plant-food-research-open/genepal

Introduction

plant-food-research-open/genepal is a bioinformatics pipeline for single genome, phased genomes and pan-genome annotation. An overview is shown in the Pipeline Flowchart and the references for the tools are listed in CITATIONS.md. Protein coding gene structures are predicted with BRAKER which uses GeneMark-ES/ET/EP+/ETP. These tools require a license for commercial works.

Pipeline Flowchart

• fasta_validator: Validate genome FASTA
• RepeatModeler or EDTA: Create TE library
• RepeatMasker: Soft mask the genome fasta
• sra-tools: RNASeq data download from SRA
• FastQC, fastp, SortMeRNA: QC, trim and filter RNASeq evidence
• STAR: RNASeq alignment
• cat: Concatenate protein FASTA files
• BRAKER: Predict protein coding gene structures with GeneMark-ES/ET/EP/ETP and AUGUSTUS
  • Directly provided BAM files should be --outSAMstrandField intronMotif compliant
  • With protein evidence alone, BRAKER workflow C is executed
  • With protein plus RNASeq evidence, BRAKER workflow D is executed
• Liftoff: Optionally, liftoff annotations from reference genome FASTA/GFF
• TSEBRA: Optionally, ensure that each BRAKER or both BRAKER and Liftoff models have full intron support
• AGAT
  • Merge multi-reference liftoffs
  • Remove liftoff transcripts marked by validORF=False_
  • Remove liftoff genes with any intron shorter than 10 bp
  • Remove rRNA, tRNA and other non-protein coding models from liftoff
  • Optionally, allow or remove iso-forms
  • Remove BRAKER models from Liftoff loci
  • Merge Liftoff and BRAKER models
  • Optionally, remove models without any EggNOG-mapper hits
  • Optionally, remove models with ORFs shorter than N amino acids
• EggNOG-mapper: Add functional annotation to gff
• GenomeTools: GFF format validation
• GffRead: Extraction of protein sequences and filtering of BRAKER models with invalid ORF(s)
• OrthoFinder: Perform phylogenetic orthology inference across genomes
• GffCompare: Compare and benchmark against an existing annotation
• BUSCO: Completeness statistics for genome and annotation through proteins
• R Markdown: Specialized pangene analysis
• MultiQC: Exhaustive QC statistics

Usage

Refer to usage, parameters and output documents for details.

[!NOTE] If you are new to Nextflow and nf-core, please refer to this page on how to set-up Nextflow. Make sure to test your setup with -profile test before running the workflow on actual data.

First, prepare an assemblysheet with your input genomes that looks as follows:

assemblysheet.csv:

csv tag ,fasta ,is_masked a_thaliana ,/path/to/genome.fa ,yes

Each row represents an input genome and the fields are:

• tag: A unique tag which represents the genome throughout the pipeline
• fasta: fasta file for the genome
• is_masked: yes or no to denote whether the fasta file is already masked or not

At minimum, a file with proteins as evidence is also required. Now, you can run the pipeline using:

bash nextflow run plant-food-research-open/genepal \ -revision <version> \ -profile <docker/singularity/.../institute> \ --input assemblysheet.csv \ --protein_evidence proteins.faa \ --outdir <OUTDIR>

[!WARNING] Please provide pipeline parameters via the CLI or Nextflow -params-file option. Custom config files including those provided by the -c Nextflow option can be used to provide any configuration except for parameters; see docs.

Plant&Food Users

Download the pipeline to your /workspace/$USER folder. Change the parameters defined in the pfr/params.json file. Submit the pipeline to SLURM for execution.

bash sbatch ./pfr_genepal

Credits

plant-food-research-open/genepal workflows were originally scripted by Jason Shiller (@jasonshiller). Usman Rashid (@gallvp) wrote the Nextflow pipeline.

We thank the following people for extensive assistance in the development of the pipeline,

• Cecilia Deng @CeciliaDeng
• Charles David @charlesdavid
• Chen Wu @christinawu2008
• Leonardo Salgado @leorippel
• Ross Crowhurst @rosscrowhurst
• Susan Thomson @cflsjt
• Ting-Hsuan Chen @ting-hsuan-chen

and for contributions to the codebase,

• Liam Le Lievre @liamlelievre

The pipeline uses nf-core modules contributed by following authors:

Contributions and Support

If you would like to contribute to this pipeline, please see the contributing guidelines.

Citations

If you use plant-food-research-open/genepal for your analysis, please cite it as:

genepal: A Nextflow pipeline for genome and pan-genome annotation.

Usman Rashid, Jason Shiller, Ross Crowhurst, Chen Wu, Ting-Hsuan Chen, Leonardo Salgado, Charles David, Sarah Bailey, Ignacio Carvajal, Anand Rampadarath, Ken Smith, Liam Le Lievre, Cecilia Deng, Susan Thomson

zenodo. 2024. doi: 10.5281/zenodo.14195006.

An extensive list of references for the tools used by the pipeline can be found in the CITATIONS.md file.

This pipeline uses code and infrastructure developed and maintained by the nf-core community, reused here under the MIT license.

The nf-core framework for community-curated bioinformatics pipelines.

Philip Ewels, Alexander Peltzer, Sven Fillinger, Harshil Patel, Johannes Alneberg, Andreas Wilm, Maxime Ulysse Garcia, Paolo Di Tommaso & Sven Nahnsen.

Nat Biotechnol. 2020 Feb 13. doi: 10.1038/s41587-020-0439-x.