Abstract

Whole genome sequencing offers genome wide, unbiased markers, and inexpensive library preparation. With the cost of sequencing decreasing rapidly, many plant genomes of modest size are amenable to skim whole genome resequencing (skim WGR). The use of skim WGR in diverse sample sets without the use of imputation was evaluated in silico in 149 canola samples representative of global diversity. Fastq files with an average of 10x coverage of the reference genome were used to generate skim samples representing 0.25x, 0.5x, 1x, 2x, 3x, 4x, and 5x sequencing coverage. Applying a pre-defined list of SNPs versus de novo SNP discovery was evaluated. As skim WGR is expected to result in some degree of insufficient allele sampling, all skim coverage levels were filtered at a range of minimum read depths from a relaxed minimum read depth of 2 to a stringent read depth of 5, resulting in 28 list-based SNP sets. As a broad recommendation, genotyping pre-defined SNPs between 1x and 2x coverage with relatively stringent depth filtering is appropriate for a diverse sample set of canola due to a balance between marker number, sufficient accuracy, and sequencing cost, but depends on the intended application. This was experimentally examined in two sample sets with different genetic backgrounds: 1x coverage of 1,590 individuals from 84 Australian spring type four-parent crosses aimed at maximizing diversity as well as one commercial F1 hybrid, and 2x coverage of 379 doubled haploids (DHs) derived from a subset of the four-parent crosses. To determine optimal coverage in a simpler genetic background, the DH sample sequence coverage was further down sampled in silico. The flexible and cost-effective nature of the protocol makes it highly applicable across a range of species and purposes.

Highlights

  • Advances in next-generation sequencing have enabled the application of genomics for the improvement of agronomically important crop species

  • The aim of the current study was to determine the effect of sequencing coverage, minimum read depth and maximum missing data filtering on SNP genotyping, and apply the method in a range of genetic backgrounds of varying complexity, to determine the applicability of skim WGR as a routine genotyping tool in canola, a highly duplicated allotetraploid with a genome size of 1.13 Gbp, of which 850 Mbp is covered in the Darmor-bzh reference genome (Chalhoub et al, 2014)

  • The present study has found skim WGR to be applicable in canola, an allotetraploid with a relatively modest genome size, in a range of genetic backgrounds

Read more

Summary

Introduction

Advances in next-generation sequencing have enabled the application of genomics for the improvement of agronomically important crop species. Genomic selection (GS) and genome-wide association studies (GWAS) have delivered considerable crop improvements and rely on high density markers spread throughout the genome (Goddard and Hayes, 2007; Desta and Ortiz, 2014). Genotyping-by-sequencing (GBS) in the form of target capture and complexity reduction methods have greatly facilitated the use of genomics by cost-effectively providing dense SNP markers (Mamanova et al, 2010; Davey et al, 2011; Hirsch et al, 2014). The other complexity reduction method, GBS-transcriptomics (Malmberg et al, 2018a) relies on mRNA, which must be of high quality and only delivers SNPs within the exome (Scheben et al, 2017)

Objectives
Methods
Results
Discussion
Conclusion
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.