A critical comparison of technologies for a plant genome sequencing project

This article has been Reviewed by the following groups

Read the full article See related articles

Discuss this preprint

Start a discussion What are Sciety discussions?

Abstract

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 species S. 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.

Article activity feed

  1. Now published in GigaScience doi: 10.1093/gigascience/giy163

    Pirita Paajanen 1Earlham Institute, Norwich, UK;Find this author on Google ScholarFind this author on PubMedSearch for this author on this siteGeorge Kettleborough 1Earlham Institute, Norwich, UK;Find this author on Google ScholarFind this author on PubMedSearch for this author on this siteORCID record for George KettleboroughElena López-Girona 2The James Hutton Institute, Invergowrie, Dundee, UK.Find this author on Google ScholarFind this author on PubMedSearch for this author on this siteMichael Giolai 1Earlham Institute, Norwich, UK;Find this author on Google ScholarFind this author on PubMedSearch for this author on this siteDarren Heavens 1Earlham Institute, Norwich, UK;Find this author on Google ScholarFind this author on PubMedSearch for this author on this siteDavid Baker 1Earlham Institute, Norwich, UK;Find this author on Google ScholarFind this author on PubMedSearch for this author on this siteAshleigh Lister 1Earlham Institute, Norwich, UK;Find this author on Google ScholarFind this author on PubMedSearch for this author on this siteORCID record for Ashleigh ListerGail Wilde 2The James Hutton Institute, Invergowrie, Dundee, UK.Find this author on Google ScholarFind this author on PubMedSearch for this author on this siteIngo Hein 2The James Hutton Institute, Invergowrie, Dundee, UK.Find this author on Google ScholarFind this author on PubMedSearch for this author on this siteIain Macaulay 1Earlham Institute, Norwich, UK;Find this author on Google ScholarFind this author on PubMedSearch for this author on this siteORCID record for Iain MacaulayGlenn J. Bryan 2The James Hutton Institute, Invergowrie, Dundee, UK.Find this author on Google ScholarFind this author on PubMedSearch for this author on this siteMatthew D. Clark 1Earlham Institute, Norwich, UK;Find this author on Google ScholarFind this author on PubMedSearch for this author on this siteORCID record for Matthew D. ClarkFor correspondence: matt.clark@earlham.ac.uk

    A version of this preprint has been published in the Open Access journal GigaScience (see paper https://doi.org/10.1093/gigascience/giy163 ), where the paper and peer reviews are published openly under a CC-BY 4.0 license.

    These peer reviews were as follows:

    Reviewer 1: http://dx.doi.org/10.5524/REVIEW.101497 Reviewer 2: http://dx.doi.org/10.5524/REVIEW.101498