Computational Pangenomics: Software Tools and Applications in Plants and Animals

Improvements in DNA sequencing, assembly algorithms, and computing infrastructure have resulted in the proliferation of multiple reference-quality genomes within individual species. These pangenomes are a more comprehensive representation of the conservation and variation of sequences within a species and promise to be a powerful tool for identifying critical genes and regulatory regions that define the species. They also allow for the detection of diverse genomic regions that are important for adaptation, improving our ability to monitor, conserve, and shape genetic diversity in the face of changing climates.

While the pangenome paradigm is already widely used for human and microbial genomes, its application in plants and animals has historically been hindered by the size and complexity of these genomes. Many existing bioinformatics tools were originally optimized for the human genome, which is relatively stable, diploid, and well-characterized. However, these tools often struggle when applied to the high levels of polyploidy common in crops like wheat or potatoes, or the extreme density of transposable elements and repetitive sequences found in many animals and plants, which can lead to computational bottlenecks and assembly errors. Furthermore, human pangenome variation is often dominated by SNPs, while plant and animal genomes frequently exhibit massive structural variations and Presence-Absence Variations (PAVs) that may cause existing human-centric software issues with scaling and accurate representation. Given that many high quality plant and animal genomes are currently being generated, the development and application of pangenomics tools in this domain is urgent.

The emergence of new bioinformatics software, such as graph-based architectures or the integration of AI and Machine Learning, enables the handling of these high-dimensional data structures. The development of these tools and the effective application of existing software to non-human pangenomes could have significant implications for plants, agriculture, and livestock genomics, which may be critical to global food security, wildlife conservation, and combating climate change
The focus of this Research Topic is the presentation of new bioinformatics tools and computational approaches for the analysis of pangenomics data, with applications to plants, livestock, and wild animal species.

* Showing the efficacy of novel algorithms for computational pangenomics
* Presenting new software tools for computational pangenome analysis
* Novel research in plants and livestock enabled by pangenomic techniques
* Association studies that connect pangenomes to phenotypes
* Surveys of existing software tools and protocols for pangenome analysis in plants and animals
* Identifying unmet needs in the plant pangenome space