The human salivary microbiome may play a role in diseases of the oral cavity and interact with microbiomes from other parts of the human body (in particular, the intestinal tract), but little is known about normal variation in the salivary microbiome. We analyzed 14,115 partial (∼500 bp) 16S ribosomal RNA (rRNA) sequences from saliva samples from 120 healthy individuals (10 individuals from each of 12 worldwide locations). These sequences could be assigned to 101 known bacterial genera, of which 39 were not previously reported from the human oral cavity; phylogenetic analysis suggests that an additional 64 unknown genera are present. There is high diversity in the salivary microbiome within and between individuals, but little geographic structure. Overall, ∼13.5% of the total variance in the composition of genera is due to differences among individuals, which is remarkably similar to the fraction of the total variance in neutral genetic markers that can be attributed to differences among human populations. Investigation of some environmental variables revealed a significant association between the genetic distances among locations and the distance of each location from the equator. Further characterization of the enormous diversity revealed here in the human salivary microbiome will aid in elucidating the role it plays in human health and disease, and in the identification of potentially informative species for studies of human population history.

BackgroundAlthough the importance of the human oral microbiome for health and disease is increasingly recognized, variation in the composition of the oral microbiome across different climates and geographic regions is largely unexplored.ResultsHere we analyze the saliva microbiome from native Alaskans (76 individuals from 4 populations), Germans (10 individuals from 1 population), and Africans (66 individuals from 3 populations) based on next-generation sequencing of partial 16S rRNA gene sequences. After quality filtering, a total of 67,916 analyzed sequences resulted in 5,592 OTUs (defined at ≥97% identity) and 123 genera. The three human groups differed significantly by the degree of diversity between and within individuals (e.g. beta diversity: Africans > Alaskans > Germans; alpha diversity: Germans > Alaskans > Africans). UniFrac, network, ANOSIM, and correlation analyses all indicated more similarities in the saliva microbiome of native Alaskans and Germans than between either group and Africans. The native Alaskans and Germans also had the highest number of shared bacterial interactions. At the level of shared OTUs, only limited support for a core microbiome shared across all three continental regions was provided, although partial correlation analysis did highlight interactions involving several pairs of genera as conserved across all human groups. Subsampling strategies for compensating for the unequal number of individuals per group or unequal sequence reads confirmed the above observations.ConclusionOverall, this study illustrates the distinctiveness of the saliva microbiome of human groups living under very different climatic conditions.Electronic supplementary materialThe online version of this article (doi:10.1186/s12866-014-0316-1) contains supplementary material, which is available to authorized users.

No abstract

SummaryWe have analyzed mtDNA HVI sequences and Y chromosome haplogroups based on 11 binary markers in 371 individuals, from 11 populations in the Caucasus and the neighbouring countries of Turkey and Iran. Y chromosome haplogroup diversity in the Caucasus was almost as high as in Central Asia and the Near East, and significantly higher than in Europe. More than 27% of the variance in Y-haplogroups can be attributed to differences between populations, whereas mtDNA showed much lower heterogeneity between populations (less then 5%), suggesting a strong influence of patrilocal social structure. Several groups from the highland region of the Caucasus exhibited low diversity and high differentiation for either or both genetic systems, reflecting enhanced genetic drift in these small, isolated populations. Overall, the Caucasus groups showed greater similarity with West Asian than with European groups for both genetic systems, although this similarity was much more pronounced for the Y chromosome than for mtDNA, suggesting that male-mediated migrations from West Asia have influenced the genetic structure of Caucasus populations.

We report targeted sequencing of 63 known prostate cancer risk regions in a multi-ancestry study of 9,237 men and use the data to explore the contribution of low-frequency variation to disease risk. We show that SNPs with minor allele frequencies (MAFs) of 0.1-1% explain a substantial fraction of prostate cancer risk in men of African ancestry. We estimate that these SNPs account for 0.12 (standard error (s.e.) = 0.05) of variance in risk (∼42% of the variance contributed by SNPs with MAF of 0.1-50%). This contribution is much larger than the fraction of neutral variation due to SNPs in this class, implying that natural selection has driven down the frequency of many prostate cancer risk alleles; we estimate the coupling between selection and allelic effects at 0.48 (95% confidence interval [0.19, 0.78]) under the Eyre-Walker model. Our results indicate that rare variants make a disproportionate contribution to genetic risk for prostate cancer and suggest the possibility that rare variants may also have an outsize effect on other common traits.

The 8q24 region harbors multiple risk variants for distinct cancers, including >8 for prostate cancer. In this study, we conducted fine mapping of the 8q24 risk region (127.8-128.8Mb) in search of novel associations with common and rare variation in 4853 prostate cancer case patients and 4678 control subjects of African ancestry. All statistical tests were two-sided. We identified three independent associations at P values of less than 5.00×10(-8), all of which were replicated in studies from Ghana and Uganda (combined sample = 5869 case patients, 5615 control subjects; rs114798100: risk allele frequency [RAF] = 0.04, per-allele odds ratio [OR] = 2.31, 95% confidence interval [CI] = 2.04 to 2.61, P = 2.38×10(-40); rs72725879: RAF = 0.33, OR = 1.37, 95% CI = 1.30 to 1.45, P = 3.04×10(-27); and rs111906932: RAF = 0.03, OR = 1.79, 95% CI = 1.53 to 2.08, P = 1.39×10(-13)). Risk variants rs114798100 and rs111906923 are only found in men of African ancestry, with rs111906923 representing a novel association signal. The three variants are located within or near a number of prostate cancer-associated long noncoding RNAs (lncRNAs), including PRNCR1, PCAT1, and PCAT2. These findings highlight ancestry-specific risk variation and implicate prostate-specific lncRNAs at the 8q24 prostate cancer susceptibility region.

BackgroundIt is increasingly recognized that the bacteria that live in and on the human body (the microbiome) can play an important role in health and disease. The composition of the microbiome is potentially influenced by both internal factors (such as phylogeny and host physiology) and external factors (such as diet and local environment), and interspecific comparisons can aid in understanding the importance of these factors.ResultsTo gain insights into the relative importance of these factors on saliva microbiome diversity, we here analyze the saliva microbiomes of chimpanzees (Pan troglodytes) and bonobos (Pan paniscus) from two sanctuaries in Africa, and from human workers at each sanctuary. The saliva microbiomes of the two Pan species are more similar to one another, and the saliva microbiomes of the two human groups are more similar to one another, than are the saliva microbiomes of human workers and apes from the same sanctuary. We also looked for the existence of a core microbiome and find no evidence for a taxon-based core saliva microbiome for Homo or Pan. In addition, we studied the saliva microbiome from apes from the Leipzig Zoo, and found an extraordinary diversity in the zoo ape saliva microbiomes that is not found in the saliva microbiomes of the sanctuary animals.ConclusionsThe greater similarity of the saliva microbiomes of the two Pan species to one another, and of the two human groups to one another, are in accordance with both the phylogenetic relationships of the hosts as well as with host physiology. Moreover, the results from the zoo animals suggest that novel environments can have a large impact on the microbiome, and that microbiome analyses based on captive animals should be viewed with caution as they may not reflect the microbiome of animals in the wild.

Interacting with others by interpreting and responding to their facial expressions is an essential and early developing social skill in humans. We examined whether and how variation in catechol-O-methyltransferase (COMT) and serotonin transporter (5-HTTLPR) genes is associated with 7-month-old infants' electrocortical responses to facial expressions. The results revealed that COMT variants are associated with differences in infants' brain responses to fearful faces over centro-parietal regions, whereas 5-HTTLPR variants are associated with differences in infants' brain responses to happy faces over fronto-temporal regions. Further support for differential associations of these gene variants with emotional processing came from our analysis of infant behavioral temperament: variation in COMT was associated with differences in infants' recovery from distress, whereas variation in 5-HTTLPR was associated with infants' smiling and laughter. This pattern of findings indicates that, in infancy, these genetic variants influence distinct brain systems involved in the processing of either positive or negative emotions. This has wide reaching implications for our understanding of how genetic variation biases specific brain mechanisms, giving rise to individual differences in emotional sensitivity and temperament.