TY - JOUR
T1 - A critical comparison of technologies for a plant genome sequencing project
AU - Paajanen, Pirita
AU - Kettleborough, George
AU - López-Girona, Elena
AU - Giolai, Michael
AU - Heavens, Darren
AU - Baker, David
AU - Lister, Ashleigh
AU - Cugliandolo, Fiorella
AU - Wilde, Gail
AU - Hein, Ingo
AU - MacAulay, Iain
AU - Bryan, Glenn J.
AU - Clark, Matthew D.
N1 - Funding Information:
This work was funded with BBSRC project grants (BB/K019325/1) and (BB/K019090/1). This work was strategically funded by the BBSRC, Core Strategic Programme Grant (BB/CSP17270/1) at the Earlham Institute. High-throughput sequencing and library construction was delivered via the BBSRC National Capability in Genomics (BB/CCG1720/1) at the Earlham Institute (EI, formerly The Genome Analysis Centre, Norwich), by members of the Platforms and Pipelines Group. This research was supported in part by the NBI Computing infrastructure for Science (CiS) group through the HPC cluster and UV systems. We thank Duke University for providing sequencing costs via Dugsim (https://dugs im.net/).
Publisher Copyright:
© 2019 The Author(s). Published by Oxford University Press.
PY - 2019/1/9
Y1 - 2019/1/9
N2 - Background A high-quality genome sequence of any model organism is an essential starting point for genetic and other studies. Older clone-based methods are slow and expensive, whereas faster, cheaper short-read-only assemblies can be incomplete and highly fragmented, which minimizes their usefulness. The last few years have seen the introduction of many new technologies for genome assembly. These new technologies and associated new algorithms are typically benchmarked on microbial genomes or, if they scale appropriately, on larger (e.g., human) genomes. However, plant genomes can be much more repetitive and larger than the human genome, and plant biochemistry often makes obtaining high-quality DNA that is free from contaminants difficult. Reflecting their challenging nature, we observe that plant genome assembly statistics are typically poorer than for vertebrates. Results Here, we compare Illumina short read, Pacific Biosciences 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 species Solanum verrucosum. We benchmark the assemblies for completeness and accuracy, as well as DNA compute requirements and sequencing costs. Conclusions The field of genome sequencing and assembly is reaching maturity, and the differences we observe between assemblies are surprisingly small. We expect that our results will be helpful to other genome projects, and that these datasets will be used in benchmarking by assembly algorithm developers.
AB - Background A high-quality genome sequence of any model organism is an essential starting point for genetic and other studies. Older clone-based methods are slow and expensive, whereas faster, cheaper short-read-only assemblies can be incomplete and highly fragmented, which minimizes their usefulness. The last few years have seen the introduction of many new technologies for genome assembly. These new technologies and associated new algorithms are typically benchmarked on microbial genomes or, if they scale appropriately, on larger (e.g., human) genomes. However, plant genomes can be much more repetitive and larger than the human genome, and plant biochemistry often makes obtaining high-quality DNA that is free from contaminants difficult. Reflecting their challenging nature, we observe that plant genome assembly statistics are typically poorer than for vertebrates. Results Here, we compare Illumina short read, Pacific Biosciences 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 species Solanum verrucosum. We benchmark the assemblies for completeness and accuracy, as well as DNA compute requirements and sequencing costs. Conclusions The field of genome sequencing and assembly is reaching maturity, and the differences we observe between assemblies are surprisingly small. We expect that our results will be helpful to other genome projects, and that these datasets will be used in benchmarking by assembly algorithm developers.
KW - 10x Genomics
KW - assembly
KW - long reads
KW - optical mapping
KW - PacBio
KW - Pacific Biosciences
KW - short reads
UR - http://www.scopus.com/inward/record.url?scp=85063272046&partnerID=8YFLogxK
U2 - 10.1093/gigascience/giy163
DO - 10.1093/gigascience/giy163
M3 - Article
C2 - 30624602
AN - SCOPUS:85063272046
VL - 8
JO - GigaScience
JF - GigaScience
SN - 2047-217X
IS - 3
M1 - giy163
ER -