A critical comparison of technologies for a plant genome sequencing project

• DOI: 10.1101/201830
• Publication Date: 2017-10-12T05:10:13Z
• Authors: Pirita Paajanen; George Kettleborough; Elena López-Girona; Michael Giolai; Darren Heavens; David Baker; Ashleigh Lister; Gail Wilde; Ingo Hein; Iain Macaulay; Glenn J. Bryan; Matthew D. Clark
• Keywords: PacBio; assembly; 0301 basic medicine; /dk/atira/pure/subjectarea/asjc/1700/1706; 570; Research; 10x Genomics; name=Health Informatics; Genomics; Sequence Analysis, DNA; /dk/atira/pure/subjectarea/asjc/2700/2718; name=Computer Science Applications; Genes, Plant; short reads; optical mapping; Contig Mapping; 03 medical and health sciences; long reads; Costs and Cost Analysis; Pacific Biosciences; Humans; RNA, Messenger; Genome, Plant; Solanaceae

A high quality genome sequence of your model organism is an essential starting point for many studies. Old clone based methods are slow and expensive, whereas faster, cheaper short read only assemblies can be incomplete and highly fragmented, which minimises their usefulness. The last few years have seen the introduction of many new technologies for genome assembly. These new technologies and new algorithms are typically benchmarked on microbial genomes or, if they scale appropriately, human. However, plant genomes can be much more repetitive and larger than human, and plant biology makes obtaining high quality DNA free from contaminants difficult. Reflecting their challenging nature we observe that plant genome assembly statistics are typically poorer than for vertebrates. Here we compare Illumina short read, PacBio long read, 10x Genomics linked reads, Dovetail Hi-C and BioNano Genomics optical maps, singly and combined, in producing high quality long range genome assemblies of the potato speciesS. verrucosum. We benchmark the assemblies for completeness and accuracy, as well as DNA, compute requirements and sequencing costs. We expect our results will be helpful to other genome projects, and that these datasets will be used in benchmarking by assembly algorithm developers.