Super Pangenome of Grapevines Empowers Improvement of the Oldest Domesticated Fruit

Motivation Pangenome graphs offer a comprehensive way of capturing genomic variability across multiple genomes. However, current construction methods often introduce biases, excluding complex sequences or relying on references. The PanGenome Graph Builder (PGGB) addresses these issues. To date, though, there is no state-of-the-art pipeline allowing for easy deployment, efficient and dynamic use of available resources, and scalable usage at the same time. Results To overcome these limitations, we present nf-core/pangenome, a reference-unbiased approach implemented in Nextflow following nf-core’s best practices. Leveraging biocontainers ensures portability and seamless deployment in HPC environments. Unlike PGGB, nf-core/pangenome distributes alignments across cluster nodes, enabling scalability. Demonstrating its efficiency, we constructed pangenome graphs for 1000 human chromosome 19 haplotypes and 2146 E. coli sequences, achieving a two to threefold speedup compared to PGGB without increasing greenhouse gas emissions. Availability Nf-core/pangenome is released under the MIT open-source license, available on GitHub and Zenodo, with documentation accessible at https://nf-co.re/pangenome/1.1.2/docs/usage. Supplementary Supplementary data are available at Bioinformatics online.

show abstract

Cluster efficient pangenome graph construction with nf-core/pangenome

Heumos,

Heuer,

Hanssen

et al. 2024

Preprint

View full text Add to dashboard Cite

Motivation: Pangenome graphs offer a comprehensive way of capturing genomic variability across multiple genomes. However, current construction methods often introduce biases, excluding complex sequences or relying on references. The PanGenome Graph Builder (PGGB) addresses these issues. To date, though, there is no state-of-the-art pipeline allowing for easy deployment, efficient and dynamic use of available resources, and scalable usage at the same time. Results: To overcome these limitations, we present nf-core/pangenome, a reference-unbiased approach implemented in Nextflow following nf-core's best practices. Leveraging biocontainers ensures portability and seamless deployment in HPC environments. Unlike PGGB, nf-core/pangenome distributes alignments across cluster nodes, enabling scalability. Demonstrating its efficiency, we constructed pangenome graphs for 1000 human chromosome 19 haplotypes and 2146 E. coli sequences, achieving a two to threefold speedup compared to PGGB without increasing greenhouse gas emissions. Availability: nf-core/pangenome is released under the MIT open-source license, available on GitHub and Zenodo, with documentation accessible at https://nf-co.re/pangenome/1.1.2/docs/usage. Contact: simon.heumos@qbic.uni-tuebingen.de, sven.nahnsen@qbic.uni-tuebingen.de

show abstract

Super Pangenome of Grapevines Empowers Improvement of the Oldest Domesticated Fruit

Cited by 3 publications

References 108 publications

Comprehensive insights on association mapping in perennial fruit crops breeding – Its implications, current status and future perspectives

Comprehensive insights on association mapping in perennial fruit crops breeding – Its implications, current status and future perspectives

Cluster-efficient pangenome graph construction with nf-core/pangenome

Cluster efficient pangenome graph construction with nf-core/pangenome

Contact Info

Product

Resources

About