The homology between hylobatid chromosomes and other primates has long remained elusive. We used chromosomal in situ suppression hybridization of all human chromosome-specific DNA libraries to "paint" the chromosomes of primates and establish homologies between the human, great ape (chimpanzee, gorilla, and orangutan), and gibbon karyotypes (Hylobates lar species group, 2n = 44). The hybridization patterns unequivocally demonstrate the high degree of chromosomal homology and synteny of great ape and human chromosomes. Relative to human, no translocations were detected in great apes, except for the well-known fusion-origin of human chromosome 2 and a 5;17 translocation in the gorilla. In contrast, numerous translocations were detected that have led to the massive reorganization of the gibbon karyotype: the 22 autosomal human chromosomes have been divided into 51 elements to compose the 21 gibbon autosomes. Molecular cytogenetics promises to finally allow hylobatids to be integrated into the overall picture of chromosomal evolution in the primates.

Examining Y: The evolution of human populations has long been studied with unique sequences from the nonrecombining, male-specific Y chromosome (see the Perspective by Cann ). Poznik et al. (p. 562 ) examined 9.9 Mb of the Y chromosome from 69 men from nine globally divergent populations—identifying population and individual specific sequence variants that elucidate the evolution of the Y chromosome. Sequencing of maternally inherited mitochondrial DNA allowed comparison between the relative rates of evolution, which suggested that the coalescence, or origin, of the human Y chromosome and mitochondria both occurred approximately 120 thousand years ago. Francalacci et al. (p. 565 ) investigated the sequence divergence of 1204 Y chromosomes that were sampled within the isolated and genetically informative Sardinian population. The sequence analyses, along with archaeological records, were used to calibrate and increase the resolution of the human phylogenetic tree.

The Malagasy have been shown to be a genetically admixed population combining parental lineages with African and South East Asian ancestry. In the present paper, we fit the Malagasy admixture history in a highly resolved phylogeographic framework by typing a large set of mitochondrial DNA and Y DNA markers in unrelated individuals from inland (Merina) and coastal (Antandroy, Antanosy, and Antaisaka) ethnic groups. This allowed performance of a multilevel analysis in which the diversity among main ethnic divisions, lineage ancestries, and modes of inheritance could be concurrently evaluated. Admixture was confirmed to result from the encounter of African and Southeast Asian people with minor recent male contributions from Europe. However, new scenarios are depicted about Malagasy admixture history. The distribution of ancestral components was ethnic and sex biased, with the Asian ancestry appearing more conserved in the female than in the male gene pool and in inland than in coastal groups. A statistic based on haplotype sharing (D_HS), showing low sampling error and time linearity over the last 200 generations, was introduced here for the first time and helped to integrate our results with linguistic and archeological data. The focus about the origin of Malagasy lineages was enlarged in space and pushed back in time. Homelands could not be pinpointed but appeared to comprise two vast areas containing different populations from sub-Saharan Africa and South East Asia. The pattern of diffusion of uniparental lineages was compatible with at least two events: a primary admixture of proto-Malay people with Bantu speakers bearing a western-like pool of haplotypes, followed by a secondary flow of Southeastern Bantu speakers unpaired for gender (mainly male driven) and geography (mainly coastal).

The search for a method that utilizes biological information to predict humans’ place of origin has occupied scientists for millennia. Over the past four decades, scientists have employed genetic data in an effort to achieve this goal but with limited success. While biogeographical algorithms using next-generation sequencing data have achieved an accuracy of 700 km in Europe, they were inaccurate elsewhere. Here we describe the Geographic Population Structure (GPS) algorithm and demonstrate its accuracy with three data sets using 40,000–130,000 SNPs. GPS placed 83% of worldwide individuals in their country of origin. Applied to over 200 Sardinians villagers, GPS placed a quarter of them in their villages and most of the rest within 50 km of their villages. GPS’s accuracy and power to infer the biogeography of worldwide individuals down to their country or, in some cases, village, of origin, underscores the promise of admixture-based methods for biogeography and has ramifications for genetic ancestry testing.

In this paper, we present a study of genetic variation in sub-Saharan Africa, which is based on published and unpublished data on fast-evolving (hypervariable region 1 of mitochondrial DNA and six microsatellites of Y chromosome) and slow-evolving (haplogroup frequencies) polymorphisms of mtDNA and Y chromosome. Our study reveals a striking difference in the genetic structure of food-producer (Bantu and Sudanic speakers) and hunter-gatherer populations (Pygmies, !Kung, and Hadza). In fact, the ratio of mtDNA to Y-chromosome Nυ is substantially higher in food producers than in hunter-gatherers as determined by fast-evolving polymorphisms (1.76 versus 0.11). This finding indicates that the two population groups differ substantially in female and male migration rate and/or effective size. The difference also persists when linguistically homogeneous populations are used and outlier populations are eliminated (1.78 vs 0.19) or when the jacknife procedure is applied to a paired population data set (1.32 to 7.84 versus 0.14 to 0.66). The higher ratio of mtDNA to Y-chromosome Nν in food producers than in hunter-gatherers is further confirmed by the use of slow-evolving polymorphisms (1.59 to 7.91 versus 0.12 to 0.35). To explain these results, we propose a model that integrates demographic and genetic aspects and incorporates ethnographic knowledge. In such a model, the asymmetric gene flow, polyginy, and patrilocality play an important role in differentiating the genetic structure of sub-Saharan populations. The existence of an asymmetric gene flow is supported by the phylogeographic features of mtDNA and Y-chromosome haplogroups found in the two population groups. The role of polyginy and patrilocality is sustained by the evidence of a differential pressure of genetic drift and gene flow on maternal and paternal lineages of food producers and hunter-gatherers that is revealed through the analysis of mitochondrial and Y-chromosomal intrapopulational variation.

The ability to taste phenylthiocarbamide (PTC) and 6-n-propylthiouracil (PROP) is a polymorphic trait mediated by the TAS2R38 bitter taste receptor gene. It has long been hypothesized that global genetic diversity at this locus evolved under pervasive pressures from balancing natural selection. However, recent high-resolution population genetic studies of TAS2Rs suggest that demographic events have played a critical role in the evolution of these genes. We here utilized the largest TAS2R38 database yet analyzed, consisting of 5,589 individuals from 105 populations, to examine natural selection, haplotype frequencies and linkage disequilibrium to estimate the effects of both selection and demography on contemporary patterns of variation at this locus. We found signs of an ancient balancing selection acting on this gene but no post Out-Of-Africa departures from neutrality, implying that the current observed patterns of variation can be predominantly explained by demographic, rather than selective events. In addition, we found signatures of ancient selective forces acting on different African TAS2R38 haplotypes. Collectively our results provide evidence for a relaxation of recent selective forces acting on this gene and a revised hypothesis for the origins of the present-day worldwide distribution of TAS2R38 haplotypes.