The large genome and polyploidy of wheat (Triticum aestivum L.) makes it difficult to identify desirable genetic changes based on phenotypic screening due to gene redundancy. Forward genetics is, therefore, more difficult in wheat than in diploid plants. A modified TILLING (Targeting Induced Local Lesions IN Genomes) method including the harvest of five heads per M1 plant, storage of M2 seeds, using unlabeled primers and agarose gels for mutation detection, and crossing of useful mutants for desired grain quality was explored in this report. A soft wheat cultivar, QAL2000, and a hard wheat cultivar, Ventura, were mutagenized with ethyl methanesulfonate (EMS). Screening of the waxy genes Wx‐A1 and Wx‐D1 in 2348 EMS‐treated M2 plants allowed identification of 121 mutants, including silent, missense, and knockout (truncation) mutations. A complete waxy wheat was successfully bred in 18 mo by crossing two truncation mutants (Wx‐A1‐truncation and Wx‐D1‐truncation; Wx‐B1 is naturally null in both mutants). Screening of two puroindoline genes (Pina and Pinb) in QAL2000 identified 19 mutants. A hard grain variant of a soft cultivar was identified due to a mutation in Pinb caused by a premature stop codon. Background mutations were observed and further self‐fertilization or crossing with a wild type was performed to eliminate deleterious mutations. With the rapid accumulation of wheat genomics information, many potential target genes of interest can be screened for mutations in these TILLING populations.

Germplasm collections provide an extremely valuable resource for breeders and researchers. However, misclassification of accessions by species often hinders the effective use of these collections. We propose that use of high-throughput genotyping tools can provide a fast, efficient and cost-effective way of confirming species in germplasm collections, as well as providing valuable genetic diversity data. We genotyped 180 Brassicaceae samples sourced from the Australian Grains Genebank across the recently released Illumina Infinium Brassica 60K SNP array. Of these, 76 were provided on the basis of suspected misclassification and another 104 were sourced independently from the germplasm collection. Presence of the A- and C-genomes combined with principle components analysis clearly separated Brassica rapa, B. oleracea, B. napus, B. carinata and B. juncea samples into distinct species groups. Several lines were further validated using chromosome counts. Overall, 18% of samples (32/180) were misclassified on the basis of species. Within these 180 samples, 23/76 (30%) supplied on the basis of suspected misclassification were misclassified, and 9/105 (9%) of the samples randomly sourced from the Australian Grains Genebank were misclassified. Surprisingly, several individuals were also found to be the product of interspecific hybridization events. The SNP (single nucleotide polymorphism) array proved effective at confirming species, and provided useful information related to genetic diversity. As similar genomic resources become available for different crops, high-throughput molecular genotyping will offer an efficient and cost-effective method to screen germplasm collections worldwide, facilitating more effective use of these valuable resources by breeders and researchers.

An Illumina Infinium array comprising 5306 single nucleotide polymorphism (SNP) markers was used to genotype 175 individuals of a doubled haploid population derived from a cross between Skipton and Ag-Spectrum, two Australian cultivars of rapeseed (Brassica napus L.). A genetic linkage map based on 613 SNP and 228 non-SNP (DArT, SSR, SRAP and candidate gene markers) covering 2514.8 cM was constructed and further utilized to identify loci associated with flowering time and resistance to blackleg, a disease caused by the fungus Leptosphaeria maculans. Comparison between genetic map positions of SNP markers and the sequenced Brassica rapa (A) and Brassica oleracea (C) genome scaffolds showed several genomic rearrangements in the B. napus genome. A major locus controlling resistance to L. maculans was identified at both seedling and adult plant stages on chromosome A07. QTL analyses revealed that up to 40.2% of genetic variation for flowering time was accounted for by loci having quantitative effects. Comparative mapping showed Arabidopsis and Brassica flowering genes such as Phytochrome A/D, Flowering Locus C and agamous-Like MADS box gene AGL1 map within marker intervals associated with flowering time in a DH population from Skipton/Ag-Spectrum. Genomic regions associated with flowering time and resistance to L. maculans had several SNP markers mapped within 10 cM. Our results suggest that SNP markers will be suitable for various applications such as trait introgression, comparative mapping and high-resolution mapping of loci in B. napus.