SummaryThe application of genomics in crops has the ability to significantly improve genetic gain for agriculture. Many marker‐dense tools have been developed, but few have seen broad adoption in plant genomics due to issues of significant variations of genome size, levels of ploidy, single nucleotide polymorphism (SNP) frequency and reproductive habit. When combined with limited breeding activities, small research communities and scant sequence resources, the suitability of popular systems is often suboptimal and routinely fails to effectively balance cost‐effectiveness and sample throughput. Genotyping‐by‐sequencing (GBS) encompasses a range of protocols including resequencing of the transcriptome. This study describes a skim GBS‐transcriptomics (GBS‐t) approach developed to be broadly applicable, cost‐effective and high‐throughput while still assaying a significant number of SNP loci. A range of crop species with differing levels of ploidy and degree of inbreeding/outbreeding were chosen, including perennial ryegrass, a diploid outbreeding forage grass; phalaris, a putative segmental allotetraploid outbreeding forage grass; lentil, a diploid inbreeding grain legume; and canola, an allotetraploid partially outbreeding oilseed. GBS‐t was validated as a simple and largely automated, cost‐effective method which generates sufficient SNPs (from 89 738 to 231 977) with acceptable levels of missing data and even genome coverage from c. 3 million sequence reads per sample. GBS‐t is therefore a broadly applicable system suitable for many crops, offering advantages over other systems. The correct choice of subsequent sequence analysis software is important, and the bioinformatics process should be iterative and tailored to the specific challenges posed by ploidy variation and extent of heterozygosity.

Intensive breeding of Brassica napus has resulted in relatively low diversity, such that B. napus would benefit from germplasm improvement schemes that sustain diversity. As such, samples representative of global germplasm pools need to be assessed for existing population structure, diversity and linkage disequilibrium (LD). Complexity reduction genotyping-by-sequencing (GBS) methods, including GBS-transcriptomics (GBS-t), enable cost-effective screening of a large number of samples, while whole genome re-sequencing (WGR) delivers the ability to generate large numbers of unbiased genomic single nucleotide polymorphisms (SNPs), and identify structural variants (SVs). Furthermore, the development of genomic tools based on whole genomes representative of global oilseed diversity and orientated by the reference genome has substantial industry relevance and will be highly beneficial for canola breeding. As recent studies have focused on European and Chinese varieties, a global diversity panel as well as a substantial number of Australian spring types were included in this study. Focusing on industry relevance, 633 varieties were initially genotyped using GBS-t to examine population structure using 61,037 SNPs. Subsequently, 149 samples representative of global diversity were selected for WGR and both data sets used for a side-by-side evaluation of diversity and LD. The WGR data was further used to develop genomic resources consisting of a list of 4,029,750 high-confidence SNPs annotated using SnpEff, and SVs in the form of 10,976 deletions and 2,556 insertions. These resources form the basis of a reliable and repeatable system allowing greater integration between canola genomics studies, with a strong focus on breeding germplasm and industry applicability.