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Whole-genome sequencing of 1,171 elderly admixed individuals from São Paulo, Brazil.

Michel Satya NaslavskyMarilia O ScliarGuilherme L YamamotoJaqueline Yu Ting WangStepanka ZverinovaTatiana KarpKelly NunesJosé Ricardo Magliocco CeroniDiego Lima de CarvalhoCarlos Eduardo da Silva SimõesDaniel BozoklianRicardo NonakaNayane Dos Santos Brito SilvaAndreia da Silva SouzaHeloisa de Souza AndradeMarília Rodrigues Silva PassosCamila Ferreira Bannwart CastroCelso Teixeira Mendes-JuniorRafael L V MercuriThiago L A MillerJose Leonel BuzzoFernanda O RegoNathalia M AraújoWagner C S MagalhãesRegina Célia Mingroni-NettoVictor BordaHeinner GuioCarlos P RojasCesar SanchezOmar Alberto Caceres ReyMichael DeanMauricio L BarretoMaria Fernanda Lima-CostaBernardo Lessa HortaEduardo Tarazona-SantosDiogo MeyerPedro Alexandre Favoretto GalanteVictor GuryevErick C CastelliYeda A O DuarteMaria Rita Passos-BuenoMayana Zatz
Published in: Nature communications (2022)
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.
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