Pangenome Graphs
Open accessAbstract
Low-cost whole-genome assembly has enabled the collection of haplotype-resolved pangenomes for numerous organisms. In turn, this technological change is encouraging the development of methods that can precisely address the sequence and variation described in large collections of related genomes. These approaches often use graphical models of the pangenome to support algorithms for sequence alignment, visualization, functional genomics, and association studies. The additional information provided to these methods by the pangenome allows them to achieve superior performance on a variety of bioinformatic tasks, including read alignment, variant calling, and genotyping. Pangenome graphs stand to become a ubiquitous tool in genomics. Although it is unclear whether they will replace linearreference genomes, their ability to harmoniously relate multiple sequence and coordinate systems will make them useful irrespective of which pangenomic models become most common in the future.
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Graph-based pangenomes replace that single path with a network of alternative haplotypes, explicitly modeling variation from single-nucleotide polymorphisms to megabase-scale structural changes.
“Graph-based pangenomes replace that single path with a network of alternative haplotypes, explicitly modeling variation from single-nucleotide polymorphisms to megabase-scale structural changes ( 95 ).”
From Topological Approaches in Animal Comparative Genomics (2026) · cites this paper as [95]
The Introduction describes replacing a linear reference with a graphical pangenome, and Graphical models explains that alternative paths represent variation. The Adding variation and Variant calling and genotyping sections cover small variants and structural variants, but the passages found do not establish the claim’s specific megabase scale. (LLM, conf=0.82)
Experimental — accuracy not yet measuredPangenomic methods have rapidly progressed such that it is now practical to propose that common genomic analyses use a pangenome.
“Pangenomic methods have rapidly progressed over the past few years13–15 such that it is now practical to propose that common genomic analyses use a pangenome.”
From A draft human pangenome reference. (2023) · cites this paper as [14]
Pangenome graphs capture more known variation by storing more knowledge about genomic diversity than is possible with a single genome.
“These are graph-theoretic extensions to the standard linear reference genomes that are able to capture more known variation by storing more knowledge about genomic diversity in an organism than is possible with a single genome [15].”
From <tt>SAFARI</tt> : pangenome alignment of ancient DNA using purine/pyrimidine encodings (2025) · cites this paper as [15]
Linear reference genomes collapse population diversity into a single path, which biases alignment and variant discovery from different individuals of the same species.
“Linear reference genomes collapse population diversity into a single path, which biases alignment and variant discovery from different individuals of the same species.”
From Topological Approaches in Animal Comparative Genomics (2026) · cites this paper as [95]
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Genome GraphsPreprint
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Self-citationPangenomics enables genotyping of known structural variants in 5202 diverse genomes
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Recombination between heterologous human acrocentric chromosomes
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“In genome assembly, pangenome graphs, which model direct relationships between all genomes in the analysis, can be utilized to capture genetic diversity and understand genetic variations across different populations and species [82].”
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Self-citationPangenome graphs and their applications in biodiversity genomics
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Leveraging a phased pangenome for haplotype design of hybrid potato
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Computational graph pangenomics: a tutorial on data structures and their applications
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Self-citationVisualizing metagenomic and metatranscriptomic data: A comprehensive review
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The Practical Haplotype Graph, a platform for storing and using pangenomes for imputation
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A gentle introduction to pangenomics
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A Draft Human Pangenome ReferencePreprint
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Pangenomes as a Resource to Accelerate Breeding of Under-Utilised Crop Species
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The role of pangenomics in orphan crop improvement
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Storing and analyzing a genome on a blockchain
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Personalized pangenome references
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Pangenome Graph Construction from Genome Alignment with Minigraph-Cactus
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Genomic variant benchmark: if you cannot measure it, you cannot improve it
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Unravelling inversions: Technological advances, challenges, and potential impact on crop breeding
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GBZ file format for pangenome graphs
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Self-citationReference Genome Choice and Filtering Thresholds Jointly Influence Phylogenomic Analyses
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Technological Development and Advances for Constructing and Analyzing Plant Pangenomes
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Accurate and fast graph-based pangenome annotation and clustering with ggCallerPreprint
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Fitness consequences of structural variation inferred from a House Finch pangenome
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From genotype to phenotype with 1,086 near telomere-to-telomere yeast genomes
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Design, execution, and interpretation of plant RNA-seq analyses
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A revamped rat reference genome improves the discovery of genetic diversity in laboratory rats
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Self-citationGWAS for genetics of complex quantitative traits: Genome to pangenome and SNPs to SVs and k‐mers
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Are we there yet? Driving the road to evolutionary graph-pangenomics
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Quest for Orthologs in the Era of Biodiversity Genomics
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New genomic approaches for enhancing maize genetic improvement
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Supporting crop plant resilience during climate change
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Haplotype-Resolved, Chromosome-Level Assembly of White Clover (Trifolium repens L., Fabaceae)
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Advances in next-generation sequencing and emerging technologies for hematologic malignancies
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k-mer-Based Genome-Wide Association Studies in Plants: Advances, Challenges, and Perspectives
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Chaining for accurate alignment of erroneous long reads to acyclic variation graphs
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Plant graph-based pangenomics: techniques, applications, and challenges
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Cluster-efficient pangenome graph construction with nf-core/pangenome
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Multispecies pangenomes reveal a pervasive influence of population size on structural variation
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Self-citationMethods and Developments in Graphical Pangenomics
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Advancing Genetic Methods in the Study of Parrot Biology and Conservation
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Self-citationWhen less is more: sketching with minimizers in genomics
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A Hitchhiker's Guide to long-read genomic analysisPreprint
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- Authors
- Eizenga, J. M., Novak, A. M., Sibbesen, J. A., Heumos, S., Ghaffaari, A., Hickey, G., Chang, X., Seaman, J. D., Rounthwaite, R., Ebler, J., Rautiainen, M., Garg, S., Paten, B., Marschall, T., Sirén, J., & Garrison, E.
- Affiliations
- University of California, Santa Cruz (US)
- Quantitative Biology Center (DE)
- Max Planck Institute for Informatics (DE)
- Queen Mary University of London (GB)
- Harvard University (US)
- Corresponding author
- Garrison, Erik
- ORCID
- Venue
- Annual Review of Genomics and Human Genetics
- Publisher
- Annual Reviews
- Published
- 2020-08-31
- Volume
- 21
- Issue
- 1
- Pages
- 139-162
- ISSN
- 1527-8204 (ISSN-L)
- 1545-293X
- PMC
- PMC8006571
- OpenAlex
- W4255836900
- Cited by
- 320
- References
- 139
- Citations by year
- 2026: 57 · 2025: 64 · 2024: 66 · 2023: 64 · 2022: 47 · 2021: 19 · 2020: 2
- FWCI
- 3.38
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Annual Review of Genomics and Human Genetics (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- W. M. Keck Foundation
- Bundesministerium für Wirtschaft und Energie
- National Institutes of Health
- Directorate for Biological Sciences
- Biotechnology and Biological Sciences Research Council (BB/S004661/1)
- National Heart, Lung, and Blood Institute (U01HL137183)
- National Human Genome Research Institute (R01HG010485, U41HG007234, U54HG007990)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Physical Sciences › Computer Science › Artificial Intelligence › Algorithms and Data Compression
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genome Rearrangement Algorithms
- Keywords
- pangenome graphs, pangenome assembly, read mapping, variant calling, genotyping, sequence variation, haplotype structure
- MeSH terms
- Algorithms, Computer Graphics, Humans, Genome, Human, Sequence Analysis, DNA, Computational Biology, High-Throughput Nucleotide Sequencing
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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