The genetic background of the Brazilian population is mainly characterized by three parental populations: European, African, and Native American. The aim of this study was to overview the genetic ancestry estimates for different Brazilian geographic regions and analyze factors involved in these estimates. In this systematic scoping review were included 51 studies, comprehending 81 populations of 19 states from five regions of Brazil. To reduce the potential of bias from studies with different sampling methods, we calculated the mean genetic ancestry weighted by the number of individuals. The weighted mean proportions of European, African, and Native American ancestries were 68.1%, 19.6%, and 11.6%, respectively. At the regional level, the highest European contribution occurred in the South, while the highest African and Native American contributions occurred in the Northeastern and Northern regions, respectively. Among states in the Northeast region, Bahia and Ceará showed significant differences, suggesting distinct demographic histories. This review contributes for a broader understanding of the Brazilian ancestry and indicates that the ancestry estimates are influenced by the type of molecular marker and the sampling method.

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BackgroundSignal peptide is one of the most important motifs involved in protein trafficking and it ultimately influences protein function. Considering the expected functional conservation among orthologs it was hypothesized that divergence in signal peptides within orthologous groups is mainly due to N-terminal protein sequence misannotation. Thus, discrepancies in signal peptide prediction of orthologous proteins were used to identify misannotated proteins in five Plasmodium species.MethodsSignal peptide (SignalP) and orthology (OrthoMCL) were combined in an innovative strategy to identify orthologous groups showing discrepancies in signal peptide prediction among their protein members (Mixed groups). In a comparative analysis, multiple alignments for each of these groups and gene models were visually inspected in search of misannotated proteins and, whenever possible, alternative gene models were proposed. Thresholds for signal peptide prediction parameters were also modified to reduce their impact as a possible source of discrepancy among orthologs. Validation of new gene models was based on RT-PCR (few examples) or on experimental evidence already published (ApiLoc).ResultsThe rate of misannotated proteins was significantly higher in Mixed groups than in Positive or Negative groups, corroborating the proposed hypothesis. A total of 478 proteins were reannotated and change of signal peptide prediction from negative to positive was the most common. Reannotations triggered the conversion of almost 50% of all Mixed groups, which were further reduced by optimization of signal peptide prediction parameters.ConclusionsThe methodological novelty proposed here combining orthology and signal peptide prediction proved to be an effective strategy for the identification of proteins showing wrongly N-terminal annotated sequences, and it might have an important impact in the available data for genome-wide searching of potential vaccine and drug targets and proteins involved in host/parasite interactions, as demonstrated for five Plasmodium species.

The molecular basis of Plasmodium vivax chloroquine (CQ) resistance is still unknown. Elucidating the molecular background of parasites that are sensitive or resistant to CQ will help to identify and monitor the spread of resistance. By genotyping a panel of molecular markers, we demonstrate a similar genetic variability between in vitro CQ-resistant and sensitive phenotypes of P. vivax parasites. However, our studies identified two loci (MS8 and MSP1-B10) that could be used to discriminate between both CQ-susceptible phenotypes among P. vivax isolates in vitro. These preliminary data suggest that microsatellites may be used to identify and to monitor the spread of P. vivax-resistance around the world.