Assembling highly repetitive Xanthomonas TALomes using Oxford Nanopore sequencing

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Erkes, A.; Grove, R.P.; Žarković, M.; Krautwurst, S.; Koebnik, R. et al.: Assembling highly repetitive Xanthomonas TALomes using Oxford Nanopore sequencing. In: BMC Genomics 24 (2023), Nr. 1, 151. DOI: https://doi.org/10.1186/s12864-023-09228-1

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Background: Most plant-pathogenic Xanthomonas bacteria harbor transcription activator-like effector (TALE) genes, which function as transcriptional activators of host plant genes and support infection. The entire repertoire of up to 29 TALE genes of a Xanthomonas strain is also referred to as TALome. The DNA-binding domain of TALEs is comprised of highly conserved repeats and TALE genes often occur in gene clusters, which precludes the assembly of TALE-carrying Xanthomonas genomes based on standard sequencing approaches. Results: Here, we report the successful assembly of the 5 Mbp genomes of five Xanthomonas strains from Oxford Nanopore Technologies (ONT) sequencing data. For one of these strains, Xanthomonas oryzae pv. oryzae (Xoo) PXO35, we illustrate why Illumina short reads and longer PacBio reads are insufficient to fully resolve the genome. While ONT reads are perfectly suited to yield highly contiguous genomes, they suffer from a specific error profile within homopolymers. To still yield complete and correct TALomes from ONT assemblies, we present a computational correction pipeline specifically tailored to TALE genes, which yields at least comparable accuracy as Illumina-based polishing. We further systematically assess the ONT-based pipeline for its multiplexing capacity and find that, combined with computational correction, the complete TALome of Xoo PXO35 could have been reconstructed from less than 20,000 ONT reads. Conclusions: Our results indicate that multiplexed ONT sequencing combined with a computational correction of TALE genes constitutes a highly capable tool for characterizing the TALomes of huge collections of Xanthomonas strains in the future.
License of this version: CC BY 4.0 Unported
Document Type: Article
Publishing status: publishedVersion
Issue Date: 2023
Appears in Collections:Naturwissenschaftliche Fakultät

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1 image of flag of Germany Germany 10 52.63%
2 image of flag of United States United States 7 36.84%
3 image of flag of China China 1 5.26%
4 image of flag of Canada Canada 1 5.26%

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