Exploring the biomedical consequences of genetic differentiation of Native Americans.

The goal of our laboratory is to identify genes involved in immunity and cancer that bear variants common in Native Americans and rare elsewhere, and to understand their effect on susceptibility to complex diseases. We study the pattern of genetic diversity of these genes, infer their evolutionary histories and functionally characterize the variants for which we have strong evidence of influence on complex diseases.

The EPIGEN-Brazil project and the use of admixture to map susceptibility to complex traits.

The EPIGEN-BRAZIL initiative is supported by the Brazilian Ministry of Health. We are genotyping ~6,600 Brazilians from the three largest cohorts in the country: the 1982 Pelotas birth cohort (n=3,900), the Bambui (Minas Gerais) cohort study of aging (n=1,500, baseline year: 1997) and the Salvador children cohort (n=1,200, baseline year: 1997). This initiative involves four other Brazilian groups: the Fundação Oswaldo Cruz from Belo Horizonte (Bambui cohort coordinator: Dr. Maria Fernanda Lima-Costa), the University of Pelotas (Dr. Bernardo Lessa-Horta), the University of Bahia (Dr. Mauricio L Barreto) and the University of São Paulo (Dr. Jorge E Krieger). Because we expect higher European ancestry in Pelotas, higher African ancestry in Salvador, and intermediate levels of each in Bambui, there are specific methodological challenges in the association studies to be performed. This genome-wide dataset and its associated clinical information will be one of the first and largest in non-European populations, requiring robust bioinformatics support. It will allow us to study gene-environment interactions and to perform admixture mapping of several biomedical outcomes such as rheumatoid arthritis, blood pressure, and anthropometric characteristics. 

We also want to identify genes responsible for the decimation of Native Americans by infectious disease by performing “natural selection-admixture mapping” (NSAM)11. When Europeans and Africans arrived in the New World after 1492, they brought pathogens to which the Native American immune system was naive. Smallpox, measles, typhus and influenza decimated the autochthonous populations across the Americas1, and are still relevant pathogens today. 


The production of biological data by high-throughput technologies has revolutionized biology. In genetics, classical and emerging scientific questions are being approached using SNPs and CNVs genotyping and Next Generation Sequencing platforms, as in this proposal. Today, the body of investigators in biology is composed of two distinct groups: a few large research groups that produce high-throughput data, and thousands of small- and medium-sized groups such as our laboratory that produce smaller amounts of data, but also integrate it with the high-throughput data to resolve relevant scientific questions. While large-scale genomics initiatives such as the HapMap and the 1000-genomes projects rely on powerful computational and bioinformatics support to assist in data production and analysis, there are very few bioinformatics platforms oriented to small/medium-scale groups to store, handle, integrate, and analyze data from different sources, as well as to assist in combining different kinds of analyses. As a consequence, these tasks are frequently performed sub-optimally by manually handling data files, an error-prone task that is seldom coupled with adequate quality control procedures. To support investigators from small/medium-sized research groups in human population genetics and genetic epidemiology, we developed a bioinformatics platform called DIVERGENOME. This platform is designed to manage and analyze large amounts of data, and includes two components: DIVERGENOMEdb and DIVERGENOMEtools. DIVERGENOMEdb is a relational database that can integrate data from different sources, including data from the investigator himself. 

More information about DIVERGENOME can be found at:

Magalhães, Wagner C. S. ; Rodrigues, Maíra R. ; Silva, Donnys ; Soares-Souza, Giordano ; Iannini, Márcia L. ; Cerqueira, Gustavo C. ; Faria-Campos, Alessandra C. ; TARAZONA-SANTOS E. DIVERGENOME: A Bioinformatics platform to assist population genetics and genetic epidemiology studies. Genetic Epidemiology (Print), v. 36, p. n/a-n/a, 2012.  

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