Performing genetic studies in multiple human populations can identify disease risk alleles that are common in one population but rare in others1, with the potential to illuminate pathophysiology, health disparities, and the population genetic origins of disease alleles. We analyzed 9.2 million single nucleotide polymorphisms (SNPs) in each of 8,214 Mexicans and Latin Americans: 3,848 with type 2 diabetes (T2D) and 4,366 non-diabetic controls. In addition to replicating previous findings2–4, we identified a novel locus associated with T2D at genome-wide significance spanning the solute carriers SLC16A11 and SLC16A13 (P=3.9×10−13; odds ratio (OR)=1.29). The association was stronger in younger, leaner people with T2D, and replicated in independent samples (P=1.1×10−4; OR=1.20). The risk haplotype carries four amino acid substitutions, all in SLC16A11; it is present at ≈50% frequency in Native American samples and ≈10% in East Asian, but rare in European and African samples. Analysis of an archaic genome sequence indicated the risk haplotype introgressed into modern humans via admixture with Neandertals. The SLC16A11 mRNA is expressed in liver, and V5-tagged SLC16A11 protein localizes to the endoplasmic reticulum. Expression of SLC16A11 in heterologous cells alters lipid metabolism, most notably causing an increase in intracellular triacylglycerol levels. Despite T2D having been well studied by genome-wide association studies (GWAS) in other populations, analysis in Mexican and Latin American individuals identified SLC16A11 as a novel candidate gene for T2D with a possible role in triacylglycerol metabolism.

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Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40–50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10–20% (14–24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.

Loss of gut microbial diversity1–6 in industrial populations is associated with chronic diseases7, underscoring the importance of studying our ancestral gut microbiome. However, relatively little is known about the composition of pre-industrial gut microbiomes. Here we performed a large-scale de novo assembly of microbial genomes from palaeofaeces. From eight authenticated human palaeofaeces samples (1,000–2,000 years old) with well-preserved DNA from southwestern USA and Mexico, we reconstructed 498 medium- and high-quality microbial genomes. Among the 181 genomes with the strongest evidence of being ancient and of human gut origin, 39% represent previously undescribed species-level genome bins. Tip dating suggests an approximate diversification timeline for the key human symbiont Methanobrevibacter smithii. In comparison to 789 present-day human gut microbiome samples from eight countries, the palaeofaeces samples are more similar to non-industrialized than industrialized human gut microbiomes. Functional profiling of the palaeofaeces samples reveals a markedly lower abundance of antibiotic-resistance and mucin-degrading genes, as well as enrichment of mobile genetic elements relative to industrial gut microbiomes. This study facilitates the discovery and characterization of previously undescribed gut microorganisms from ancient microbiomes and the investigation of the evolutionary history of the human gut microbiota through genome reconstruction from palaeofaeces.