A possible pipeline for the uses of a pangenome graph. This pipeline can be roughly divided into three main sections (on the right): build a graph, using it, and adding reads. A first pangenome graph is created, usually with almost complete haplotype as- semblies. Since graph creating methods vary, and may be fraught with errors (unaligned regions, broken paths), assessing the quality of a graph is useful (this can be applied after each subsequent step). Similarly, it is also crucial to be able to visualize the graph, espe- cially on particular loci of interest (can also be done throughout the pipe-line). The graph can be augmented with additional data increasing allele counts, including known con- tig alignment or read mapping. Several augmentation iterations, with different types of data, can be considered. Since most analyses focus on genes and transposable elements, it is usually useful to add an annotation (available on one or several reference genomes), which projected to the graph. This graph, possibly extended with new variants and an- notation, should be then shared with the community, following FAIR practices. Most analyses then focus on graphs with only one species, and the graph can be analyzed in order to find regions of interest. However, dual pangenomics, which studies the joint diversities of two species, can be envisioned. More generally, many species can also be modeled, for instance in the case of meta-genomics. Low coverage sequencing data of individuals can be compared or aligned to the graph in order to produce large genotyp- ing sets enabling population genetics studies (i.e. coalescence, association). Other omics (e.g. RNA-Seq, ChIP-Seq, Hi-C, LC-MS, BS-Seq etc.) data can be added to the graph, and potentially aggregated to multi-omic layers.
With many colleagues, we tried to gather the future prospects and challenges for #Pangenomics and #Pangenome research in agronomy, that can however be adopted more largely
hal.science/hal-05357866/
@ird-fr.bsky.social @inrae-france.bsky.social #FAIR #OpenScience #vizu
