Plastid Genome Assembly Using Long‐read data

Although plastid genome (plastome) structure is highly conserved across most seed plants, investigations during the past two decades have revealed several disparately related lineages that experienced substantial rearrangements. Most plastomes contain a large inverted repeat and two single‐copy regi...

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Veröffentlicht in:Molecular ecology resources 2023-08, Vol.23 (6), p.1442-1457
Hauptverfasser: Zhou, Wenbin, Armijos, Carolina E., Lee, Chaehee, Lu, Ruisen, Wang, Jeremy, Ruhlman, Tracey A., Jansen, Robert K., Jones, Alan M., Jones, Corbin D.
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Sprache:eng
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Zusammenfassung:Although plastid genome (plastome) structure is highly conserved across most seed plants, investigations during the past two decades have revealed several disparately related lineages that experienced substantial rearrangements. Most plastomes contain a large inverted repeat and two single‐copy regions, and a few dispersed repeats; however, the plastomes of some taxa harbour long repeat sequences (>300 bp). These long repeats make it challenging to assemble complete plastomes using short‐read data, leading to misassemblies and consensus sequences with spurious rearrangements. Single‐molecule, long‐read sequencing has the potential to overcome these challenges, yet there is no consensus on the most effective method for accurately assembling plastomes using long‐read data. We generated a pipeline, plastid Genome Assembly Using Long‐read data (ptGAUL), to address the problem of plastome assembly using long‐read data from Oxford Nanopore Technologies (ONT) or Pacific Biosciences platforms. We demonstrated the efficacy of the ptGAUL pipeline using 16 published long‐read data sets. We showed that ptGAUL quickly produces accurate and unbiased assemblies using only ~50× coverage of plastome data. Additionally, we deployed ptGAUL to assemble four new Juncus (Juncaceae) plastomes using ONT long reads. Our results revealed many long repeats and rearrangements in Juncus plastomes compared with basal lineages of Poales. The ptGAUL pipeline is available on GitHub: https://github.com/Bean061/ptgaul.
ISSN:1755-098X
1755-0998
DOI:10.1111/1755-0998.13787