Explore the vast range of titles available.

The ability to detect recent natural selection in the human population would have profound implications for the study of human history and for medicine. Here, we introduce a framework for detecting the genetic imprint of recent positive selection by analysing long-range haplotypes in human populations. We first identify haplotypes at a locus of interest (core haplotypes). We then assess the age of each core haplotype by the decay of its association to alleles at various distances from the locus, as measured by extended haplotype homozygosity (EHH). Core haplotypes that have unusually high EHH and a high population frequency indicate the presence of a mutation that rose to prominence in the human gene pool faster than expected under neutral evolution. We applied this approach to investigate selection at two genes carrying common variants implicated in resistance to malaria: G6PD 1 and CD40 ligand 2 . At both loci, the core haplotypes carrying the proposed protective mutation stand out and show significant evidence of selection. More generally, the method could be used to scan the entire genome for evidence of recent positive selection.

Human populations have undergone dramatic expansions in size, but other than the growth associated with agriculture, the dates and magnitudes of those expansions have never been resolved. Here, we introduce two new statistical tests for population expansion, which use variation at a number of unlinked genetic markers to study the demographic histories of natural populations. By analyzing genetic variation in various aboriginal populations from throughout the world, we show highly significant evidence for a major human population expansion in Africa, but no evidence of expansion outside of Africa. The inferred African expansion is estimated to have occurred between 49,000 and 640,000 years ago, certainly before the Neolithic expansions, and probably before the splitting of African and non-African populations. In showing a significant difference between African and non-African populations, our analysis supports the unique role of Africa in human evolutionary history, as has been suggested by most other genetic work. In addition, the missing signal in non-African populations may be the result of a population bottleneck associated with the emergence of these populations from Africa, as postulated in the ``Out of Africa'' model of modern human origins.

Whole-genome association studies are predicted to be especially powerful in isolated populations owing to increased linkage disequilibrium (LD) and decreased allelic diversity, but this possibility has not been empirically tested 1 , 2 , 3 . We compared genome-wide data on 113,240 SNPs typed on 30 trios from the Pacific island of Kosrae to the same markers typed in the 270 samples from the International HapMap Project 4 , 5 . The extent of LD is longer and haplotype diversity is lower in Kosrae than in the HapMap populations. More than 98% of Kosraen haplotypes are present in HapMap populations, indicating that HapMap will be useful for genetic studies on Kosrae. The long-range LD around common alleles and limited diversity result in improved efficiency in genetic studies in this population and augments the power to detect association of 'hidden SNPs'.

The authors report on ancient DNA data from two human skeletons buried within the chancel of the 1608–1616 church at the North American colonial settlement of Jamestown, Virginia. Available archaeological, osteological and documentary evidence suggest that these individuals are Sir Ferdinando Wenman and Captain William West, kinsmen of the colony's first Governor, Thomas West, Third Baron De La Warr. Genomic analyses of the skeletons identify unexpected maternal relatedness as both carried the mitochondrial haplogroup H10e. In this unusual case, aDNA prompted further historical research that led to the discovery of illegitimacy in the West family, an aspect of identity omitted, likely intentionally, from genealogical records.

With the availability of a dense genome-wide map of single nucleotide polymorphisms (SNPs) 1 , a central issue in human genetics is whether it is now possible to use linkage disequilibrium (LD) to map genes that cause disease. LD refers to correlations among neighbouring alleles, reflecting ‘haplotypes’ descended from single, ancestral chromosomes. The size of LD blocks has been the subject of considerable debate. Computer simulations 2 and empirical data 3 have suggested that LD extends only a few kilobases (kb) around common SNPs, whereas other data have suggested that it can extend much further, in some cases greater than 100 kb 4 , 5 , 6 . It has been difficult to obtain a systematic picture of LD because past studies have been based on only a few (1–3) loci and different populations. Here, we report a large-scale experiment using a uniform protocol to examine 19 randomly selected genomic regions. LD in a United States population of north-European descent typically extends 60 kb from common alleles, implying that LD mapping is likely to be practical in this population. By contrast, LD in a Nigerian population extends markedly less far. The results illuminate human history, suggesting that LD in northern Europeans is shaped by a marked demographic event about 27,000–53,000 years ago.

To address the quality and completeness of single-nucleotide polymorphism (SNP) databases, we resequenced 173 kb (spanning 17 loci) in 150 chromosomes of west African and European ancestry. Over 88% of SNPs in the public (TSC and BAC overlap) and Celera databases were confirmed in independent resequencing. Approximately 45% of all human heterozygosity is attributable to SNPs already available from the two databases, and of SNPs with minor-allele frequencies >10%, more than half are represented.

Microsatellite length mutations are often modeled using the generalized stepwise mutation process, which is a type of random walk. If this model is sufficiently accurate, one can estimate the coalescence time between alleles of a locus after a mathematical transformation of the allele lengths. When large-scale microsatellite genotyping first became possible, there was substantial interest in using this approach to make inferences about time and demography, but that interest has waned because it has not been possible to empirically validate the clock by comparing it with data in which the mutation process is well understood. We analyzed data from 783 microsatellite loci in human populations and 292 loci in chimpanzee populations, and compared them with up to one gigabase of aligned sequence data, where the molecular clock based upon nucleotide substitutions is believed to be reliable. We empirically demonstrate a remarkable linearity (r[sup]2 > 0.95) between the microsatellite average square distance statistic and sequence divergence. We demonstrate that microsatellites are accurate molecular clocks for coalescent times of at least 2 million years (My). We apply this insight to confirm that the African populations San, Biaka Pygmy, and Mbuti Pygmy have the deepest coalescent times among populations in the Human Genome Diversity Project. Furthermore, we show that microsatellites support unbiased estimates of population differentiation (F[sub]ST) that are less subject to ascertainment bias than single nucleotide polymorphism (SNP) F[sub]ST. These results raise the prospect of using microsatellite data sets to determine parameters of population history. When genotyped along with SNPs, microsatellite data can also be used to correct for SNP ascertainment bias. [PUBLICATION ABSTRACT]

Variation in the human genome sequence is key to understanding susceptibility to disease in modern populations and the history of ancestral populations. Unlocking this information requires knowledge of the patterns and underlying causes of human sequence diversity. By applying a new population-genetic framework to two genome-wide polymorphism surveys, we find that the human genome contains sizeable regions (stretching over tens of thousands of base pairs) that have intrinsically high and low rates of sequence variation. We show that the primary determinant of these patterns is shared genealogical history. Only a fraction of the variation (at most 25%) is due to the local mutation rate. By measuring the average distance over which genealogical histories are typically preserved, these data provide the first genome-wide estimate of the average extent of correlation among variants (linkage disequilibrium). The results are best explained by extreme variability in the recombination rate at a fine scale, and provide the first empirical evidence that such recombination 'hot spots' are a general feature of the human genome and have a principal role in shaping genetic variation in the human population.

Single-nucleotide polymorphisms (SNPs) have been the focus of much attention in human genetics because they are extremely abundant and well-suited for automated large-scale genotyping. Human SNPs, however, are less informative than other types of genetic markers (such as simple-sequence length polymorphisms or microsatellites) and thus more loci are required for mapping traits. SNPs offer similar advantages for experimental genetic organisms such as the mouse, but they entail no loss of informativeness because bi-allelic markers are fully informative in analysing crosses between inbred strains. Here we report a large-scale analysis of SNPs in the mouse genome. We characterized the rate of nucleotide polymorphism in eight mouse strains and identified a collection of 2,848 SNPs located in 1,755 sequence-tagged sites (STSs) using high-density oligonucleotide arrays. Three-quarters of these SNPs have been mapped on the mouse genome, providing a first-generation SNP map of the mouse. We have also developed a multiplex genotyping procedure by which a genome scan can be performed with only six genotyping reactions per animal.

The timing of the initial peopling of the Polynesian islands remains highly debated. Suggested dates are primarily based on archaeological evidence and differ by several hundred years. Ioannidis et al. [2021] used genome-wide data from 430 modern individuals from 21 Pacific islands to obtain genetic estimates. Their results supported late settlement dates, e.g. approximately 1200 CE for Rapa Nui. However, when investigating the underlying model we found that the genetic estimator used by Ioannidis et al. [2021] is biased to be about 300 years too old. Correcting for this bias gives genetic settlement dates that are more recent than any dates consistent with archaeological records, as radiocarbon dating of human-modified artifacts shows settlement definitively earlier than the bias-corrected genetic estimates. These too-recent estimates can only be explained by substantial gene flow between islands after their initial settlements. Therefore, contacts attested by archaeological and linguistic evidence must have been accompanied also by demographically significant movement of people. This gene flow well after the initial settlements was not modelled by Ioannidis et al. [2021] and challenges their interpretation that carving anthropomorphic stone statues was spread during initial settlements of islands. Instead, the distribution of this cultural practice likely reflects later inter-island exchanges, as suggested earlier.Competing Interest StatementThe authors have declared no competing interest.