Mitochondrial DNA variation across 56,434 individuals in gnomAD

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: (i) detecting homoplasmic and heteroplasmic variants, present respectively in all or a fraction of mtDNA molecules, (ii) circular mtDNA genome, and (iii) 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 greater than 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. 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.

A bioinformatics pipeline for estimating mitochondrial DNA copy number and heteroplasmy levels from whole genome sequencing data

“…We investigated different calculations for mtDNA-CN, and found that there was no significant difference between them. We demonstrate that we detect true population-level SNV variants at 2000× chrM coverage, as shown by our high overlap with variants in the gnomAD database ( 42 ). The most novel aspect of MitoHPC is the second iteration variant identification, which calls variants using a sample's unique chrM sequence as the reference.…”

“…To cross-validate the variants we identified, we determined how many of the variants were also present in the gnomAD v3 database of over 56 000 WGS samples ( 42 ). We took 8793 unique chrM homoplasmic and heteroplasmic variants from gnomAD.…”

“…In addition to homopolymer regions, samples with low mtDNA-CN (<100) may be more likely to yield NUMT variants as false-positive mitochondrial heteroplasmic calls ( 42 ). We plotted mtDNA-CN versus heteroplasmy count to visualize the relationship between these two measurements ( Supplementary Figure S9 ).…”

Novel method for multiplexed full-length single-molecule sequencing of the human mitochondrial genome

“…In addition, non-pathogenic polymorphic variants were identified in all samples mostly in homoplasmy or high-level heteroplasmy (>90%) along with variants of unknown significance which were observed mostly in low heteroplasmic frequency (<10%) (Supplementary Table 8). Assessing variant frequency within the general population and specific haplogroups is helpful when evaluating the pathogenicity of such variants 39 . The pathogenic variants identified by the Cas9-mtDNA-enrichment nanopore sequencing were compared with the clinical laboratory results.…”

Benchmarking Low-Frequency Variant Calling With Long-Read Data on Mitochondrial DNA

“…variants that are present in a fraction of the mtDNA copies) is associated with aging as well as various diseases such as neurological and cardiovascular, cancer and diabetes ( Stewart and Chinnery, 2021 ). At the population level, Laricchia et al analyzed 56,434 mtDNA samples, where most samples showed no heteroplasmy; however, one in 250 samples carried pathogenic heteroplasmic variants above the 10% ( Laricchia et al, 2022 ). Bolze et al analyzed ∼200,000 mitochondrial genomes between 5% and 1% and identified one heteroplasmic variant per person on average (range from 0 to 13, median 0) ( Bolze et al, 2020 ).…”