Jul 2026· International Journal of Innovative Science and Research Technology· pp. 3201· 0 citations· 54 references
TL;DR
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.
Abstract
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.
As climate change intensifies abiotic and biotic stresses, expanding the genetic base of cultivated chickpea (Cicer arietinum) is crucial for sustaining global pulse production. Modern chickpea cultivars have a narrow genetic base, restricting genetic gain especially for adaptation to environmental stresses, soil constraints and disease resistance. The wild Cicer species, particularly Cicer reticulatum and Cicer echinospermum, represent valuable reservoirs of genetic diversity for the improvement of existing chickpea cultivars, but their potential has not been fully exploited. Here, we evaluated genome-wide diversity and population structure in 317 Cicer accessions, comprising C. reticulatum (234), C. echinospermum (68) and C. arietinum (15), using 5792 high-confidence DArTseq SNP and 4628 SilicoDArT markers. We observed moderate polymorphic information content values, ranging from 0.25 (DArTseq SNPs) to 0.30 (SilicoDArT), indicating a medium level of informativeness and demonstrating that both marker systems are appropriate for diversity analysis for identifying useful variation for chickpea breeding. Genetic diversity indices revealed high diversity in C. reticulatum accessions. Analysis of molecular variance indicated that most molecular variation occurred within species rather than among species, indicating substantial intraspecific variation that can be exploited in chickpea breeding programs. Principal coordinates and neighbour-joining analyses resolved clear clustering at the species-level, confirming close genetic relationships between C. arietinum and C. reticulatum. The probability of identity-by-descent analysis and genome-wide linkage disequilibrium revealed extensive diversity in C. reticulatum compared to C. arietinum and C. echinospermum. Overall, this study establishes that high allelic diversity present in C. reticulatum accessions can be accessed for cultivated chickpea improvement.
Edward Asare, R. Raman, Peter R. Ryan et al.· Genetic Resources and Crop E...· 0 citations
Elucidating the evolutionary trajectories and genetic basis of critical agronomic traits in regional rice germplasm is paramount for discovering elite allelic variations for crop improvement. Here, we systematically characterized a panel of 109 rice accessions from Zhejiang Province through whole-genome resequencing (~10× coverage) coupled with two years of rigorous field phenotypic evaluations. A total of 4,753,071 high-quality genomic variants, including 4,147,316 SNPs, were identified across the genome. Population structure and evolutionary analyses revealed sharp genetic differentiation at the subspecies level, partitioning the panel into distinct indica and japonica clusters accompanied by intricate subpopulation stratification and historical gene flow. Through a joint scanning of the fixation index (Fst) and nucleotide diversity (Pi) ratios, three prominent selective sweep regions (qSS1, qSS10, and qSS12) driving subspecific differentiation were captured on chromosomes 1, 10, and 12. Notably, the qSS12 locus harbors the sucrose transporter gene OsSUT2, indicating that carbohydrate transport and energy metabolism served as core genomic targets driving the indica–japonica divergence. Furthermore, genome-wide association studies (GWAS) successfully mapped 9 significant loci modulating heading date, effective tiller number, and grain size. Subsequent gene-based haplotype analyses within these target intervals pinpointed elite allelic variations in core candidate genes, including OsSPX1 (phosphate homeostasis, 1000-grain weight), Chl9 (chlorophyll synthesis, grain width), and OsCER1 (wax biosynthesis, panicle length). Collectively, this study deciphers the genomic landscape and subspecies differentiation patterns of Zhejiang rice germplasm, providing pivotal molecular targets and invaluable genomic resources for germplasm conservation and precision molecular breeding.
Yang Lv, Hao Wu, M. Asad et al.· Plants· 0 citations
Alfalfa (Medicago sativa L.) is a globally cultivated perennial forage legume whose productivity is increasingly constrained by climate-induced stresses, yet its autotetraploid genome, self-incompatibility, and 8–12-year breeding cycles impede rapid cultivar development. This review critically evaluates the transition from conventional phenotypic selection to data-driven breeding strategies, examining genomic selection (GS), genome-wide association studies (GWAS), multi-omics integration, CRISPR/Cas9 genome editing, and high-throughput phenotyping (HTP) within the context of polyploid crop improvement. We demonstrate that GS offers the most practical near-term path for polygenic trait improvement, with prediction accuracies enhanced through marker importance weighting and genotype-by-environment covariance modeling, while GWAS and pan-genome analyses, including structural variant incorporation improving GS accuracy, enable high-resolution trait dissection. Multi-omics integration shows greatest utility for oligogenic traits with moderate-to-high heritability, whereas CRISPR/Cas9 has enabled functional validation of key loci but faces transformation bottlenecks and regulatory barriers precluding commercial deployment. HTP platforms coupled with machine learning provide scalable phenotyping, though standardization gaps and infrastructure costs persist. We propose an integrated digital breeding pipeline connecting trait discovery through cultivar deployment, supported by community reference resources and actionable breeding recommendations including rapid-cycle GS and sparse testing designs. This framework positions alfalfa breeding for systematic translation of molecular discovery into climate-resilient, high-yielding cultivars.
Muhammad Abu Bakar Ghalib, Ayesha Khawar, M. Ramzan et al.· Discover Plants· 0 citations
Egyptian cotton, derived primarily from Gossypium barbadense L., has shaped the country’s agricultural economy and international reputation for nearly two centuries. Among these, the Giza varieties—renowned for their exceptional fiber length, fineness, and strength—have garnered global recognition and made substantial contributions to export revenues and rural livelihoods. This review systematically analyzes more than 120 scientific publications from the past 30 years. It synthesizes research advances in Egypt, focusing on germplasm resources, fiber anatomical characteristics, variety improvement, and the integration of molecular and biotechnological tools. Progress in molecular markers, quantitative trait locus (QTL) mapping, and genome-wide association studies (GWAS) is highlighted for its role in dissecting traits related to fiber quality and stress tolerance. Experimental transformation studies and functional genomics have provided proof-of-concept for genes involved in insect resistance and fiber development. At the same time, genome editing—particularly clustered regularly interspaced short palindromic repeats/CRISPR-associated protein (CRISPR/Cas) systems—represents an emerging frontier for precise trait improvement in G. barbadense. Molecular markers have been used to assess genetic diversity within Egyptian cotton germplasm, enabling the development of unique varietal fingerprints and guiding breeding programs to improve yield, quality, and stress resilience. Techniques such as QTL mapping and GWAS facilitate the identification of genomic regions underlying key traits, thereby establishing a foundation for marker-assisted selection. Specific Egyptian varieties—including Giza 94 (a heat-tolerant variety), Giza 95 (a drought-tolerant variety), and Giza 90/Giza 97 (salinity-tolerant varieties)—have demonstrated measurable stress resilience in controlled and field trials. However, formal release designations for these traits remain lacking. Concurrently, functional genomics approaches have enabled the characterization of genes involved in fiber development in Egyptian cotton. Furthermore, biotechnological innovations—including experimental Bt-transformation and the emerging precision of CRISPR/Cas genome editing—offer promising pathways to introduce adaptive traits more efficiently.
Ibrahim A. A. Mohamed, Usama Abdel Hameid Abdel Razek, Junjuan Wang et al.· Journal of Cotton Research· 0 citations
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.
Long Chen, Shujuan Li, Xiaoyu Wang et al.· Journal of Cotton Research· 0 citations
The integration of molecular markers into agricultural biotechnology has fundamentally transformed crop breeding paradigms, particularly concerning disease-resistance screening and the identification of complex agronomic traits. Global agricultural systems face unprecedented challenges from biotic stressors, shifting climatic patterns, and the continuous evolution of pathogenic microorganisms, thereby necessitating the rapid development of resilient crop varieties. This paper provides a comprehensive analysis of the methodological, theoretical, and practical frameworks underlying molecular-marker applications in modern plant breeding. By exploring the historical evolution from classical phenotypic selection to advanced genomics-assisted breeding, the discussion elucidates the mechanisms through which single nucleotide polymorphisms and simple sequence repeats facilitate the precise localization of quantitative trait loci. Furthermore, the paper details the analytical pipelines required for high-throughput genotyping, marker-assisted selection, and genome-wide association studies, highlighting their respective impacts on selection efficiency and cost reduction in crop improvement programs. An evaluation of contemporary empirical data reveals that integrating multi-omic approaches with established molecular markers significantly enhances the accuracy of predicting disease resistance across diverse agricultural panels. Ultimately, this research synthesizes current technological advancements and methodological constraints, offering a thorough perspective on how molecular biotechnology can be optimized to ensure future global food security.
Eva Jansen· International Journal of Com...· 0 citations