Pangenome Graphs

Author:

Eizenga Jordan M.1,Novak Adam M.1,Sibbesen Jonas A.1,Heumos Simon2,Ghaffaari Ali345,Hickey Glenn1,Chang Xian1,Seaman Josiah D.67,Rounthwaite Robin1,Ebler Jana345,Rautiainen Mikko345,Garg Shilpa89,Paten Benedict1,Marschall Tobias34,Sirén Jouni1,Garrison Erik1

Affiliation:

1. Genomics Institute, University of California, Santa Cruz, California 95064, USA;

2. Quantitative Biology Center, University of Tübingen, 72076 Tübingen, Germany

3. Center for Bioinformatics, Saarland University, 66123 Saarbrücken, Germany

4. Max Planck Institute for Informatics, 66123 Saarbrücken, Germany

5. Saarbrücken Graduate School for Computer Science, Saarland University, 66123 Saarbrücken, Germany

6. Royal Botanic Gardens, Kew, Richmond TW9 3AB, United Kingdom

7. School of Biological and Chemical Sciences, Queen Mary University of London, London E1 4NS, United Kingdom

8. Departments of Genetics and Biomedical Informatics, Harvard Medical School, Boston, Massachusetts 02215, USA

9. Department of Data Sciences, Dana-Farber Cancer Institute, Boston, Massachusetts 02215, USA

Abstract

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.

Publisher

Annual Reviews

Subject

Genetics (clinical),Genetics,Molecular Biology

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