BackgroundComparisons of maternally-inherited mitochondrial DNA (mtDNA) and paternally-inherited non-recombining Y chromosome (NRY) variation have provided important insights into the impact of sex-biased processes (such as migration, residence pattern, and so on) on human genetic variation. However, such comparisons have been limited by the different molecular methods typically used to assay mtDNA and NRY variation (for example, sequencing hypervariable segments of the control region for mtDNA vs. genotyping SNPs and/or STR loci for the NRY). Here, we report a simple capture array method to enrich Illumina sequencing libraries for approximately 500 kb of NRY sequence, which we use to generate NRY sequences from 623 males from 51 populations in the CEPH Human Genome Diversity Panel (HGDP). We also obtained complete mtDNA genome sequences from the same individuals, allowing us to compare maternal and paternal histories free of any ascertainment bias.ResultsWe identified 2,228 SNPs in the NRY sequences and 2,163 SNPs in the mtDNA sequences. Our results confirm the controversial assertion that genetic differences between human populations on a global scale are bigger for the NRY than for mtDNA, although the differences are not as large as previously suggested. More importantly, we find substantial regional variation in patterns of mtDNA versus NRY variation. Model-based simulations indicate very small ancestral effective population sizes (<100) for the out-of-Africa migration as well as for many human populations. We also find that the ratio of female effective population size to male effective population size (Nf/Nm) has been greater than one throughout the history of modern humans, and has recently increased due to faster growth in Nf than Nm.ConclusionsThe NRY and mtDNA sequences provide new insights into the paternal and maternal histories of human populations, and the methods we introduce here should be widely applicable for further such studies.

The Y chromosome is one of the best genetic materials to explore the evolutionary history of human populations. Global analyses of Y chromosomal short tandem repeats (STRs) data can reveal very interesting world population structures and histories. However, previous Y-STR works tended to focus on small geographical ranges or only included limited sample sizes. In this study, we have investigated population structure and demographic history using 17 Y chromosomal STRs data of 979 males from 44 worldwide populations. The largest genetic distances have been observed between pairs of African and non-African populations. American populations with the lowest genetic diversities also showed large genetic distances and coancestry coefficients with other populations, whereas Eurasian populations displayed close genetic affinities. African populations tend to have the oldest time to the most recent common ancestors (TMRCAs), the largest effective population sizes and the earliest expansion times, whereas the American, Siberian, Melanesian, and isolated Atayal populations have the most recent TMRCAs and expansion times, and the smallest effective population sizes. This clear geographic pattern is well consistent with serial founder model for the origin of populations outside Africa. The Y-STR dataset presented here provides the most detailed view of worldwide population structure and human male demographic history, and additionally will be of great benefit to future forensic applications and population genetic studies.

Human populations around the world encounter various environmental challenges and, consequently, develop genetic adaptations to different selection forces. Identifying the differences in natural selection between populations is critical for understanding the roles of specific genetic variants in evolutionary adaptation. Although numerous methods have been developed to detect genetic loci under recent directional selection, a probabilistic solution for testing and quantifying selection differences between populations is lacking. Here we report the development of a probabilistic method for testing and estimating selection differences between populations. By use of a probabilistic model of genetic drift and selection, we showed that logarithm odds ratios of allele frequencies provide estimates of the differences in selection coefficients between populations. The estimates approximate a normal distribution, and variance can be estimated using genome-wide variants. This allows us to quantify differences in selection coefficients and to determine the confidence intervals of the estimate. Our work also revealed the link between genetic association testing and hypothesis testing of selection differences. It therefore supplies a solution for hypothesis testing of selection differences. This method was applied to a genome-wide data analysis of Han and Tibetan populations. The results confirmed that both the EPAS1 and EGLN1 genes are under statistically different selection in Han and Tibetan populations. We further estimated differences in the selection coefficients for genetic variants involved in melanin formation and determined their confidence intervals between continental population groups. Application of the method to empirical data demonstrated the outstanding capability of this novel approach for testing and quantifying differences in natural selection.