A systems breeding framework integrating pangenomics multiomics phenomics and precision genome editing for reproductive stage drought resilience in rice

Genomics-Assisted Breeding for Drought Tolerance in Wheat (Triticum aestivum L.): Recent Advances and Future Prospects

Drought is one of the major abiotic limitations to wheat production worldwide, and the impacts of drought are worsened due to climate change. Drought tolerance consists of many genes with complex physiological and molecular processes, along with strong interactions between genotypes and environments; therefore, traditional phenotypic selection has produced minimal improvement to date. In this review we summarize recently published work (2020-2025) on genomics-assisted methods used to develop drought tolerance in bread wheat (8; 2). QTL mapping and marker-assisted backcrossing has allowed for successful validation of drought-related loci and their transfer into elite lines (3; 7). In addition, the coupling of genome-wide association studies with high-throughput phenotyping and genomic selection have improved predictability of grain yield in water-limited environments (5; 11). Overall, transcription factors from the DREB, NAC, MYB, and WRKY families are still considered the primary regulatory targets, but CRISPR/Cas-based gene editing is now able to provide precise, multiplex gene modifications in polyploid wheat (1; 10). The combination of pan-omics (the study of all omes), gene editing, speed breeding, and predictive modelling provides a realistic approach to developing climate-resilient, high-yielding cultivars. However, the rates at which phenotyping can occur and the speed at which candidate loci can be functionally validated are still the rate-limiting steps on this path (4; 6).

Integrated Genome-Wide Association and QTL Mapping Elucidate the Genetic Basis of Fruit Yield and Quality Traits in Pepper under Water Stress.

Water deficit is a major constraint on pepper (Capsicum annuum) yield, yet the genetic architecture of reproductive-stage drought tolerance remains poorly resolved. We phenotyped a Balkan C. annuum diversity panel (n = 133) and an interspecific backcross inbred line (BIL) population (n = 76) under well-watered (WW) and water-stress (WS) conditions. WS was applied from anthesis of the second truss as a stepwise reduction in irrigation volume relative to WW (30% for 7 days, then 60% thereafter), maintained for 90 days across the reproductive period. We assessed yield components, soluble solids, and stress-tolerance (STI) and stress-susceptibility (SSI) indices. Genome-wide association study (GWAS) identified 104 SNP-trait associations (P < 1×10-5), and QTL mapping detected 38 significant QTLs (1,000 permutations, α = 0.01), with the QTL intervals defined at LOD ≥ 8. Integrating GWAS and QTL mapping under WS revealed overlapping loci on chromosomes 5 and 6, harboring two consensus intergenic SNPs associated with yield components and soluble solids. Haplotype analysis linked chromosome 5 alleles to higher fruit number and soluble solids. At chromosome 6, the G allele at SNP 6_28348737 was enriched in tolerant lines for fruit number. These regions harbor candidate genes for reproductive development and stress response, including GREEN RIPE-LIKE1 (GRL1), CYP77A19, Endoglucanase-like, and FLOWERING PROMOTING FACTOR 1 (FPF1), possibly through cis-regulatory variation. Together, these results advance understanding of the genetic basis of pepper yield under drought and identify candidate breeding markers.

Emerging molecular strategies to improve drought tolerance in barley Hordeum vulgare L.)

Genomic Selection Integrated with High-Throughput Phenotyping and Speed Breeding for Smart and Greener Rice (Oryza sativa) Improvement

Background: Rice breeding requires faster development of high-yielding, climate-resilient, resource-efficient, and high-quality cultivars for production systems exposed to environmental variability and increasing input constraints. Genomic selection offers an opportunity to predict breeding value before extensive field evaluation, although its effectiveness depends on the integration of genomic, phenotypic, and environmental information. Methods: This narrative review critically examines recent advances in genomic selection for rice and its integration with high-throughput genotyping, high-throughput phenotyping, machine learning, multi-environment prediction, and speed breeding. Results: Genome-wide marker data can support early ranking of breeding materials for grain yield, grain quality, disease resistance, drought tolerance, salinity tolerance, and nutrient-use efficiency. Prediction performance is influenced by trait architecture, marker density, training-population size, genetic relatedness between training and candidate populations, phenotypic data quality, and genotype-by-environment interaction. Red-green-blue, multispectral, hyperspectral, thermal, and light detection and ranging platforms can generate temporal traits associated with plant architecture, biomass, water status, nutrient status, and stress responses, which may improve prediction under suitable population and validation designs. Speed-breeding systems shorten generation intervals and facilitate rapid advancement, recurrent selection, and recycling of superior parental lines. Conclusions: Integrated breeding pipelines that combine genomic prediction, high-throughput phenotyping, environmental data, and speed breeding can improve selection efficiency and shorten rice improvement cycles. Wider adoption will require affordable technology platforms, standardized data systems, multi-environment validation, breeder capacity development, and collaborative data-sharing frameworks for smart and greener agriculture.

Drought-Resilient Crops for Sustainable Agriculture: Genetic, Physiological, and Agronomic Advances

Drought constitutes one of the most pervasive abiotic constraints limiting global crop productivity, with its frequency and intensity projected to increase substantially under ongoing climate change. This narrative review synthesises contemporary evidence on the genetic, physiological, and agronomic dimensions of drought resilience in major food crops, drawing on peer-reviewed literature published primarily between 2000 and 2026. Physiologically, drought impairs stomatal conductance, suppresses photosynthetic carbon assimilation, disturbs osmotic equilibrium, and restricts root-mediated water acquisition, with reproductive stages being disproportionately vulnerable. At the genetic level, the deployment of quantitative trait loci (QTL) mapping, transcription-factor engineering, CRISPR-Cas9 genome editing, and the overexpression of stress-responsive functional genes has opened novel avenues for enhancing tolerance without compromising yield potential. Breeding programmes have increasingly integrated marker-assisted selection (MAS) and genomic selection to accelerate genetic gain, whilst high-throughput phenotyping platforms now enable rapid assessment of drought-adaptive traits at a population scale. Agronomic strategies, including deficit irrigation, conservation tillage, intercropping, and application of plant growth-promoting rhizobacteria (PGPR), provide complementary levers for sustaining productivity under water-limited conditions. Emerging integrative approaches that combine multi-omics, digital precision agriculture, and policy-enabled climate-smart frameworks are highlighted as critical pathways for translating laboratory and field insights into scalable solutions. The review identifies persistent knowledge gaps—including the limited translation of genomic advances to smallholder contexts and the underexplored potential of microbiome engineering—and calls for a convergence of disciplinary expertise, equitable technology transfer, and coherent policy support to achieve drought-resilient food systems globally.

Multi-Environment Multi-Locus Association Mapping Reveals Genomic Regions for Drought-Related Traits in Tropical Maize.

Maize grain yield is frequently constrained by water scarcity, particularly in tropical regions characterized by irregular rainfall patterns. Dissecting the genetic basis of drought-related traits remains challenging because their expression is strongly influenced by environmental conditions. In this study, we applied a multi-environment multi-locus genome-wide association study (MEML-GWAS) to identify genomic regions associated with drought-related traits in tropical maize. The association panel comprised 190 inbred lines from the Embrapa breeding program, which were genotyped with 500,108 GBS-derived SNPs, and crossed with two tester lines. Phenotypic data corresponded to the performance of the testcross hybrids, divided in Dent and Flint heterotic groups, evaluated across two years at two locations in Brazil under well-watered and water-stressed conditions. Traits analyzed included grain yield, anthesis-silking interval, female and male flowering time, and plant and ear height. Drought stress reduced grain yield by approximately 50% and increased the anthesis-silking interval by about two days. A total of 179 significant SNP-trait associations were detected, of which 166 showed significant SNP-by-environment interaction effects, while 13 displayed stable effects across environments. Several associations were detected specifically under water-stressed conditions, highlighting genomic regions potentially involved in drought adaptation. Functional annotation revealed candidate genes previously implicated in abiotic stress responses, including ZmTIP1, which encodes an S-acyltransferase regulating root hair development and drought tolerance. Among the novel candidate genes, GRMZM2G159125, encoding a phospholipase D, emerged as a particularly promising candidate due to its strong association with grain yield and its role in membrane lipid signaling pathways related to stress responses. Although a few associations overlapped genomic regions previously reported for drought tolerance in maize, most loci represent potentially novel genetic factors that may contribute to improving drought resilience in tropical maize breeding programs.