Modern head cabbage (Brassica oleracea var. capitata L.) breeding is based on the application of molecular markers through marker-assisted selection (MAS). In hybrid breeding, critical markers are deployed to assess cytoplasmic male sterility (CAPS and SSR for orf138), genic male sterility (KASP markers for Ms-cd1, InDel for ms3, and BoCYP704B1), fertility restoration (InDel marker for Rfo), combining ability and genetic diversity (using SSR and KASP marker sets), and to ensure F₁ hybrid seed genetic purity (RAPD and SSR markers sets). Disease resistance, a well-developed category due to frequent monogenic control, includes markers for major pathogens, including those for Fusarium wilt (for Foc-Bo1 gene), black rot (race 1–7 specific SSR and InDel markers), clubroot (Kamogawa, Anno, and Yuki isolates), and downy mildew (BoDMR2 InDel marker). Markers have also been identified for key agronomic and morphological traits, such as those governing petal color (InDel markers for BoCCD4), leaf waxiness (BoGL1, BoGL-3, Cgl1, Cgl2, BoWax1, and BoCER2), and leaf color (ygl-1, BoMYB2, BoMYBL2-1). The review also included markers for resistance to abbioticaly induced negative physiological processes, such as head splitting (QTL SPL-2-1, Bol016058), bolting (resistance loci-associated SSR marker), prolonged flowering time (BoFLC1,2 genes), and high- and low-temperature tolerance (BoTPPI-2, BoCSDP5, BoCCA1). Despite these advancements, the review highlights that the marker repertoire for cabbage remains limited compared with other Brassicaceae species, particularly for complex polygenic traits. This synthesis is a valuable resource for breeders and researchers, facilitating the development of superior head cabbage cultivars and hybrids.

Developing soy cultivars for northern long-day regions requires understanding how alleles of protein accumulation genes function in non-optimal environments like Western Siberia, where their effects may diverge from those established in other regions. We hypothesized that allelic variation in the genes GmSWEET39, Glyma.03G219900, Glyma.14G119000, Glyma.17G074400, and POWR1 would have measurable and predictable effects on seed composition and plant architecture in soybean, even under the stressful long-day conditions of Western Siberia (Omsk Oblast). Over a three-year period (2021–2023), a diverse collection of 58 soybean accessions was phenotyped for yield-related traits and genotyped using established KASP and PCR markers and a novel KASP marker for GmSWEET39. Our results demonstrate that the GmSWEET39 CC+ allele is significantly associated with an increase in seed protein content by up to 1.9 pp, a decrease in seed oil content up to 1.4 pp, and a reduction in plant height by up to 20%, while the Glyma.17G074400 SNP(T) allele was associated with an increase in oil content up to 1.4 pp. Strong negative correlations were found between protein content and plant height, whereas plant height was positively correlated with flowering time. Broad-sense heritability was high (H² > 0.82) for all traits except fiber content. The genotypic structure of the collection revealed a predominance of oil-favoring alleles, with rare protein-enhancing alleles identified in accessions from Sweden, Poland, China, and Japan. These accessions have been proposed as valuable donors for breeding. This study validates the utility of marker-assisted selection for the development of high-protein and high-oil soybean varieties tailored to the challenging photoperiod and climatic conditions of northern regions.

High-throughput genomic technologies are enabling the identification of thousands or even millions of single-nucleotide polymorphisms (SNPs). SNP markers are frequently used to analyze crop varieties, with the marker data summarized in a common VCF file. At present, it is difficult to identify the minimal SNP set, the smallest sets that can distinguish between all crop varieties listed in a VCF file, due to the absence of available ready-to-use tools capable of such characterization. Here, we describe the development of the ready-to-use open-source tool MDSearch (Minimal Discriminatory SNP Set Search) based on the identification of the MDS (minimal discriminatory set) of SNPs using random walking staring from the maximal discriminatory set. MDSearch can be used for disploid as well as poliploid species and both phased and unphased VCF files. MDSearch has been validated using a publicly available dataset of barley SNPs obtained by genotyping-by-sequencing. As a result, we have successfully identified a discriminating set of 19 SNP markers capable of distinguishing all 254 barley varieties included in our study. We expect that this program will prove useful to genomics researchers to support a variety of certifications.