Genômica e miscigenação nos contextos biomédico e evolutivo

Abstract

This dissertation provides contributions to the progress of different areas of the Bioinformatics and Genomics fields in several dimensions. It presents studies lying on the generation and analysis of genetic data and its applicability for biomedical and evolutionary purposes. Readers will find contributions toward generation of good-quality genomic data, discussions on biomedical consequences suffered by neglected populations given underestimation of global human population genetic diversity, and perspectives for a better comprehension of polygenic adaptation in admixed populations. Results presented in chapter one highlight the importance of genetic data generation, discussing steps ranging from the biological material handling to genetic variant calling. This chapter addresses the importance of choosing correct analytical methods and computational tools suitable to deal with the particularities of the biological assay. Analyses show differences in results according to variant calling strategies and point out issues to be considered when customizing processes for data generation and analyses. Part of the dataset generated in the first chapter was used for population-genetics analyses performed in the second chapter. Given previously reported evidences supporting association among PDE4B and MYT1L molecular markers, native-american ancestry and acute lymphoblastic leukemia (ALL) relapse, molecular diversities of such genes were assessed in admixed and native-american populations from Latin America. One of the major findings shows linkage disequilibrium association in several populations between markers whose ALL-relapse risk-alleles frequencies are directly related with proportion of native-american ancestry. The genetic structure and diversities of such genes are analyzed and also discussed regarding potential regulatory functions, since they may directly affect ALL treatment outcome in native-americans. Several reports have highlighted uncompleteness of studies focusing on diseases comprehension and treatment outcome if not considering global human genetic diversity. Thus, this chapter contributes for fixing such distortion by analyzing and discussing results which may have consequences for ALL treatment protocols applied in Latin America countries. Studies performed with neglected populations, especially those historically arising from admixture processes, do not benefit from advances in Genomics solely due to progresses in knowledge and better-quality analyses for biomedical purposes. Technical advances and methods improvements also allow testing hypotheses about human populations evolution in the broad context of Genomics. The last chapter presents perspectives after an initial effort toward using admixed populations particularities for seeking polygenic adaptative signals. Slight alleles frequencies shifts in multiple loci may reveal selection footprints not yet identified. Hence, admixed populations may be used as a model system for applying new methods suitable to point out natural selection polygenic signals not yet reported. Thus, major discussions involve the generation of good-quality data and application of new methods to study populations underrepresented in scientific reports. One expect to provide an overview of how Bioinformatics aids in dealing with the high-complexity of building biological knowledge considering modern methods and technologies.