Genome-wide Analysis in Brazilians Reveals Highly Differentiated Native American Genome Regions

Mychaleckyj, Josyf C.; Havt, Alexandre; Nayak, Uma; Pinkerton, Relana C.; Farber, Emily; Concannon, Patrick; Lima, Aldo A. M.; Guerrant, Richard L.

doi:10.1093/molbev/msw249

Cited by 20 publications

(25 citation statements)

References 75 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This observation remains true even if one includes Latin American populations represented in worldwide collaborative studies, such as the 1000 Genomes Project and gnomAD, which involved Colombian, Peruvian, Puerto Rican, and Mexican populations 4 , 14 , 22 . Indeed, among the 3529 studies published in the GWAS catalogue 3 , only 75 studies contain data from Brazilian individuals, and only three are exclusively comprised of Brazilian populations 23 – 25 .…”

Section: Introductionmentioning

confidence: 99%

The Brazilian Initiative on Precision Medicine (BIPMed): fostering genomic data-sharing of underrepresented populations

et al. 2020

View full text Add to dashboard Cite

The development of precision medicine strategies requires prior knowledge of the genetic background of the target population. However, despite the availability of data from admixed Americans within large reference population databases, we cannot use these data as a surrogate for that of the Brazilian population. This lack of transferability is mainly due to differences between ancestry proportions of Brazilian and other admixed American populations. To address the issue, a coalition of research centres created the Brazilian Initiative on Precision Medicine (BIPMed). In this study, we aim to characterise two datasets obtained from 358 individuals from the BIPMed using two different platforms: whole-exome sequencing (WES) and a single nucleotide polymorphism (SNP) array. We estimated allele frequencies and variant pathogenicity values from the two datasets and compared our results using the BIPMed dataset with other public databases. Here, we show that the BIPMed WES dataset contains variants not included in dbSNP, including 6480 variants that have alternative allele frequencies (AAFs) >1%. Furthermore, after merging BIPMed WES and SNP array data, we identified 809,589 variants (47.5%) not present within the 1000 Genomes dataset. Our results demonstrate that, through the incorporation of Brazilian individuals into public genomic databases, BIPMed not only was able to provide valuable knowledge needed for the implementation of precision medicine but may also enhance our understanding of human genome variability and the relationship between genetic variation and disease predisposition.

show abstract

Section: Introductionmentioning

confidence: 99%

The Brazilian Initiative on Precision Medicine (BIPMed): fostering genomic data-sharing of underrepresented populations

et al. 2020

View full text Add to dashboard Cite

show abstract

“…The Indigenous peoples of North America are underrepresented in the population genetics literature as a whole (5) and in studies of selection in particular. Only a handful of genomic studies of natural selection have been conducted in the Americas, and the majority of these have focused on populations in South America (6)(7)(8)(9). To our knowledge, only two genomic studies of selection in North American populations have been published.…”

mentioning

confidence: 99%

Comparing signals of natural selection between three Indigenous North American populations

Reynolds

Mata‐Míguez

Miró-Herrans

et al. 2019

Proc. Natl. Acad. Sci. U.S.A.

View full text Add to dashboard Cite

While many studies have highlighted human adaptations to diverse environments worldwide, genomic studies of natural selection in Indigenous populations in the Americas have been absent from this literature until very recently. Since humans first entered the Americas some 20,000 years ago, they have settled in many new environments across the continent. This diversity of environments has placed variable selective pressures on the populations living in each region, but the effects of these pressures have not been extensively studied to date. To help fill this gap, we collected genome-wide data from three Indigenous North American populations from different geographic regions of the continent (Alaska, southeastern United States, and central Mexico). We identified signals of natural selection in each population and compared signals across populations to explore the differences in selective pressures among the three regions sampled. We find evidence of adaptation to cold and high-latitude environments in Alaska, while in the southeastern United States and central Mexico, pathogenic environments seem to have created important selective pressures. This study lays the foundation for additional functional and phenotypic work on possible adaptations to varied environments during the history of population diversification in the Americas.

show abstract

“…In Brazil, distinct geographical regions present dissimilar patterns of genetic ancestry due to specific migratory currents from distinct continents (Alves-Silva et al, 2000 ; Mychaleckyj et al, 2017 ). In the light of this knowledge, we investigated SNPs allelic and genotypes distribution in the influenza cases according to their geographical Brazilian region.…”

Section: Resultsmentioning

confidence: 99%

Investigation of Human IFITM3 Polymorphisms rs34481144A and rs12252C and Risk for Influenza A(H1N1)pdm09 Severity in a Brazilian Cohort

Martins

Oliveira

Garcia

et al. 2020

Front. Cell. Infect. Microbiol.

View full text Add to dashboard Cite

Genome-wide Analysis in Brazilians Reveals Highly Differentiated Native American Genome Regions

Cited by 20 publications

References 75 publications

The Brazilian Initiative on Precision Medicine (BIPMed): fostering genomic data-sharing of underrepresented populations

The Brazilian Initiative on Precision Medicine (BIPMed): fostering genomic data-sharing of underrepresented populations

Comparing signals of natural selection between three Indigenous North American populations

Investigation of Human IFITM3 Polymorphisms rs34481144A and rs12252C and Risk for Influenza A(H1N1)pdm09 Severity in a Brazilian Cohort

Contact Info

Product

Resources

About