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. 2022 Jul 22;20(1):168.
doi: 10.1186/s12915-022-01373-5.

Identification of human mitochondrial RNA cleavage sites and candidate RNA processing factors

Affiliations

Identification of human mitochondrial RNA cleavage sites and candidate RNA processing factors

Guillermo Carbajosa et al. BMC Biol. .

Abstract

Background: The human mitochondrial genome is transcribed as long strands of RNA containing multiple genes, which require post-transcriptional cleavage and processing to release functional gene products that play vital roles in cellular energy production. Despite knowledge implicating mitochondrial post-transcriptional processes in pathologies such as cancer, cardiovascular disease and diabetes, very little is known about the way their function varies on a human population level and what drives changes in these processes to ultimately influence disease risk. Here, we develop a method to detect and quantify mitochondrial RNA cleavage events from standard RNA sequencing data and apply this approach to human whole blood data from > 1000 samples across independent cohorts.

Results: We detect 54 putative mitochondrial RNA cleavage sites that not only map to known gene boundaries, short RNA ends and RNA modification sites, but also occur at internal gene positions, suggesting novel mitochondrial RNA cleavage junctions. Inferred RNA cleavage rates correlate with mitochondrial-encoded gene expression across individuals, suggesting an impact on downstream processes. Furthermore, by comparing inferred cleavage rates to nuclear genetic variation and gene expression, we implicate multiple genes in modulating mitochondrial RNA cleavage (e.g. MRPP3, TBRG4 and FASTKD5), including a potentially novel role for RPS19 in influencing cleavage rates at a site near to the MTATP6-COX3 junction that we validate using shRNA knock down data.

Conclusions: We identify novel cleavage junctions associated with mitochondrial RNA processing, as well as genes newly implicated in these processes, and detect the potential impact of variation in cleavage rates on downstream phenotypes and disease processes. These results highlight the complexity of the mitochondrial transcriptome and point to novel mechanisms through which nuclear-encoded genes can potentially influence key mitochondrial processes.

Keywords: Mitochondria; QTL; RNA; Transcriptomics.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Inferred cleavage rates in mitochondrial RNA. A Starts and ends of original genuine RNA fragments should ‘stack’ at the same positions in the genome. B Cleavage ratio of a site calculated as the number of processed reads (those starting or ending either side of the site) as a proportion of total reads across the site (processed and unprocessed)
Fig. 2
Fig. 2
Relationship between genotype and inferred cleavage rate at multiple positions on the nuclear genome and mitochondrial transcriptome, respectively. Inferred cleavage positions are represented by red circles along the mitochondrial transcriptome, and inferred cleavage ratios are colour coded using three categories: yellow on known gene boundaries, blue within tRNAs, green on mRNAs within a tRNA flanked boundary and red on mRNA within a non-tRNA flanked boundary. Beta estimates, P-values, cleavage rates and genotypes displayed in boxplots originate from the CARTaGENE dataset (N = 799 for each plot)
Fig. 3
Fig. 3
Comparison of inferred cleavage rates in mitochondrial RNA between control and shRNA knock down data for candidate genes (N = 8 in each plot, 4 from KD and 4 from controls). A Control vs sh knock down cleavage ratio for TBRG4 at position 9219 near the MT-ATP6 to MT-CO3 gene boundary. B Control vs sh knock down cleavage ratio for RPS19 at position 9157 near the MT-ATP6 to MT-CO3 gene boundary

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