Universität zu Köln

Ebler, Jana, Ebert, Peter ORCID: 0000-0001-7441-532X, Clarke, Wayne E., Rausch, Tobias ORCID: 0000-0001-5773-5620, Audano, Peter A., Houwaart, Torsten ORCID: 0000-0002-4525-7593, Mao, Yafei ORCID: 0000-0002-9648-4278, Korbel, Jan O., Eichler, Evan E., Zody, Michael C., Dilthey, Alexander T. and Marschall, Tobias (2022). Pangenome-based genome inference allows efficient and accurate genotyping across a wide spectrum of variant classes. Nature Genet., 54 (4). S. 518 - 541. BERLIN: NATURE PORTFOLIO. ISSN 1546-1718

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Abstract

PanGenie is an alignment-free, k-mer-based tool that utilizes a haplotype-resolved pangenome reference to genotype a wide range of variants. Typical genotyping workflows map reads to a reference genome before identifying genetic variants. Generating such alignments introduces reference biases and comes with substantial computational burden. Furthermore, short-read lengths limit the ability to characterize repetitive genomic regions, which are particularly challenging for fast k-mer-based genotypers. In the present study, we propose a new algorithm, PanGenie, that leverages a haplotype-resolved pangenome reference together with k-mer counts from short-read sequencing data to genotype a wide spectrum of genetic variation-a process we refer to as genome inference. Compared with mapping-based approaches, PanGenie is more than 4 times faster at 30-fold coverage and achieves better genotype concordances for almost all variant types and coverages tested. Improvements are especially pronounced for large insertions (>= 50 bp) and variants in repetitive regions, enabling the inclusion of these classes of variants in genome-wide association studies. PanGenie efficiently leverages the increasing amount of haplotype-resolved assemblies to unravel the functional impact of previously inaccessible variants while being faster compared with alignment-based workflows.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Ebler, Jana UNSPECIFIED UNSPECIFIED UNSPECIFIED Ebert, Peter UNSPECIFIED orcid.org/0000-0001-7441-532X UNSPECIFIED Clarke, Wayne E. UNSPECIFIED UNSPECIFIED UNSPECIFIED Rausch, Tobias UNSPECIFIED orcid.org/0000-0001-5773-5620 UNSPECIFIED Audano, Peter A. UNSPECIFIED UNSPECIFIED UNSPECIFIED Houwaart, Torsten UNSPECIFIED orcid.org/0000-0002-4525-7593 UNSPECIFIED Mao, Yafei UNSPECIFIED orcid.org/0000-0002-9648-4278 UNSPECIFIED Korbel, Jan O. UNSPECIFIED UNSPECIFIED UNSPECIFIED Eichler, Evan E. UNSPECIFIED UNSPECIFIED UNSPECIFIED Zody, Michael C. UNSPECIFIED UNSPECIFIED UNSPECIFIED Dilthey, Alexander T. UNSPECIFIED UNSPECIFIED UNSPECIFIED Marschall, Tobias UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-685046
DOI:	10.1038/s41588-022-01043-w
Journal or Publication Title:	Nature Genet.
Volume:	54
Number:	4
Page Range:	S. 518 - 541
Date:	2022
Publisher:	NATURE PORTFOLIO
Place of Publication:	BERLIN
ISSN:	1546-1718
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language DE-NOVO CNVS; STRUCTURAL VARIATION; SEQUENCING READS; IMPUTATION; DISCOVERY; DUPLICATIONS; ASSOCIATION; THOUSANDS; ALIGNMENT; DISORDER Multiple languages Genetics & Heredity Multiple languages
URI:	http://kups.ub.uni-koeln.de/id/eprint/68504