Pangenome graph layout by Path-Guided Stochastic Gradient Descent

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Abstract

Motivation:

The increasing availability of complete genomes demands for models to study genomic variability within entire populations. Pangenome graphs capture the full genetic diversity between multiple genomes, but their layouts may exhibit complex structures due to common, nonlinear patterns of genome variation and evolution. These structures hamper downstream analyses, visualization, and interpretation.

Results:

In response, we introduce a novel graph layout algorithm: the Path-Guided Stochastic Gradient Descent (PG-SGD). PG-SGD uses the genomes, represented in the pangenome graph as paths, to move pairs of nodes in parallel applying a modified HOGWILD! strategy. We show that our implementation efficiently computes the layout of gigabase-scale pangenome graphs, unveiling their biological features.

Availability:

We integrated PG-SGD in ODGI which is released as free software under the MIT open source license. Source code is available at https://github.com/pangenome/odgi.

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Most cited references 21

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Bandage: interactive visualization of de novo genome assemblies

Ryan Wick, Mark B. Schultz, Justin Zobel … (2015)

Summary: Although de novo assembly graphs contain assembled contigs (nodes), the connections between those contigs (edges) are difficult for users to access. Bandage (a Bioinformatics Application for Navigating De novo Assembly Graphs Easily) is a tool for visualizing assembly graphs with connections. Users can zoom in to specific areas of the graph and interact with it by moving nodes, adding labels, changing colors and extracting sequences. BLAST searches can be performed within the Bandage graphical user interface and the hits are displayed as highlights in the graph. By displaying connections between contigs, Bandage presents new possibilities for analyzing de novo assemblies that are not possible through investigation of contigs alone. Availability and implementation: Source code and binaries are freely available at https://github.com/rrwick/Bandage. Bandage is implemented in C++ and supported on Linux, OS X and Windows. A full feature list and screenshots are available at http://rrwick.github.io/Bandage. Contact: rrwick@gmail.com Supplementary information : Supplementary data are available at Bioinformatics online.

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Evaluation of GRCh38 and de novo haploid genome assemblies demonstrates the enduring quality of the reference assembly

Valerie A Schneider, Tina Graves-Lindsay, Kerstin Howe … (2017)

The human reference genome assembly plays a central role in nearly all aspects of today's basic and clinical research. GRCh38 is the first coordinate-changing assembly update since 2009; it reflects the resolution of roughly 1000 issues and encompasses modifications ranging from thousands of single base changes to megabase-scale path reorganizations, gap closures, and localization of previously orphaned sequences. We developed a new approach to sequence generation for targeted base updates and used data from new genome mapping technologies and single haplotype resources to identify and resolve larger assembly issues. For the first time, the reference assembly contains sequence-based representations for the centromeres. We also expanded the number of alternate loci to create a reference that provides a more robust representation of human population variation. We demonstrate that the updates render the reference an improved annotation substrate, alter read alignments in unchanged regions, and impact variant interpretation at clinically relevant loci. We additionally evaluated a collection of new de novo long-read haploid assemblies and conclude that although the new assemblies compare favorably to the reference with respect to continuity, error rate, and gene completeness, the reference still provides the best representation for complex genomic regions and coding sequences. We assert that the collected updates in GRCh38 make the newer assembly a more robust substrate for comprehensive analyses that will promote our understanding of human biology and advance our efforts to improve health.

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A draft human pangenome reference

Wen-Wei Liao, Mobin Asri, Jana Ebler … (2023)

Here the Human Pangenome Reference Consortium presents a first draft of the human pangenome reference. The pangenome contains 47 phased, diploid assemblies from a cohort of genetically diverse individuals 1 . These assemblies cover more than 99% of the expected sequence in each genome and are more than 99% accurate at the structural and base pair levels. Based on alignments of the assemblies, we generate a draft pangenome that captures known variants and haplotypes and reveals new alleles at structurally complex loci. We also add 119 million base pairs of euchromatic polymorphic sequences and 1,115 gene duplications relative to the existing reference GRCh38. Roughly 90 million of the additional base pairs are derived from structural variation. Using our draft pangenome to analyse short-read data reduced small variant discovery errors by 34% and increased the number of structural variants detected per haplotype by 104% compared with GRCh38-based workflows, which enabled the typing of the vast majority of structural variant alleles per sample.

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Author and article information

Journal

Journal ID (nlm-ta): bioRxiv

Journal ID (publisher-id): BIORXIV

Title: bioRxiv

Publisher: Cold Spring Harbor Laboratory

Publication date (Electronic): 23 September 2023

Electronic Location Identifier: 2023.09.22.558964

Affiliations

[1 ]Quantitative Biology Center (QBiC), University of Tübingen, Tübingen 72076, Germany

[2 ]Biomedical Data Science, Department of Computer Science, University of Tübingen, Tübingen 72076, Germany

[3 ]Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN 38163, USA

[4 ]Genomics Research Centre, Human Technopole, Milan 20157, Italy

[5 ]Department of Computer Engineering, School of Computation, Information and Technology (CIT), Technical University of Munich, Munich 80333, Germany

[6 ]School of Electrical and Computer Engineering, Cornell University, Ithaca, NY 14853, USA

[7 ]Computomics GmbH, Eisenbahnstr. 1, 72072 Tübingen, Germany

Author notes

[* ]To whom correspondence should be addressed. Contact: egarris5@ 123456uthsc.edu

[†]

The authors wish it to be known that, in their opinion, the first two authors should be regarded as Joint First Authors.

Author information

Simon Heumos http://orcid.org/0000-0003-3326-817X

Andrea Guarracino http://orcid.org/0000-0001-9744-131X

Jan-Niklas Manuel Schmelzle http://orcid.org/0000-0001-8566-4049

Jiajie Li http://orcid.org/0000-0002-6775-2843

Zhiru Zhang http://orcid.org/0000-0002-0778-0308

Jörg Hagmann http://orcid.org/0000-0002-7232-3103

Sven Nahnsen http://orcid.org/0000-0002-4375-0691

Pjotr Prins http://orcid.org/0000-0002-8021-9162

Erik Garrison http://orcid.org/0000-0003-3821-631X

Article

DOI: 10.1101/2023.09.22.558964

PMC ID: 10542513

PubMed ID: 37790531

SO-VID: fccda619-98ec-49d4-af6d-0f38e8315efb

License:

This work is licensed under a Creative Commons Attribution 4.0 International License, which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use.

History

Funding

Funded by: S.H., Central Innovation Programme (ZIM) for SMEs of the Federal Ministry for Economic Affairs and Energy of Germany

Funded by: S.N., Germany’s Excellence Strategy (CMFI), iFIT

Award ID: EXC-2124, EXC 2180–390900677

Funded by: BMBF-funded de.NBI Cloud, German Network for Bioinformatics Infrastructure (de.NBI)

Award ID: 031A532B, 031A533A, 031A533B, 031A534A, 031A535A, 031A537A, 031A537B, 031A537C, 031A537D, 031A538A

Funded by: A.G., Nicole Soranzo, a pangenome research unit at the Human Technopole in Milan, Italy

Funded by: JNM.S., J.L., Z.Z., P.P., E.G., NSFPPoSS

Award ID: #2118709

Funded by: National Institutes of Health/NIDA, E.G.

Award ID: U01DA047638

Funded by: National Institutes of Health/NIGMS, E.G., P.P.

Award ID: R01GM123489

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Pangenome graph layout by Path-Guided Stochastic Gradient Descent

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Most cited references 21

Bandage: interactive visualization of de novo genome assemblies

Evaluation of GRCh38 and de novo haploid genome assemblies demonstrates the enduring quality of the reference assembly

A draft human pangenome reference

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