Extraction and annotation of human mitochondrial genomes from 1000 Genomes Whole Exome Sequencing data

Abstract

BackgroundWhole Exome Sequencing (WES) is one of the most used and cost-effective next generation technologies that allows sequencing of all nuclear exons. Off-target regions may be captured if they present high sequence similarity with baits. Bioinformatics tools have been optimized to retrieve a large amount of WES off-target mitochondrial DNA (mtDNA), by exploiting the aspecificity of probes, partially overlapping to Nuclear mitochondrial Sequences (NumtS). The 1000 Genomes project represents one of the widest resources to extract mtDNA sequences from WES data, considering the large effort the scientific community is undertaking to reconstruct human population history using mtDNA as marker, and the involvement of mtDNA in pathology.ResultsA previously published pipeline aimed at assembling mitochondrial genomes from off-target WES reads and further improved to detect insertions and deletions (indels) and heteroplasmy in a dataset of 1242 samples from the 1000 Genomes project, enabled to obtain a nearly complete mitochondrial genome from 943 samples (76% analyzed exomes). The robustness of our computational strategy was highlighted by the reduction of reads amount recognized as mitochondrial in the original annotation produced by the Consortium, due to NumtS filtering.An accurate survey was carried out on 1242 individuals. 215 indels, mostly heteroplasmic, and 3407 single base variants were mapped. A homogeneous mismatches distribution was observed along the whole mitochondrial genome, while a lower frequency of indels was found within protein-coding regions, where frameshift mutations may be deleterious. The majority of indels and mismatches found were not previously annotated in mitochondrial databases since conventional sequencing methods were limited to homoplasmy or quasi-homoplasmy detection. Intriguingly, upon filtering out non haplogroup-defining variants, we detected a widespread population occurrence of rare events predicted to be damaging. Eventually, samples were stratified into blood- and lymphoblastoid-derived to detect possibly different trends of mutability in the two datasets, an analysis which did not yield significant discordances.ConclusionsTo the best of our knowledge, this is likely the most extended population-scale mitochondrial genotyping in humans enriched with the estimation of heteroplasmies.

Genetic Evidence for Elevated Pathogenicity of Mitochondrial DNA Heteroplasmy in Autism Spectrum Disorder

“…The exome sequencing data from the father were processed using the same method but were only utilized for exploring data quality and detecting sample contamination. The average depth of mtDNA coverage in the remaining samples was ~141X, comparable to the coverage reported in previous studies using whole-exome or whole-genome sequencing data [38,39,73]. Comparisons of site-specific sequencing coverage for homoplasmic and heteroplasmic sites also showed strong correlations between individuals within the same family ( R 2 >0.6, S14 Fig).…”

“…To evaluate mtDNA heteroplasmy among healthy individuals, next-generation sequencing technologies such as mtDNA-targeted sequencing [33–36] or computational approaches, which directly leverage (off-target) reads from existing datasets produced by whole-genome sequencing [37,38] or whole-exome sequencing [39,40] have been widely harnessed in recent years. These approaches largely outperform Sanger sequencing and microarray-based sequencing in their ability to detect mtDNA heteroplasmies, and have proven practical for large population-based studies [37–39]. …”

HmtDB 2016: data update, a better performing query system and human mitochondrial DNA haplogroup predictor

“…Indeed, since mtDNA mutations, in most cases, exert their phenotypic effect only above a certain mutation load threshold (6,7), a wide range of low heteroplasmic variants is identified even in healthy individuals (8,9). …”

“…In the last 10 years, the number of sequenced genomes has continued to increase exponentially (Figure 3). Currently there are 32 922 mitochondrial genomes publicly available in HmtDB, including 1427 mitochondrial genomes reconstructed as off-target sequences from exome data (9,18) generated by the 1000 Genomes Project (19,20). The sequences are organized in two data sets representing individuals with healthy and disease phenotype, including 29 274 and 3648 samples, respectively.…”

Mitochondrial Disease Sequence Data Resource (MSeqDR): A global grass-roots consortium to facilitate deposition, curation, annotation, and integrated analysis of genomic data for the mitochondrial disease clinical and research communities

“…Users can select specific „tracks” of data to readily show, hide, re-order or zoom from chromosome to single basepair level resolution, which conveniently allows interpretation of genetic variants in specific genomic contexts and for any specific genomic region of interest. Key standard reference gene and variant annotation tracks are available to enable users to visualize all variant-level data in public exome and genome datasets, including those in the National Heart Lung and Blood Institute (NHLBI) exome variant server (“EVS Exome Variants” track) and 1000 Genomes Project (“1000 Genomes” and “1000 Genomes Whole Exome Sequencing Mitochondrial Variants” tracks [6, 7]. …”