An Improved, High-quality Ovine Reference Genome Assembly

Abstract Sheep are an important agricultural species used for both food and fiber in the United States and globally. A high-quality reference genome enhances the ability to discover genetic and biological mechanisms influencing important traits, such as meat and wool quality. The rapid advances in genome assembly algorithms and emergence of increasingly long sequence read length provide the opportunity for an improved de novo assembly of the sheep reference genome. Tissue was collected postmortem from an adult Rambouillet ewe selected by USDA-ARS for the Ovine Functional Annotation of Animal Genomes project. Short-read (55x coverage), long-read PacBio (75x coverage), and Hi-C data from this ewe were retrieved from public databases. We generated an additional 50x coverage of Oxford Nanopore data and assembled the combined long-read data with canu v1.9. The assembled contigs were polished with Nanopolish v0.12.5 and scaffolded using Hi-C data with Salsa v2.2. Gaps were filled with PBsuite v15.8.24 and polished with Nanopolish v0.12.5 followed by removal of duplicate contigs with PurgeDups v1.0.1. Chromosomes were oriented by identifying centromeres and telomeres with RepeatMasker v4.1.1, indicating a need to reverse the orientation of chromosome 11 relative to Oar_rambouillet_v1.0. Final polishing was performed with two rounds of a pipeline which consisted of freebayes v1.3.1 to call variants, Merfin to validate them, and BCFtools to generate the consensus fasta. The ARS-UI_Ramb_v2.0 assembly has improved continuity (contig N50 of 43.19 Mb) with a 19-fold and 38-fold decrease in the number of scaffolds compared with Oar_rambouillet_v1.0 and Oar_v4.0. ARS-UI_Ramb_v2.0 has greater per-base accuracy and fewer insertions and deletions identified from mapped RNA sequence than previous assemblies. This significantly improved reference assembly, public at NCBI GenBank under accession number GCA_016772045, will optimize the functional annotation of the sheep genome and facilitate improved mapping accuracy of genetic variant and expression data for traits relevant the sheep industry.