Produção Nacional
Whole-genome sequencing of 1,171 elderly admixed individuals from the largest Latin American metropolis (São Paulo, Brazil)
2020; Research Square (United States); Linguagem: Inglês
10.21203/rs.3.rs-85969/v1
AutoresMichel Satya Naslavsky, Marília O. Scliar, Guilherme Lopes Yamamoto, Jaqueline Wang, Stepanka Zverinova, Tatiana Karp, Kelly Nunes, José Ricardo Magliocco Ceroni, Diego Lima de Carvalho, Cerlos Eduardo Simões, Daniel Bozoklian, Ricardo Nonaka, Nayane Silva, Andréia S. Souza, Heloisa S. Andrade, Marília Rodrigues Silva Passos, Camila Ferreira Bannwart Castro, Celso Teixeira Mendes‐Junior, Rafael L. V. Mercuri, Thiago L. A. Miller, José Leonel Buzzo, Fernanda Orpinelli Ramos do Rego, Nathalia Matta Araujo, Wagner C. S. Magalhães, Regina Célia Mingroni‐Netto, Vctor Borda, Heinner Guio, Maurício L. Barreto, Maria Fernanda Lima‐Costa, Bernardo Lessa Horta, Eduardo Tarazona‐Santos, Diogo Meyer, Pedro A. F. Galante, Genome of the Netherlands Consortium, Erick C. Castelli, Yeda A. O. Duarte, Maria Rita Passos‐Bueno, Mayana Zatz,
Tópico(s)Genetic Associations and Epidemiology
ResumoAbstract As whole-genome sequencing (WGS) becomes the gold standard tool for studying population genomics and medical applications, data on diverse non-European and admixed individuals are still scarce. Here, we present a high-coverage WGS dataset of 1,171 highly admixed elderly Brazilians from a census-based cohort, providing over 76 million variants, of which ~ 2 million are absent from large public databases. WGS enabled identifying ~ 2,000 novel mobile element insertions, nearly 5 Mb of genomic segments absent from human genome reference, and over 140 novel alleles from HLA genes. We reclassified and curated nearly four hundred variant's pathogenicity assertions in genes associated with dominantly inherited Mendelian disorders and calculated the incidence for selected recessive disorders, demonstrating the clinical usefulness of the present study. Finally, we observed that whole-genome and HLA imputation could be significantly improved compared to available datasets since rare variation represents the largest proportion of input from WGS. These results demonstrate that even smaller sample sizes of underrepresented populations bring relevant data for genomic studies, especially when exploring analyses allowed only by WGS.
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