Pangenome Graph Construction from Genome Alignment with Minigraph-Cactus

Reference genomes provide mapping targets and coordinate systems but introduce biases when samples under study diverge sufficiently from them. Pangenome references seek to address this by storing a representative set of diverse haplotypes and their alignment, usually as a graph. Alternate alleles de...

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Published inbioRxiv
Main Authors Hickey, Glenn, Monlong, Jean, Ebler, Jana, Novak, Adam, Eizenga, Jordan M, Gao, Yan, Human Pangenome Reference Consortium, Marschall, Tobias, Li, Heng, Paten, Benedict
Format Paper
LanguageEnglish
Published Cold Spring Harbor Cold Spring Harbor Laboratory Press 06.03.2023
Cold Spring Harbor Laboratory
Edition1.3
Subjects
Online AccessGet full text
ISSN2692-8205
2692-8205
DOI10.1101/2022.10.06.511217

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Summary:Reference genomes provide mapping targets and coordinate systems but introduce biases when samples under study diverge sufficiently from them. Pangenome references seek to address this by storing a representative set of diverse haplotypes and their alignment, usually as a graph. Alternate alleles determined by variant callers can be used to construct pangenome graphs, but thanks to advances in long-read sequencing, high-quality phased assemblies are becoming widely available. Constructing a pangenome graph directly from assemblies, as opposed to variant calls, leverages the graph's ability to consistently represent variation at different scales and reduces biases introduced by reference-based variant calls. Pangenome construction in this way is equivalent to multiple genome alignment. Here we present the Minigraph-Cactus pangenome pipeline, a method to create pangenomes directly from whole-genome alignments, and demonstrate its ability to scale to 90 human haplotypes from the Human Pangenome Reference Consortium (HPRC). This tool was designed to build graphs containing all forms of genetic variation while still being practical for use with current mapping and genotyping tools. We show that this graph is useful both for studying variation within the input haplotypes, but also as a basis for achieving state of the art performance in short and long read mapping, small variant calling and structural variant genotyping. We further measure the effect of the quality and completeness of reference genomes used for analysis within the pangenomes, and show that using the CHM13 reference from the Telomere-to-Telomere Consortium improves the accuracy of our methods, even after projecting back to GRCh38. We also demonstrate that our method can apply to nonhuman data by showing improved mapping and variant detection sensitivity with a Drosophila melanogaster pangenome.Competing Interest StatementThe authors have declared no competing interest.Footnotes* This draft contains extensive rewrites to clarify methods, expand discussion, better specify novelty and impact, as well as new SV genotyping and long read mapping results for the human pangenome.* https://github.com/ComparativeGenomicsToolkit/cactus
Bibliography:SourceType-Working Papers-1
ObjectType-Working Paper/Pre-Print-1
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Competing Interest Statement: The authors have declared no competing interest.
ISSN:2692-8205
2692-8205
DOI:10.1101/2022.10.06.511217