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Hunter-gatherer populations in Africa preserve unique information about human history, but genetic sub-structures of these populations remain unclear. Using newly designed microarray and statistical methods, these authors analyse genetic compositions of southern African populations and reveal an ancient link between southern and eastern Africa.

A large proportion of genetic variants in the human genome have been predicted to be deleterious. This Review examines the frequency and patterns of deleterious alleles in the human genome and considers recent studies with conflicting findings on whether the mutation load, or burden of deleterious alleles, differs across populations.

Geneticists must rethink how they conduct their research and how they communicate results.

An analysis of models of human populations in Africa, using some newly sequenced genomes, finds that human origins in the continent can best be described by a weakly structured stem model.

Analysis of ancient nuclear DNA, recovered from 40,000-year-old remains in the Denisova Cave, Siberia, hints at the multifaceted interaction of human populations following their migration out of Africa. See Article p.1053

The Tyrolean Iceman is 5,300 years old and his mitochondrial genome has been previously sequenced. This study reports the full genome sequence of the Iceman and reveals that he probably had brown eyes, was at risk for coronary disease and may have been infected with the pathogen Lyme borreliosis.

Deep whole-genome sequencing of 300 individuals from 142 diverse populations provides insights into key population genetic parameters, shows that all modern human ancestry outside of Africa including in Australasians is consistent with descending from a single founding population, and suggests a higher rate of accumulation of mutations in non-Africans compared to Africans since divergence.

Accounting for DNA sequence variation improves epigenetic age prediction accuracy in diverse African cohorts and transferability across diverse genetic ancestries.

DNA methylation patterns are studied in five diverse human populations. The evolutionary stability of DNA methylation in humans is found to be much greater than that observed previously in plants.

Selective sweeps are events in which beneficial mutations spread rapidly through a population. Here, Sugden et al. develop SWIF(r), a probabilistic classification framework for detecting and localizing selective sweeps, and apply it to genomic data from the ‡Khomani San.

Genetic analyses of ancestrally diverse populations show evidence of heterogeneity across ancestries and provide insights into clinical implications, highlighting the importance of including ancestrally diverse populations to maximize genetic discovery and reduce health disparities.

1000 Genomes imputation can increase the power of genome-wide association studies to detect genetic variants associated with human traits and diseases. Here, the authors develop a method to integrate and analyse low-coverage sequence data and SNP array data, and show that it improves imputation performance.

A sequencing study comparing ancient and contemporary genomes reveals that most present-day Europeans derive from at least three highly differentiated populations: west European hunter-gatherers, ancient north Eurasians (related to Upper Palaeolithic Siberians) and early European farmers of mainly Near Eastern origin.

This report from the 1000 Genomes Project describes the genomes of 1,092 individuals from 14 human populations, providing a resource for common and low-frequency variant analysis in individuals from diverse populations; hundreds of rare non-coding variants at conserved sites, such as motif-disrupting changes in transcription-factor-binding sites, can be found in each individual.

Results for the final phase of the 1000 Genomes Project are presented including whole-genome sequencing, targeted exome sequencing, and genotyping on high-density SNP arrays for 2,504 individuals across 26 populations, providing a global reference data set to support biomedical genetics.