ): 108 – 113 . doi: 10.1038/s41586-024-07612-9 OpenUrl CrossRef 10. Tsutaya T , Sawafuji R , Taurozzi AJ , et al. A male Denisovan mandible from Pleistocene Taiwan . Science . Apr 11 2025 ; 388 ( 6743 ): 176 – 180 . doi: 10.1126/science.ads3888 OpenUrl CrossRef PubMed 11. ↵ Fu Q , Bai F , Rao H , et al. The proteome of the late Middle Pleistocene Harbin individual . Science . Aug 14 2025 ; 389 ( 6761 ): 704 – 707 . doi: 10.1126/science.adu9677 OpenUrl CrossRef 12. ↵ Fu Q , Cao P , Dai Q , et al. Denisovan mitochondrial DNA from dental calculus of the >146,000-year-old Harbin cranium . Cell . Jul 24 2025 ; 188 ( 15 ): 3919 – 3926 e9 . doi: 10.1016/j.cell.2025.05.040 OpenUrl CrossRef PubMed 13. ↵ Meyer M , Kircher M , Gansauge MT , et al. A high-coverage genome sequence from an archaic Denisovan individual . Science . Oct 12 2012 ; 338 ( 6104 ): 222 – 6 . doi: 10.1126/science.1224344 OpenUrl Abstract / FREE Full Text 14. ↵ Zavala EI , Jacobs Z , Vernot B , et al. Pleistocene sediment DNA reveals hominin and faunal turnovers at Denisova Cave . Nature . Jul 2021 ; 595 ( 7867 ): 399 – 403 . doi: 10.1038/s41586-021-03675-0 OpenUrl CrossRef 15. ↵ Jacobs Z , Zavala EI , Li B , et al. Pleistocene chronology and history of hominins and fauna at Denisova Cave . Nat Commun . May 21 2025 ; 16 ( 1 ): 4738 . doi: 10.1038/s41467-025-60140-6 OpenUrl CrossRef PubMed 16. ↵ Zhang D , Xia H , Chen F , et al. Denisovan DNA in Late Pleistocene sediments from Baishiya Karst Cave on the Tibetan Plateau . Science . Oct 30 2020 ; 370 ( 6516 ): 584 – 587 . doi: 10.1126/science.abb6320 OpenUrl Abstract / FREE Full Text 17. ↵ Reich D , Patterson N , Kircher M , et al. Denisova admixture and the first modern human dispersals into Southeast Asia and Oceania . Am J Hum Genet . Oct 7 2011 ; 89 ( 4 ): 516 – 28 . doi: 10.1016/j.ajhg.2011.09.005 OpenUrl CrossRef PubMed 18. Skoglund P , Jakobsson M. Archaic human ancestry in East Asia . Proc Natl Acad Sci U S A . Nov 8 2011 ; 108 ( 45 ): 18301 – 6 . doi: 10.1073/pnas.1108181108 OpenUrl Abstract / FREE Full Text 19. Qin P , Stoneking M. Denisovan Ancestry in East Eurasian and Native American Populations . Mol Biol Evol . Oct 2015 ; 32 ( 10 ): 2665 – 74 . doi: 10.1093/molbev/msv141 OpenUrl CrossRef PubMed 20. ↵ Jacobs GS , Hudjashov G , Saag L , et al. Multiple Deeply Divergent Denisovan Ancestries in Papuans . Cell . May 2 2019 ; 177 ( 4 ): 1010 – 1021 e32 . doi: 10.1016/j.cell.2019.02.035 OpenUrl CrossRef PubMed 21. ↵ Browning SR , Browning BL , Zhou Y , Tucci S , Akey JM . Analysis of Human Sequence Data Reveals Two Pulses of Archaic Denisovan Admixture . Cell . Mar 22 2018 ; 173 ( 1 ): 53 – 61 e9 . doi: 10.1016/j.cell.2018.02.031 OpenUrl CrossRef PubMed 22. ↵ Choin J , Mendoza-Revilla J , Arauna LR , et al. Genomic insights into population history and biological adaptation in Oceania . Nature . Apr 2021 ; 592 ( 7855 ): 583 – 589 . doi: 10.1038/s41586-021-03236-5 OpenUrl CrossRef PubMed 23. Larena M , McKenna J , Sanchez-Quinto F , et al. Philippine Ayta possess the highest level of Denisovan ancestry in the world . Curr Biol . Oct 11 2021 ; 31 ( 19 ): 4219 – 4230 e10 . doi: 10.1016/j.cub.2021.07.022 OpenUrl CrossRef 24. Ongaro L , Huerta-Sanchez E. A history of multiple Denisovan introgression events in modern humans . Nat Genet . Dec 2024 ; 56 ( 12 ): 2612 – 2622 . doi: 10.1038/s41588-024-01960-y OpenUrl CrossRef PubMed 25. ↵ He Y , Zhang X , Peng MS , et al. Genome diversity and signatures of natural selection in mainland Southeast Asia . Nature . Jul 2025 ; 643 ( 8071 ): 417 – 426 . doi: 10.1038/s41586-025-08998-w OpenUrl CrossRef PubMed 26. ↵ Ni X , Ji Q , Wu W , et al. Massive cranium from Harbin in northeastern China establishes a new Middle Pleistocene human lineage . Innovation (Camb) . Aug 28 2021 ; 2 ( 3 ): 100130 . doi: 10.1016/j.xinn.2021.100130 OpenUrl CrossRef 27. ↵ Cooper A , Stringer CB . Did the Denisovans cross Wallace’s Line? Science . Oct 18 2013 ; 342 ( 6156 ): 321 – 3 . doi: 10.1126/science.1244869 OpenUrl Abstract / FREE Full Text 28. Kaifu Y. Archaic Hominin Populations in Asia before the Arrival of Modern Humans: Their Phylogeny and Implications for the “Southern Denisovans” . Current Anthropology . 2017 ; 58 ( S17 ): S418 – S433 . doi: 10.1086/694318 OpenUrl CrossRef PubMed 29. ↵ Li ZY , Wu XJ , Zhou LP , et al. Late Pleistocene archaic human crania from Xuchang, China . Science . Mar 3 2017 ; 355 ( 6328 ): 969 – 972 . doi: 10.1126/science.aal2482 OpenUrl Abstract / FREE Full Text 30. ↵ Douka K , Slon V , Jacobs Z , et al. Age estimates for hominin fossils and the onset of the Upper Palaeolithic at Denisova Cave . Nature . Jan 2019 ; 565 ( 7741 ): 640 – 644 . doi: 10.1038/s41586-018-0870-z OpenUrl CrossRef PubMed 31. ↵ Bouckaert R , Heled J , Kuhnert D , et al. BEAST 2: a software platform for Bayesian evolutionary analysis . PLoS Comput Biol . Apr 2014 ; 10 ( 4 ): e1003537 . doi: 10.1371/journal.pcbi.1003537 OpenUrl CrossRef PubMed 32. ↵ Swiel Y , Kelso J , Peyregne S. Resolving the source of branch length variation in the Y chromosome phylogeny . Genome Biol . Jan 6 2025 ; 26 ( 1 ): 4 . doi: 10.1186/s13059-024-03468-4 OpenUrl CrossRef PubMed 33. ↵ Prüfer K , de Filippo C , Grote S , et al. A high-coverage Neandertal genome from Vindija Cave in Croatia . Science . Nov 3 2017 ; 358 ( 6363 ): 655 – 658 . doi: 10.1126/science.aao1887 OpenUrl Abstract / FREE Full Text 34. ↵ Prüfer K , Racimo F , Patterson N , et al. The complete genome sequence of a Neanderthal from the Altai Mountains . Nature . Jan 2 2014 ; 505 ( 7481 ): 43 – 9 . doi: 10.1038/nature12886 OpenUrl CrossRef GeoRef PubMed Web of Science 35. ↵ Peter BM . 100,000 years of gene flow between Neandertals and Denisovans in the Altai mountains . bioRxiv . 2020 :2020.03.13.990523. doi: 10.1101/2020.03.13.990523 OpenUrl Abstract / FREE Full Text 36. ↵ Green RE , Krause J , Briggs AW , et al. A draft sequence of the Neandertal genome . Science . May 7 2010 ; 328 ( 5979 ): 710 – 722 . doi: 10.1126/science.1188021 OpenUrl Abstract / FREE Full Text 37. ↵ Pouyet F , Aeschbacher S , Thiery A , Excoffier L. Background selection and biased gene conversion affect more than 95% of the human genome and bias demographic inferences . Elife . Aug 23 2018 ; 7 doi: 10.7554/eLife.36317 OpenUrl CrossRef 38. Johri P , Riall K , Becher H , Excoffier L , Charlesworth B , Jensen JD . The Impact of Purifying and Background Selection on the Inference of Population History: Problems and Prospects . Mol Biol Evol . Jun 25 2021 ; 38 ( 7 ): 2986 – 3003 . doi: 10.1093/molbev/msab050 OpenUrl CrossRef PubMed 39. ↵ Cousins T , Tabin D , Patterson N , Reich D , Durvasula A. Accurate inference of population history in the presence of background selection . bioRxiv . Jan 20 2024 ; doi: 10.1101/2024.01.18.576291 OpenUrl Abstract / FREE Full Text 40. ↵ McVicker G , Gordon D , Davis C , Green P. Widespread genomic signatures of natural selection in hominid evolution . PLoS Genet . May 2009 ; 5 ( 5 ): e1000471 . doi: 10.1371/journal.pgen.1000471 OpenUrl CrossRef PubMed 41. ↵ Gómez-Robles A. Dental evolutionary rates and its implications for the Neanderthal-modern human divergence . Sci Adv . May 2019 ; 5 ( 5 ): eaaw1268 . doi: 10.1126/sciadv.aaw1268 OpenUrl FREE Full Text 42. ↵ Quam R , Martinez I , Rak Y , et al. The Neandertal nature of the Atapuerca Sima de los Huesos mandibles . Anat Rec (Hoboken) . Jul 2024 ; 307 ( 7 ): 2343 – 2393 . doi: 10.1002/ar.25190 OpenUrl CrossRef PubMed 43. Bermudez de Castro JM , Martinez de Pinillos M , Martin-Frances L , et al. Dental remains of the Middle Pleistocene hominins from the Sima de los Huesos site (Sierra de Atapuerca, Spain): Maxillary dentition . Anat Rec (Hoboken) . Jul 2024 ; 307 ( 7 ): 2325 – 2342 . doi: 10.1002/ar.24841 OpenUrl CrossRef PubMed 44. ↵ Bermudez de Castro JM , Martinez de Pinillos M , Martin-Frances L , et al. Dental remains of the Middle Pleistocene hominins from the Sima de los Huesos site (Sierra de Atapuerca, Spain): Mandibular dentition . Anat Rec (Hoboken) . Jul 2024 ; 307 ( 7 ): 2394 – 2409 . doi: 10.1002/ar.24840 OpenUrl CrossRef PubMed 45. ↵ Ragsdale AP , Weaver TD , Atkinson EG , et al. A weakly structured stem for human origins in Africa . Nature . May 2023 ; 617 ( 7962 ): 755 – 763 . doi: 10.1038/s41586-023-06055-y OpenUrl CrossRef PubMed 46. ↵ Cousins T , Scally A , Durbin R. A structured coalescent model reveals deep ancestral structure shared by all modern humans . Nat Genet . Apr 2025 ; 57 ( 4 ): 856 – 864 . doi: 10.1038/s41588-025-02117-1 OpenUrl CrossRef 47. ↵ Mafessoni F , Grote S , de Filippo C , et al. A high-coverage Neandertal genome from Chagyrskaya Cave . Proceedings of the National Academy of Sciences . 2020 ; 117 ( 26 ): 15132 . doi: 10.1073/pnas.2004944117 OpenUrl Abstract / FREE Full Text 48. ↵ Hubisz MJ , Williams AL , Siepel A. Mapping gene flow between ancient hominins through demography-aware inference of the ancestral recombination graph . PLoS Genet . Aug 2020 ; 16 ( 8 ): e1008895 . doi: 10.1371/journal.pgen.1008895 OpenUrl CrossRef PubMed 49. Kuhlwilm M , Gronau I , Hubisz MJ , et al. Ancient gene flow from early modern humans into Eastern Neanderthals . Nature . Feb 25 2016 ; 530 ( 7591 ): 429 – 33 . doi: 10.1038/nature16544 OpenUrl CrossRef PubMed Web of Science 50. Meyer M , Arsuaga JL , de Filippo C , et al. Nuclear DNA sequences from the Middle Pleistocene Sima de los Huesos hominins . Nature . Mar 24 2016 ; 531 ( 7595 ): 504 – 7 . doi: 10.1038/nature17405 OpenUrl CrossRef GeoRef PubMed 51. Petr M , Hajdinjak M , Fu Q , et al. The evolutionary history of Neanderthal and Denisovan Y chromosomes . Science . Sep 25 2020 ; 369 ( 6511 ): 1653 – 1656 . doi: 10.1126/science.abb6460 OpenUrl Abstract / FREE Full Text 52. Peyrégne S , Kelso J , Peter BM , Pääbo S. The evolutionary history of human spindle genes includes back-and-forth gene flow with Neandertals . Elife . Jul 11 2022 ; 11 doi: 10.7554/eLife.75464 OpenUrl CrossRef 53. Harris DN , Platt A , Hansen MEB , et al. Diverse African genomes reveal selection on ancient modern human introgressions in Neanderthals . Curr Biol . Nov 20 2023 ; 33 ( 22 ): 4905 – 4916 e5 . doi: 10.1016/j.cub.2023.09.066 OpenUrl CrossRef PubMed 54. ↵ Posth C , Wissing C , Kitagawa K , et al. Deeply divergent archaic mitochondrial genome provides lower time boundary for African gene flow into Neanderthals . Nat Commun . Jul 4 2017 ; 8 : 16046 . doi: 10.1038/ncomms16046 OpenUrl CrossRef PubMed 55. ↵ Skov L , Hui R , Shchur V , et al. Detecting archaic introgression using an unadmixed outgroup . PLoS Genet . Sep 2018 ; 14 ( 9 ): e1007641 . doi: 10.1371/journal.pgen.1007641 OpenUrl CrossRef PubMed 56. ↵ Mallick S , Li H , Lipson M , et al. The Simons Genome Diversity Project: 300 genomes from 142 diverse populations . Nature . Oct 13 2016 ; 538 ( 7624 ): 201 – 206 . doi: 10.1038/nature18964 OpenUrl CrossRef PubMed 57. ↵ Reyes-Centeno H , Ghirotto S , Detroit F , Grimaud-Herve D , Barbujani G , Harvati K. Genomic and cranial phenotype data support multiple modern human dispersals from Africa and a southern route into Asia . Proc Natl Acad Sci U S A . May 20 2014 ; 111 ( 20 ): 7248 – 53 . doi: 10.1073/pnas.1323666111 OpenUrl Abstract / FREE Full Text 58. ↵ Iasi LNM , Chintalapati M , Skov L , et al. Neanderthal ancestry through time: Insights from genomes of ancient and present-day humans . Science . Dec 13 2024 ; 386 ( 6727 ): eadq3010 . doi: 10.1126/science.adq3010 OpenUrl CrossRef PubMed 59. ↵ Demeter F , Zanolli C , Westaway KE , et al. A Middle Pleistocene Denisovan molar from the Annamite Chain of northern Laos . Nat Commun . May 17 2022 ; 13 ( 1 ): 2557 . doi: 10.1038/s41467-022-29923-z OpenUrl CrossRef 60. ↵ Sankararaman S , Mallick S , Patterson N , Reich D. The Combined Landscape of Denisovan and Neanderthal Ancestry in Present-Day Humans . Curr Biol . May 9 2016 ; 26 ( 9 ): 1241 – 7 . doi: 10.1016/j.cub.2016.03.037 OpenUrl CrossRef PubMed 61. ↵ Spence JP , Song YS . Inference and analysis of population-specific fine-scale recombination maps across 26 diverse human populations . Sci Adv . Oct 2019 ; 5 ( 10 ): eaaw9206 . doi: 10.1126/sciadv.aaw9206 OpenUrl FREE Full Text 62. ↵ Sümer AP , Rougier H , Villalba-Mouco V , et al. Earliest modern human genomes constrain timing of Neanderthal admixture . Nature . Dec 12 2024 ; doi: 10.1038/s41586-024-08420-x OpenUrl CrossRef 63. ↵ Hinch AG , Tandon A , Patterson N , et al. The landscape of recombination in African Americans . Nature . Jul 20 2011 ; 476 ( 7359 ): 170 – 5 . doi: 10.1038/nature10336 OpenUrl CrossRef PubMed Web of Science 64. ↵ Genomes Project C , Auton A , Brooks LD , et al. A global reference for human genetic variation . Nature . Oct 1 2015 ; 526 ( 7571 ): 68 – 74 . doi: 10.1038/nature15393 OpenUrl CrossRef PubMed 65. ↵ Huerta-Sanchez E , Jin X , Asan, et al. Altitude adaptation in Tibetans caused by introgression of Denisovan-like DNA . Nature . Aug 14 2014 ; 512 ( 7513 ): 194 – 7 . doi: 10.1038/nature13408 OpenUrl CrossRef PubMed Web of Science 66. Racimo F , Gokhman D , Fumagalli M , et al. Archaic Adaptive Introgression in TBX15/WARS2 . Mol Biol Evol . Mar 1 2017 ; 34 ( 3 ): 509 – 524 . doi: 10.1093/molbev/msw283 OpenUrl CrossRef PubMed 67. Racimo F , Marnetto D , Huerta-Sanchez E. Signatures of Archaic Adaptive Introgression in Present-Day Human Populations . Mol Biol Evol . Feb 1 2017 ; 34 ( 2 ): 296 – 317 . doi: 10.1093/molbev/msw216 OpenUrl CrossRef PubMed 68. Racimo F , Sankararaman S , Nielsen R , Huerta-Sanchez E. Evidence for archaic adaptive introgression in humans . Nat Rev Genet . Jun 2015 ; 16 ( 6 ): 359 – 71 . doi: 10.1038/nrg3936 OpenUrl CrossRef PubMed 69. Gower G , Picazo PI , Fumagalli M , Racimo F. Detecting adaptive introgression in human evolution using convolutional neural networks . Elife . May 25 2021 ; 10 doi: 10.7554/eLife.64669 OpenUrl CrossRef PubMed 70. Zhang X , Kim B , Singh A , Sankararaman S , Durvasula A , Lohmueller KE . MaLAdapt Reveals Novel Targets of Adaptive Introgression From Neanderthals and Denisovans in Worldwide Human Populations . Mol Biol Evol . Jan 4 2023 ; 40 ( 1 ) doi: 10.1093/molbev/msad001 OpenUrl CrossRef PubMed 71. ↵ Yermakovich D , Andre M , Brucato N , et al. Denisovan admixture facilitated environmental adaptation in Papua New Guinean populations . Proc Natl Acad Sci U S A . Jun 25 2024 ; 121 ( 26 ): e2405889121 . doi: 10.1073/pnas.2405889121 OpenUrl CrossRef PubMed 72. ↵ Lemmink HH , Mochizuki T , van den Heuvel LP , et al. Mutations in the type IV collagen alpha 3 (COL4A3) gene in autosomal recessive Alport syndrome . Hum Mol Genet . Aug 1994 ; 3 ( 8 ): 1269 – 73 . doi: 10.1093/hmg/3.8.1269 OpenUrl CrossRef PubMed Web of Science 73. Storey H , Savige J , Sivakumar V , Abbs S , Flinter FA . COL4A3/COL4A4 mutations and features in individuals with autosomal recessive Alport syndrome . J Am Soc Nephrol . Dec 2013 ; 24 ( 12 ): 1945 – 54 . doi: 10.1681/ASN.2012100985 OpenUrl Abstract / FREE Full Text 74. ↵ Wagner CA , Unwin R , Lopez-Garcia SC , Kleta R , Bockenhauer D , Walsh S. The pathophysiology of distal renal tubular acidosis . Nat Rev Nephrol . Jun 2023 ; 19 ( 6 ): 384 – 400 . doi: 10.1038/s41581-023-00699-9 OpenUrl CrossRef PubMed 75. ↵ Gokhman D , Mishol N , de Manuel M , et al. Reconstructing Denisovan Anatomy Using DNA Methylation Maps . Cell . Sep 19 2019 ; 179 ( 1 ): 180 – 192 e10 . doi: 10.1016/j.cell.2019.08.035 OpenUrl CrossRef PubMed 76. Mishol N , Herzlinger G , Rak Y , Smilanksy U , Carmel L , Gokhman D. Candidate Denisovan fossils identified through gene regulatory phenotyping . Proc Natl Acad Sci U S A . Sep 2 2025 ; 122 ( 35 ): e2513968122 . doi: 10.1073/pnas.2513968122 OpenUrl CrossRef PubMed 77. Peyrégne S , Slon V , Kelso J. More than a decade of genetic research on the Denisovans . Nat Rev Genet . Feb 2024 ; 25 ( 2 ): 83 – 103 . doi: 10.1038/s41576-023-00643-4 OpenUrl CrossRef 78. ↵ Bonfante B , Faux P , Navarro N , et al. A GWAS in Latin Americans identifies novel face shape loci, implicating VPS13B and a Denisovan introgressed region in facial variation . Sci Adv . Feb 2021 ; 7 ( 6 ) doi: 10.1126/sciadv.abc6160 OpenUrl FREE Full Text 79. ↵ Gao H , Hamp T , Ede J , et al. The landscape of tolerated genetic variation in humans and primates . Science . Jun 2 2023 ; 380 ( 6648 ): eabn8153 . doi: 10.1126/science.abn8197 OpenUrl CrossRef 80. ↵ Gargano MA , Matentzoglu N , Coleman B , et al. The Human Phenotype Ontology in 2024: phenotypes around the world . Nucleic Acids Res . Jan 5 2024 ; 52 ( D1 ): D1333 – D1346 . doi: 10.1093/nar/gkad1005 OpenUrl CrossRef PubMed 81. ↵ Bennett EA , Crevecoeur I , Viola B , et al. Morphology of the Denisovan phalanx closer to modern humans than to Neanderthals . Sci Adv . Sep 2019 ; 5 ( 9 ): eaaw3950 . doi: 10.1126/sciadv.aaw3950 OpenUrl FREE Full Text 82. ↵ Kuderna LFK , Ulirsch JC , Rashid S , et al. Identification of constrained sequence elements across 239 primate genomes . Nature . Jan 2024 ; 625 ( 7996 ): 735 – 742 . doi: 10.1038/s41586-023-06798-8 OpenUrl CrossRef 83. ↵ Christmas MJ , Kaplow IM , Genereux DP , et al. Evolutionary constraint and innovation across hundreds of placental mammals . Science . Apr 28 2023 ; 380 ( 6643 ): eabn3943 . doi: 10.1126/science.abn3943 OpenUrl CrossRef PubMed 84. ↵ Enard W , Gehre S , Hammerschmidt K , et al. A humanized version of Foxp2 affects cortico-basal ganglia circuits in mice . Cell . May 29 2009 ; 137 ( 5 ): 961 – 71 . doi: 10.1016/j.cell.2009.03.041 OpenUrl CrossRef PubMed Web of Science 85. ↵ Lai CS , Fisher SE , Hurst JA , Vargha-Khadem F , Monaco AP . A forkhead-domain gene is mutated in a severe speech and language disorder . Nature . Oct 4 2001 ; 413 ( 6855 ): 519 – 23 . doi: 10.1038/35097076 OpenUrl CrossRef PubMed Web of Science 86. ↵ Sollis E , Mosaku A , Abid A , et al. The NHGRI-EBI GWAS Catalog: knowledgebase and deposition resource . Nucleic Acids Res . Jan 6 2023 ; 51 ( D1 ): D977 – D985 . doi: 10.1093/nar/gkac1010 OpenUrl CrossRef View the discussion thread. Back to top Previous Next Posted October 20, 2025. Download PDF Supplementary Material Email Thank you for your interest in spreading the word about bioRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. You are going to email the following A high-coverage genome from a 200,000-year-old Denisovan Message Subject (Your Name) has forwarded a page to you from bioRxiv Message Body (Your Name) thought you would like to see this page from the bioRxiv website. Your Personal Message CAPTCHA This question is for testing whether or not you are a human visitor and to prevent automated spam submissions. Share A high-coverage genome from a 200,000-year-old Denisovan Stéphane Peyrégne , Diyendo Massilani , Yaniv Swiel , Michael James Boyle , Leonardo N. M. Iasi , Arev P. Sümer , Alba Bossoms Mesa , Cesare de Filippo , Bence Viola , Elena Essel , Sarah Nagel , Julia Richter , Antje Weihmann , Barbara Schellbach , Hugo Zeberg , Johann Visagie , Maxim B. Kozlikin , Michael V. Shunkov , Anatoly P. Derevianko , Kay Prüfer , Benjamin M. Peter , Matthias Meyer , Svante Pääbo , Janet Kelso bioRxiv 2025.10.20.683404; doi: https://doi.org/10.1101/2025.10.20.683404 Share This Article: Copy Citation Tools A high-coverage genome from a 200,000-year-old Denisovan Stéphane Peyrégne , Diyendo Massilani , Yaniv Swiel , Michael James Boyle , Leonardo N. M. Iasi , Arev P. Sümer , Alba Bossoms Mesa , Cesare de Filippo , Bence Viola , Elena Essel , Sarah Nagel , Julia Richter , Antje Weihmann , Barbara Schellbach , Hugo Zeberg , Johann Visagie , Maxim B. Kozlikin , Michael V. Shunkov , Anatoly P. Derevianko , Kay Prüfer , Benjamin M. Peter , Matthias Meyer , Svante Pääbo , Janet Kelso bioRxiv 2025.10.20.683404; doi: https://doi.org/10.1101/2025.10.20.683404 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Genomics Subject Areas All Articles Animal Behavior and Cognition (7637) Biochemistry (17705) Bioengineering (13899) Bioinformatics (41970) Biophysics (21463) Cancer Biology (18605) Cell Biology (25526) Clinical Trials (138) Developmental Biology (13385) Ecology (19911) Epidemiology (2067) Evolutionary Biology (24329) Genetics (15615) Genomics (22514) Immunology (17743) Microbiology (40424) Molecular Biology (17194) Neuroscience (88650) Paleontology (667) Pathology (2835) Pharmacology and Toxicology (4827) Physiology (7648) Plant Biology (15160) Scientific Communication and Education (2046) Synthetic Biology (4302) Systems Biology (9825) Zoology (2271)