Your browser doesn't support javascript.
loading
Mitochondrial DNA variation across 56,434 individuals in gnomAD.
Laricchia, Kristen M; Lake, Nicole J; Watts, Nicholas A; Shand, Megan; Haessly, Andrea; Gauthier, Laura; Benjamin, David; Banks, Eric; Soto, Jose; Garimella, Kiran; Emery, James; Rehm, Heidi L; MacArthur, Daniel G; Tiao, Grace; Lek, Monkol; Mootha, Vamsi K; Calvo, Sarah E.
Afiliação
  • Laricchia KM; Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.
  • Lake NJ; Massachusetts General Hospital, Boston, Massachusetts 02114, USA.
  • Watts NA; Yale School of Medicine, New Haven, Connecticut 06510, USA.
  • Shand M; Murdoch Children's Research Institute, Melbourne, Victoria 3052, Australia.
  • Haessly A; Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.
  • Gauthier L; Massachusetts General Hospital, Boston, Massachusetts 02114, USA.
  • Benjamin D; Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.
  • Banks E; Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.
  • Soto J; Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.
  • Garimella K; Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.
  • Emery J; Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.
  • Rehm HL; Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.
  • MacArthur DG; Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.
  • Lek M; Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.
  • Mootha VK; Massachusetts General Hospital, Boston, Massachusetts 02114, USA.
  • Calvo SE; Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.
Genome Res ; 32(3): 569-582, 2022 03.
Article em En | MEDLINE | ID: mdl-35074858
ABSTRACT
Genomic databases of allele frequency are extremely helpful for evaluating clinical variants of unknown significance; however, until now, databases such as the Genome Aggregation Database (gnomAD) have focused on nuclear DNA and have ignored the mitochondrial genome (mtDNA). Here, we present a pipeline to call mtDNA variants that addresses three technical challenges (1) detecting homoplasmic and heteroplasmic variants, present, respectively, in all or a fraction of mtDNA molecules; (2) circular mtDNA genome; and (3) misalignment of nuclear sequences of mitochondrial origin (NUMTs). We observed that mtDNA copy number per cell varied across gnomAD cohorts and influenced the fraction of NUMT-derived false-positive variant calls, which can account for the majority of putative heteroplasmies. To avoid false positives, we excluded contaminated samples, cell lines, and samples prone to NUMT misalignment due to few mtDNA copies. Furthermore, we report variants with heteroplasmy ≥10%. We applied this pipeline to 56,434 whole-genome sequences in the gnomAD v3.1 database that includes individuals of European (58%), African (25%), Latino (10%), and Asian (5%) ancestry. Our gnomAD v3.1 release contains population frequencies for 10,850 unique mtDNA variants at more than half of all mtDNA bases. Importantly, we report frequencies within each nuclear ancestral population and mitochondrial haplogroup. Homoplasmic variants account for most variant calls (98%) and unique variants (85%). We observed that 1/250 individuals carry a pathogenic mtDNA variant with heteroplasmy above 10%. These mtDNA population allele frequencies are freely accessible and will aid in diagnostic interpretation and research studies.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: DNA Mitocondrial / Genoma Mitocondrial Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: DNA Mitocondrial / Genoma Mitocondrial Idioma: En Ano de publicação: 2022 Tipo de documento: Article