Genome Biology and EvolutionGenomicsPeer-reviewed journal article
The mitogenome of Norway spruce and a reappraisal of mitochondrial recombination in plants
Alexis R. SullivaniD, Yrin Eldfjell, Bastian SchiffthaleriD, Nicolas DelhommeiD, Torben AspiD, Kim Henrik HebelstrupiD, Olivier KeechiD, Lisa Öberg, Ian Max MølleriD, Lars ArvestadiD, Nathaniel Robert StreetiD, Xiaoru WangiD
Abstract
Plant mitogenomes can be difficult to assemble because they are structurally dynamic and prone to intergenomic DNA transfers, leading to the unusual situation where an organelle genome is far outnumbered by its nuclear counterparts. As a result, comparative mitogenome studies are in their infancy and some key aspects of genome evolution are still known mainly from pre-genome, qualitative methods. To help address these limitations, we combined machine learning and in silico enrichment of mitochondrial-like long reads to assemble the bacterial-sized mitogenome of Norway spruce (Pinaceae: Picea abies). We conducted comparative analyses of repeat abundance, intergenomic transfers, substitution and rearrangement rates, and estimated repeat-by-repeat homologous recombination rates. Prompted by our discovery of highly recombinogenic small repeats in P. abies, we assessed the genomic support for the prevailing hypothesis that intramolecular recombination is predominantly driven by repeat length, with larger repeats facilitating DNA exchange more readily. Overall, we found mixed support for this view: recombination dynamics were heterogeneous across vascular plants and highly active small repeats (ca. 200 bp) were present in about a third of studied mitogenomes. As in previous studies, we did not observe any robust relationships among commonly-studied genome attributes, but we identify variation in recombination rates as a underinvestigated source of plant mitogenome diversity.
- organism: plant (other)
- assay: long-read sequencing
- research focus: genome assembly
- approach: machine learning (classical)
- Citations
- 82
- FWCI
- 10.32
- Field percentile
- top 1%
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