# Pangenome (cattle) The bovine super-pangenome aligns twelve cattle assemblies against ARS-UCD1.2. The panel is unusually wide for a livestock pangenome, with taurine and indicine breeds beside yak, bison and gaur, so a locus that varies here varies across most of the genus. Each of those assemblies walks the graph as a named path, and `vg deconstruct` turns those paths into a VCF. The same locus then reads twice: as a graph showing where sequence is present and absent, and as a callset naming who carries it. We serve the graph as the same rGFA projections the [HPRC pangenome page](https://jbrowse.org/jb2/docs/tutorials/pangenome_hprc/) opens, so the tracks, the adapters and the coarse tier are that page's. :::caution Experimental The graph view is a beta plugin, and this tutorial covers experimental ideas. Where a step below says the view works a particular way today, the step describes a current limit of the view. We welcome your [feedback](https://jbrowse.org/jb2/contact). ::: ## Prerequisites - [the GraphGenomeView plugin](https://jbrowse.org/jb2/docs/tutorials/pangenome_hprc#the-graphgenomeview-plugin), loaded the way the HPRC page loads it ## Where the data comes from The projections are hosted beside the graph: - the segment and link index: https://jbrowse.org/demos/bovine_pangenome/bovine-arsucd12-minigraph.segs.bed.gz and https://jbrowse.org/demos/bovine_pangenome/bovine-arsucd12-minigraph.links.bed.gz - the bubble index: https://jbrowse.org/demos/bovine_pangenome/bovine-arsucd12-minigraph.bubbles.bed.gz - the allele inventory: https://jbrowse.org/demos/bovine_pangenome/bovine-arsucd12-minigraph.alleles.bed.gz - the coarse tier: https://jbrowse.org/demos/bovine_pangenome/bovine-arsucd12-minigraph.tier10000 - the deconstructed callset: https://jbrowse.org/demos/bovine_pangenome/bovine-arsucd12-minigraph.vcf.gz [Preparing your own graph](https://jbrowse.org/jb2/docs/tutorials/pangenome_prepare_graph) describes what each of those files holds and how a graph produces them. ## Where the graph and the callset show different things In the BoLA class II region the **graph** shows a lot of sequence present in some assemblies and absent from the reference. It attributes that sequence only by convention. These graphs record no construction rank, so `firstSeenIn` in the allele file names the first assembly in a fixed list, and that assembly need not carry the sequence. The **callset** attributes each allele. One `vg deconstruct` call per chromosome over the same graph gives a genotype per assembly: ```bash vg convert -g "$TMPDIR/$k.renamed.gfa" -p > "$TMPDIR/$k.vg" vg deconstruct -p "chr$k" -a -t "$THREADS" "$TMPDIR/$k.vg" > "vcf/chr$k.vcf.tmp" ```
Read the genotype rows across. Most assemblies carry a different allele here, much as human MHC does. The graph lanes around the callset show none of these genotypes. The mouse graph is the other end of this. `minigraph` writes no path lines at all, so there is no callset to deconstruct and nothing recovers carriage. [](https://jbrowse.org/jb2/docs/tutorials/pangenome_mouse) works with what is left. ## A whole chromosome, off the coarse tier The level-of-detail tier has one node per bubble, which makes a whole chromosome drawable. Type `chr23` on ARS-UCD1.2 with the tier and the bubble curve showing. Over a full cattle chromosome the _fine_ segments track refuses with "Too many features", and the tier draws.
A graph view pointed at a tier raises `maxRegionBp` explicitly. The view refuses a cut wider than 5 Mb. That width limit stands in for node count, and it tracks node count well only at segment granularity. :::note This panel holds a dozen assemblies, against ninety haplotypes for HPRC. Its cuts are chains with a few loops, and the anchored layout often reads better. Check the node and edge counts in the graph pane's header before switching to the force layout. Use the force layout where the bubbles lane reports a tangled window. ::: BoLA came out of the same ranking the [mouse page](https://jbrowse.org/jb2/docs/tutorials/pangenome_mouse#finding-the-loci) describes: rank the coarse tier by segments per bubble, then name each entry off the reference annotation. It is the densest stretch of chr23 in the figure above, and the ranking found it without a curated list. ## Build it yourself [`build_bovine_pangenome.sh`](https://github.com/GMOD/jbrowse-components/blob/main/scripts/build_bovine_pangenome.sh) downloads the published archive, recovers rGFA tags from its path lines with [`gfa_paths_to_rgfa.py`](https://github.com/GMOD/jbrowse-components/blob/main/scripts/gfa_paths_to_rgfa.py), projects the files above, and deconstructs the callset. It takes about half an hour after the download. The script writes a `README.txt` beside the data recording the source, the modifications, the tool versions and the audits that ran. Copy the audits into your own build. The build stops unless the reference path reproduces the reference chromosome lengths, and stops on a duplicate segment id after renumbering. Without these audits, either failure produces a graph with wrong coordinates, and every downstream check passes on it. If your own graph has path lines, use [`build_pggb_tabix.sh`](https://github.com/GMOD/jbrowse-components/blob/main/scripts/build_pggb_tabix.sh) in place of `build_rgfa_tabix.sh`. The PGGB script walks the paths and writes a carriage tag, which rGFA has no field for. The graph view then shows which samples cross each node. ## See also - [](https://jbrowse.org/jb2/docs/tutorials/pangenome_mouse) - [](https://jbrowse.org/jb2/docs/tutorials/pangenome_hprc_part2) - [](https://jbrowse.org/jb2/docs/tutorials/pangenome_prepare_graph) ## References - Leonard AS, Crysnanto D, Mapel XM, Bhati M, Pausch H. Graph construction method impacts variation representation and analyses in a bovine super-pangenome. Genome Biology. 2023;24:128. https://doi.org/10.1186/s13059-023-02969-y - Li H, Feng X, Chu C. The design and construction of reference pangenome graphs with minigraph. Genome Biology. 2020;21:265. https://doi.org/10.1186/s13059-020-02168-z