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\"Technological innovations now allow scientists to extract and analyze ancient DNA as never before, and it has become clear--in part from David Reich's own contributions to the field--that genomics is as important a means of understanding the human past as archeology, linguistics, and the written word. Now, in [this book], Reich describes ... just how the human genome provides not only all the information that a fertilized human egg needs to develop but also contains within it the history of our species\"-- Provided by publisher.

The challenge of sequencing ancient DNA has led to the development of specialized laboratory protocols that have focused on reducing contamination and maximizing the number of molecules that are extracted from ancient remains. Despite the fact that success in ancient DNA studies is typically obtained by screening many samples to identify a promising subset, ancient DNA protocols have not, in general, focused on reducing the time required to screen samples. We present an adaptation of a popular ancient library preparation method that makes screening more efficient. First, the DNA extract is treated using a protocol that causes characteristic ancient DNA damage to be restricted to the terminal nucleotides, while nearly eliminating it in the interior of the DNA molecules, allowing a single library to be used both to test for ancient DNA authenticity and to carry out population genetic analysis. Second, the DNA molecules are ligated to a unique pair of barcodes, which eliminates undetected cross-contamination from this step onwards. Third, the barcoded library molecules include incomplete adapters of short length that can increase the specificity of hybridization-based genomic target enrichment. The adapters are completed just before sequencing, so the same DNA library can be used in multiple experiments, and the sequences distinguished. We demonstrate this protocol on 60 ancient human samples.

Mutations occur at vastly different rates across the genome, and populations, leading to differences in the spectrum of segregating polymorphisms. Here, we investigate variation in the rare variant spectrum in a sample of human genomes representing all major world populations. We find at least two distinct signatures of variation. One, consistent with a previously reported signature is characterized by an increased rate of TCC>TTC mutations in people from Western Eurasia and South Asia, likely related to differences in the rate, or efficiency of repair, of damage due to deamination of methylated guanine. We describe the geographic extent of this signature and show that it is detectable in the genomes of ancient, but not archaic humans. The second signature is private to certain Native American populations, and is concentrated at CpG sites. We show that this signature is not driven by differences in the CpG mutation rate, but is a result of the fact that highly mutable CpG sites are more likely to undergo multiple independent mutations across human populations, and the spectrum of such mutations is highly sensitive to recent demography. Both of these effects dramatically affect the spectrum of rare variants across human populations, and should be taken into account when using mutational clocks to make inference about demography.

Individuals sharing recent ancestors are likely to co-inherit large identical-by-descent (IBD) genomic regions. The distribution of these IBD segments in a population may be used to reconstruct past demographic events such as effective population size variation, but accurate IBD detection is difficult in ancient DNA data and in underrepresented populations with limited reference data. In this work, we introduce an accurate method for inferring effective population size variation during the past ~2000 years in both modern and ancient DNA data, called HapNe. HapNe infers recent population size fluctuations using either IBD sharing (HapNe-IBD) or linkage disequilibrium (HapNe-LD), which does not require phasing and can be computed in low coverage data, including data sets with heterogeneous sampling times. HapNe shows improved accuracy in a range of simulated demographic scenarios compared to currently available methods for IBD-based and LD-based inference of recent effective population size, while requiring fewer computational resources. We apply HapNe to several modern populations from the 1,000 Genomes Project, the UK Biobank, the Allen Ancient DNA Resource, and recently published samples from Iron Age Britain, detecting multiple instances of recent effective population size variation across these groups. The authors introduce a new computational method, HapNe, for inferring the recent effective size of human populations. HapNe does not require high-quality genotype data, making it suitable for the study of ancient DNA samples.

More than two hundred papers have reported genome-wide data from ancient humans. While the raw data for the vast majority are fully publicly available testifying to the commitment of the paleogenomics community to open data, formats for both raw data and meta-data differ. There is thus a need for uniform curation and a centralized, version-controlled compendium that researchers can download, analyze, and reference. Since 2019, we have been maintaining the Allen Ancient DNA Resource (AADR), which aims to provide an up-to-date, curated version of the world’s published ancient human DNA data, represented at more than a million single nucleotide polymorphisms (SNPs) at which almost all ancient individuals have been assayed. The AADR has gone through six public releases at the time of writing and review of this manuscript, and crossed the threshold of >10,000 individuals with published genome-wide ancient DNA data at the end of 2022. This note is intended as a citable descriptor of the AADR.

Our understanding of population history in deep time has been assisted by fitting admixture graphs (AGs) to data: models that specify the ordering of population splits and mixtures, which along with the amount of genetic drift and the proportions of mixture, is the only information needed to predict the patterns of allele frequency correlation among populations. The space of possible AGs relating populations is vast, and thus most published studies have identified fitting AGs through a manual process driven by prior hypotheses, leaving the majority of alternative models unexplored. Here, we develop a method for systematically searching the space of all AGs that can incorporate non-genetic information in the form of topology constraints. We implement this findGraphs tool within a software package, ADMIXTOOLS 2 , which is a reimplementation of the ADMIXTOOLS software with new features and large performance gains. We apply this methodology to identify alternative models to AGs that played key roles in eight publications and find that in nearly all cases many alternative models fit nominally or significantly better than the published one. Our results suggest that strong claims about population history from AGs should only be made when all well-fitting and temporally plausible models share common topological features. Our re-evaluation of published data also provides insight into the population histories of humans, dogs, and horses, identifying features that are stable across the models we explored, as well as scenarios of populations relationships that differ in important ways from models that have been highlighted in the literature.

In the modern human genome, elevated Neanderthal ancestry is found at genes affecting keratin filaments, suggesting that gene flow with Neanderthals helped modern humans to adapt to non-African environments; deficiencies of Neanderthal ancestry are also found, particularly on the X chromosome and in genes expressed highly in testes, suggesting that some Neanderthal mutations were not tolerated on a modern human genetic background as they reduced male fertility. Neanderthal genes today The modern human genome contains traces of Neanderthal ancestry. But is Neanderthal DNA distributed uniformly across the human genome, or is it concentrated more in some parts than in others? Sriram Sankararaman et al . show that parts of the human genome enriched for genes affecting keratin filaments (in hair, for example) also contain a relatively high concentration of Neanderthal DNA, suggesting that this DNA helped modern humans adapt to the chillier non-African environment. On the downside, many Neanderthal-derived alleles are associated with disease risk. Other parts of the human genome contain a deficiency of Neanderthal alleles, implying their active removal in evolution. Among the 'lost' genes are a number expressed in the testis and on the X chromosome, implying that Neanderthal DNA reduced human fertility when moved to a modern human genetic background. Genomic studies have shown that Neanderthals interbred with modern humans, and that non-Africans today are the products of this mixture 1 , 2 . The antiquity of Neanderthal gene flow into modern humans means that genomic regions that derive from Neanderthals in any one human today are usually less than a hundred kilobases in size. However, Neanderthal haplotypes are also distinctive enough that several studies have been able to detect Neanderthal ancestry at specific loci 1 , 3 , 4 , 5 , 6 , 7 , 8 . We systematically infer Neanderthal haplotypes in the genomes of 1,004 present-day humans 9 . Regions that harbour a high frequency of Neanderthal alleles are enriched for genes affecting keratin filaments, suggesting that Neanderthal alleles may have helped modern humans to adapt to non-African environments. We identify multiple Neanderthal-derived alleles that confer risk for disease, suggesting that Neanderthal alleles continue to shape human biology. An unexpected finding is that regions with reduced Neanderthal ancestry are enriched in genes, implying selection to remove genetic material derived from Neanderthals. Genes that are more highly expressed in testes than in any other tissue are especially reduced in Neanderthal ancestry, and there is an approximately fivefold reduction of Neanderthal ancestry on the X chromosome, which is known from studies of diverse species to be especially dense in male hybrid sterility genes 10 , 11 , 12 . These results suggest that part of the explanation for genomic regions of reduced Neanderthal ancestry is Neanderthal alleles that caused decreased fertility in males when moved to a modern human genetic background.

One enduring question in evolutionary biology is the extent of archaic admixture in the genomes of present-day populations. In this paper, we present a test for ancient admixture that exploits the asymmetry in the frequencies of the two nonconcordant gene trees in a three-population tree. This test was first applied to detect interbreeding between Neandertals and modern humans. We derive the analytic expectation of a test statistic, called the D statistic, which is sensitive to asymmetry under alternative demographic scenarios. We show that the D statistic is insensitive to some demographic assumptions such as ancestral population sizes and requires only the assumption that the ancestral populations were randomly mating. An important aspect of D statistics is that they can be used to detect archaic admixture even when no archaic sample is available. We explore the effect of sequencing error on the false-positive rate of the test for admixture, and we show how to estimate the proportion of archaic ancestry in the genomes of present-day populations. We also investigate a model of subdivision in ancestral populations that can result in D statistics that indicate recent admixture.

Population mixture is an important process in biology. We present a suite of methods for learning about population mixtures, implemented in a software package called ADMIXTOOLS, that support formal tests for whether mixture occurred and make it possible to infer proportions and dates of mixture. We also describe the development of a new single nucleotide polymorphism (SNP) array consisting of 629,433 sites with clearly documented ascertainment that was specifically designed for population genetic analyses and that we genotyped in 934 individuals from 53 diverse populations. To illustrate the methods, we give a number of examples that provide new insights about the history of human admixture. The most striking finding is a clear signal of admixture into northern Europe, with one ancestral population related to present-day Basques and Sardinians and the other related to present-day populations of northeast Asia and the Americas. This likely reflects a history of admixture between Neolithic migrants and the indigenous Mesolithic population of Europe, consistent with recent analyses of ancient bones from Sweden and the sequencing of the genome of the Tyrolean “Iceman.”