Egyptian cotton: harnessing genetic diversity, molecular tools, fiber anatomy, and innovation for a climate-smart future

Molecular Markers Associated with Genetic Diversity, Stress Tolerance, and Breeding Traits in Theobroma cacao: A Review

Global chocolate production depends entirely on Theobroma cacao, a perennial tree crop severely bottlenecked by an extended juvenile phase, extreme heterozygosity, and accelerating climate and pathogen pressures. Because conventional phenotypic selection cannot keep pace with rapidly compounding ecological threats, molecular breeding has transitioned from an exploratory tool to an absolute necessity for crop survival. This review critically evaluates the evolutionary trajectory, real-world deployment, and functional breakthroughs of diverse molecular marker systems designed to accelerate cacao genetic improvement. We trace the technological paradigm shift from legacy marker configurations (RAPD, RFLP, AFLP)—which established foundational germplasm architecture among Criollo, Forastero, and Trinitario groups—to ultra-precise, co-dominant platforms (SSR, SNP, cpSSR). Beyond mere identification, our synthesis of major findings highlights how these advanced markers have successfully decoupled target agronomic traits from environmental noise. We detail verified loci mapped via quantitative trait loci (QTL) analysis and genome-wide association studies (GWAS) that govern crucial abiotic stress adaptations (drought, waterlogging, oxidative stress) and destructive disease resistance profiles (black pod, frosty pod rot, witches' broom, and viral or insect vectors). Furthermore, the integration of these genetic resources with advanced tissue culture and micropropagation protocols is evaluated as a vehicle to ensure high-fidelity clonal multiplication of elite genotypes. Looking forward, we map critical future prospects where high-density SNP genotyping, comparative transcriptomics, and genomic selection models converge directly with CRISPR/Cas-mediated genome editing systems. This comprehensive review demonstrates that shifting from reactive field evaluation to marker-driven, genomics-assisted precision design provides the definitive molecular framework required to engineer high-yielding, climate-resilient, and disease-proof cacao cultivars, thereby permanently safeguarding the long-term economic sustainability of global cocoa supply chains.

Genetic architecture of Karnal bunt resistance in wheat: A review

Genetic diversity of Camelina sativa: implications for sustainable crop improvement through Genotyping-by-Sequencing (GBS).

BACKGROUND Camelina sativa, an oilseed crop from the Brassicaceae family, has gained attention over the past two decades due to its resilience to harsh environments, short growth cycle, low input needs, and high omega-3 fatty acid content. These traits make it a promising candidate for industrial and bio-based applications, including edible and industrial oils, biofuels, and soil enhancement. This study aimed to identify and genotype SNPs on a genome-wide scale to assess genetic diversity and population structure for breeding programs and conservation efforts. RESULTS Using Genotyping-by-Sequencing (GBS) technology, we investigated 86 C. sativa doubled haploid lines from 15 crosses, mapping 5,872 high-quality SNP markers across the genome. Population structure analysis revealed two main subpopulations, with evidence of genetic exchange likely influenced by geographic factors and human activity. AMOVA results indicated that 90% of variation occurred within subpopulations, with a low Fst value (0.096) suggesting high gene flow (Nm = 2.343). Hierarchical cluster analysis (HCA) based on genetic distances grouped the lines into two main clusters, each further subdivided into two distinct subgroups, highlighting the existence of a well-defined genetic structure within the population. CONCLUSIONS These findings confirm low genetic diversity within C. sativa populations, which has significant implications for breeding strategies aimed at improving yield and resilience in industrial applications. This research provides crucial insights for future genetic studies and breeding efforts in Camelina, particularly regarding genome-wide association studies (GWAS) and marker-assisted selection (MAS) to enhance genetic gains.

From Gene to Bloom: Unlocking Ornamental Plant Potential Through Genomic Technologies

Ornamental plants represent an economically and culturally important component of horticulture, yet their improvement has historically relied mainly on phenotypic selection with limited mechanistic understanding. This review synthesises how genomic technologies are expanding knowledge of ornamental plant biology and supporting breeding practice. It considers reference genome resources for major ornamental taxa, including rose, chrysanthemum, petunia, orchid, carnation, and morning glory, and examines how these resources clarify the genetic and regulatory basis of commercially important traits. Particular attention is given to floral colour, form, fragrance, post-harvest longevity, and stress-related adaptation, with emphasis on anthocyanin, carotenoid, phenylpropanoid, MADS-box, and ethylene-related pathways. The review also evaluates transcriptomics, epigenomics, molecular markers, linkage mapping, genome-wide association studies, marker-assisted selection, genomic selection, transgenic approaches, RNA interference, and CRISPR-Cas9-based gene editing. These tools have improved trait discovery and created opportunities for more targeted cultivar development, although their translation remains uneven across genera. Persistent constraints include polyploid genome complexity, large and repetitive genomes, limited transformation and regeneration systems, multigenic trait architecture, fragmented regulatory frameworks, and insufficient genomic resources for several commercially important ornamentals. The review concludes that genomic technologies can strengthen ornamental breeding when supported by reliable phenotyping, validated trait associations, appropriate regulatory pathways, and sustained collaboration between research and commercial breeding sectors.

Unraveling the complexity of the oilseed rape genome: from sequencing to gene discovery for trait improvement

Oilseed rape (Brassica napus) serves as a cornerstone of global vegetable oil production, yet its genetic improvement has historically been impeded by a complex allopolyploid genome. This review synthesizes the transformative evolution of rapeseed genomics, traversing from initial fragmented references to the modern era of gap-free Telomere-to-Telomere (T2T) assemblies and graph-based pan-genomes. We highlight how these advanced resources resolve previously inaccessible repetitive regions and centromeres, revealing how structural variations (SVs) and homoeologous exchanges (HEs) drive key adaptive traits and morphotype diversification. Furthermore, we examine the integration of large-scale resequencing with sophisticated multi-omics pipelines to bridge the gap between statistical associations and biological causality. Through case studies, such as the characterization of BnRRF for seed weight and BnA09MYB47a for seed coloration, we illustrate the power of combining transcriptomics with Clustered Regularly Interspaced Short Palindromic Repeats-associated Protein 9 (CRISPR-Cas9) for functional validation. Finally, we explore the frontier of “Genomic Design,” where Artificial Intelligence (AI) algorithms like Target-Oriented Prioritization (TOP), combined with Speed Breeding 2.0 protocols, promise to accelerate the development of next-generation cultivars. This synthesis underscores the pivotal shift from descriptive genomics to the precision engineering of climate-resilient, high-yielding polyploid crops.

Advancing cotton improvement: a review of functional gene mining through molecular markers, GWAS, and map-based cloning

The production of cotton (Gossypium spp.) faces significant challenges, including stagnating yields, climate change, and both biotic and abiotic stresses, while conventional breeding remains time-consuming and inefficient. This review summarizes recent advances in functional gene mining using molecular markers, genome-wide association studies (GWAS), and map-based cloning. Map-based cloning has facilitated the identification of key genes that control petal color (GaPC, GhTT19), brown fiber (GhTT2-3A), and fiber quality (GH_D02G2269, qFL-chr1). GWAS has revealed hundreds of loci linked to fiber yield, quality, and stress tolerance, including the identification of GhMYB_D13 for fiber length, GhBRH1_A12 for boll weight, and GhAMT2 for Verticillium wilt resistance. The combination of high-throughput genotyping with association mapping has accelerated marker-assisted selection and the introgression of superior alleles from wild germplasm. These technologies collectively address key limitations of traditional breeding and provide direct targets for genetic improvement. The future integration of multi-omics data with artificial intelligence (Breeding 5.0) promises to further revolutionize cotton breeding, enabling the development of high-yielding, climate-resilient varieties for a sustainable textile industry.