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

被引:0
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作者
Michel S. Naslavsky
Marilia O. Scliar
Guilherme L. Yamamoto
Jaqueline Yu Ting Wang
Stepanka Zverinova
Tatiana Karp
Kelly Nunes
José Ricardo Magliocco Ceroni
Diego Lima de Carvalho
Carlos Eduardo da Silva Simões
Daniel Bozoklian
Ricardo Nonaka
Nayane dos Santos Brito Silva
Andreia da Silva Souza
Heloísa de Souza Andrade
Marília Rodrigues Silva Passos
Camila Ferreira Bannwart Castro
Celso T. Mendes-Junior
Rafael L. V. Mercuri
Thiago L. A. Miller
Jose Leonel Buzzo
Fernanda O. Rego
Nathalia M. Araújo
Wagner C. S. Magalhães
Regina Célia Mingroni-Netto
Victor Borda
Heinner Guio
Carlos P. Rojas
Cesar Sanchez
Omar Caceres
Michael Dean
Mauricio L. Barreto
Maria Fernanda Lima-Costa
Bernardo L. Horta
Eduardo Tarazona-Santos
Diogo Meyer
Pedro A. F. Galante
Victor Guryev
Erick C. Castelli
Yeda A. O. Duarte
Maria Rita Passos-Bueno
Mayana Zatz
机构
[1] University of São Paulo,Human Genome and Stem Cell Research Center
[2] University of São Paulo,Department of Genetics and Evolutionary Biology, Biosciences Institute
[3] Hospital Israelita Albert Einstein,Instituto da Criança
[4] Faculdade de Medicina da Universidade de São Paulo,Laboratory of Genome Structure and Ageing, European Research Institute for the Biology of Ageing
[5] Orthopedic Research Labs,Departamento de Química, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto
[6] Boston Children’s Hospital and Department of Genetics,Department of Biochemistry, Institute of Chemistry
[7] Harvard Medical School,Bioinformatics Graduate program
[8] Laboratório DASA,Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas
[9] University Medical Center Groningen,Instituto de Saúde Coletiva
[10] São Paulo State University (UNESP),Programa De Pós
[11] Molecular Genetics and Bioinformatics Laboratory,Graduação em Saúde Pública
[12] School of Medicine,Programa de Pós
[13] São Paulo State University (UNESP),Graduação em Epidemiologia
[14] Department of Pathology,Mosaico Translational Genomics Initiative
[15] School of Medicine,Facultad de Salud Pública y Administración
[16] Universidade de São Paulo,Instituto de Estudos Avançados Transdisciplinares
[17] Centro de Oncologia Molecular,Medical
[18] Hospital Sirio-Libanes,Surgical Nursing Department, School of Nursing
[19] University of São Paulo São Paulo,Epidemiology Department, Public Health School
[20] University of São Paulo,undefined
[21] Universidade Federal de Minas Gerais,undefined
[22] Núcleo de Ensino e Pesquisa,undefined
[23] Instituto Mário Penna,undefined
[24] Laboratorio de Biotecnologia y Biologia Molecular,undefined
[25] Instituto Nacional de Salud,undefined
[26] Universidad de Huánuco,undefined
[27] Division of Cancer Epidemiology and Genetics,undefined
[28] National Cancer Institute,undefined
[29] Universidade Federal da Bahia,undefined
[30] Center for Data and Knowledge Integration for Health,undefined
[31] Institute Gonçalo Muniz,undefined
[32] Fundação Oswaldo Cruz,undefined
[33] Instituto de Pesquisas René Rachou,undefined
[34] Fundação Oswaldo Cruz,undefined
[35] Universidade Federal de Minas Gerais,undefined
[36] Universidade Federal de Pelotas,undefined
[37] Universidade Federal de Minas Gerais,undefined
[38] Universidad Peruana Cayetano Heredia,undefined
[39] Universidade Federal de Minas Gerais,undefined
[40] University of São Paulo,undefined
[41] University of São Paulo,undefined
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摘要
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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