Does ethnic ancestry play a role in smoking?

The higher proportion of smokers among Black people in Brazil has been attributed to socioeconomic disparities, but genetic factors could also contribute for this finding. This study aimed at investigating associations between smoking status with genetically defined ethnic ancestry and socioeconomic features in Brazilians. Blood samples were collected from 448 volunteers (66.7% male; age: 37.1±11.4 years) classified as current smokers (CS: 60.9%), former smokers (FS: 8.9%) and never smokers (NS: 30.1%). Individual interethnic admixtures were determined using a 48 insertion-deletion polymorphisms ancestry-informative-marker panel. CS showed a lower amount of European ancestry than NS (0.837±0.243 X 0.883±0.194, p≤0.05) and FS (0.837±0.243 X 0.864±0.230, p≤0.05), and a higher proportion of African Sub-Saharan ancestry than FS (0.128±0.222 X 0.07±0.174, p≤0.05) and NS (0.128±0.222 X 0.085±0.178, p≤0.05). NS reported a higher number of years in school than CS (11.2±3.7 X 8.9±3.8, p≤0.001). CS were less common in economic Class A (30%) and more common in Class B (56.8%). In multivariate analysis, only lower number of school years and lower economic class were associated with higher chances for CS. The use of genetic molecular markers for characterizing ethnic background confirmed that socioeconomic disparities are the main determinants of higher smoking rates among Blacks in Brazil

High-throughput sequencing of a South American Amerindian.

The emergence of next-generation sequencing technologies allowed access to the vast amounts of information that are contained in the human genome. This information has contributed to the understanding of individual and population-based variability and improved the understanding of the evolutionary history of different human groups. However, the genome of a representative of the Amerindian populations had not been previously sequenced. Thus, the genome of an individual from a South American tribe was completely sequenced to further the understanding of the genetic variability of Amerindians. A total of 36.8 giga base pairs (Gbp) were sequenced and aligned with the human genome. These Gbp corresponded to 95.92% of the human genome with an estimated miscall rate of 0.0035 per sequenced bp. The data obtained from the alignment were used for SNP (single-nucleotide) and INDEL (insertion-deletion) calling, which resulted in the identification of 502,017 polymorphisms, of which 32,275 were potentially new high-confidence SNPs and 33,795 new INDELs, specific of South Native American populations. The authenticity of the sample as a member of the South Native American populations was confirmed through the analysis of the uniparental (maternal and paternal) lineages. The autosomal comparison distinguished the investigated sample from others continental populations and revealed a close relation to the Eastern Asian populations and Aboriginal Australian. Although, the findings did not discard the classical model of America settlement; it brought new insides to the understanding of the human population history. The present study indicates a remarkable genetic variability in human populations that must still be identified and contributes to the understanding of the genetic variability of South Native American populations and of the human populations history

Comparative population-based genetic analysis of the Amerindian with the populations in the HapMap database.

<p>The Amerindian sample (IND) was compared to 20 randomly selected samples from the following populations in the HapMap database: JPT (Japanese in Tokyo, Japan), CHD (Chinese in metropolitan Denver, Colorado, USA), CHB (Han Chinese in Beijing, China), CEU (residents of Utah, Nevada, USA with Northern and Western European ancestry from the CEPH collection), TSI (Tuscans in Italy), GIH (Gujarati Indians in Houston, Texas, USA), YRI (Yoruba in Ibadan, Nigeria), ASW (individuals with African ancestry in Southwest USA), LWK (Luhya in Webuye, Kenya), MKK (Maasai in Kinyawa, Kenya), and MEX (individuals with Mexican ancestry in Los Angeles, California, USA). The populations were clustered according to their geographic origin as follows: East-Asia (JPT, CHB, and CHD), Europe (CEU and TSI), South-West Asia (SWA, formed by the GIH population), Africa (YRI, ASW, LWK, and MKK) and North America (NA, formed by the MEX population). A) Diagram of the genetic contribution of the models for a value of K in the range of four to seven. The x-axis represents the different samples that were clustered according to the population and the geographic area of origin. B) Principal Component Analysis (PCA) of the Amerindian sample (indicated with the arrow) and the samples extracted from the HapMap database. The abscissa represents the 1^st component, and the ordinate represents the 2^nd component. C) Heat map of the FST index between the investigated populations and the Amerindian sample.</p

Population genetic structure analysis of 1,000 genomes project's, Aboriginal Australian and Native South American genotype dataset.

<p>The diagram of genetic contribution was obtained using Structure software for models of 4 to 6 subpopulations. The populations were grouped labeled as follow, according to their major continental ancestry: IND (Native South American individual, this work); ABO (Aboriginal Australian individual, Rasmussen et al. 2011); Eastern Asian (CHS, CHB and JPT); Europeans (CEU, IBS, TSI, FIN and GBR); African (ASW, LWK, MKK and YRI); and New Americans (CLM, PUR and MXL). The plot represents the rate of contribution from each subpopulation (colors) to the samples (x axis).</p

High-quality polymorphisms identified and not identified in the dbSNP build 135 database.

<p>*These percentages correspond to the column total.</p

Three-population admixture test <i>f₃</i>^*.

<p>*The <i>f₃</i> tests the hypothesis that the outgroup is result of admixture of two ingroups (see Material and Methods). The groups were identified as: IND - South Native American; ABO - Australian Aboriginal (Rasmussen et al. 2011); ASN - Asian populations (CHS, CHB and JPT); EUR - European populations (CEU, IBS, TSI, FIN and GBR); AFR - African populations (ASW, LWK, MKK and YRI); and AMR - American populations (CLM, PUR and MXL).</p

Characterisation of microbial attack on archaeological bone

As part of an EU funded project to investigate the factors influencing bone preservation in the archaeological record, more than 250 bones from 41 archaeological sites in five countries spanning four climatic regions were studied for diagenetic alteration. Sites were selected to cover a range of environmental conditions and archaeological contexts. Microscopic and physical (mercury intrusion porosimetry) analyses of these bones revealed that the majority (68%) had suffered microbial attack. Furthermore, significant differences were found between animal and human bone in both the state of preservation and the type of microbial attack present. These differences in preservation might result from differences in early taphonomy of the bones. © 2003 Elsevier Science Ltd. All rights reserved