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Unlocking the origins and biology of domestic animals using ancient DNA and paleogenomics


Animal domestication has fascinated biologists since Charles Darwin first drew the parallel between evolution via natural selection and human-mediated breeding of livestock and companion animals. In this review we show how studies of ancient DNA from domestic animals and their wild progenitors and congeners have shed new light on the genetic origins of domesticates, and on the process of domestication itself. High-resolution paleogenomic data sets now provide unprecedented opportunities to explore the development of animal agriculture across the world. In addition, functional population genomics studies of domestic and wild animals can deliver comparative information useful for understanding recent human evolution.

The origins and evolution of domestic animals

Plant and animal domestication are justifiably considered to be major human cultural innovations that rank in importance with the manufacture of tools, the conquest of fire or the evolution of verbal language. V. Gordon Childe, one of the twentieth century’s greatest archaeologists, considered domestication to be “…that revolution whereby man ceased to be purely parasitic and, with the adoption of agriculture and stock-raising, became a creator emancipated from the whims of his environment” [1].

Homo sapiens is not alone in subverting the biology of another species through a process of domestication; leafcutter ant species maintain fungus “gardens” as a source of food [2], while other ant species exploit aphids in a semi-symbiotic interaction in which the ant colony gains honeydew and the aphids gain protection from other insect predators [3]. However, domestication of plants or animals by ancient human populations is categorically different from ant–fungus or ant–aphid mutualisms because it required intentionality and conscious planning and understanding of the behavior and reproductive biology of another species [4, 5]. Therefore, the cognitive demands of human-directed domestication constitute a phenomenon distinct from the interspecific mutualisms evolved by social insects [6, 7].

Wholesale domestication of plants and animals by humans, which began with the wolf (Canis lupus) at least 15 thousand years ago (kya) [8,9,10,11], was likely triggered by significant environmental and climatic change that accompanied the global transition from the Last Glacial Maximum (LGM) peak approximately 21 kya to the current Holocene interglacial period [12]. It has been proposed that intense climatic variability in the Late Pleistocene would have made food production extremely difficult, if not impossible [13,14,15]. Conversely, it has been hypothesized that, in the long run, plant and animal agriculture became “compulsory” in the relatively favorable climatic conditions of the Holocene [16], which commenced abruptly at 11.7 kya subsequent to the Younger Dryas, a short 1.2 kya pulse of marked cold and aridity [17]. Intensifying agricultural subsistence strategies during this period exerted pressure on smaller populations that retained less intensive foraging strategies. This generated a competitive ratchet that encouraged the spread of plant and animal agriculture [16]. The demographic pressure of increasing human populations has also been proposed as a causal factor for domestication, resulting in the gradual intensification of relationships between humans and animals over time and culminating in the substantial biological modifications observed in domesticates [6, 18].

The appearance of the domestic dog (Canis familiaris) in the archaeological record was followed relatively soon afterwards by crop and livestock domestication, which allowed humans to substantially augment the food they obtained from hunting and gathering. Consequently, during the Neolithic Transition—the archaeologically documented shift from hunter-gatherer modes of food production to plant cultivation and animal husbandry—increasingly sophisticated agricultural societies developed in multiple locations across Eurasia, North Africa and South and Central America [19, 20]. The zooarchaeology of Southwest Asia indicates that sheep (Ovis aries), goats (Capra hircus), humpless taurine cattle (Bos taurus) and pigs (Sus scrofa) were some of the first livestock to be domesticated, 10–11 kya in the Fertile Crescent region [4, 21, 22]. Approximately two millennia later, humped zebu cattle (Bos indicus) were domesticated, likely by the early Neolithic cultures located in present-day Baluchistan, Pakistan [4, 23]. Pigs were also separately domesticated about 8 kya in East Asia from a population of wild boar genetically distinct from those in Southwest Asia [4, 24]. The horse (Equus caballus) was domesticated on the Central Asian steppes approximately 5.5 kya [4, 25, 26], and the chicken (Gallus gallus) and cat (Felis catus) went down the same path about 4 kya in Southeast Asia and North Africa (Egypt), respectively [4, 27]. Domestication timelines are shown in Fig. 1 for a range of animal species with corresponding information on key climatic events during the last 20,000 years that likely influenced the emergence of agriculture.

Fig. 1

Timelines of domestication for 11 animal species with relevant stratigraphy and climate chronologies. For each species, the time periods of significant pre-domestication human–animal interactions are also shown. Domestication timeline data [4, 5]. Stratigraphy information was obtained from the International Commission on Stratigraphy website [264, 265]. The Quaternary temperature plot was generated from the GISP2 ice core temperature and accumulation data [266,267,268]

As a well-travelled ship’s naturalist in the 1830s, Charles Darwin enthusiastically observed, studied and catalogued more exotic flora and fauna than almost anyone else living at the time. However, he found the relatively mundane domestic animals of his native island equally fascinating. Darwin’s “long argument” for evolution via natural selection in On the Origin of Species was critically underpinned by the analogy between artificial selection of domestic breeds and natural selection in wild populations [28]. Indeed, it has been emphasized that Darwin “found his ‘laboratory’ in the fields and stalls of England” [29, 30]. Stephen Jay Gould, one of the most prolific essayists on Darwinian evolution and biogeography, has noted that the Galápagos finches (Geospiza spp.) were not actually discussed in On the Origin of Species, and that “…the ornithological star of that great book is the domesticated pigeon” [31]. During the last three decades, studies encompassing molecular population genetics, ancient DNA (aDNA), population genomics and, more recently, paleogenomics, have provided strong support for Darwin’s contention that domestic animal populations and domestication from wild progenitors represent fantastic models for understanding evolutionary processes at a broader level and over longer timescales [32,33,34,35,36,37]. Fig. 2 shows evolution and phenotypic diversity of domestic animals and corresponding wild ancestral or congener species.

Fig. 2

Evolution and phenotypic diversity of domestic animals. The wild progenitor species are shown on the left and the domesticated animals are shown on the right. Except for the aurochs, all wild progenitor species are extant. The aurochs image is an artistic reconstruction of Bos primigenius. Image permissions: wolf (Creative Commons CC BY-SA 4.0); dog (CC BY-SA 2.5); bezoar (ID 79845213©Wrangel |; goat (CC BY-NC 2.0 - Fir0002/Flagstaffotos); aurochs and taurine bull (CC BY-SA 3.0); wild boar (CC BY-SA 3.0); pig (public domain), red jungle fowl (CC BY-SA 3.0); and chicken (CC BY-NC 2.0 - Fir0002/Flagstaffotos)

The primary goal of this review is to demonstrate how paleogenomics is revolutionizing our understanding of the origins and biology of domestic animals, including both livestock and companion animals. During the last 10 years there has been an explosion of interest in domestic animal aDNA as sequencing technologies suitable for paleogenomics have become increasingly powerful. We therefore focus on several studies that illustrate the relatively long history of aDNA research in livestock and companion animals. We also use notable published examples to show how paleogenomics is shedding new light on the phylogeography of domestic animals and improving our understanding of the physiological and neurobiological effects of domestication and microevolution of functional traits. In addition, we demonstrate that understanding the genetic origins and spread of domestic animals through analysis of aDNA and paleogenomes can provide new insights into human history, migration and trade. Finally, we propose that paleogenomics and population genomics studies of domestic animals can provide valuable comparative information concerning the paleogenomics and evolutionary history of anatomically modern humans (H. sapiens), particularly their interactions with related hominins such as Neanderthals (Homo neanderthalensis) and Denisovans (Homo denisova).

Ancient DNA: the beginnings and early studies in domestic animals and related species

Scientists have long speculated about systematically analyzing ancient biomolecules, particularly information-rich molecules such as DNA and proteins (for an early review see [38]). This became technically feasible for aDNA in the early 1980s, albeit through cumbersome molecular cloning methods [39, 40], which ultimately proved unreliable—notably generating spurious DNA sequences from a 2400-year-old Egyptian mummy [40]. A significant breakthrough in the late 1980s was amplification of aDNA from archaeological material and museum specimens using the polymerase chain reaction (PCR) technique, which had recently been developed [41,42,43,44]. However, it was also during this time that the significant challenges associated with retrieval of reliable and reproducible aDNA data first began to be appreciated [38, 41, 43, 45]. Consequently, almost from the very beginning, the aDNA field has been beset with significant methodological obstacles including post-mortem damage to preserved biomolecules, contamination of samples and reagents by modern DNA and the presence of inhibitors of enzymatic reactions; all factors that can irrevocably comprise the authenticity and reproducibility of aDNA amplified from archaeological samples [38, 45,46,47,48,49,50]. However, over the last four decades, as the field of archaeogenetics has matured, scientists have systematically addressed the technical challenges associated with retrieving aDNA from long-dead organisms and it is now well established that vertebrate subfossils can yield authentic and reproducible endogenous molecular genetic information.

The aDNA field has had a long-standing interest in understanding the evolution and biology of domestic animals and their wild relatives [51,52,53,54,55]. The subject of the very first aDNA study published 35 years ago [39] was the quagga (Equus quagga quagga), an African equid related to the domestic horse (Equus caballus) that was hunted to extinction by the end of the nineteenth century. This work was performed in the pre-PCR era and involved molecular cloning of DNA fragments from dried tissue attached to a quagga skin from a German museum collection. Bacterial colonies containing λ phage vector inserts with mitochondrial DNA (mtDNA) were identified using a mtDNA probe from the mountain zebra (Equus zebra) [39]. Following this, two short 117 bp and 112 bp quagga mtDNA clones were sequenced and placed in a phylogeny with mtDNA data from other mammals, thereby opening a whole new scientific discipline of evolutionary archaeogenetics.

The embryonic aDNA field languished as an intellectual curiosity for much of the 1980s; however, this changed rapidly with the introduction of the PCR amplification technique, which kickstarted aDNA research, particularly through work driven by Svante Pääbo and published across a series of seminal papers in 1988 and 1989 [41,42,43,44]. Roughly at the same time, parallel work at the University of Oxford by Erika Hagelberg and colleagues showed that aDNA could be retrieved, amplified and analyzed from hard tissues such as bone, which would prove a major boon to the emerging field of molecular archaeology [56,57,58]. A critical aspect of this work involved retrieval of mtDNA sequences from a 445-year-old domestic pig bone to verify that endogenous DNA could be amplified from hard tissues [57]. In 1990, a French group showed that DNA could also be extracted and analyzed from mammalian teeth [59], again an important technological breakthrough for archaeogenetics in domestic animals.

In common with studies on humans and other vertebrates, the first ancient DNA studies of domestic animals and related species in the 1990s and early 2000s were focused almost exclusively on mtDNA, particularly the hypervariable displacement loop (D-loop) or control region (CR) sequence [51,52,53,54,55, 60,61,62,63,64]. In many respects, mtDNA was ideally suited for the early “proof-of-principle” aDNA-based evolutionary studies: there are hundreds or even thousands of copies in a single animal cell [65] and mtDNA has a markedly higher mutation rate than the nuclear genome [66,67,68]. It is important to keep in mind that mtDNA represents only a single, non-recombining, maternally transmitted locus. However, PCR amplification of mtDNA from domestic animal subfossils and comparative analyses with extant populations led to some landmark papers and important discoveries, examples of which are described below.

In 1996, Jillian Bailey and her colleagues were the first scientists to recover and analyze ancient DNA from an extinct progenitor of a domestic species, when they sequenced mtDNA from aurochs (Bos primigenius), wild cattle that ranged across Eurasia during the Pleistocene and early Holocene [51]. A subsequent study in 2001 corroborated these results with additional ancient mtDNA CR sequence data and also posited a scenario where European aurochs did not contribute to the gene pool of domestic cattle [54]—a hypothesis later disproved by the same group using aurochs nuclear DNA sequence data [69]. The first study of ancient DNA in domestic horses, also published in 2001, used comparative analyses of modern equine mtDNA CR data with sequences from pre-domestic permafrost specimens and Viking-era bones to show extensive retention of diverse ancestral matrilines [55]. These results led the authors to propose a model where domestication was an ongoing process from the late Chalcolithic period through the Bronze Age as the technology for capturing, taming and rearing wild-caught horses disseminated across Central Asia.

In 2002, a comprehensive domestic dog aDNA study was published; using South American and Alaskan specimens that predated European contact, Jennifer Leonard and coworkers showed that mtDNA CR sequence analysis supported the hypothesis that ancient American and Eurasian domestic dogs share a common origin from Old World gray wolves (C. lupus) [52]. The first chicken aDNA study ignited a firestorm among archaeologists and paleogeneticists [70]; the authors of this work proposed that mtDNA CR sequence from an archaeological site in Chile provided firm evidence for a pre-Columbian Polynesian introduction of domestic chickens (G. gallus) to South America. Additional results from a larger survey of chicken aDNA samples provided support for this hypothesis [71]. However, independent analyses of ancient and modern chicken mtDNA CR sequences robustly disputed this conclusion with suggestions of sloppy laboratory techniques and modern contamination [72, 73], leading inevitably to heated scientific correspondence among the main protagonists [74,75,76,77].

As was the case with human archaeogenetics, and population genetics in general, the overreliance on uniparental genetic markers such as mtDNA and Y chromosome polymorphisms led to evolutionary inferences and phylogeographic and demographic reconstructions that, in the long term, could be misleading and generally not robust or well-supported [78,79,80]. These problems became particularly apparent once high-resolution data became available from the autosomal genome in the form of single-nucleotide polymorphisms (SNPs) and ultimately whole-genome sequence (WGS) data [81,82,83,84,85,86,87]. The first phase of aDNA research in domestic animals, therefore, will be remembered for providing tantalizing glimpses of what would ultimately be possible; however, dramatic new technological developments would be required to deliver this ambition.

Technology advances: deep sequencing + dense bones = paleogenomics

It has long been realized that performing archaeogenetics research correctly is extremely difficult [38, 45, 46, 48,49,50]. However, by the same token, during the last three decades the challenging nature of aDNA research has spurred significant technical innovation and rapid deployment of state-of-the-art genomics and ancillary technologies [46, 50, 88,89,90,91,92,93]. Undoubtedly, the most important scientific advance was the introduction of high-throughput sequencing (HTS) to archaeogenetics [94,95,96,97]. High-throughput sequencing technologies have been commercially available since 2005 [98] and between 2007 and 2019 there has been an almost 100,000-fold reduction in the raw, per-megabase (Mb) cost of DNA sequencing [99]. Currently, the dominant commercial HTS technology is based on massively parallel sequencing-by-synthesis of relatively short DNA segments [100, 101], which is ideally suited to fragmented aDNA molecules extracted from archaeological and museum specimens. In addition, the vast quantities of sequence data generated—literally hundreds of gigabases (Gb) from a single instrument run—can facilitate cost-effective analyses of archaeological specimens containing relatively modest amounts of endogenous aDNA (for technical reviews see [89,90,91,92,93, 102]).

The introduction of HTS and ancillary specialized methods for sample treatment, aDNA extraction, purification and library preparation have represented a genuinely transformative paradigm shift in archaeogenetics. It has ushered in the era of paleogenomics and the capacity to robustly genotype, analyze and integrate SNP data from thousands of genomic locations in purified aDNA from human and animal subfossils [103,104,105,106,107,108,109,110,111,112,113]. In a comparable fashion to human archaeogenetics [84], the first HTS paleogenomics studies of domestic animals or related species were focused on a single or a small number of “golden samples” [10, 69, 109, 114, 115].

One of the first HTS studies directly relevant to domestic animals was a technical tour de force which pushed the time frame for retrieval of aDNA and reconstruction of paleogenomes beyond 500 kya to the early stages of the Middle Pleistocene [109]. In this study, Ludovic Orlando and colleagues were able to generate a 1.12× coverage genome from a horse bone excavated from permafrost at the Thistle Creek site in north-western Canada and dated to approximately 560–780 kya. Using this Middle Pleistocene horse genome in conjunction with another ancient genome from a 43 kya Late Pleistocene horse, and genome sequence data from Przewalski’s horse (Equus ferus przewalskii), the donkey (Equus asinus) and a range of modern horses, these authors showed that all extant equids shared a common ancestor at least four million years ago (mya), which is twice the previously accepted age for the Equus genus. They also showed that the demographic history of the horse has been profoundly impacted by climate history, particularly during warmer periods such as the interval after the LGM (Fig. 1), when population numbers retracted dramatically in the 15 millennia prior to domestication 5.5 kya. Finally, by focusing on genomic regions exhibiting unusual patterns of derived mutations in domestic horses, it was possible to tentatively identify genes that may have been subject to human-mediated selection during and after domestication [109].

The origins of the domestic dog (C. familiaris) and the dispersal of dogs across the globe during the Late Pleistocene and Holocene periods have been extremely contentious, particularly as population genetic, archaeogenetic and paleogenomic data sets have accumulated during the last two decades [8, 116, 117]. Again, like the Thistle Creek horse bone, a small number of key subfossil specimens have provided critical paleogenomic evidence concerning the evolutionary origins of domestic dogs and their genetic relationships with Late Pleistocene Eurasian wolf populations [10, 11, 115]. Pontus Skoglund and colleagues were able to generate a low coverage (~ 1×) nuclear genome from a 35 kya wolf (C. lupis) from the Taimyr Peninsula in northern Siberia [115]. Analysis of this Taimyr specimen with WGS data from modern canids showed that this ancient wolf belonged to a population that was genetically close to the ancestor of modern gray wolves and dogs. The results supported a scenario whereby the ancestors of domestic dogs diverged from wolves by 27 kya, with domestication happening at some point subsequent to that event. In addition, this study provided compelling evidence that high-latitude dog breeds such as the Siberian Husky trace some of their ancestry back to the extinct wolf population represented by the Taimyr animal [115].

Another important paleogenome study, published one year after the Taimyr wolf paper, described a high coverage (~ 28×) nuclear genome from a late Neolithic (4.8 kya) domestic dog specimen from Newgrange, a monumental passage grave tomb in eastern Ireland [10]. Analyses of the ancient Newgrange dog genome, additional mtDNA genomes from ancient European dogs and modern wolf and dog genome-wide SNP data suggested that dogs were domesticated independently in the Late Pleistocene from distinct East and West Eurasian wolf populations and that East Eurasian dogs, migrating alongside humans at some time between 6.4 and 14 kya, partially replaced indigenous European dogs [10]. In 2017, following publication of the Newgrange dog genome, Laura Botigué and colleagues generated two ~ 9× coverage domestic dog nuclear genomes from Early (Herxheim, ~ 7 kya) and Late (Cherry Tree Cave, ~ 4.7 kya) Neolithic sites in present-day Germany [11]. Comparison of these two ancient dog genomes with almost 100 modern canid whole genomes and a large genome-wide SNP data set of modern dogs and wolves did not support the dual domestication hypothesis proposed by Frantz et al. one year earlier [10], or the suggested East Eurasian partial replacement of Late Paleolithic or Early Neolithic European dogs.

The origins and fate of the domestic dog populations of the Americas prior to contact with European and African peoples has been the subject of a recent paleogenomics study involving comparisons of ancient and modern dogs. Máire Ní Leathlobhair and colleagues sequenced 71 mitochondrial and seven nuclear genomes from ancient North American and Siberian dogs [118]. Comparative population genomics analyses of these data demonstrated that the first American domestic dogs did not trace their ancestry to American wolves. Instead, however, these pre-contact American dogs (PCDs) represent a distinct lineage that migrated from northeast Asia across the Beringian Steppe with humans more than 10 kya [118]. These analyses also demonstrated that PCD populations were almost completely replaced by European dogs due to large-scale colonization of North and South America within the last 500 years. In a similar fashion to the post-contact human demographic transition in the Americas [119, 120], the authors hypothesize that infectious disease likely played a major role in the replacement of PCDs by European dogs. Finally, they also show that the genome of the canine transmissible venereal tumor (CTVT) cancer lineage, which has evolved to become an obligate conspecific asexual parasite [121], is the closest genomic relative of the first American dogs.

As has been previously noted, understanding the origins and early domestic history of dogs has been complicated by population bottlenecks, expansions, local extinctions and replacements and geographically localized gene flow among wolves and dogs and genetically distinct dog populations [8]. It will, therefore, require systematic large-scale retrieval and analysis of ancient wolf and dog genomes across space and time to accurately reconstruct the evolutionary history of the first animal domesticate [122]. However, this and similar undertakings for other domestic species will be greatly facilitated by another recent technical breakthrough that is described below.

In 2014, a team of Irish geneticists and archaeologists showed that the petrous portion of the temporal bone—the densest bone in the mammalian skeleton—produced the highest yields of endogenous DNA; in some cases, up to 183-fold higher than other skeletal elements [123]. The impact of this discovery has been such that the ancient DNA community now dub the period prior to 2014 “BP” (“before petrous”) [124]. During the last 5 years, DNA extraction from petrous bones, coupled with constantly improving HTS and ancillary technologies, has led to a dramatic scale-up of human archaeogenetics, the cutting edge of which is now the statistically rigorous field of high-resolution population paleogenomics [82, 125,126,127,128,129]. Another notable outcome has been a substantial increase in the proportion of the Earth’s surface area where archaeological excavation can uncover suitable material for successful aDNA extraction and paleogenomics analysis. Previously, for the most part, aDNA research has been confined to regions of the globe where climate and topography were conducive to taphonomic preservation of skeletal DNA (Fig. 3) [90, 130]. However, in recent years human paleogenomics studies have been successfully conducted using samples from arid, subtropical and even tropical zones [131,132,133,134,135,136,137,138,139,140,141,142].

Fig. 3

Geography of archaeological DNA survival prior to the discovery of high endogenous DNA content in the mammalian petrous bone. a Expected DNA survival after 10,000 years for 25-bp fragments and 150-bp fragments close to the ground surface (modified with permission from [90]). b Illustration of a sheep (Ovis aries) petrous bone retrieved from a Middle Neolithic site at Le Peuilh, France (modified with permission from [269])

Expanding the canvas: population paleogenomics in domestic animals

Domestic animal paleogenomics has generally followed in the wake of human archaeogenetics and during the last 2 years the first large-scale population-level surveys of ancient livestock genomes have begun to appear [143,144,145,146]. This has led to a marked increase in the number of sequenced paleogenomes from domestic animals and their progenitors and congeners (Fig. 4).

Fig. 4

Stacked bar chart and line graph showing the number of ancient samples with whole-genome sequence data (paleogenomes) from domesticated species and their wild relatives. Each genus is represented by a different color and the line indicates the total number of paleogenomes generated. The graph was produced in R using ggplot2 (data from [10, 11, 69, 109, 114, 115, 118, 143,144,145,146, 169, 191])

Kevin Daly and colleagues were able to generate genome-wide sequence data from four pre-domestic goats (bezoars—Capra aegagrus) and 47 domestic goats (C. hircus) excavated from sites traversing Southeastern Europe and the Near East and spanning almost 50,000 years from the mid-Upper Paleolithic (> 47 kya) to the early modern period (~ 0.5 kya). It is also notable that many of these goat subfossils were petrous bones excavated from archaeological sites where summer temperatures regularly exceed 35 °C. The diversity of bezoar and goat mtDNA and nuclear genomes across Southeastern Europe and the Near East supports the hypothesis that goat domestication in the Near East took place over an extended period of time and in a spatially dispersed manner, which is contrary to a simplified Vavilovian model of a single core domestication zone with radial dispersal of early domesticates. These observations mirror paleogenomics data from early Neolithic farmers, which also show discontinuous genomic diversity across the region [133, 147,148,149].

From a functional population genomics perspective, detection of outlier genomic loci exhibiting signatures of selective sweeps identified several plausible candidate genes that may have undergone rapid microevolution during and soon after goat domestication. Prominent among these were genes for pigmentation proteins such as the KIT proto-oncogene receptor tyrosine kinase (encoded by KIT) and KIT ligand (encoded by KITLG). Early human-mediated selection at these loci may have been to facilitate visual recognition of individual animals, or as a pleiotropic consequence of breeding for behavioral traits such as tameness (see the following section). In addition to pigmentation and other signals associated with growth and reproduction, Daly and colleagues identified an intriguing selection signature centered on the caprine ortholog of the human cytochrome P450, family 2, subfamily C, polypeptide 19 gene (CYP2C19), which has been implicated in metabolism of a mycotoxin produced by Fusarium spp. that cause Fusarium ear blight disease in cereals. They hypothesized, therefore, that a caprine CYP2C19 variant that protects against this toxin would have been under positive selection in response to a diet containing increasing amounts of cereal waste byproducts [143].

Additional high-resolution population-level studies of domestic and wild paleogenomes have recently been published that illustrate the power of this approach in providing new insight on the origins, biogeography and functional biology of mammalian livestock [144,145,146]. For example, Antoine Fages and colleagues analyzed a very large genome-wide sequence data set generated from 278 domestic equid subfossils that span the last 6000 years [144]. A notable outcome from this work is strong support for the hypothesis that the advent of agricultural mechanization and motorized transport led to a marked decrease in genomic diversity of modern horses compared to populations that existed prior to the Industrial Revolution. Examining patterns of genomic variation further back in time also revealed that the influence of Persian-derived lineages increased following the expansions of Islamic cultures in the second half of the first millennium CE. In addition, evaluation of positive selection using population branch statistics showed that by the second millennium CE there was evidence for significant changes in genes regulating skeletal development and anatomy. Finally, this study uncovered two additional horse lineages that existed during the fifth millennium BCE at the northeastern and southwestern extremities of Eurasia, but which became extinct with minimal genetic contributions to modern domestic horses.

A similarly in-depth study of domestic and wild paleogenomes but with a geographical focus on the Fertile Crescent and surrounding regions has also shed new light on the domestic origins and spread of cattle during the Neolithic period and in subsequent millennia [146]. Using WGS data from 67 ancient cattle, including six aurochs (B. primigenius) specimens and genome-wide SNP data from modern cattle, Marta Verdugo and her colleagues were able to investigate the domestic history and microevolution of cattle across nine millennia beginning at the latter stage of the seventh millennium BCE. They showed that there was significant male-mediated gene flow from arid-adapted zebu cattle (B. indicus) into the greater Near East, which commenced with a multi-century period of drought that began 4.2 kya and marks the beginning of the recently ratified Meghalayan stage of the Holocene Epoch [150]. In addition, analyses of WGS data from ancient domestic cattle that inhabited the southern Levant and a Moroccan aurochs specimen dated to approximately 9 kya demonstrated that a distinct subpopulation of aurochs ranged across the Levant and the North African littoral. This led the authors to hypothesize that the previously recognized genetic distinctiveness of African B. taurus cattle [54, 151, 152] may stem from roots in the southern Fertile Crescent.

Laurent Frantz and his colleagues have recently published the first comprehensive population paleogenomics study of wild and domestic pigs in the Near East and Europe [145]. Using 63 nuclear paleogenome data sets in conjunction with mtDNA sequences from more than 2000 modern and ancient animals, they were able to reconstruct a detailed genetic history for S. scrofa in western Eurasia over the last 14 millennia. The most notable outcome from this work was confirmation that the domestic pig populations that have inhabited mainland Europe for approximately 8 kya have undergone a complete genomic turnover via gene flow from indigenous wild boars that was particularly rapid during the centuries after first contact. This process had been suggested by earlier studies of modern and ancient mtDNA [63] and by medium-density SNP array data from European and Near Eastern wild boar and three European domestic pig populations [153]. However, it required the extensive paleogenomics data generated by Frantz et al. [145] to tease out the chronology and dynamics of admixture between wild boar and the early domestic pig populations of Europe.

The functional impact of wild boar introgression was also assessed through comparative analyses of haplotypes previously reported to have been subject to human-mediated selection [24]. These analyses demonstrated that the small proportion of retained Near Eastern genomic ancestry in modern European pigs has not been specifically targeted by selective breeding. One exception to this general trend, however, may be the D124N variant of the melanocortin 1 receptor protein (encoded by MC1R) associated with black (or black and white spotted) pigmentation in many western Eurasian domestic pig breeds. This non-camouflage coat-color phenotype has been maintained in the face of substantial gene flow from wild boar and phylogenetic analyses of the genomic region surrounding MC1R led Frantz and colleagues to hypothesize an origin for the D124N variant in Anatolian domestic pigs more than 8 kya [145].

Interrogating paleogenomes to understand the biology of animal domestication

The vanguard of high-resolution surveys of livestock paleogenomes described in the previous section signpost the future of archaeogenetics in domestic animals. They point towards high-resolution studies across time and space that will reveal the genetic architecture of animal domestication and the physiological and neurobiological changes that occur as livestock and companion animals are brought under human control and subject to long-term reproductive management and artificial selection. It is likely that high-resolution surveys of pre-domestic and early animal paleogenomes will provide important new information on intriguing features of domestic animals and the domestication process that were first highlighted by Charles Darwin more than 150 years ago [154].

Because of his interest in human-mediated breeding and selection, Darwin had spent many years studying behavioral, physiological and morphological traits in domestic animals. He observed that the diverse range of domesticated mammals—rodents, lagomorphs, carnivores, artiodactyls and perissodactyls—exhibit a shared collection of developmental, anatomical, physiological and behavioral traits that set them apart from wild mammals. This “domestication syndrome” now encompasses a catalogue of biological features that include pedomorphosis with increased tameness and docility; reduction in sexual dimorphism; modifications to craniofacial morphology and decreased brain size; dramatic coat color variation and depigmentation; non-erect floppy and small ears; and alterations of the endocrine system with significant changes to female reproductive physiology, particularly frequent and nonseasonal estrus cycles [155,156,157].

As an explanatory framework for a deeper understanding of this phenomenon, it has been hypothesized [158,159,160,161] that domestication has selected for pre-existing and novel genomic variants that perturb the gene regulatory networks (GRNs) underpinning ontogeny of the myriad tissues and anatomical structures derived from the vertebrate neural crest stem/progenitor cell population [162,163,164]. The neural crest hypothesis proposes that traits associated with the domestication syndrome have a shared developmental basis. This is due to the role of stem cells from the crest or dorsal edge of the neural tube of vertebrate embryos, which ultimately form or influence a range of anatomical features, and neurobiological and physiological processes [161]. The neural crest hypothesis has recently been supported by comparative studies of whole-genome sequence and SNP data from domestic dogs, cats and foxes (Vulpes vulpes) and their wild counterparts [165,166,167,168]. These studies demonstrated that some of the genes in these species that exhibit signatures of selection due to domestication are embedded in the GRNs that determine the fate of neural crest cells during early embryonic development.

To date, only one in-depth paleogenomics study has provided convincing evidence in support of the neural crest hypothesis. Pablo Librado and colleagues examined a series of 14 Central Asian domestic horse paleogenomes spanning the Bronze and Iron Ages between 4.1 and 2.3 kya [169]. They applied a novel statistical method based on levels of exclusively shared differences (LSD) for genome-wide selection scans that can identify loci that underwent selection in a population with high sensitivity and specificity [170]. Comparisons of the Bronze and Iron Age horse paleogenomes with groups of pre-domestic, modern domestic and Przewalski’s horse (E. f. przewalskii) using the LSD method identified genes positively selected during the early domestication process. Genes detected as enriched by this approach included genes related to ear shape, neural crest cell morphology, neural mesenchyme and neural crest-derived neurons involved with movement, learning and reward [169]. In particular, these analyses highlighted the treacle ribosome biogenesis factor 1 (TCOF1), KIT ligand (KITLG) and fibroblast growth factor receptor 1 (FGFR1) genes associated with neural crest cell development and regulation. In the coming years, it is likely that high-resolution surveys of paleogenomes across time and space in other species will shed further light on the role of neural crest cell GRN perturbation in animal domestication. It should also be possible to determine if this process is universal across mammalian livestock and companion animals, and whether it also extends to other domestic vertebrates such as birds and fish [161].

Based on progress during the past decade, paleogenomics combined with comparative evolutionary genomics will provide a deeper understanding of the genetic architecture, neurobiology and physiology of mammalian domestication [33,34,35,36,37]. In this regard, it has been proposed that treating modern humans as “self-domesticated” could provide a new avenue to understanding both early and recent human evolution [171,172,173]. Unsurprisingly, the original idea that modern humans are self-domesticated can also be attributed to Charles Darwin; however, he remained equivocal as to whether the unusual biology of our species could really be associated with the same processes that gave rise to domestic animals [174]. In addition, later scientists were generally hostile to the concept; for example, in 1962, Theodosius Dobzhansky wrote “… ‘domestication’ of man is too vague an idea to be scientifically productive” [175]. Recently, however, as the field of domestication studies has advanced, the hypothesis of human self-domestication is increasingly being revisited—particularly with regards to the evolution of prosociality and language [176,177,178,179,180,181]. The rapid accumulation of paleogenomes from early domestic animals, and anatomically modern humans, Neanderthals and Denisovans, would therefore suggest that the self-domestication hypothesis can finally be rigorously tested and assessed using high-resolution comparative genomics.

Another feature of domestication that has been explored using population genomics and paleogenomics of livestock and companion animal populations is the documented increase in deleterious genetic variation that has been termed the “cost of domestication” [182, 183]. The intellectual roots of this concept can again be traced back to Charles Darwin and also to Alfred Russel Wallace, both of whom suggested that the benign “conditions of life” for domestic animals may ultimately have negative consequences in terms of evolutionary fitness [154, 184]. Prior to the genomics era, theoretical population genetics models predicted domestication and artificial selection would lead to accumulation of deleterious alleles and an increase in the genetic load through genetic hitchhiking [185], population bottlenecks that negatively affect purifying selection [186] and reductions in locus-specific effective population size [187].

In recent years, comparisons of genome sequence data from domestic dogs, yaks (Bos grunniens), rabbits (Oryctolagus cuniculus) and chickens with their wild congeners have supported the cost of domestication hypothesis [188,189,190]. Again, equine studies have led the way in investigating the cost of domestication using paleogenomics data. Mikkel Schubert and colleagues compared two ancient pre-domestic Asian horse genomes sequenced to relatively high coverage (7.4× and 24.3×) with modern genomes. They observed significantly increased deleterious mutation loads in the extant genomes that could not simply be attributed to increased rates of inbreeding in present-day horse populations [114]. It is important to note, however, that more extensive tracking of genomic variation across time has shown that the mutational load in modern horses has accumulated relatively recently, presumably because of selective breeding practices that have become increasingly sophisticated over the centuries [144, 169, 191].

Notwithstanding the general pattern observed for other species, European pigs seem to have escaped the genetic load imposed by domestication and artificial selection through long-term gene flow from wild boar and more recent admixture with East Asian pig populations [190]. This leads us to the next important contribution of paleogenomics to understanding the origins and genetic history of domestic animals.

Multiple melting pots: reticulate gene flow and admixture in domestic animals

The 2010 paper [103] from Svante Pääbo’s group describing the draft Neanderthal nuclear genome—a seminal contribution to our understanding of recent human evolution—was followed swiftly the same year by publication of the Denisovan genome, which was arguably even more revelatory [105]. Comparative analyses of these paleogenomes provided surprising but convincing evidence of reticulate gene flow and admixture between these archaic groups and anatomically modern humans during the Late Pleistocene [103, 105]. Additional Neanderthal and Denisovan genome sequence data have been assembled over the past decade, some of which are at sufficiently high depth for functional population genomics investigations of adaptive and maladaptive introgression into modern human populations (for reviews see [129, 192,193,194,195,196]). It is now well established that people outside of sub-Saharan Africa exhibit varying but consistently detectable genomic signatures of admixture with these archaic hominins [82, 126, 129, 192, 194,195,196]. In addition, introgression of Neanderthal and Denisovan protein-coding gene segments and genomic regulatory elements (GREs) has had functional consequences, the textbook example being positive selection of a Denisovan haplotype of the endothelial PAS domain protein 1 gene (EPAS1) for altitude adaptation in Tibetan human populations [197].

In a comparable fashion to studies of modern and archaic humans, high-resolution population genomics and paleogenomics have begun to demonstrate that the evolutionary origins and genetic history of domestic animals are generally more complex and scientifically intriguing than the relatively simplistic scenarios originally posited using small numbers of uniparental genetic markers and autosomal polymorphisms [8, 25, 33,34,35,36, 198]. An early and instructive example derives from relatively comprehensive surveys of a single uniparental marker (mtDNA) in extant cattle populations [151, 199, 200]. This work clearly demonstrated the substantial evolutionary divergence between B. taurus (taurine) and B. indicus (zebu) cattle that had previously been hinted at by protein polymorphism data [201, 202]. However, the early focus on mtDNA meant that detecting and disentangling sex-biased hybridization and extensive zebu–taurine admixture in African and Middle Eastern cattle populations only became possible with the availability of both modern and ancient nuclear genetic marker data [146, 152, 203,204,205]. Fig. 5 shows patterns of admixture between taurine and zebu cattle in Africa at geographic, population and genomic scales. In this regard, the estimated evolutionary divergence between the B. taurus and B. indicus lineages, at 0.2–0.5 kya [206,207,208] suggests that taurine–zebu hybridization and adaptive introgression may ultimately provide a useful genomic framework for understanding admixture and subchromosomal local ancestry in other mammalian species, including archaic hominins and anatomically modern humans. For example, mitonuclear interactions with biochemical and physiological impacts, which can be examined at high resolution in hybrid African cattle (Fig. 5), have also recently been described in admixed modern human populations [209] and for maladaptive Neanderthal haplotypes at human nuclear loci [210].

Fig. 5

Taurine–zebu admixture and genomic introgression in hybrid African cattle. a Interpolated synthetic map illustrating spatial distribution of admixture, which is generated from the first principal component (PC1) of a principal component analysis (PCA) of genetic variation across African cattle populations (modified with permission from [205]). b Genetic structure plot generated from high-density SNP data (Illumina BovineHD BeadChip with 777,962 SNPs) showing individual animal proportions assuming two source populations (N’Dama, n = 24; East African Zebu, n = 92; Nellore, n = 34) (the authors, unpublished results). The structure plot was generated using fastSTRUCTURE [270] and visualised using DISTRUCT [271]. c Chromosomal local ancestry plot for bovine chromosome 7 (BTA7) showing Bos taurus and Bos indicus ancestry in East African Zebu cattle (the authors, unpublished results). Nuclear oxidative phosphorylation (OXPHOS) genes are highlighted, illustrating the potential of admixed cattle for evaluating mitonuclear disequilibria. The plot was generated using the efficient local ancestry inference (ELAI) method [272]

The problems associated with overreliance on mtDNA sequence diversity data are also encapsulated in one of the first aDNA studies of ancient wild cattle, which concluded that native European aurochs (B. primigenius) did not contribute to the gene pool of domestic cattle [54]. However, it was only when WGS data became available from a pre-domestic northern European aurochs that a more nuanced scenario of localized gene flow became apparent [69, 211]. In our opinion, therefore, once paleogenomic data are assembled for wild and early domestic cattle across Eurasia, this pattern will crystallize into a spatio-temporal mosaic of reticulate aurochs admixture and introgression that may have profound consequences for understanding phenotypic diversity in modern cattle populations. Fig. 6 illustrates this model, which may also be applicable to other domestic livestock as they migrated with early agriculturalists and encountered related wild species. For example, the recent work of Verdugo and colleagues described above that encompassed analyses of cattle paleogenomes from the Fertile Crescent and surrounding areas revealed an intricate pattern of admixture and introgression over time [146].

Fig. 6

Reticulate evolution in European wild aurochs and domestic cattle. a Geographic contour map of localized ancient British aurochs (Bos primigenius) genomic admixture with modern European cattle breeds (modified from [69] under the terms of the Creative Commons Attribution 4.0 International License, b Spatio-temporal model of historical admixture and gene flow in European cattle populations

Complex reticulate evolutionary histories have come into focus for other domestic animals and wild congeners during the past decade—over both long and short evolutionary timescales [10, 24, 115, 206, 208, 212,213,214,215,216,217,218,219,220,221,222]. In a remarkable example of convergent adaptive introgression—mirroring ancient genetic exchange between Denisovans and humans—a canine EPAS1 variant from altitude-adapted gray wolves has been selected in mastiff dogs that have inhabited the Tibetan Plateau for hundreds of years [215, 216].

Domestic pigs, wild boar and other suid species also have a highly complex reticulate and multilayered history of intraspecific and interspecific admixture [223, 224]. In the first instance, genome sequence data have provided convincing evidence for ancient admixture and gene flow over a relatively long timescale among S. scrofa and other Sus spp. across the islands and mainland of Southeast Asia where the group first evolved more than 4 mya [219, 225]. Secondly, two separately domesticated major west and east Eurasian lineages of domestic pigs share a common ancestor more than 1 mya [221, 225, 226] and have been subject to extensive human-mediated crossbreeding to enhance traits of commercial interest, particularly in northern European production pig breeds [221, 227,228,229,230,231]. Thirdly, since the early Neolithic, the genetic composition of pig populations across Eurasia has been profoundly influenced by recurrent gene flow from wild boar [24, 63, 232,233,234,235,236,237]. In particular, analyses of aDNA from archaeological material have shown that there was mtDNA turnover with wild boar as early domestic pigs migrated into Europe during the Neolithic [63, 235, 237]. Finally, an additional layer of complexity became evident with detection of back migration and introgression of European mtDNA haplotypes into Bronze and Iron Age Middle Eastern domestic pig populations [236,237,238,239]. It is important to note, however, that the complex genetic history and biogeography of domestic pigs during the Holocene will only become understood with detailed spatio-temporal paleogenomics data from across Eurasia and beyond. In this regard, the recent study by Frantz and colleagues described above is an important first step towards this goal [145].

Forward to the past: the outlook for archaeogenetics in domestic animals

During the past decade progress in archaeogenetics has been driven by spectacular technology developments in genomics and other fields. This has led to the establishment of paleogenomics “factories” for studying recent human evolution, migration and admixture at increasingly high resolution [240]. There have also been significant developments in other areas of biomolecular archaeology, some of which we outline below in the context of understanding the genetic history and recent evolution of domestic animals.

Ancient DNA may also be readily extracted from a wide range of museum specimens containing biological material from domestic animals [241,242,243]. However, it is important that minimally or non-destructive sampling methods are employed for these items, many of which are literally irreplaceable [244, 245]. Novel sources of aDNA such as avian eggshells and feathers [246], animal glues [247] and parchment made from processed livestock skins [248, 249] will likely have a major impact on archaeogenetics studies of domestic animals. Written documents made from parchment have been carefully maintained and curated for many centuries and therefore represent a valuable repository of genomic information that could illuminate livestock agriculture, breeding and trade stretching back to the early Middle Ages [249].

The expansion of livestock paleogenomics studies to encompass wide spatio-temporal surveys of archaeological material will provide new information concerning the development of secondary animal products and resources such as milk, wool, traction and transport that can be repeatedly exploited throughout an animal’s lifespan [250, 251]. Over the coming years it is likely that high-resolution paleogenomics will shed light on human-mediated selection and the phenotypic changes in livestock that underpinned the “Secondary Products Revolution” in early agricultural societies [252]. Another major area of growth during the coming decade will be identifying and analyzing microbial pathogen genomes using archaeological material from domestic animals and wild congeners [253, 254]. This approach will provide new information for infectious disease research in livestock and companion animals, particularly for diseases such as bovine tuberculosis caused by Mycobacterium bovis, which may have emerged as livestock population densities increased during the Neolithic period [255].

The introduction of aDNA and particularly paleogenomics to archaeology has not been universally welcomed [256]. In this regard, some commentators have proposed a “new archaeology”, which suggests that the role of archaeologists in population paleogenomics should be to ensure geneticists are fully informed about the complexities of human actions, interactions and population movements during the past [257]. Accordingly, this multidisciplinary approach would fully encompass existing scholarship on human history and prehistory, thereby facilitating accurate interpretations of paleogenomics data from ancient peoples and their animal companions [258,259,260]. Going forward, therefore, it will be important to ensure that archaeologists and historians are actively involved in large-scale paleogenomics studies of livestock and other domestic animals, and that these experts are considered to be more than just passive “sample providers” [256, 261].

It is important to finish this review by emphasizing that there will be myriad practical applications for systematically exploring and cataloguing domestic animal genome diversity using high resolution population genomics of extant and extinct domestic animal populations and their wild ancestors. For example, the Functional Annotation of Animal Genomes (FAANG) initiative that aims to identify all functional elements in animal genomes [262] will directly benefit from understanding how genomic regulatory networks have been shaped by domestication, migration and adaptive introgression from wild populations, as well as ancient and more recent human-mediated selection. Finally, identifying and tracking functionally important genomic variation in livestock across space and time will provide novel information for enhancement of welfare, health and production traits using new breeding technologies that are underpinned by genome editing [263].

Availability of data and materials

Not applicable.


  1. 1.

    Childe VG. The Most Ancient East: the Oriental prelude to European prehistory. London: Kegan, Paul, Trubner Ltd; 1928.

    Google Scholar 

  2. 2.

    Currie CR. A community of ants, fungi, and bacteria: a multilateral approach to studying symbiosis. Annu Rev Microbiol. 2001;55:357–80.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  3. 3.

    Stadler B, AFG D. Ecology and evolution of aphid-ant interactions. Annu Rev Ecol Evol Syst. 2005;36:345–72.

    Article  Google Scholar 

  4. 4.

    Larson G, Piperno DR, Allaby RG, Purugganan MD, Andersson L, Arroyo-Kalin M, Barton L, Climer Vigueira C, Denham T, Dobney K, et al. Current perspectives and the future of domestication studies. Proc Natl Acad Sci U S A. 2014;111(17):6139–46.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  5. 5.

    Larson G, Fuller DQ. The evolution of animal domestication. Annu Rev Ecol Evol Syst. 2014;45(1):115–36.

    Article  Google Scholar 

  6. 6.

    Vigne JD. Early domestication and farming: what should we know or do for a better understanding? Anthropozoologica. 2015;50(2):123–50 128.

    Article  Google Scholar 

  7. 7.

    Zeder MA. Core questions in domestication research. Proc Natl Acad Sci U S A. 2015;112(11):3191–8.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  8. 8.

    Freedman AH, Wayne RK. Deciphering the origin of dogs: From fossils to genomes. Annu Rev Anim Biosci. 2017;5:281–307.

    PubMed  Article  PubMed Central  Google Scholar 

  9. 9.

    Larson G, Karlsson EK, Perri A, Webster MT, Ho SY, Peters J, Stahl PW, Piper PJ, Lingaas F, Fredholm M, et al. Rethinking dog domestication by integrating genetics, archeology, and biogeography. Proc Natl Acad Sci U S A. 2012;109(23):8878–83.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  10. 10.

    Frantz LA, Mullin VE, Pionnier-Capitan M, Lebrasseur O, Ollivier M, Perri A, Linderholm A, Mattiangeli V, Teasdale MD, Dimopoulos EA, et al. Genomic and archaeological evidence suggest a dual origin of domestic dogs. Science. 2016;352(6290):1228–31.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  11. 11.

    Botigue LR, Song S, Scheu A, Gopalan S, Pendleton AL, Oetjens M, Taravella AM, Seregely T, Zeeb-Lanz A, Arbogast RM, et al. Ancient European dog genomes reveal continuity since the Early Neolithic. Nat Commun. 2017;8:16082.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  12. 12.

    Rehfeld K, Munch T, Ho SL, Laepple T. Global patterns of declining temperature variability from the Last Glacial Maximum to the Holocene. Nature. 2018;554(7692):356–9.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  13. 13.

    Bettinger R, Richerson P, Boyd R. Constraints on the development of agriculture. Curr Anthropol. 2009;50(5):627–31.

    PubMed  Article  PubMed Central  Google Scholar 

  14. 14.

    Ferrio JP, Voltas J, Araus JL. Global change and the origins of agriculture. In: Araus JL, Slafer GA, editors. Crop stress management and global climate change, vol. 2. Wallingford: CABI; 2011. p. 1–14.

    Google Scholar 

  15. 15.

    Kavanagh PH, Vilela B, Haynie HJ, Tuff T, Lima-Ribeiro M, Gray RD, Botero CA, Gavin MC. Hindcasting global population densities reveals forces enabling the origin of agriculture. Nat Hum Behav. 2018;2(7):478–84.

    PubMed  Article  PubMed Central  Google Scholar 

  16. 16.

    Richerson PJ, Boyd R, Bettinger RL. Was agriculture impossible during the Pleistocene but mandatory during the Holocene? A climate change hypothesis. Am Antiq. 2001;66(3):387–411.

    Article  Google Scholar 

  17. 17.

    Carlson AE. The Younger Dryas climate event. In: Elias SA, Mock CJ, editors. Encyclopedia of quaternary science. 2nd ed. Amsterdam: Elsevier; 2013. p. 126–34.

    Chapter  Google Scholar 

  18. 18.

    Vigne J-D. The origins of animal domestication and husbandry: a major change in the history of humanity and the biosphere. C R Biol. 2011;334(3):171–81.

    PubMed  Article  PubMed Central  Google Scholar 

  19. 19.

    Diamond J. Evolution, consequences and future of plant and animal domestication. Nature. 2002;418(6898):700.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  20. 20.

    Bar-Yosef O. Multiple origins of agriculture in Eurasia and Africa. In: Tibayrenc M, Ayala FJ, editors. On human nature: biology, psychology, ethics, politics, and religion. Cambridge: Academic; 2017. p. 297–331.

    Chapter  Google Scholar 

  21. 21.

    Conolly J, Colledge S, Dobney K, Vigne J-D, Peters J, Stopp B, Manning K, Shennan S. Meta-analysis of zooarchaeological data from SW Asia and SE Europe provides insight into the origins and spread of animal husbandry. J Archaeol Sci. 2011;38(3):538–45.

    Article  Google Scholar 

  22. 22.

    Zeder MA. The origins of agriculture in the Near East. Curr Anthropol. 2011;52(S4):S221–S35.

    Article  Google Scholar 

  23. 23.

    Fuller DQ. Agricultural origins and frontiers in South Asia: a working synthesis. J World Prehist. 2006;20(1):1–86.

    Article  Google Scholar 

  24. 24.

    Frantz LA, Schraiber JG, Madsen O, Megens HJ, Cagan A, Bosse M, Paudel Y, Crooijmans RP, Larson G, Groenen MA. Evidence of long-term gene flow and selection during domestication from analyses of Eurasian wild and domestic pig genomes. Nat Genet. 2015;47(10):1141–8.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  25. 25.

    Orlando L. An ancient DNA perspective on horse evolution. In: Lindqvist C, Rajora OP, editors. Paleogenomics: genome-scale analysis of ancient DNA. Cham: Springer International Publishing; 2019. p. 325–51.

    Google Scholar 

  26. 26.

    Outram AK, Stear NA, Bendrey R, Olsen S, Kasparov A, Zaibert V, Thorpe N, Evershed RP. The earliest horse harnessing and milking. Science. 2009;323(5919):1332–5.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  27. 27.

    Linseele V, Van Neer W, Hendrickx S. Evidence for early cat taming in Egypt. J Archaeol Sci. 2007;34(12):2081–90.

    Article  Google Scholar 

  28. 28.

    Darwin C. On the origin of species by means of natural selection. London: John Murray; 1859.

    Google Scholar 

  29. 29.

    Theunissen B. Darwin and his pigeons. The analogy between artificial and natural selection revisited. J Hist Biol. 2012;45(2):179–212.

    PubMed  Article  PubMed Central  Google Scholar 

  30. 30.

    Rheinberger H-J, McLaughlin P. Darwin's experimental natural history. J Hist Biol. 1984;17(3):345–68.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  31. 31.

    Gould SJ. The flamingo's smile: reflections in natural history. New York. London: W.W. Norton & Company; 1985.

    Google Scholar 

  32. 32.

    Bruford MW, Bradley DG, Luikart G. DNA markers reveal the complexity of livestock domestication. Nat Rev Genet. 2003;4(11):900–10.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  33. 33.

    Brunson K, Reich D. The promise of paleogenomics beyond our own species. Trends Genet. 2019;35(5):319–29.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  34. 34.

    Irving-Pease EK, Ryan H, Jamieson A, Dimopoulos EA, Larson G, Frantz LAF. Paleogenomics of animal domestication. In: Lindqvist C, Rajora OP, editors. Paleogenomics: genome-scale analysis of ancient DNA. Cham: Springer International Publishing; 2019. p. 225–72.

    Google Scholar 

  35. 35.

    MacHugh DE, Larson G, Orlando L. Taming the past: ancient DNA and the study of animal domestication. Annu Rev Anim Biosci. 2017;5:329–51.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  36. 36.

    Scheu A. Neolithic animal domestication as seen from ancient DNA. Quat Int. 2018;496:102–7.

    Article  Google Scholar 

  37. 37.

    Wiener P, Wilkinson S. Deciphering the genetic basis of animal domestication. Proc R Soc Lond B Biol Sci. 2011;278(1722):3161–70.

    Article  Google Scholar 

  38. 38.

    Pääbo S, Higuchi RG, Wilson AC. Ancient DNA and the polymerase chain reaction. The emerging field of molecular archaeology. J Biol Chem. 1989;264(17):9709–12.

    PubMed  PubMed Central  Google Scholar 

  39. 39.

    Higuchi R, Bowman B, Freiberger M, Ryder OA, Wilson AC. DNA sequences from the quagga, an extinct member of the horse family. Nature. 1984;312(5991):282–4.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  40. 40.

    Pääbo S. Molecular cloning of ancient Egyptian mummy DNA. Nature. 1985;314(6012):644–5.

    PubMed  Article  PubMed Central  Google Scholar 

  41. 41.

    Pääbo S. Ancient DNA: extraction, characterization, molecular cloning, and enzymatic amplification. Proc Natl Acad Sci U S A. 1989;86(6):1939–43.

    PubMed  PubMed Central  Article  Google Scholar 

  42. 42.

    Pääbo S, Gifford JA, Wilson AC. Mitochondrial DNA sequences from a 7000-year old brain. Nucleic Acids Res. 1988;16(20):9775–87.

    PubMed  PubMed Central  Article  Google Scholar 

  43. 43.

    Pääbo S, Wilson AC. Polymerase chain reaction reveals cloning artefacts. Nature. 1988;334(6181):387–8.

    PubMed  Article  PubMed Central  Google Scholar 

  44. 44.

    Thomas RH, Schaffner W, Wilson AC, Paabo S. DNA phylogeny of the extinct marsupial wolf. Nature. 1989;340(6233):465–7.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  45. 45.

    Handt O, Hoss M, Krings M, Paabo S. Ancient DNA: methodological challenges. Experientia. 1994;50(6):524–9.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  46. 46.

    Willerslev E, Cooper A. Ancient DNA. Proc R Soc Lond B Biol Sci. 2005;272(1558):3–16.

    CAS  Article  Google Scholar 

  47. 47.

    Leonard JA, Shanks O, Hofreiter M, Kreuz E, Hodges L, Ream W, Wayne RK, Fleischer RC. Animal DNA in PCR reagents plagues ancient DNA research. J Archaeol Sci. 2007;34(9):1361–6.

    Article  Google Scholar 

  48. 48.

    Lindahl T. Facts and artifacts of ancient DNA. Cell. 1997;90(1):1–3.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  49. 49.

    Cooper A, Poinar HN. Ancient DNA: do it right or not at all. Science. 2000;289(5482):1139.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  50. 50.

    Hofreiter M, Serre D, Poinar HN, Kuch M, Paabo S. Ancient DNA. Nat Rev Genet. 2001;2(5):353–9.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  51. 51.

    Bailey JF, Richards MB, Macaulay VA, Colson IB, James IT, Bradley DG, Hedges RE, Sykes BC. Ancient DNA suggests a recent expansion of European cattle from a diverse wild progenitor species. Proc R Soc Lond B Biol Sci. 1996;263(1376):1467–73.

    CAS  Article  Google Scholar 

  52. 52.

    Leonard JA, Wayne RK, Wheeler J, Valadez R, Guillen S, Vila C. Ancient DNA evidence for Old World origin of New World dogs. Science. 2002;298(5598):1613–6.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  53. 53.

    MacHugh DE, Troy CS, McCormick F, Olsaker I, Eythorsdottir E, Bradley DG. Early medieval cattle remains from a Scandinavian settlement in Dublin: genetic analysis and comparison with extant breeds. Philos Trans R Soc Lond B Biol Sci. 1999;354(1379):99–108 discussion 108–9.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  54. 54.

    Troy CS, MacHugh DE, Bailey JF, Magee DA, Loftus RT, Cunningham P, Chamberlain AT, Sykes BC, Bradley DG. Genetic evidence for Near-Eastern origins of European cattle. Nature. 2001;410(6832):1088–91.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  55. 55.

    Vila C, Leonard JA, Gotherstrom A, Marklund S, Sandberg K, Liden K, Wayne RK, Ellegren H. Widespread origins of domestic horse lineages. Science. 2001;291(5503):474–7.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  56. 56.

    Hagelberg E, Bell LS, Allen T, Boyde A, Jones SJ, Clegg JB. Analysis of ancient bone DNA: techniques and applications. Philos Trans R Soc Lond B Biol Sci. 1991;333(1268):399–407.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  57. 57.

    Hagelberg E, Clegg JB. Isolation and characterization of DNA from archaeological bone. Proc R Soc Lond B Biol Sci. 1991;244(1309):45–50.

    CAS  Article  Google Scholar 

  58. 58.

    Hagelberg E, Sykes B, Hedges R. Ancient bone DNA amplified. Nature. 1989;342(6249):485.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  59. 59.

    Hanni C, Laudet V, Sakka M, Begue A, Stehelin D. Amplification of mitochondrial-DNA fragments from ancient human teeth and bones. C R Acad Sci III. 1990;310(9):365–70.

    CAS  PubMed  PubMed Central  Google Scholar 

  60. 60.

    Edwards CJ, MacHugh DE, Dobney KM, Martin L, Russell N, Horwitz LK, McIntosh SK, MacDonald KC, Helmer D, Tresset A, et al. Ancient DNA analysis of 101 cattle remains: limits and prospects. J Archaeol Sci. 2004;31(6):695–710.

    Article  Google Scholar 

  61. 61.

    Verginelli F, Capelli C, Coia V, Musiani M, Falchetti M, Ottini L, Palmirotta R, Tagliacozzo A, De Grossi MI, Mariani-Costantini R. Mitochondrial DNA from prehistoric canids highlights relationships between dogs and South-East European wolves. Mol Biol Evol. 2005;22(12):2541–51.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  62. 62.

    Fernandez H, Hughes S, Vigne JD, Helmer D, Hodgins G, Miquel C, Hanni C, Luikart G, Taberlet P. Divergent mtDNA lineages of goats in an Early Neolithic site, far from the initial domestication areas. Proc Natl Acad Sci U S A. 2006;103(42):15375–9.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  63. 63.

    Larson G, Albarella U, Dobney K, Rowley-Conwy P, Schibler J, Tresset A, Vigne JD, Edwards CJ, Schlumbaum A, Dinu A, et al. Ancient DNA, pig domestication, and the spread of the Neolithic into Europe. Proc Natl Acad Sci U S A. 2007;104(39):15276–81.

    PubMed  PubMed Central  Article  Google Scholar 

  64. 64.

    Larson G, Cucchi T, Fujita M, Matisoo-Smith E, Robins J, Anderson A, Rolett B, Spriggs M, Dolman G, Kim TH, et al. Phylogeny and ancient DNA of Sus provides insights into neolithic expansion in Island Southeast Asia and Oceania. Proc Natl Acad Sci U S A. 2007;104(12):4834–9.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  65. 65.

    Robin ED, Wong R. Mitochondrial DNA molecules and virtual number of mitochondria per cell in mammalian cells. J Cell Physiol. 1988;136(3):507–13.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  66. 66.

    Brown WM, George M Jr, Wilson AC. Rapid evolution of animal mitochondrial DNA. Proc Natl Acad Sci U S A. 1979;76(4):1967–71.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  67. 67.

    Parsons TJ, Muniec DS, Sullivan K, Woodyatt N, Alliston-Greiner R, Wilson MR, Berry DL, Holland KA, Weedn VW, Gill P, et al. A high observed substitution rate in the human mitochondrial DNA control region. Nat Genet. 1997;15(4):363–8.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  68. 68.

    Ingman M, Kaessmann H, Paabo S, Gyllensten U. Mitochondrial genome variation and the origin of modern humans. Nature. 2000;408(6813):708–13.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  69. 69.

    Park SD, Magee DA, McGettigan PA, Teasdale MD, Edwards CJ, Lohan AJ, Murphy A, Braud M, Donoghue MT, Liu Y, et al. Genome sequencing of the extinct Eurasian wild aurochs, Bos primigenius, illuminates the phylogeography and evolution of cattle. Genome Biol. 2015;16(1):234.

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  70. 70.

    Storey AA, Ramirez JM, Quiroz D, Burley DV, Addison DJ, Walter R, Anderson AJ, Hunt TL, Athens JS, Huynen L, et al. Radiocarbon and DNA evidence for a pre-Columbian introduction of Polynesian chickens to Chile. Proc Natl Acad Sci U S A. 2007;104(25):10335–9.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  71. 71.

    Storey AA, Athens JS, Bryant D, Carson M, Emery K, deFrance S, Higham C, Huynen L, Intoh M, Jones S, et al. Investigating the global dispersal of chickens in prehistory using ancient mitochondrial DNA signatures. PLoS One. 2012;7(7):e39171.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  72. 72.

    Thomson VA, Lebrasseur O, Austin JJ, Hunt TL, Burney DA, Denham T, Rawlence NJ, Wood JR, Gongora J, Girdland Flink L, et al. Using ancient DNA to study the origins and dispersal of ancestral Polynesian chickens across the Pacific. Proc Natl Acad Sci U S A. 2014;111(13):4826–31.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  73. 73.

    Gongora J, Rawlence NJ, Mobegi VA, Jianlin H, Alcalde JA, Matus JT, Hanotte O, Moran C, Austin JJ, Ulm S, et al. Indo-European and Asian origins for Chilean and Pacific chickens revealed by mtDNA. Proc Natl Acad Sci U S A. 2008;105(30):10308–13.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  74. 74.

    Beavan N. No evidence for sample contamination or diet offset for pre-Columbian chicken dates from El Arenal. Proc Natl Acad Sci U S A. 2014;111(35):E3582.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  75. 75.

    Bryant D. Statistical flaws undermine pre-Columbian chicken debate. Proc Natl Acad Sci U S A. 2014;111(35):E3584.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  76. 76.

    Storey AA, Matisoo-Smith EA. No evidence against Polynesian dispersal of chickens to pre-Columbian South America. Proc Natl Acad Sci U S A. 2014;111(35):E3583.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  77. 77.

    Thomson VA, Lebrasseur O, Austin JJ, Hunt TL, Burney DA, Denham T, Gongora J, Girdland Flink L, Linderholm A, Dobney K, et al. Reply to Beavan, Bryant, and Storey and Matisoo-Smith: Ancestral Polynesian "D" haplotypes reflect authentic Pacific chicken lineages. Proc Natl Acad Sci U S A. 2014;111(35):E3585–6.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  78. 78.

    Pakendorf B, Stoneking M. Mitochondrial DNA and human evolution. Annu Rev Genomics Hum Genet. 2005;6:165–83.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  79. 79.

    Galtier N, Nabholz B, Glemin S, Hurst GD. Mitochondrial DNA as a marker of molecular diversity: a reappraisal. Mol Ecol. 2009;18(22):4541–50.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  80. 80.

    Ballard JW, Whitlock MC. The incomplete natural history of mitochondria. Mol Ecol. 2004;13(4):729–44.

    PubMed  Article  PubMed Central  Google Scholar 

  81. 81.

    Ellegren H. Genome sequencing and population genomics in non-model organisms. Trends Ecol Evol. 2014;29(1):51–63.

    PubMed  Article  PubMed Central  Google Scholar 

  82. 82.

    Nielsen R, Akey JM, Jakobsson M, Pritchard JK, Tishkoff S, Willerslev E. Tracing the peopling of the world through genomics. Nature. 2017;541(7637):302–10.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  83. 83.

    Luikart G, England PR, Tallmon D, Jordan S, Taberlet P. The power and promise of population genomics: from genotyping to genome typing. Nat Rev Genet. 2003;4(12):981–94.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  84. 84.

    Pickrell JK, Reich D. Toward a new history and geography of human genes informed by ancient DNA. Trends Genet. 2014;30(9):377–89.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  85. 85.

    Schraiber JG, Akey JM. Methods and models for unravelling human evolutionary history. Nat Rev Genet. 2015;16(12):727–40.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  86. 86.

    Veeramah KR, Hammer MF. The impact of whole-genome sequencing on the reconstruction of human population history. Nat Rev Genet. 2014;15(3):149–62.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  87. 87.

    Boussau B, Daubin V. Genomes as documents of evolutionary history. Trends Ecol Evol. 2010;25(4):224–32.

    PubMed  Article  PubMed Central  Google Scholar 

  88. 88.

    Pääbo S, Poinar H, Serre D, Jaenicke-Despres V, Hebler J, Rohland N, Kuch M, Krause J, Vigilant L, Hofreiter M. Genetic analyses from ancient DNA. Annu Rev Genet. 2004;38:645–79.

    PubMed  Article  CAS  PubMed Central  Google Scholar 

  89. 89.

    Der Sarkissian C, Allentoft ME, Avila-Arcos MC, Barnett R, Campos PF, Cappellini E, Ermini L, Fernandez R, da Fonseca R, Ginolhac A, et al. Ancient genomics. Philos Trans R Soc Lond B Biol Sci. 2015;370(1660):20130387.

    Article  CAS  Google Scholar 

  90. 90.

    Hofreiter M, Paijmans JL, Goodchild H, Speller CF, Barlow A, Fortes GG, Thomas JA, Ludwig A, Collins MJ. The future of ancient DNA: technical advances and conceptual shifts. Bioessays. 2015;37(3):284–93.

    PubMed  Article  PubMed Central  Google Scholar 

  91. 91.

    Marciniak S, Klunk J, Devault A, Enk J, Poinar HN. Ancient human genomics: the methodology behind reconstructing evolutionary pathways. J Hum Evol. 2015;79:21–34.

    PubMed  Article  PubMed Central  Google Scholar 

  92. 92.

    Orlando L, Gilbert MT, Willerslev E. Reconstructing ancient genomes and epigenomes. Nat Rev Genet. 2015;16(7):395–408.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  93. 93.

    Cappellini E, Prohaska A, Racimo F, Welker F, Pedersen MW, Allentoft ME, de Barros DP, Gutenbrunner P, Dunne J, Hammann S, et al. Ancient biomolecules and evolutionary inference. Annu Rev Biochem. 2018;87:1029–60.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  94. 94.

    Green RE, Krause J, Ptak SE, Briggs AW, Ronan MT, Simons JF, Du L, Egholm M, Rothberg JM, Paunovic M, et al. Analysis of one million base pairs of Neanderthal DNA. Nature. 2006;444(7117):330–6.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  95. 95.

    Green RE, Malaspinas AS, Krause J, Briggs AW, Johnson PL, Uhler C, Meyer M, Good JM, Maricic T, Stenzel U, et al. A complete Neandertal mitochondrial genome sequence determined by high-throughput sequencing. Cell. 2008;134(3):416–26.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  96. 96.

    Miller W, Drautz DI, Ratan A, Pusey B, Qi J, Lesk AM, Tomsho LP, Packard MD, Zhao F, Sher A, et al. Sequencing the nuclear genome of the extinct woolly mammoth. Nature. 2008;456(7220):387–90.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  97. 97.

    Poinar HN, Schwarz C, Qi J, Shapiro B, Macphee RD, Buigues B, Tikhonov A, Huson DH, Tomsho LP, Auch A, et al. Metagenomics to paleogenomics: large-scale sequencing of mammoth DNA. Science. 2006;311(5759):392–4.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  98. 98.

    Shendure J, Balasubramanian S, Church GM, Gilbert W, Rogers J, Schloss JA, Waterston RH. DNA sequencing at 40: past, present and future. Nature. 2017;550(7676):345–53.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  99. 99.

    Wetterstrand KA. DNA sequencing costs: data from the NHGRI Genome Sequencing Program (GSP). 2019. Accessed 2 Sept 2019.

    Google Scholar 

  100. 100.

    Heather JM, Chain B. The sequence of sequencers: The history of sequencing DNA. Genomics. 2016;107(1):1–8.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  101. 101.

    Mardis ER. DNA sequencing technologies: 2006–2016. Nat Protoc. 2017;12(2):213–8.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  102. 102.

    Lan T, Lindqvist C. Technical advances and challenges in genome-scale analysis of ancient DNA. In: Lindqvist C, Rajora OP, editors. Paleogenomics: genome-scale analysis of ancient DNA. Cham: Springer International Publishing; 2019. p. 3–29.

    Google Scholar 

  103. 103.

    Green RE, Krause J, Briggs AW, Maricic T, Stenzel U, Kircher M, Patterson N, Li H, Zhai W, Fritz MH, et al. A draft sequence of the Neandertal genome. Science. 2010;328(5979):710–22.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  104. 104.

    Rasmussen M, Li Y, Lindgreen S, Pedersen JS, Albrechtsen A, Moltke I, Metspalu M, Metspalu E, Kivisild T, Gupta R, et al. Ancient human genome sequence of an extinct Palaeo-Eskimo. Nature. 2010;463(7282):757–62.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  105. 105.

    Reich D, Green RE, Kircher M, Krause J, Patterson N, Durand EY, Viola B, Briggs AW, Stenzel U, Johnson PL, et al. Genetic history of an archaic hominin group from Denisova Cave in Siberia. Nature. 2010;468(7327):1053–60.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  106. 106.

    Rasmussen M, Guo X, Wang Y, Lohmueller KE, Rasmussen S, Albrechtsen A, Skotte L, Lindgreen S, Metspalu M, Jombart T, et al. An Aboriginal Australian genome reveals separate human dispersals into Asia. Science. 2011;334(6052):94–8.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  107. 107.

    Meyer M, Kircher M, Gansauge MT, Li H, Racimo F, Mallick S, Schraiber JG, Jay F, Prufer K, de Filippo C, et al. A high-coverage genome sequence from an archaic Denisovan individual. Science. 2012;338(6104):222–6.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  108. 108.

    Fu Q, Meyer M, Gao X, Stenzel U, Burbano HA, Kelso J, Paabo S. DNA analysis of an early modern human from Tianyuan Cave, China. Proc Natl Acad Sci U S A. 2013;110(6):2223–7.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  109. 109.

    Orlando L, Ginolhac A, Zhang G, Froese D, Albrechtsen A, Stiller M, Schubert M, Cappellini E, Petersen B, Moltke I, et al. Recalibrating Equus evolution using the genome sequence of an early Middle Pleistocene horse. Nature. 2013;499(7456):74–8.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  110. 110.

    Fu Q, Li H, Moorjani P, Jay F, Slepchenko SM, Bondarev AA, Johnson PL, Aximu-Petri A, Prufer K, de Filippo C, et al. Genome sequence of a 45,000-year-old modern human from western Siberia. Nature. 2014;514(7523):445–9.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  111. 111.

    Prufer K, Racimo F, Patterson N, Jay F, Sankararaman S, Sawyer S, Heinze A, Renaud G, Sudmant PH, de Filippo C, et al. The complete genome sequence of a Neanderthal from the Altai Mountains. Nature. 2014;505(7481):43–9.

    PubMed  Article  CAS  PubMed Central  Google Scholar 

  112. 112.

    Raghavan M, Skoglund P, Graf KE, Metspalu M, Albrechtsen A, Moltke I, Rasmussen S, Stafford TW Jr, Orlando L, Metspalu E. Upper Palaeolithic Siberian genome reveals dual ancestry of Native Americans. Nature. 2014;505(7481):87.

    PubMed  Article  CAS  PubMed Central  Google Scholar 

  113. 113.

    Rasmussen M, Anzick SL, Waters MR, Skoglund P, DeGiorgio M, Stafford TW Jr, Rasmussen S, Moltke I, Albrechtsen A, Doyle SM, et al. The genome of a Late Pleistocene human from a Clovis burial site in western Montana. Nature. 2014;506(7487):225–9.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  114. 114.

    Schubert M, Jonsson H, Chang D, Der Sarkissian C, Ermini L, Ginolhac A, Albrechtsen A, Dupanloup I, Foucal A, Petersen B, et al. Prehistoric genomes reveal the genetic foundation and cost of horse domestication. Proc Natl Acad Sci U S A. 2014;111(52):E5661–9.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  115. 115.

    Skoglund P, Ersmark E, Palkopoulou E, Dalen L. Ancient wolf genome reveals an early divergence of domestic dog ancestors and admixture into high-latitude breeds. Curr Biol. 2015;25(11):1515–9.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  116. 116.

    Grimm D. Dawn of the dog. Science. 2015;348(6232):274–9.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  117. 117.

    Thalmann O, Perri AR. Paleogenomic inferences of dog domestication. In: Lindqvist C, Rajora OP, editors. Paleogenomics: genome-scale analysis of ancient DNA. Cham: Springer International Publishing; 2019. p. 273–306.

    Google Scholar 

  118. 118.

    Ni Leathlobhair M, Perri AR, Irving-Pease EK, Witt KE, Linderholm A, Haile J, Lebrasseur O, Ameen C, Blick J, Boyko AR, et al. The evolutionary history of dogs in the Americas. Science. 2018;361(6397):81–5.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  119. 119.

    Koch A, Brierley C, Maslin MM, Lewis SL. Earth system impacts of the European arrival and Great Dying in the Americas after 1492. Quat Sci Rev. 2019;207:13–36.

    Article  Google Scholar 

  120. 120.

    Nunn N, Qian N. The Columbian Exchange: A history of disease, food, and ideas. J Econ Perspect. 2010;24(2):163–88.

    Article  Google Scholar 

  121. 121.

    Baez-Ortega A, Gori K, Strakova A, Allen JL, Allum KM, Bansse-Issa L, Bhutia TN, Bisson JL, Briceno C, Castillo Domracheva A, et al. Somatic evolution and global expansion of an ancient transmissible cancer lineage. Science. 2019;365(6452):eaau9923.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  122. 122.

    Ostrander EA, Wang G-D, Larson G, vonHoldt BM, Davis BW, Jagannathan V, Hitte C, Wayne RK, Zhang Y-P, Dog10K Consortium. Dog10K: an international sequencing effort to advance studies of canine domestication, phenotypes and health. Natl Sci Rev. 2019;6(4):810–24.

    PubMed  PubMed Central  Article  Google Scholar 

  123. 123.

    Gamba C, Jones ER, Teasdale MD, McLaughlin RL, Gonzalez-Fortes G, Mattiangeli V, Domboroczki L, Kovari I, Pap I, Anders A, et al. Genome flux and stasis in a five millennium transect of European prehistory. Nat Commun. 2014;5:5257.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  124. 124.

    Geigl EM, Grange T. Ancient DNA: The quest for the best. Mol Ecol Resour. 2018;18(6):1185–7.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  125. 125.

    Achilli A, Olivieri A, Semino O, Torroni A. Ancient human genomes—keys to understanding our past. Science. 2018;360(6392):964–5.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  126. 126.

    Skoglund P, Mathieson I. Ancient genomics of modern humans: the first decade. Annu Rev Genomics Hum Genet. 2018;19:381–404.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  127. 127.

    Yang MA, Fu Q. Insights into modern human prehistory using ancient genomes. Trends Genet. 2018;34(3):184–96.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  128. 128.

    Llamas B, Willerslev E, Orlando L. Human evolution: a tale from ancient genomes. Philos Trans R Soc Lond B Biol Sci. 2017;372(1713):20150484.

    Article  CAS  Google Scholar 

  129. 129.

    Marciniak S, Perry GH. Harnessing ancient genomes to study the history of human adaptation. Nat Rev Genet. 2017;18(11):659–74.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  130. 130.

    Smith CI, Chamberlain AT, Riley MS, Stringer C, Collins MJ. The thermal history of human fossils and the likelihood of successful DNA amplification. J Hum Evol. 2003;45(3):203–17.

    PubMed  Article  PubMed Central  Google Scholar 

  131. 131.

    Fregel R, Mendez FL, Bokbot Y, Martin-Socas D, Camalich-Massieu MD, Santana J, Morales J, Avila-Arcos MC, Underhill PA, Shapiro B, et al. Ancient genomes from North Africa evidence prehistoric migrations to the Maghreb from both the Levant and Europe. Proc Natl Acad Sci U S A. 2018;115(26):6774–9.

    PubMed  PubMed Central  Article  Google Scholar 

  132. 132.

    Gallego Llorente M, Jones ER, Eriksson A, Siska V, Arthur KW, Arthur JW, Curtis MC, Stock JT, Coltorti M, Pieruccini P, et al. Ancient Ethiopian genome reveals extensive Eurasian admixture throughout the African continent. Science. 2015;350(6262):820–2.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  133. 133.

    Lazaridis I, Nadel D, Rollefson G, Merrett DC, Rohland N, Mallick S, Fernandes D, Novak M, Gamarra B, Sirak K. Genomic insights into the origin of farming in the ancient Near East. Nature. 2016;536(7617):419.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  134. 134.

    Lipson M, Cheronet O, Mallick S, Rohland N, Oxenham M, Pietrusewsky M, Pryce TO, Willis A, Matsumura H, Buckley H, et al. Ancient genomes document multiple waves of migration in Southeast Asian prehistory. Science. 2018;361(6397):92–5.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  135. 135.

    Mathieson I, Alpaslan-Roodenberg S, Posth C, Szecsenyi-Nagy A, Rohland N, Mallick S, Olalde I, Broomandkhoshbacht N, Candilio F, Cheronet O, et al. The genomic history of southeastern Europe. Nature. 2018;555(7695):197–203.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  136. 136.

    McColl H, Racimo F, Vinner L, Demeter F, Gakuhari T, Moreno-Mayar JV, van Driem G, Gram Wilken U, Seguin-Orlando A, de la Fuente CC, et al. The prehistoric peopling of Southeast Asia. Science. 2018;361(6397):88–92.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  137. 137.

    Moreno-Mayar JV, Vinner L, de Barros DP, de la Fuente C, Chan J, Spence JP, Allentoft ME, Vimala T, Racimo F, Pinotti T, et al. Early human dispersals within the Americas. Science. 2018;362(6419):eaav2621.

    PubMed  Article  CAS  PubMed Central  Google Scholar 

  138. 138.

    Olalde I, Mallick S, Patterson N, Rohland N, Villalba-Mouco V, Silva M, Dulias K, Edwards CJ, Gandini F, Pala M, et al. The genomic history of the Iberian Peninsula over the past 8000 years. Science. 2019;363(6432):1230–4.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  139. 139.

    Prendergast ME, Lipson M, Sawchuk EA, Olalde I, Ogola CA, Rohland N, Sirak KA, Adamski N, Bernardos R, Broomandkhoshbacht N, et al. Ancient DNA reveals a multistep spread of the first herders into sub-Saharan Africa. Science. 2019;365(6448):eaaw6275.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  140. 140.

    Schlebusch CM, Malmstrom H, Gunther T, Sjodin P, Coutinho A, Edlund H, Munters AR, Vicente M, Steyn M, Soodyall H, et al. Southern African ancient genomes estimate modern human divergence to 350,000 to 260,000 years ago. Science. 2017;358(6363):652–5.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  141. 141.

    Skoglund P, Thompson JC, Prendergast ME, Mittnik A, Sirak K, Hajdinjak M, Salie T, Rohland N, Mallick S, Peltzer A, et al. Reconstructing prehistoric African population structure. Cell. 2017;171(1):59–71.e21.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  142. 142.

    van de Loosdrecht M, Bouzouggar A, Humphrey L, Posth C, Barton N, Aximu-Petri A, Nickel B, Nagel S, Talbi EH, El Hajraoui MA, et al. Pleistocene North African genomes link Near Eastern and sub-Saharan African human populations. Science. 2018;360(6388):548–52.

    PubMed  Article  CAS  PubMed Central  Google Scholar 

  143. 143.

    Daly KG, Maisano Delser P, Mullin VE, Scheu A, Mattiangeli V, Teasdale MD, Hare AJ, Burger J, Verdugo MP, Collins MJ, et al. Ancient goat genomes reveal mosaic domestication in the Fertile Crescent. Science. 2018;361(6397):85–8.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  144. 144.

    Fages A, Hanghoj K, Khan N, Gaunitz C, Seguin-Orlando A, Leonardi M, McCrory Constantz C, Gamba C, Al-Rasheid KAS, Albizuri S, et al. Tracking five millennia of horse management with extensive ancient genome time series. Cell. 2019;177(6):1419–35 e1431.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  145. 145.

    Frantz LAF, Haile J, Lin AT, Scheu A, Georg C, Benecke N, Alexander M, Linderholm A, Mullin VE, Daly KG, et al. Ancient pigs reveal a near-complete genomic turnover following their introduction to Europe. Proc Natl Acad Sci U S A. 2019;116(35):17231–8.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  146. 146.

    Verdugo MP, Mullin VE, Scheu A, Mattiangeli V, Daly KG, Maisano Delser P, Hare AJ, Burger J, Collins MJ, Kehati R, et al. Ancient cattle genomics, origins, and rapid turnover in the Fertile Crescent. Science. 2019;365(6449):173–6.

    CAS  PubMed  PubMed Central  Google Scholar 

  147. 147.

    Broushaki F, Thomas MG, Link V, Lopez S, van Dorp L, Kirsanow K, Hofmanova Z, Diekmann Y, Cassidy LM, Diez-Del-Molino D, et al. Early Neolithic genomes from the eastern Fertile Crescent. Science. 2016;353(6298):499–503.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  148. 148.

    Feldman M, Fernandez-Dominguez E, Reynolds L, Baird D, Pearson J, Hershkovitz I, May H, Goring-Morris N, Benz M, Gresky J, et al. Late Pleistocene human genome suggests a local origin for the first farmers of central Anatolia. Nat Commun. 2019;10(1):1218.

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  149. 149.

    Gallego-Llorente M, Connell S, Jones ER, Merrett DC, Jeon Y, Eriksson A, Siska V, Gamba C, Meiklejohn C, Beyer R, et al. The genetics of an early Neolithic pastoralist from the Zagros, Iran. Sci Rep. 2016;6:31326.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  150. 150.

    Walker M, Head MJ, Berkelhammer M, Bjorck S, Cheng H, Cwynar L, Fisher D, Gkinis V, Long A, Lowe J, et al. Formal ratification of the subdivision of the Holocene Series/Epoch (Quaternary System/Period): two new Global Boundary Stratotype Sections and Points (GSSPs) and three new stages/subseries. Episodes. 2018;41(4):213–23.

    Article  Google Scholar 

  151. 151.

    Bradley DG, MacHugh DE, Cunningham P, Loftus RT. Mitochondrial diversity and the origins of African and European cattle. Proc Natl Acad Sci U S A. 1996;93(10):5131–5.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  152. 152.

    MacHugh DE, Shriver MD, Loftus RT, Cunningham P, Bradley DG. Microsatellite DNA variation and the evolution, domestication and phylogeography of taurine and zebu cattle (Bos taurus and Bos indicus). Genetics. 1997;146(3):1071–86.

    CAS  PubMed  PubMed Central  Google Scholar 

  153. 153.

    Manunza A, Zidi A, Yeghoyan S, Balteanu VA, Carsai TC, Scherbakov O, Ramirez O, Eghbalsaied S, Castello A, Mercade A, et al. A high throughput genotyping approach reveals distinctive autosomal genetic signatures for European and Near Eastern wild boar. PLoS One. 2013;8(2):e55891.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  154. 154.

    Darwin C. The variation of animals and plants under domestication. London: John Murray; 1868.

    Google Scholar 

  155. 155.

    Dobney K, Larson G. Genetics and animal domestication: new windows on an elusive process. J Zool. 2006;269(2):261–71.

    Google Scholar 

  156. 156.

    Driscoll CA, Macdonald DW, O'Brien SJ. From wild animals to domestic pets, an evolutionary view of domestication. Proc Natl Acad Sci U S A. 2009;106(Suppl 1):9971–8.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  157. 157.

    Jensen P. Behavior genetics and the domestication of animals. Annu Rev Anim Biosci. 2014;2:85–104.

    PubMed  Article  Google Scholar 

  158. 158.

    Sanchez-Villagra MR, Geiger M, Schneider RA. The taming of the neural crest: a developmental perspective on the origins of morphological covariation in domesticated mammals. R Soc Open Sci. 2016;3(6):160107.

    PubMed  PubMed Central  Article  Google Scholar 

  159. 159.

    Wilkins AS. A striking example of developmental bias in an evolutionary process: The “domestication syndrome”. Evol Dev. 2019; in press.

  160. 160.

    Wilkins AS. Revisiting two hypotheses on the domestication syndrome” in light of genomic data. Vavilovskii Zhurnal Genet Selektsii. 2017;21(4):435–442.

    Article  Google Scholar 

  161. 161.

    Wilkins AS, Wrangham RW, Fitch WT. The “Domestication Syndrome” in mammals: A unified explanation based on neural crest cell behavior and genetics. Genetics. 2014;197(3):795–808.

    PubMed  PubMed Central  Article  Google Scholar 

  162. 162.

    Simoes-Costa M, Bronner ME. Establishing neural crest identity: a gene regulatory recipe. Development. 2015;142(2):242–57.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  163. 163.

    Bronner ME, Simoes-Costa M. The neural crest migrating into the twenty-first century. Curr Top Dev Biol. 2016;116:115–34.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  164. 164.

    Etchevers HC, Dupin E, Le Douarin NM. The diverse neural crest: from embryology to human pathology. Development. 2019;146(5):dev169821.

    PubMed  Article  CAS  PubMed Central  Google Scholar 

  165. 165.

    Montague MJ, Li G, Gandolfi B, Khan R, Aken BL, Searle SM, Minx P, Hillier LW, Koboldt DC, Davis BW, et al. Comparative analysis of the domestic cat genome reveals genetic signatures underlying feline biology and domestication. Proc Natl Acad Sci U S A. 2014;111(48):17230–5.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  166. 166.

    Pilot M, Malewski T, Moura AE, Grzybowski T, Olenski K, Kaminski S, Fadel FR, Alagaili AN, Mohammed OB, Bogdanowicz W. Diversifying selection between pure-breed and free-breeding dogs inferred from genome-wide SNP analysis. G3 (Bethesda). 2016;6(8):2285–98.

    CAS  Article  Google Scholar 

  167. 167.

    Pendleton AL, Shen F, Taravella AM, Emery S, Veeramah KR, Boyko AR, Kidd JM. Comparison of village dog and wolf genomes highlights the role of the neural crest in dog domestication. BMC Biol. 2018;16(1):64.

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  168. 168.

    Wang X, Pipes L, Trut LN, Herbeck Y, Vladimirova AV, Gulevich RG, Kharlamova AV, Johnson JL, Acland GM, Kukekova AV, et al. Genomic responses to selection for tame/aggressive behaviors in the silver fox (Vulpes vulpes). Proc Natl Acad Sci U S A. 2018;115(41):10398–403.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  169. 169.

    Librado P, Gamba C, Gaunitz C, Der Sarkissian C, Pruvost M, Albrechtsen A, Fages A, Khan N, Schubert M, Jagannathan V, et al. Ancient genomic changes associated with domestication of the horse. Science. 2017;356(6336):442–5.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  170. 170.

    Librado P, Orlando L. Detecting signatures of positive selection along defined branches of a population tree using LSD. Mol Biol Evol. 2018;35(6):1520–35.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  171. 171.

    Wrangham R, Pilbeam D. African apes as time machines. In: BMF G, Briggs NE, Sheeran LK, Shapiro GL, Goodall J, editors. All apes great and small. Vol. 1: African apes. Boston: Springer US; 2001. p. 5–17.

    Google Scholar 

  172. 172.

    Leach HM. Human domestication reconsidered. Curr Anthropol. 2003;44(3):349–68.

    Article  Google Scholar 

  173. 173.

    Hare B, Wobber V, Wrangham R. The self-domestication hypothesis: evolution of bonobo psychology is due to selection against aggression. Anim Behav. 2012;83(3):573–85.

    Article  Google Scholar 

  174. 174.

    Darwin C. The descent of man, and selection in relation to sex. London: John Murray; 1871.

    Book  Google Scholar 

  175. 175.

    Dobzhansky T. Mankind evolving: the evolution of the human species. New Haven: Yale University Press; 1962.

    Google Scholar 

  176. 176.

    Hare B. Survival of the friendliest: Homo sapiens evolved via selection for prosociality. Annu Rev Psychol. 2017;68:155–86.

    PubMed  Article  PubMed Central  Google Scholar 

  177. 177.

    Theofanopoulou C, Gastaldon S, O'Rourke T, Samuels BD, Martins PT, Delogu F, Alamri S, Boeckx C. Self-domestication in Homo sapiens: insights from comparative genomics. PLoS One. 2017;12(10):e0185306.

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  178. 178.

    Benítez-Burraco A, Theofanopoulou C, Boeckx C. Globularization and domestication. Topoi. 2018;37(2):265–78.

    Article  Google Scholar 

  179. 179.

    Thomas J, Kirby S. Self domestication and the evolution of language. Biol Philos. 2018;33(1):9.

    PubMed  PubMed Central  Article  Google Scholar 

  180. 180.

    Niego A, Benitez-Burraco A. Williams syndrome, human self-domestication, and language evolution. Front Psychol. 2019;10:521.

    PubMed  PubMed Central  Article  Google Scholar 

  181. 181.

    Sanchez-Villagra MR, van Schaik CP. Evaluating the self-domestication hypothesis of human evolution. Evol Anthropol. 2019;28(3):133–43.

    PubMed  Article  PubMed Central  Google Scholar 

  182. 182.

    Bosse M, Megens HJ, Derks MFL, de Cara AMR, Groenen MAM. Deleterious alleles in the context of domestication, inbreeding, and selection. Evol Appl. 2019;12(1):6–17.

    PubMed  Article  PubMed Central  Google Scholar 

  183. 183.

    Moyers BT, Morrell PL, McKay JK. Genetic costs of domestication and improvement. J Hered. 2018;109(2):103–16.

    PubMed  Article  PubMed Central  Google Scholar 

  184. 184.

    Wallace AR II. On the tendency of varieties to depart indefinitely from the original type. In: Contributions to the theory of natural selection a series of essays. London: Macmillan and Co. Ltd; 1870. p. 26–44.

    Google Scholar 

  185. 185.

    Fisher RA. The genetical theory of natural selection. Oxford: Clarendon Press; 1930.

    Book  Google Scholar 

  186. 186.

    Kimura M. On the probability of fixation of mutant genes in a population. Genetics. 1962;47:713–9.

    CAS  PubMed  PubMed Central  Google Scholar 

  187. 187.

    Hill WG, Robertson A. The effect of linkage on limits to artificial selection. Genet Res. 1966;8(3):269–94.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  188. 188.

    Cruz F, Vila C, Webster MT. The legacy of domestication: accumulation of deleterious mutations in the dog genome. Mol Biol Evol. 2008;25(11):2331–6.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  189. 189.

    Marsden CD, Ortega-Del Vecchyo D, O'Brien DP, Taylor JF, Ramirez O, Vila C, Marques-Bonet T, Schnabel RD, Wayne RK, Lohmueller KE. Bottlenecks and selective sweeps during domestication have increased deleterious genetic variation in dogs. Proc Natl Acad Sci U S A. 2016;113(1):152–7.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  190. 190.

    Makino T, Rubin CJ, Carneiro M, Axelsson E, Andersson L, Webster MT. Elevated proportions of deleterious genetic variation in domestic animals and plants. Genome Biol Evol. 2018;10(1):276–90.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  191. 191.

    Gaunitz C, Fages A, Hanghoj K, Albrechtsen A, Khan N, Schubert M, Seguin-Orlando A, Owens IJ, Felkel S, Bignon-Lau O, et al. Ancient genomes revisit the ancestry of domestic and Przewalski's horses. Science. 2018;360(6384):111–4.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  192. 192.

    Dannemann M, Racimo F. Something old, something borrowed: admixture and adaptation in human evolution. Curr Opin Genet Dev. 2018;53:1–8.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  193. 193.

    Quach H, Quintana-Murci L. Living in an adaptive world: genomic dissection of the genus Homo and its immune response. J Exp Med. 2017;214(4):877–94.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  194. 194.

    Wall JD. Yoshihara Caldeira Brandt D. Archaic admixture in human history. Curr Opin Genet Dev. 2016;41:93–7.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  195. 195.

    Haber M, Mezzavilla M, Xue Y, Tyler-Smith C. Ancient DNA and the rewriting of human history: be sparing with Occam's razor. Genome Biol. 2016;17:1.

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  196. 196.

    Racimo F, Sankararaman S, Nielsen R, Huerta-Sanchez E. Evidence for archaic adaptive introgression in humans. Nat Rev Genet. 2015;16(6):359–71.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  197. 197.

    Huerta-Sánchez E, Jin X, Bianba Z, Peter BM, Vinckenbosch N, Liang Y, Yi X, He M, Somel M, Ni P. Altitude adaptation in Tibetans caused by introgression of Denisovan-like DNA. Nature. 2014;512(7513):194.

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  198. 198.

    Ostrander EA, Wayne RK, Freedman AH, Davis BW. Demographic history, selection and functional diversity of the canine genome. Nat Rev Genet. 2017;18(12):705–20.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  199. 199.

    Loftus RT, MacHugh DE, Bradley DG, Sharp PM, Cunningham P. Evidence for two independent domestications of cattle. Proc Natl Acad Sci U S A. 1994;91(7):2757–61.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  200. 200.

    Loftus RT, MacHugh DE, Ngere LO, Balain DS, Badi AM, Bradley DG, Cunningham EP. Mitochondrial genetic variation in European, African and Indian cattle populations. Anim Genet. 1994;25(4):265–71.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  201. 201.

    Manwell C, Baker CM. Chemical classification of cattle. 2. Phylogenetic tree and specific status of the Zebu. Anim Blood Groups Biochem Genet. 1980;11(3):151–62.

    CAS  PubMed  PubMed Central  Google Scholar 

  202. 202.

    Baker CM, Manwell C. Chemical classification of cattle. 1. Breed groups. Anim Blood Groups Biochem Genet. 1980;11(3):127–50.

    CAS  PubMed  PubMed Central  Google Scholar 

  203. 203.

    Loftus RT, Ertugrul O, Harba AH, El-Barody MA, MacHugh DE, Park SD, Bradley DG. A microsatellite survey of cattle from a centre of origin: the Near East. Mol Ecol. 1999;8(12):2015–22.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  204. 204.

    Hanotte O, Tawah CL, Bradley DG, Okomo M, Verjee Y, Ochieng J, Rege JE. Geographic distribution and frequency of a taurine Bos taurus and an indicine Bos indicus Y specific allele amongst sub-saharan African cattle breeds. Mol Ecol. 2000;9(4):387–96.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  205. 205.

    Hanotte O, Bradley DG, Ochieng JW, Verjee Y, Hill EW, Rege JE. African pastoralism: genetic imprints of origins and migrations. Science. 2002;296(5566):336–9.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  206. 206.

    Chen N, Cai Y, Chen Q, Li R, Wang K, Huang Y, Hu S, Huang S, Zhang H, Zheng Z, et al. Whole-genome resequencing reveals world-wide ancestry and adaptive introgression events of domesticated cattle in East Asia. Nat Commun. 2018;9(1):2337.

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  207. 207.

    Wang K, Lenstra JA, Liu L, Hu Q, Ma T, Qiu Q, Liu J. Incomplete lineage sorting rather than hybridization explains the inconsistent phylogeny of the wisent. Commun Biol. 2018;1(1):169.

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  208. 208.

    Wu DD, Ding XD, Wang S, Wojcik JM, Zhang Y, Tokarska M, Li Y, Wang MS, Faruque O, Nielsen R, et al. Pervasive introgression facilitated domestication and adaptation in the Bos species complex. Nat Ecol Evol. 2018;2(7):1139–45.

    PubMed  Article  PubMed Central  Google Scholar 

  209. 209.

    Zaidi AA, Makova KD. Investigating mitonuclear interactions in human admixed populations. Nat Ecol Evol. 2019;3(2):213–22.

    PubMed  Article  PubMed Central  Google Scholar 

  210. 210.

    Sharbrough J, Havird JC, Noe GR, Warren JM, Sloan DB. The mitonuclear dimension of Neanderthal and Denisovan ancestry in modern human genomes. Genome Biol Evol. 2017;9(6):1567–81.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  211. 211.

    Upadhyay MR, Chen W, Lenstra JA, Goderie CR, MacHugh DE, Park SD, Magee DA, Matassino D, Ciani F, Megens HJ, et al. Genetic origin, admixture and population history of aurochs (Bos primigenius) and primitive European cattle. Heredity (Edinb). 2017;118(2):169–76.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  212. 212.

    Liu L, Bosse M, Megens HJ, Frantz LAF, Lee YL, Irving-Pease EK, Narayan G, Groenen MAM, Madsen O. Genomic analysis on pygmy hog reveals extensive interbreeding during wild boar expansion. Nat Commun. 2019;10(1):1992.

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  213. 213.

    Pilot M, Greco C, vonHoldt BM, Randi E, Jedrzejewski W, Sidorovich VE, Konopinski MK, Ostrander EA, Wayne RK. Widespread, long-term admixture between grey wolves and domestic dogs across Eurasia and its implications for the conservation status of hybrids. Evol Appl. 2018;11(5):662–80.

    PubMed  PubMed Central  Article  Google Scholar 

  214. 214.

    Zhu Y, Li W, Yang B, Zhang Z, Ai H, Ren J, Huang L. Signatures of selection and interspecies introgression in the genome of Chinese domestic pigs. Genome Biol Evol. 2017;9(10):2592–603.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  215. 215.

    vonHoldt B, Fan Z, Ortega-Del Vecchyo D, Wayne RK. EPAS1 variants in high altitude Tibetan wolves were selectively introgressed into highland dogs. PeerJ. 2017;5:e3522.

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  216. 216.

    Miao B, Wang Z, Li Y. Genomic analysis reveals hypoxia adaptation in the Tibetan Mastiff by introgression of the gray wolf from the Tibetan Plateau. Mol Biol Evol. 2017;34(3):734–43.

    CAS  PubMed  PubMed Central  Google Scholar 

  217. 217.

    Medugorac I, Graf A, Grohs C, Rothammer S, Zagdsuren Y, Gladyr E, Zinovieva N, Barbieri J, Seichter D, Russ I, et al. Whole-genome analysis of introgressive hybridization and characterization of the bovine legacy of Mongolian yaks. Nat Genet. 2017;49(3):470–5.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  218. 218.

    Fan Z, Silva P, Gronau I, Wang S, Armero AS, Schweizer RM, Ramirez O, Pollinger J, Galaverni M, Ortega Del-Vecchyo D, et al. Worldwide patterns of genomic variation and admixture in gray wolves. Genome Res. 2016;26(2):163–73.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  219. 219.

    Ai H, Fang X, Yang B, Huang Z, Chen H, Mao L, Zhang F, Zhang L, Cui L, He W, et al. Adaptation and possible ancient interspecies introgression in pigs identified by whole-genome sequencing. Nat Genet. 2015;47(3):217–25.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  220. 220.

    Frantz LA, Madsen O, Megens HJ, Groenen MA, Lohse K. Testing models of speciation from genome sequences: divergence and asymmetric admixture in Island South-East Asian Sus species during the Plio-Pleistocene climatic fluctuations. Mol Ecol. 2014;23(22):5566–74.

    PubMed  PubMed Central  Article  Google Scholar 

  221. 221.

    Bosse M, Megens HJ, Madsen O, Frantz LA, Paudel Y, Crooijmans RP, Groenen MA. Untangling the hybrid nature of modern pig genomes: a mosaic derived from biogeographically distinct and highly divergent Sus scrofa populations. Mol Ecol. 2014;23(16):4089–102.

    PubMed  PubMed Central  Article  Google Scholar 

  222. 222.

    Eriksson J, Larson G, Gunnarsson U, Bed'hom B, Tixier-Boichard M, Stromstedt L, Wright D, Jungerius A, Vereijken A, Randi E, et al. Identification of the yellow skin gene reveals a hybrid origin of the domestic chicken. PLoS Genet. 2008;4(2):e1000010.

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  223. 223.

    Frantz L, Meijaard E, Gongora J, Haile J, Groenen MA, Larson G. The evolution of Suidae. Annu Rev Anim Biosci. 2016;4:61–85.

    PubMed  Article  PubMed Central  Google Scholar 

  224. 224.

    Groenen MA. A decade of pig genome sequencing: a window on pig domestication and evolution. Genet Sel Evol. 2016;48(1):23.

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  225. 225.

    Frantz LA, Schraiber JG, Madsen O, Megens HJ, Bosse M, Paudel Y, Semiadi G, Meijaard E, Li N, Crooijmans RP, et al. Genome sequencing reveals fine scale diversification and reticulation history during speciation in Sus. Genome Biol. 2013;14(9):R107.

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  226. 226.

    Groenen MA, Archibald AL, Uenishi H, Tuggle CK, Takeuchi Y, Rothschild MF, Rogel-Gaillard C, Park C, Milan D, Megens HJ, et al. Analyses of pig genomes provide insight into porcine demography and evolution. Nature. 2012;491(7424):393–8.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  227. 227.

    Yang B, Cui L, Perez-Enciso M, Traspov A, Crooijmans R, Zinovieva N, Schook LB, Archibald A, Gatphayak K, Knorr C, et al. Genome-wide SNP data unveils the globalization of domesticated pigs. Genet Sel Evol. 2017;49(1):71.

    PubMed  PubMed Central  Article  Google Scholar 

  228. 228.

    Bosse M, Megens H-J, Frantz LA, Madsen O, Larson G, Paudel Y, Duijvesteijn N, Harlizius B, Hagemeijer Y, Crooijmans RP. Genomic analysis reveals selection for Asian genes in European pigs following human-mediated introgression. Nat Commun. 2014;5:4392.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  229. 229.

    Bosse M, Madsen O, Megens H-J, Frantz LA, Paudel Y, Crooijmans RP, Groenen MA. Hybrid origin of European commercial pigs examined by an in-depth haplotype analysis on chromosome 1. Front Genet. 2015;5:442.

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  230. 230.

    Bosse M, Lopes MS, Madsen O, Megens HJ, Crooijmans RP, Frantz LA, Harlizius B, Bastiaansen JW, Groenen MA. Artificial selection on introduced Asian haplotypes shaped the genetic architecture in European commercial pigs. Proc Biol Sci. 2015;282(1821):20152019.

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  231. 231.

    Ai H, Huang L, Ren J. Genetic diversity, linkage disequilibrium and selection signatures in Chinese and Western pigs revealed by genome-wide SNP markers. PLoS One. 2013;8(2):e56001.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  232. 232.

    Larson G, Dobney K, Albarella U, Fang M, Matisoo-Smith E, Robins J, Lowden S, Finlayson H, Brand T, Willerslev E, et al. Worldwide phylogeography of wild boar reveals multiple centers of pig domestication. Science. 2005;307(5715):1618–21.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  233. 233.

    Haile J, Larson G, Owens K, Dobney K, Shapiro B. Ancient DNA typing of archaeological pig remains corroborates historical records. J Archaeol Sci. 2010;37(1):174–7.

    Article  Google Scholar 

  234. 234.

    Goedbloed DJ, van Hooft P, Megens HJ, Langenbeck K, Lutz W, Crooijmans RP, van Wieren SE, Ydenberg RC, Prins HH. Reintroductions and genetic introgression from domestic pigs have shaped the genetic population structure of Northwest European wild boar. BMC Genet. 2013;14:43.

    PubMed  PubMed Central  Article  Google Scholar 

  235. 235.

    Krause-Kyora B, Makarewicz C, Evin A, Flink LG, Dobney K, Larson G, Hartz S, Schreiber S, von Carnap-Bornheim C, von Wurmb-Schwark N, et al. Use of domesticated pigs by Mesolithic hunter-gatherers in northwestern Europe. Nat Commun. 2013;4:2348.

    PubMed  PubMed Central  Article  Google Scholar 

  236. 236.

    Meiri M, Huchon D, Bar-Oz G, Boaretto E, Horwitz LK, Maeir AM, Sapir-Hen L, Larson G, Weiner S, Finkelstein I. Ancient DNA and population turnover in southern Levantine pigs-signature of the sea peoples migration? Sci Rep. 2013;3:3035.

    PubMed  PubMed Central  Article  Google Scholar 

  237. 237.

    Ottoni C, Flink LG, Evin A, Georg C, De Cupere B, Van Neer W, Bartosiewicz L, Linderholm A, Barnett R, Peters J, et al. Pig domestication and human-mediated dispersal in western Eurasia revealed through ancient DNA and geometric morphometrics. Mol Biol Evol. 2013;30(4):824–32.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  238. 238.

    Caliebe A, Nebel A, Makarewicz C, Krawczak M, Krause-Kyora B. Insights into early pig domestication provided by ancient DNA analysis. Sci Rep. 2017;7:44550.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  239. 239.

    Meiri M, Stockhammer PW, Marom N, Bar-Oz G, Sapir-Hen L, Morgenstern P, Macheridis S, Rosen B, Huchon D, Maran J, et al. Eastern Mediterranean mobility in the Bronze and early Iron Ages: inferences from ancient DNA of pigs and cattle. Sci Rep. 2017;7(1):701.

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  240. 240.

    Reich D. Who we are and how we got here: ancient DNA and the new science of the human past: Oxford University Press; 2018.

  241. 241.

    Rowe KC, Singhal S, Macmanes MD, Ayroles JF, Morelli TL, Rubidge EM, Bi K, Moritz CC. Museum genomics: low-cost and high-accuracy genetic data from historical specimens. Mol Ecol Resour. 2011;11(6):1082–92.

    PubMed  Article  PubMed Central  Google Scholar 

  242. 242.

    Green EJ, Speller CF. Novel substrates as sources of ancient DNA: prospects and hurdles. Genes (Basel). 2017;8(7):E180.

    PubMed  Article  CAS  PubMed Central  Google Scholar 

  243. 243.

    Billerman SM, Walsh J. Historical DNA as a tool to address key questions in avian biology and evolution: A review of methods, challenges, applications, and future directions. Mol Ecol Resour. 2019;19(5):1115–30.

    PubMed  Article  PubMed Central  Google Scholar 

  244. 244.

    Fox K, Hawks J. Use ancient remains more wisely. Nature. 2019;572(7771):581–3.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  245. 245.

    Austin RM, Sholts SB, Williams L, Kistler L, Hofman CA. Opinion: To curate the molecular past, museums need a carefully considered set of best practices. Proc Natl Acad Sci U S A. 2019;116(5):1471–4.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  246. 246.

    Grealy A, Rawlence NJ, Bunce M. Time to spread your wings: a review of the avian ancient DNA field. Genes (Basel). 2017;8(7):E184.

    PubMed  Article  CAS  PubMed Central  Google Scholar 

  247. 247.

    Albertini E, Raggi L, Vagnini M, Sassolini A, Achilli A, Marconi G, Cartechini L, Veronesi F, Falcinelli M, Brunetti BG, et al. Tracing the biological origin of animal glues used in paintings through mitochondrial DNA analysis. Anal Bioanal Chem. 2011;399(9):2987–95.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  248. 248.

    Teasdale MD, Fiddyment S, Vnouček J, Mattiangeli V, Speller C, Binois A, Carver M, Dand C, Newfield TP, Webb CC. The York Gospels: a 1000-year biological palimpsest. R Soc Open Sci. 2017;4(10):170988.

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  249. 249.

    Teasdale MD, van Doorn NL, Fiddyment S, Webb CC, O'Connor T, Hofreiter M, Collins MJ, Bradley DG. Paging through history: parchment as a reservoir of ancient DNA for next generation sequencing. Philos Trans R Soc Lond B Biol Sci. 2015;370(1660):20130379.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  250. 250.

    Greenfield HJ. The Secondary Products Revolution: the past, the present and the future. World Archaeol. 2010;42(1):29–54.

    Article  Google Scholar 

  251. 251.

    Marciniak A. The Secondary Products Revolution: empirical evidence and its current zooarchaeological critique. J World Prehist. 2011;24(2–3):117–30.

    Article  Google Scholar 

  252. 252.

    Sherratt A. Plough and pastoralism: aspects of the secondary products revolution. Cambridge: Cambridge University Press; 1981.

  253. 253.

    Spyrou MA, Bos KI, Herbig A, Krause J. Ancient pathogen genomics as an emerging tool for infectious disease research. Nat Rev Genet. 2019;20(6):323–40.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  254. 254.

    Marciniak S, Poinar HN. Ancient pathogens through human history: a paleogenomic perspective. In: Lindqvist C, Rajora OP, editors. Paleogenomics: genome-scale analysis of ancient DNA. Cham: Springer International Publishing; 2019. p. 115–38.

    Google Scholar 

  255. 255.

    Hershkovitz I, Donoghue HD, Minnikin DE, May H, Lee OY, Feldman M, Galili E, Spigelman M, Rothschild BM, Bar-Gal GK. Tuberculosis origin: the Neolithic scenario. Tuberculosis (Edinb). 2015;95(Suppl 1):S122–6.

    PubMed  Article  PubMed Central  Google Scholar 

  256. 256.

    Callaway E. Divided by DNA: The uneasy relationship between archaeology and ancient genomics. Nature. 2018;555(7698):573–6.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  257. 257.

    Heyd V. Kossinna's smile. Antiquity. 2017;91(356):348–59.

    Article  Google Scholar 

  258. 258.

    Vander LM. Population history in third-millennium-BC Europe: assessing the contribution of genetics. World Archaeol. 2016;48(5):714–28.

    Article  Google Scholar 

  259. 259.

    Vander LM. Toward a clearer view into human prehistory. Science. 2019;363(6432):1153–4.

    Article  CAS  Google Scholar 

  260. 260.

    Kristiansen K, Allentoft ME, Frei KM, Iversen R, Johannsen NN, Kroonen G, Pospieszny Ł, Price TD, Rasmussen S, Sjögren KG, Sikora M. Re-theorising mobility and the formation of culture and language among the Corded Ware Culture in Europe. Antiquity. 2017;91(356):334–47.

    Article  Google Scholar 

  261. 261.

    Johannsen NN, Larson G, Meltzer DJ, Vander LM. A composite window into human history. Science. 2017;356(6343):1118–20.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  262. 262.

    Giuffra E, Tuggle CK, Consortium F. Functional Annotation of Animal Genomes (FAANG): current achievements and roadmap. Annu Rev Anim Biosci. 2019;7:65–88.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  263. 263.

    Tait-Burkard C, Doeschl-Wilson A, McGrew MJ, Archibald AL, Sang HM, Houston RD, Whitelaw CB, Watson M. Livestock 2.0 - genome editing for fitter, healthier, and more productive farmed animals. Genome Biol. 2018;19(1):204.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  264. 264.

    International Commission on Stratigraphy. International Chronostratigraphic Chart. 2018.

    Google Scholar 

  265. 265.

    Cohen KM, Finney SC, Gibbard PL, Fan JX. The ICS International Chronostratigraphic Chart. Episodes. 2013;36(3):199–204.

    Article  Google Scholar 

  266. 266.

    Alley RB. GISP2 ice core temperature and accumulation data. 2004.

    Google Scholar 

  267. 267.

    Alley RB. The Younger Dryas cold interval as viewed from central Greenland. Quat Sci Rev. 2000;19(1–5):213–26.

    Article  Google Scholar 

  268. 268.

    Cuffey KM, Clow GD. Temperature, accumulation, and ice sheet elevation in central Greenland through the last deglacial transition. J Geophys Res. 1997;102(C12):26383–96.

    Article  Google Scholar 

  269. 269.

    Mallet C, Cornette R, Guadelli J-L. Morphometrical distinction between sheep (Ovis aries) and goat (Capra hircus) using the petrosal bone: application on French protohistoric sites. Int J Osteoarchaeol. 2019; in press.

  270. 270.

    Raj A, Stephens M, Pritchard JK. fastSTRUCTURE: variational inference of population structure in large SNP data sets. Genetics. 2014;197(2):573–89.

    PubMed  PubMed Central  Article  Google Scholar 

  271. 271.

    Rosenberg NA, Pritchard JK, Weber JL, Cann HM, Kidd KK, Zhivotovsky LA, Feldman MW. Genetic structure of human populations. Science. 2002;298(5602):2381–5.

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  272. 272.

    Guan Y. Detecting structure of haplotypes and local ancestry. Genetics. 2014;196(3):625–42.

    PubMed  PubMed Central  Article  Google Scholar 

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We thank Dan Bradley for helpful discussion and feedback. Research work at the UCD Animal Genomics Laboratory is supported by a Science Foundation Ireland (SFI) Investigator Programme Award (grant code SFI/15/IA/3154), a Department of Agriculture, Food and the Marine US-Ireland R&D Partnership Project (grant code 17/RD/US-ROl/52) and an Enterprise Ireland Disruptive Technologies Innovation Fund (DTIF) Project (grant code DT2018-0144).


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GPM, MJD and DEM wrote the manuscript. All authors have read and agreed to the content. All authors read and approved the final manuscript.

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Correspondence to David E. MacHugh.

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McHugo, G.P., Dover, M.J. & MacHugh, D.E. Unlocking the origins and biology of domestic animals using ancient DNA and paleogenomics. BMC Biol 17, 98 (2019).

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