Novas abordagens para integração de bancos de dados e desenvolvimento de ferramentas bioinformáticas para estudos de genética de populações

Abstract

Genetic diversity is associated with the phenotypic differentiation among human populations. Even if most human diversity occurs within populations and the interaction with the environment is crucial to determine the phenotype, the study of variants that differentiated between human populations is essential in evolutionary studies and biomedical research. However, the analytical tools and data are heterogeneous in biology, reinforcing the need for new approaches to pipeline construction and tools that allow researchers to deal with the large amount and diversity of data and analyzes. In this work, we describe bioinformatics tools developed in the Laboratory of Human Genetic Diversity of the UFMG with the involvement of the PhD candidate: these tools include analyses pipelines and the bioinformatics platform DivergenomeTools that allows file conversions through a flexible pipeline. These tools have been applied in three articles on genetic diversity of native and admixture populations of Latin America, and for the identification of 69891 polymorphisms (SNPs) highly differentiated in Native American populations in respect to the West Africa, Europe and East Asia populations. These genetic variants were annotated using the database integration tool MASSA (Multi-Agent System for SNP Annotation), developed by the PhD candidate. Based on multi-agent technology, MASSA allows parallel and cooperative execution of tasks, bypassing the problem of the distribution, size and heterogeneity of the biological data. MASSA current version integrates information from these databases: dbSNP (SNP repository), UCSC (genomics), GO (ontologies), HGNC (gene names repository), OMIM (phenotypes), PGKB (pharmacogenetics), Reactome (metabolic pathways) and PolyPhen/SIFT/Provean (functional impact of nucleotide substitutions). Through the enrichment analysis performed by MASSA, we identified enriched terms in the annotation of differentiated genes in Native American. These analyzes confirmed previous knowledge on the genetic structure of natives, such as: high diversity in polymorphisms associated with type 2 diabetes and evidence of positive selection in genes involved in immune response and nervous system activity. We also identified new insights such as genes involved in the production of ionotropic membrane receptors related to the efficacy of treatment and severity of cognitive phenotypes; and nucleoporins associated with viral infection and carbohydrate transport. In perspective, we are improving the enrichment analysis, by implementing approaches that take into account the specificities of genomic diversity data and biological knowledge structure. These analyses allow us to enhance our knowledge of the biology of Native Americans, an ethnic group neglected in the initiatives for study of human genomic diversity, which is one of the focuses of the research of the LDGH.