Investigating the mitochondrial genomic landscape of Arabidopsis thaliana by long-read sequencing

Abstract

Plant mitochondrial genomes have distinctive features compared to those of animals; namely, they are large and divergent, with sizes ranging from hundreds of thousands of to a few million bases. Recombination among repetitive regions is thought to produce similar structures that differ slightly, known as “multipartite structures,” which contribute to different phenotypes. Although many reference plant mitochondrial genomes represent almost all the genes in mitochondria, the full spectrum of their structures remains largely unknown. The emergence of long-read sequencing technology is expected to yield this landscape; however, many studies aimed to assemble only one representative circular genome, because properly understanding multipartite structures using existing assemblers is not feasible. To elucidate multipartite structures, we leveraged the information in existing reference genomes and classified long reads according to their corresponding structures. We developed a method that exploits two classic algorithms, partial order alignment (POA) and the hidden Markov model (HMM) to construct a sensitive read classifier. This method enables us to represent a set of reads as a POA graph and analyze it using the HMM. We can then calculate the likelihood of a read occurring in a given cluster, resulting in an iterative clustering algorithm. For synthetic data, our proposed method reliably detected one variation site out of 9,000-bp synthetic long reads with a 15% sequencing-error rate and produced accurate clustering. It was also capable of clustering long reads from six very similar sequences containing only slight differences. For real data, we assembled putative multipartite structures of mitochondrial genomes of Arabidopsis thaliana from nine accessions sequenced using PacBio Sequel. The results indicated that there are recurrent and strain-specific structures in A. thaliana mitochondrial genomes.

The complete mitochondrial genome of Arabidopsis thaliana (Brassicaceae) isolated in Korea

“…No structural variation among 180404IB4, 15-11, and Col-0 mitogenomes was found, while the remaining A. thaliana genomes (Table 1) presented structural variations (Davila et al, 2011). It is also congruent to the recent analysis which presents a dynamic structure of A. thaliana mitogenome along with different ecotypes (Masutani et al, 2021).…”

Long-read sequencing characterizes mitochondrial and plastid genome variants in Arabidopsismsh1mutants

“…One recent study used a method combining Flye (not the metagenomic version) and custom clustering algorithms to study mt genome heteroplasmy using the PacBio continuous long-read (CLR) datasets of Col-0 and seven other Arabidopsis thaliana accessions (Jiao and Schneeberger, 2020; Masutani et al, 2021). We analyzed these same datasets with our mapping-based pipeline.…”

“…Despite their importance and critical roles, repeats in mt genome assemblies are not always annotated correctly or completely even in model plant species (Wynn and Christensen, 2019). Moreover, these repeats may produce complex assembly graphs, which hinder a clear characterization of mt genomes (Masutani et al, 2021). Thus, mechanisms underlining the repeats and their roles in destabilizing the mt genomes require a more thorough exploration.…”

The application of Nanopore sequencing for variant calling on the human mitochondrial DNA

“…Nanopore reads find extensive implementation in forensic sequencing (Cornelis et al, 2019), characterizing structural variations and somatic mutations in cancer samples (Orsini et al, 2018;Cumbo et al, 2019;Aganezov et al, 2020), typing STEC O157:H7 Shiga toxin-producing Escherichia coli isolates for health monitoring (Greig et al, 2019). The usage of long reads for mitochondrial genome sequencing was reported for vertebrate species identification (Franco-Sierra and Díaz-Nieto, 2020), equine genetics (Dhorne-Pollet et al, 2020), the structural-wise grouping of plan mitochondrial genomes (Masutani et al, 2021), and clinical diagnostics (Wood et al, 2019). Nevertheless, despite the growing number of studies, long reads are still rarely applied as clinical panels (Orsini et al, 2018) due to low base-to-base quality, hampering their application for variant calling in comparison with short reads, for which protocols, standards, and recommendations are being continuously developed (DePristo et al, 2011;Koboldt et al, 2012;Van der Auwera et al, 2013;Koboldt, 2020;Watson et al, 2020).…”