TY - JOUR
T1 - Whole-genome sequencing of 1,171 elderly admixed individuals from São Paulo, Brazil
AU - Naslavsky, Michel S.
AU - Scliar, Marilia O.
AU - Yamamoto, Guilherme L.
AU - Wang, Jaqueline Yu Ting
AU - Zverinova, Stepanka
AU - Karp, Tatiana
AU - Nunes, Kelly
AU - Ceroni, José Ricardo Magliocco
AU - de Carvalho, Diego Lima
AU - da Silva Simões, Carlos Eduardo
AU - Bozoklian, Daniel
AU - Nonaka, Ricardo
AU - dos Santos Brito Silva, Nayane
AU - da Silva Souza, Andreia
AU - de Souza Andrade, Heloísa
AU - Passos, Marília Rodrigues Silva
AU - Castro, Camila Ferreira Bannwart
AU - Mendes-Junior, Celso T.
AU - Mercuri, Rafael L.V.
AU - Miller, Thiago L.A.
AU - Buzzo, Jose Leonel
AU - Rego, Fernanda O.
AU - Araújo, Nathalia M.
AU - Magalhães, Wagner C.S.
AU - Mingroni-Netto, Regina Célia
AU - Borda, Victor
AU - Guio, Heinner
AU - Rojas, Carlos P.
AU - Sanchez, Cesar
AU - Caceres, Omar
AU - Dean, Michael
AU - Barreto, Mauricio L.
AU - Lima-Costa, Maria Fernanda
AU - Horta, Bernardo L.
AU - Tarazona-Santos, Eduardo
AU - Meyer, Diogo
AU - Galante, Pedro A.F.
AU - Guryev, Victor
AU - Castelli, Erick C.
AU - Duarte, Yeda A.O.
AU - Passos-Bueno, Maria Rita
AU - Zatz, Mayana
N1 - Publisher Copyright:
© 2022, The Author(s).
PY - 2022/12
Y1 - 2022/12
N2 - 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 enables identification of ~2,000 previously undescribed mobile element insertions without previous description, nearly 5 Mb of genomic segments absent from the human genome reference, and over 140 alleles from HLA genes absent from public resources. We reclassify and curate pathogenicity assertions for nearly four hundred variants in genes associated with dominantly-inherited Mendelian disorders and calculate the incidence for selected recessive disorders, demonstrating the clinical usefulness of the present study. Finally, we observe 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.
AB - 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 enables identification of ~2,000 previously undescribed mobile element insertions without previous description, nearly 5 Mb of genomic segments absent from the human genome reference, and over 140 alleles from HLA genes absent from public resources. We reclassify and curate pathogenicity assertions for nearly four hundred variants in genes associated with dominantly-inherited Mendelian disorders and calculate the incidence for selected recessive disorders, demonstrating the clinical usefulness of the present study. Finally, we observe 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.
UR - https://www.scopus.com/pages/publications/85125792333
U2 - 10.1038/s41467-022-28648-3
DO - 10.1038/s41467-022-28648-3
M3 - Article
C2 - 35246524
AN - SCOPUS:85125792333
SN - 2041-1723
VL - 13
JO - Nature Communications
JF - Nature Communications
IS - 1
M1 - 1004
ER -