Virtual genome walking across the 32 Gb Ambystoma mexicanum genome; assembling gene models and intronic sequence

Evans, Teri; D. Johnson, Andrew; Loose, Matthew

Abstract

Large repeat rich genomes present challenges for assembly using short read technologies. The 32 Gb axolotl genome is estimated to contain ~19 Gb of repetitive DNA making an assembly from short reads alone effectively impossible. Indeed, this model species has been sequenced to 20× coverage but the reads could not be conventionally assembled. Using an alternative strategy, we have assembled subsets of these reads into scaffolds describing over 19,000 gene models. We call this method Virtual Genome Walking as it locally assembles whole genome reads based on a reference transcriptome, identifying exons and iteratively extending them into surrounding genomic sequence. These assemblies are then linked and refined to generate gene models including upstream and downstream genomic, and intronic, sequence. Our assemblies are validated by comparison with previously published axolotl bacterial artificial chromosome (BAC) sequences. Our analyses of axolotl intron length, intron-exon structure, repeat content and synteny provide novel insights into the genic structure of this model species. This resource will enable new experimental approaches in axolotl, such as ChIP-Seq and CRISPR and aid in future whole genome sequencing efforts. The assembled sequences and annotations presented here are freely available for download from https://tinyurl.com/y8gydc6n. The software pipeline is available from https://github.com/LooseLab/iterassemble.

Citation

Evans, T., D. Johnson, A., & Loose, M. (in press). Virtual genome walking across the 32 Gb Ambystoma mexicanum genome; assembling gene models and intronic sequence. Scientific Reports, 8(1), Article 618. https://doi.org/10.1038/s41598-017-19128-6

• Journal Article Type: Article
• Acceptance Date: Dec 19, 2017
• Online Publication Date: Jan 12, 2018
• Deposit Date: Jan 23, 2018
• Publicly Available Date: Jan 23, 2018
• Journal: Scientific Reports
• Electronic ISSN: 2045-2322
• Publisher: Nature Publishing Group
• Peer Reviewed: Peer Reviewed
• Volume: 8
• Issue: 1
• Article Number: 618
• DOI: https://doi.org/10.1038/s41598-017-19128-6
• Public URL: https://nottingham-repository.worktribe.com/output/904385
• Publisher URL: https://www.nature.com/articles/s41598-017-19128-6