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Open access 2026

Molecular genetic analysis of potato genotypes for late blight resistance

Increasing crop yields and enhancing their adaptation to changing growing conditions are among the key strategies for ensuring food security. Potato is one of the most important food crops worldwide and is cultivated on all continents. Plant breeders play a crucial role in ensuring sustainable potato production by developing new resistant varieties with increased yield per hectare. Since the 1990s, genetics has played an increasingly important role in plant breeding through the introduction of DNA markers as indirect selection tools and for the assessment of genetic diversity. Today, genomics-based plant breeding approaches, such as marker-assisted selection (MAS) and genomic selection (GS), accelerate the breeding process for many major crops. The aim of this study was to identify genes conferring late blight resistance in 30 promising potato hybrids using DNA markers. Laboratory analyses for late blight resistance were conducted at the Laboratory of Molecular Genetic Research of Agricultural Plants at the Vladikavkaz Scientific Center of the Russian Academy of Sciences. The breeding material was preliminarily evaluated under field conditions in accordance with the recommendations for potato breeding programs. Genomic DNA was extracted from potato leaves during the flowering period using the CTAB method. For molecular genetic analysis of late blight resistance, the following R-gene molecular markers were used: R1–1250, R3a-1380, and R3b-378. The molecular genetic analysis revealed the presence of all three markers R1–1250, R3a-1380, and R3b-378. They were identified in five different potato hybrids. These hybrids included: 3375–1 (Tiras × Breeze), 3403–2 (Arizona × Fritella), 3341–2 (Innovator × Mirage), 3352–1 (Kolette × Mirage), and 3352–4 (Kolette × Mirage). The presence of all three genes indicates a high degree of late blight resistance. Thus, the identification of potato genotypes using molecular markers facilitates the acceleration of the breeding process for developming new resistant potato varieties.

N. Doguzova · 0 citations
Open access 2026

Leveraging molecular tools for cereal breeding: Progress, limitations, and prospects

Rice, wheat, and maize cereals are the major foundation of global food security. However, climate change makes it more challenging to achieve high crop yield, the challenge occurs due to improper management of cereal diseases and pests, and limitations of traditional breeding processes. This study aimed to update the process, limitations, and prospects of molecular tools for cereal breeding, and to explore the significance of marker-assisted selection, marker-assisted backcrossing, gene pyramiding, genomic selection, and modern breeding for improving yield, stress tolerance, and grain quality of cereals. Based on recent studies, we have explored the advances and applications of high-throughput genotyping platforms like the single nucleotide polymorphism (SNP) array and genotyping by sequencing technology in cereals. In this study, we found several limitations, such as a low number of studies with large amounts of data, genotype-environment interactions, lack of study findings at the field level, cost implications, and integration of complex multi-omics data. This study further reveals that many crucial agronomic traits are polygenic in their mode of inheritance, and the hidden genetic links make selection weak and uncertain. However, the application of molecular tools such as CRISPR/Cas genome editing, speed breeding, pan-genomics, artificial intelligence, and high-throughput phenomics provides sustainable solutions to these challenges in cereal improvement. The application of these modern breeding tools, combined with microbiome-assisted breeding and agricultural technologies in precision cereal breeding, opens new opportunities for enhancing yield and climate-smart, sustainable cereal production for global food and nutrition security.

M. Hayat, R. Cengiz, Umair Gull et al. · 0 citations
Review Open access Aug 2026

Advances in predictive breeding for wheat: concepts, methods, and applications

Wheat is one of the world’s main crops. Its improvement is pivotal given the threat of climate change and the growing population. However, enhancing breeding efficiency and improving wheat are challenging due to strong genotype-by-environment (G×E) interactions and the biological complexity underlying the wheat genome and key agronomic traits. In this context, predictive frameworks and data-driven approaches can offer new strategies to address these challenges. This article provides a comprehensive review of the latest developments in wheat breeding, highlighting emerging predictive frameworks and their contributions to modern breeding pipelines. First, we report on genomic selection (GS) applications, emphasizing GS’s ability to improve complex traits by shortening the breeding cycle and increasing selection accuracy. We then describe the applications of phenomics in wheat breeding, including both ground- and unmanned aerial vehicle (UAVs)-based systems. We also discuss the potential for implementing multi-omics strategies to improve complex wheat traits. We debate how predictive breeding frameworks can assist in identifying the best parents and crosses in wheat breeding. Finally, we presented the latest panorama of software for predictive breeding and its integration with other technologies. This review reports recent advances demonstrating how predictive frameworks are reshaping wheat breeding methods, highlighting current progress and outlining future opportunities to accelerate genetic gain in wheat improvement.

P. Vitale, Karim Ammar, Flávio Breseghello et al. · 0 citations
Review Open access Jul 2026

Status, Challenges, and Future Perspectives in the Genetic Improvement of Major Oilseed Crops: A Critical Narrative Review

The evidence indicates that breeding has delivered clear gains in adaptation, hybrid performance, oil composition and resistance to selected diseases, but progress is markedly less consistent for complex traits expressed across variable environments.

P. Kumari, Deep Shikha, A. Jha et al. · 0 citations
Review Open access Aug 2026

Mutation Breeding as a Tool for Sustainable Crop Production and Climate Resilience: Experiences from the South-Eastern Europe (SEE) and Central Asia (CA)

The review summarizes practical experiences in using mutation breeding for crop improvement in South-Eastern Europe (SEE) and Central Asia (CA), demonstrating that mutation breeding can be a field-validated, effective approach for developing climate-resilient crops. Drawing on coordinated research conducted within national breeding programs and international initiatives supported by FAO/IAEA, applied methodologies, trait-evaluation strategies, and concrete breeding outputs in cereals, legumes, and industrial crops are presented. The use of gamma irradiation, fast neutrons, and chemical mutagens has successfully generated stable mutant lines stable mutant lines with enhanced traits, such as increased thousand-grain weight in wheat, altered oil quality in sunflower, and improved drought tolerance in common bean and sesame. The integration of classical pedigree selection with modern breeding tools such as high-throughput phenotyping, molecular and biochemical markers, and doubled-haploid technology has enabled earlier and more efficient identification of superior genotypes in mutation breeding programs. The review underscores the practical relevance of mutation breeding in contemporary pipelines to maintain yield stability and quality under adverse environmental conditions.

Sandra Cvejić, Aleksandra Radanović, D. Trkulja et al. · 0 citations
Open access Aug 2026

Bioinformatics in crop research: using genomic data for crop improvement

By combining genomic data with precision breeding techniques, researchers are developing crops that are better adapted to a growing population and a changing climate, positioning the integration of molecular breeding and bioinformatics as a central pillar of future global food security.

Muhammad Shahid Iqbal, Z. Sarfraz, Muhammad Mujahid et al. · 0 citations