Splice-Break: exploiting an RNA-seq splice junction algorithm to discover mitochondrial DNA deletion breakpoints and analyses of psychiatric disorders

摘要

Deletions in the 16.6?kb mitochondrial genome have been implicated in numerous disorders that often display muscular and/or neurological symptoms due to the high-energy demands of these tissues. We describe a catalogue of 4489 putative mitochondrial DNA (mtDNA) deletions, including their frequency and relative read rate, using a combinatorial approach of mitochondria-targeted PCR, next-generation sequencing, bioinformatics, post-hoc filtering, annotation, and validation steps. Our bioinformatics pipeline uses MapSplice, an RNA-seq splice junction detection algorithm, to detect and quantify mtDNA deletion breakpoints rather than mRNA splices. Analyses of 93 samples from postmortem brain and blood found (i) the 4977?bp ‘common deletion’ was neither the most frequent deletion nor the most abundant; (ii) brain contained significantly more deletions than blood; (iii) many high frequency deletions were previously reported in MitoBreak, suggesting they are present at low levels in metabolically active tissues and are not exclusive to individuals with diagnosed mitochondrial pathologies; (iv) many individual deletions (and cumulative metrics) had significant and positive correlations with age and (v) the highest deletion burdens were observed in major depressive disorder brain, at levels greater than Kearns–Sayre Syndrome muscle. Collectively, these data suggest the Splice-Break pipeline can detect and quantify mtDNA deletions at a high level of resolution.