In the 15th century, ∼900,000 Native Americans, mostly Tupí speakers, lived on the Brazilian coast. By the end of the 18th century, the coastal native populations were declared extinct. The Tupí arrived on the east coast after leaving the Amazonian basin ∼2,000 y before present; however, there is no consensus on how this migration occurred: toward the northern Amazon and then directly to the Atlantic coast, or heading south into the continent and then migrating to the coast. Here we leveraged genomic data from one of the last remaining putative representatives of the Tupí coastal branch, a small, admixed, self-reported Tupiniquim community, as well as data of a Guaraní Mbyá native population from Southern Brazil and of three other native populations from the Amazonian region. We demonstrated that the Tupiniquim Native American ancestry is not related to any extant Brazilian Native American population already studied, and thus they could be considered the only living representatives of the extinct Tupí branch that used to settle the Atlantic Coast of Brazil. Furthermore, these data show evidence of a direct migration from Amazon to the Northeast Coast in pre-Columbian time, giving rise to the Tupí Coastal populations, and a single distinct migration southward that originated the Guaraní people from Brazil and Paraguay. This study elucidates the population dynamics and diversification of the Brazilian natives at a genomic level, which was made possible by recovering data from the Brazilian coastal population through the genomes of mestizo individuals.

The analysis of genomic data (~400,000 autosomal SNPs) enabled the reliable estimation of inbreeding levels in a sample of 541 individuals sampled from a highly admixed Brazilian population isolate (an African-derived quilombo in the State of São Paulo). To achieve this, different methods were applied to the joint information of two sets of markers (one complete and another excluding loci in patent linkage disequilibrium). This strategy allowed the detection and exclusion of markers that biased the estimation of the average population inbreeding coefficient (Wright’s fixation index FIS), which value was eventually estimated as around 1% using any of the methods we applied. Quilombo demographic inferences were made by analyzing the structure of runs of homozygosity (ROH), which were adapted to cope with a highly admixed population with a complex foundation history. Our results suggest that the amount of ROH <2Mb of admixed populations should be somehow proportional to the genetic contribution from each parental population.

The Andean Altiplano has been occupied continuously since the late Pleistocene, ~12,000 years ago, which places the Andean natives as one of the most ancient populations living at high altitudes. In the present study, we analyzed genomic data from Native Americans living a long-time at Andean high altitude and at Amazonia and Mesoamerica lowland areas. We have identified three new candidate genes - SP100, DUOX2 and CLC - with evidence of positive selection for altitude adaptation in Andeans. These genes are involved in the TP53 pathway and are related to physiological routes important for high-altitude hypoxia response, such as those linked to increased angiogenesis, skeletal muscle adaptations, and immune functions at the fetus-maternal interface. Our results, combined with other studies, showed that Andeans have adapted to the Altiplano in different ways and using distinct molecular strategies as compared to those of other natives living at high altitudes.

Hepatoblastomas exhibit the lowest mutational burden among pediatric tumors. We previously showed that epigenetic disruption is crucial for hepatoblastoma carcinogenesis. Our data revealed hypermethylation of nicotinamide N-methyltransferase, a highly expressed gene in adipocytes and hepatocytes. The expression pattern and the role of nicotinamide N-methyltransferase in pediatric liver tumors have not yet been explored, and this study aimed to evaluate the effect of nicotinamide N-methyltransferase hypermethylation in hepatoblastomas. We evaluated 45 hepatoblastomas and 26 non-tumoral liver samples. We examined in hepatoblastomas if the observed nicotinamide N-methyltransferase promoter hypermethylation could lead to dysregulation of expression by measuring mRNA and protein levels by real-time quantitative polymerase chain reaction, immunohistochemistry, and Western blot assays. The potential impact of nicotinamide N-methyltransferase changes was evaluated on the metabolic profile by high-resolution magic angle spinning nuclear magnetic resonance spectroscopy. Significant nicotinamide N-methyltransferase downregulation was revealed in hepatoblastomas, with two orders of magnitude lower nicotinamide N-methyltransferase expression in tumor samples and hepatoblastoma cell lines than in hepatocellular carcinoma cell lines. A specific TSS1500 CpG site (cg02094283) of nicotinamide N-methyltransferase was hypermethylated in tumors, with an inverse correlation between its methylation level and nicotinamide N-methyltransferase expression. A marked global reduction of the nicotinamide N-methyltransferase protein was validated in tumors, with strong correlation between gene and protein expression. Of note, higher nicotinamide N-methyltransferase expression was statistically associated with late hepatoblastoma diagnosis, a known clinical variable of worse prognosis. In addition, untargeted metabolomics analysis detected aberrant lipid metabolism in hepatoblastomas. Data presented here showed the first evidence that nicotinamide N-methyltransferase reduction occurs in hepatoblastomas, providing further support that the nicotinamide N-methyltransferase downregulation is a wide phenomenon in liver cancer. Furthermore, this study unraveled the role of DNA methylation in the regulation of nicotinamide N-methyltransferase expression in hepatoblastomas, in addition to evaluate the potential effect of nicotinamide N-methyltransferase reduction in the metabolism of these tumors. These preliminary findings also suggested that nicotinamide N-methyltransferase level may be a potential prognostic biomarker for hepatoblastoma.

This article deals with the estimation of inbreeding and substructure levels in a set of 10 (later regrouped as eight) African-derived quilombo communities from the Ribeira River Valley in the southern portion of the state of São Paulo, Brazil. Inbreeding levels were assessed through F-values estimated from the direct analysis of genealogical data and from the statistical analysis of a large set of 30 molecular markers. The levels of population substructure found were modest, as was the degree of inbreeding: in the set of all communities considered together, F-values were 0.00136 and 0.00248 when using raw and corrected data from their complete genealogical structures, respectively, and 0.022 and 0.036 when using the information taken from the statistical analysis of all 30 loci and of 14 single-nucleotide polymorphic loci, respectively. The overall frequency of consanguineous marriages in the set of all communities considered together was ∼ 2%. Although modest, the values of the estimated parameters are much larger than those obtained for the overall Brazilian population and in general much smaller than the ones recorded for other Brazilian isolates. To circumvent problems related to heterogeneous sampling and virtual absence of reliable records of biological relationships, we had to develop or adapt several methods for making valid estimates of the prescribed parameters.

The mutation age and local ancestry of chromosomal segments harbouring mutations associated with autosomal recessive (AR) disorders in Brazilian admixed populations remain unknown; additionally, inbreeding levels for these affected individuals continue to be estimated based on genealogical information. Here, we calculated inbreeding levels using a runs of homozygosity approach, mutation age and local ancestry to infer the origin of each chromosomal segments containing disorder-causing mutations in KLC2, IMPA1, MED25 and WNT7A. Genotyped data were generated from 18 patients affected by AR diseases and combined to the 1000 genome project (1KGP) and Simons genome diversity project (SGDP) databases to infer local ancestry. We found a major European contribution for mutated haplotypes with recent mutation age and inbreeding values found only in Native American and Middle East individuals. These results contribute to identifying the origin of and to understanding how these diseases are maintained and spread in Brazilian and world populations.

This paper deals with the frequency and structure of first-cousin marriages, by far the most important and frequent type of consanguineous mating in human populations. Based on the analysis of large amounts of data from the world literature and from large Brazilian samples recently collected, we suggest some explanations for the asymmetry of sexes among the parental sibs of first-cousin marriages. We suggest also a simple manner to correct the method that uses population surnames to assess the different Wright fixation indexes FIS, FST and FIT taking into account not only alternative methods of surname transmission, but also the asymmetries that are almost always observed in the distribution of sexes among the parental sibs of first-cousins.

In this paper we consider the problem of segmenting n aligned random sequences of equal length m into a finite number of independent blocks. We propose to use a penalized maximum likelihood criterion to infer simultaneously the number of points of independence as well as the position of each one of these points. We show how to compute the estimator efficiently by means of a dynamic programming algorithm with time complexity O(m 2 n). We also propose another algorithm, called hierarchical algorithm, that provides an approximation to the estimator when the sample size increases and runs in time O(mn). Our main theoretical result is the proof of almost sure consistency of the estimator and the convergence of the hierarchical algorithm when the sample size n grows to infinity. We illustrate the convergence of these algorithms through some simulation examples and we apply the method to real protein sequence alignments of Ebola Virus.