Background Assemblies of diploid genomes are generally unphased, pseudo-haploid representations that do not correctly reconstruct the two parental haplotypes present in the individual sequenced. Instead, the assembly alternates between parental haplotypes and may contain duplications in regions where the parental haplotypes are sufficiently different. Trio binning is an approach to genome assembly that uses short reads from both parents to classify long reads from the offspring according to maternal or paternal haplotype origin, and is thus helped rather than impeded by heterozygosity. Using this approach, it is possible to derive two assemblies from an individual, accurately representing both parental contributions in their entirety with higher continuity and accuracy than is possible with other methods.Results We used trio binning to assemble reference genomes for two species from a single individual using an interspecies cross of yak (Bos grunniens) and cattle (Bos taurus). The high heterozygosity inherent to interspecies hybrids allowed us to confidently assign >99% of long reads from the F1 offspring to parental bins using unique k-mers from parental short reads. Both the maternal (yak) and paternal (cattle) assemblies contain over one third of the acrocentric chromosomes, including the two largest chromosomes, in single haplotigs.Conclusions These haplotigs are the first vertebrate chromosome arms to be assembled gap-free and fully phased, and the first time assemblies for two species have been created from a single individual. Both assemblies are the most continuous currently available for non-model vertebrates.MbmegabaseskbkilobasesMYAmillions of years agoMHCmajor histocompatibility complexSMRTsingle molecule real time
Benchmark small variant calls are required for developing, optimizing and assessing the performance of sequencing and bioinformatics methods. Here, as part of the Genome in a Bottle (GIAB) Consortium, we apply a reproducible, cloud-based pipeline to integrate multiple short- and linked-read sequencing datasets and provide benchmark calls for human genomes. We generate benchmark calls for one previously analyzed GIAB sample, as well as six genomes from the Personal Genome Project. These new genomes have broad, open consent, making this a ‘first of its kind’ resource that is available to the community for multiple downstream applications. We produce 17% more benchmark single nucleotide variations, 176% more indels and 12% larger benchmark regions than previously published GIAB benchmarks. We demonstrate that this benchmark reliably identifies errors in existing callsets and highlight challenges in interpreting performance metrics when using benchmarks that are not perfect or comprehensive. Finally, we identify strengths and weaknesses of callsets by stratifying performance according to variant type and genome context.