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. 2022 Nov 3:13:1011948.
doi: 10.3389/fpls.2022.1011948. eCollection 2022.

Plastaumatic: Automating plastome assembly and annotation

Affiliations

Plastaumatic: Automating plastome assembly and annotation

Wenyi Chen et al. Front Plant Sci. .

Abstract

Plastome sequence data is most often extracted from plant whole genome sequencing data and need to be assembled and annotated separately from the nuclear genome sequence. In projects comprising multiple genomes, it is labour intense to individually process the plastomes as it requires many steps and software. This study developed Plastaumatic - an automated pipeline for both assembly and annotation of plastomes, with the scope of the researcher being able to load whole genome sequence data with minimal manual input, and therefore a faster runtime. The main structure of the current automated pipeline includes trimming of adaptor and low-quality sequences using fastp, de novo plastome assembly using NOVOPlasty, standardization and quality checking of the assembled genomes through a custom script utilizing BLAST+ and SAMtools, annotation of the assembled genomes using AnnoPlast, and finally generating the required files for NCBI GenBank submissions. The pipeline is demonstrated with 12 potato accessions and three soybean accessions.

Keywords: chloroplast genome; organellar genome; plant; plastome; sequence assembly.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Schematic representation of the Plastaumatic plastome assembly pipeline with details. There are six steps involved in the Plastaumatic pipeline i.e., trimming, creating config file for assembly, de novo assembly, standardization, annotation, and generating a feature table file. The pipeline can be run using Snakemake or a shell script, both of which produce the same output. The input data required for the Plastaumatic is the raw WGS reads in fastq format, a seed file in fasta format, and an annotation file in GenBank format. The pipeline creates multiple directories as detailed in the figure to store all the output.

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