The Human Pangenome Reference Consortium’s (HPRC) Release 2 (HPRC2) is presented, an openly available, second phase pangenome that is an approximately fivefold expansion in genome number over HPRC Release 1 (HPRC1) and measurable improvement in genome completeness, contiguity, and accuracy.
Abstract
A pangenome reference overcomes the inherent limitation of any individual reference genome by integrating the variation present in a population. We present the Human Pangenome Reference Consortium’s (HPRC) Release 2 (HPRC2), an openly available, second phase pangenome that is an approximately fivefold expansion in genome number over HPRC Release 1 (HPRC1) and measurable improvement in genome completeness, contiguity, and accuracy. Selecting samples with a principled algorithm prioritising common variant coverage, HPRC2 contributes 460 haplotypes that together capture over 99% of common variation observed in the All of Us Research Program v8 cohort. Combining high-coverage long and ultra-long reads with modern assemblers and polishers, we produce thousands of telomere-to-telomere (T2T) chromosomes, and relative to HPRC1 halve the number of structurally unreliable regions as well as individual base errors per haplotype. We complement the assemblies with whole genome multiple alignments and gene annotations, and derive formal pangenome coordinate systems for addressing off-reference variation, demonstrating that individual human genomes contain more than one hundred thousand variants not succinctly described with respect to existing reference genomes. We also present the first matched long-read backed pantranscriptome and panepigenome at this scale, provide continuous local-ancestry estimates spanning every genome, and outline a host of new tools and applications that leverage the pangenome resource for improved genomics analysis.
Reference bias is an issue that affects most genomic studies analysing short reads mapped to a reference genome1,2. It can be mitigated by mapping to multiple haplotypes represented in a pangenome3-5. Here we introduce two new methods to address reference bias: Emblask for pangenome construction and Weaver for mapping...
Guillaume Holley, H. Eggertsson, Snaedis Kristmundsdottir et al.· Nature· 0 citations
This work describes the full spectrum of genetic variation and shows that while 99% of the variants between any two genomes are single base-pair substitutions, 88% of the euchromatic variant base pairs are SVs, including insertions, deletions, duplications, and inversions.
J. Lin, J. Gustafson, J. Wertz et al.· medRxiv· 1 citation
Human pangenomics is moving beyond the single linear reference paradigm towards population-scale representations that better capture complex genomic variation. Many current human pangenomes include both global and regional initiatives, but their limited sample sizes constrain the representation of population diversity....
Kai-Lin Chen, Zhao-Yuan Fang· The Innovation Life· 0 citations
It is found that reference choice substantially influences genome interpretation: ancestry-matched linear T2T references provided the most faithful representation of individual genomic variation and enabled more accurate genome reconstruction than unmatched linear, diploid and graph-based references.
TruPath Genome achieves high-resolution detection of SNVs and indels alongside long-range phasing for CNVs and structural variant (SV) refinement and facilitates telomere-to-telomere assemblies and pangenome development, advancing the understanding of genome biology at an unprecedented scale.
The results indicate that pangenome-based workflows aid improved detection of large variants from targeted sequencing data in the clinical context and suggest that they may contribute to more unified variant detection frameworks for all-size genetic variants in the future.
F. Mazzarotto, Özem Kalay, E. Arslan et al.· Genome Medicine· 0 citations
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