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. 2023 Feb;20(2):239-247.
doi: 10.1038/s41592-022-01731-9. Epub 2023 Jan 16.

Haplotype-aware pantranscriptome analyses using spliced pangenome graphs

Jonas A Sibbesen #  1 , Jordan M Eizenga #  1 , Adam M Novak  1 , Jouni Sirén  1 , Xian Chang  1 , Erik Garrison  2 , Benedict Paten  3
Affiliations

Haplotype-aware pantranscriptome analyses using spliced pangenome graphs

Jonas A Sibbesen et al. Nat Methods. 2023 Feb.

Abstract

Pangenomics is emerging as a powerful computational paradigm in bioinformatics. This field uses population-level genome reference structures, typically consisting of a sequence graph, to mitigate reference bias and facilitate analyses that were challenging with previous reference-based methods. In this work, we extend these methods into transcriptomics to analyze sequencing data using the pantranscriptome: a population-level transcriptomic reference. Our toolchain, which consists of additions to the VG toolkit and a standalone tool, RPVG, can construct spliced pangenome graphs, map RNA sequencing data to these graphs, and perform haplotype-aware expression quantification of transcripts in a pantranscriptome. We show that this workflow improves accuracy over state-of-the-art RNA sequencing mapping methods, and that it can efficiently quantify haplotype-specific transcript expression without needing to characterize the haplotypes of a sample beforehand.

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