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Constructing a pangenome gene graph

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Getting Started

# Check prebuilt graphs at https://pangene.bioinweb.org

# Install pangene
git clone https://github.com/lh3/pangene
cd pangene && make

# Alternatively, download the precompiled binaries for arm-mac and x64-linux
curl -L https://github.com/lh3/pangene/releases/download/v1.1/pangene-1.1-bin.tar.bz2|tar jxf -

# The C4 example with provided alignment
./pangene test/C4/*.paf.gz > C4.gfa        # generate the graph
k8 pangene.js call C4.gfa > C4.bubble.txt  # identify bubbles

# Deploy the GFA server on the C4 example; require pangene-1.1-bin
cd pangene-1.1-bin                         # run gfa-server in this directory
bin_arm64-mac/gfa-server /path/to/C4.gfa   # or use bin_linux-x64 on x64-linux
# open "http://127.0.0.1:8000/view?gene=C4A,C4B" in a web browser

# Deploy the GFA server on the human graph
bin_arm64-mac/gfa-server -d html data/*.gfa.gz 2> server.log &
# open "http://127.0.0.1:8000" in a web browser

# Align proteins to each genome (general use cases; no example data)
miniprot --outs=0.97 --no-cs -Iut16 genome1.fna proteins.faa > genome1.paf
miniprot --outs=0.97 --no-cs -Iut16 genome2.fna proteins.faa > genome2.paf

# Construct a pangene graph
pangene genome1.paf genome2.paf > graph.gfa

# Check manpage
man ./pangene.1

Table of Contents

Introduction

Pangene is a command-line tool to construct a pangenome gene graph. In this graph, a node repsents a marker gene and an edge between two genes indicates their genomic adjaceny on input genomes. Pangene takes the miniprot alignment between a protein set and multiple genomes and produces a graph in the GFA format. It attempts to reduce the redundancy in the input proteins and filter spurious alignments while preserving close but non-identical paralogs. The output graph can be visualized in generic GFA viewers such as BandageNG or via a web interface. Users can explore local human subgraphs at a public server. Prebuilt pangene graphs can be found at DOI:10.5281/zenodo.8118576.

Graph Construction

Pangene takes a list of protein-to-genome alignment as input. To generate these alignments, you need to align the same set of proteins to multiple genomes. How to choose the protein set can be tricky.

Preparing a protein set

For constructing a human pangene graph, the simplest choice is to use annotated genes in GRCh38. It is highly recommended to name a protein sequence like RGPD6:ENSP00000512633.1 where RGPD6 is the gene name and ENSP00000512633.1 is the unique protein identifier. In the output GFA, nodes are named after genes, so you would want to use human-readable gene names for visualization later. You may use the following command line to extract protein sequences from Ensembl or GenCode annotation:

k8 pangene.js getaa gene-anno.gtf protein-seq.faa > proteins.faa

With pangene, different isoforms or diverged alleles of the same gene can be present in the protein set, though in practice, we find selecting the canonical isoform per gene tends to give a cleaner graph probably possibly due to annotation errors among rare isoforms. For the GenCode annotation, use getaa -c to extract canonical isoforms only.

For a new species without good gene annotation, you may use protein annotations from a closely related species. You may pool proteins from multiple closely related species as well. Pangene aims to work with such input but this use case has not been thoroughly carefully evaluated. Given a bacteria pangenome of the same species, you may predict genes with existing tools, cluster them with CD-HIT or MMseqs2 and feed the representative protein in each cluster to pangene.

Aligning proteins to genomes

Pangene currently only works with miniprot's PAF output. We usually use the following command line:

miniprot --outs=0.97 --no-cs -Iut16 genomeX.fna proteins.faa > genomeX.paf

For bacterial data, add -S to disable splicing.

Constructing a pangene graph

The following command-line constructs a pangene graph

pangene *.paf > graph.gfa

If the output graph is cluttered in the Bandage viewer, you may add option -a2 to filter out edges supported by a single genome. By default, pangene filters out genes occurring in less than 5% of the genomes after deredundancy. If you want to retain low-frequency genes, add -p0 to disable the filter.

Analyzing a graph

The GFA file is the master output. You can extract various information from this file. You may find local gene-level variations with

k8 pangene.js call graph.gfa > bubble.txt

or get the presence/absence of each gene with

k8 pangene.js gfa2matrix graph.gfa > gene_presence_absence.Rtab

Graph Visualization

You can look at the entire graph in the Bandage GFA viewer. If you are interested in a particular gene, it is best to set up gfa-server which is part of gfatools. Here is a public server for human genes. You can deploy this server on your machine with

curl -L https://github.com/lh3/pangene/releases/download/v1.1/pangene-1.1-bin.tar.bz2|tar jxf -
cd pangene-1.1-bin
bin_arm64-mac/gfa-server -d html data/*.gfa.gz 2> server.log # for Mac

Then you can open link http://127.0.0.1:8000/ in your browser, type gene names and visualize a local subgraph around the desired genes.

Citation

If you use pangene in your work, please consider to cite:

H Li, M Marin, MR Farhat (2024) Exploring gene content with pangenome gene graphs, arXiv:2402.16185

Limitations

  • Pangene only works with miniprot's PAF output.

  • In the output graph, arcs on W-lines may be absent from L-lines.