Precision breeding strategy to enrich iron and zinc in rice

Key messageSequence-based AI models show great potential for prediction of variant effects at high resolution, but their practical value in plant breeding remains to be confirmed through rigorous validation studies.Plant breeding has traditionally relied on phenotyping to select individuals with desirable traits—a process that is both costly and time-consuming. Increasingly, breeding strategies are shifting toward precision breeding, where causal variants are directly targeted based on their effects. To predict the effects of causal variants, in silico methods are emerging as efficient alternatives or complements to mutagenesis screens. Here, we review state-of-the-art machine learning methods for predicting variant effects in plants across both coding and noncoding regions, contrasting supervised approaches in functional genomics with unsupervised methods in comparative genomics. We discuss challenges in validating predictions, and compare these methods with traditional association and comparative genomics techniques. We argue that modern sequence models extend traditional methods by generalizing across genomic contexts, fitting a unified model across loci rather than a separate model for each locus. In doing so, they address inherent limitations of traditional quantitative and evolutionary comparative genetics techniques. However, the accuracy and generalizability of sequence models heavily depend on the training data, highlighting the need for validation experiments. We point to successful applications of sequence models, especially with protein sequences, and identify areas for further improvement, especially in modeling regulatory sequences. While not yet mature for in silico-driven precision breeding, sequence models show strong potential to become an integral part of the breeder’s toolbox.

Climate change threatens global livestock production through rising temperatures, erratic rainfall, and extreme events. Enhancing livestock system resilience is now a strategic priority for adaptation practitioners, policymakers, researchers, and other stakeholders committed to food security and rural livelihood sustainability. Although research on livestock adaptation is expanding, a comprehensive synthesis of its thematic evolution, performance, and knowledge gaps remains limited. This study addresses this gap through a bibliometric analysis of 3,217 publications from 1994 to 2023, retrieved from the Scopus database. Analytical tools such as Biblioshiny and VOSviewer were used for data processing and visualization. Findings reveal a consistent growth in research output, particularly post-2007, with the United States, China, and France emerging as leading contributors. Prominent authors include Sejian V., Wang X., and Li Y., while influential journals comprise Agricultural Systems, Journal of Animal Science, and Tropical Animal Health and Production. Thematic trends indicate a shift from early physiological studies (1994–2003) toward genetic diversity and adaptive traits (2004–2013), and more recently (2014–2023), a focus on heat stress, methane emissions, and sustainable breeding. The current research landscape emphasizes genetic adaptation, precision breeding, and climate mitigation strategies. Future studies should deepen the exploration of methane mitigation through genetic selection and feed innovations, while integrating indigenous knowledge and interdisciplinary approaches. Policy support and sustainable management practices will be critical to ensuring the long-term viability of livestock systems under a changing climate.

Pearl millet (Pennisetum glaucum [L.] R. Br.) is a drought-resilient and nutritious staple food crop widely cultivated in arid and semi-arid regions. Worldwide, pearl millet is ranked the 6th most widely produced cereal crop after wheat, rice, maize, barley, and sorghum, with a total production of 30.5 million tons on 32.1 million hectares. In Burkina Faso, it is the 3rd widely cultivated crop next to sorghum and maize, with a mean yield of 0.8 ton ha−1, far below the potential yield of 3.0 tons ha−1 attributable to various production challenges. Among the production constraints, the parasitic weed Striga species, particularly S. hermonthica is endemic and causes up to 80% yield losses under heavy infestation. Different control methods (e.g., cultural practices, chemicals and bio-herbicides) have been recommended, but they have been largely ineffective due to diverse and complex problems, including the life cycle, seed production, and prolonged seed dormancy of S. hermonthica; poor access and cost of implementation. Breeding for host plant resistance presents a cost-effective, environmentally friendly and affordable method for smallholder farmers to control and reduce Striga infestations and improve pearl millet yields. Therefore, the objectives of this study were to present the impact of S. hermonthica damage on pearl millet production and productivity and assess the effectiveness of different management methods of S. hermonthica with an emphasis on host plant resistance. The first section of the review assesses the impact of Striga infestation on pearl millet production, followed by the developmental stages of Striga, Striga infestation and damage management strategies, breeding for Striga resistance and other Striga control methods. The paper summarises genetic resources, new breeding technologies, and innovations for the precision and speed breeding of Striga-resistant cultivars. The review will guide the use of the best breeding strategies and accelerate the breeding of new pearl millet cultivars that are best-performing and resistant to S. hermonthica to reduce damage incurred by Striga infestations on farmers’ fields in Burkina Faso and related agro-ecologies.

This review explores the integration of wild grass-derived alleles into modern bread wheat breeding to tackle the challenges of climate change and increasing food demand. With a focus on synthetic hexaploid wheat, this review highlights the potential of genetic variability in wheat wild relatives, particularly Aegilops tauschii, for improving resilience to multifactorial stresses like drought, heat, and salinity. The evolutionary journey of wheat (Triticum spp.) from diploid to hexaploid species is examined, revealing significant genetic contributions from wild grasses. We also emphasize the importance of understanding incomplete lineage sorting in the genomic evolution of wheat. Grasping this information is crucial as it can guide breeders in selecting the appropriate alleles from the gene pool of wild relatives to incorporate into modern wheat varieties. This approach improves the precision of phylogenetic relationships and increases the overall effectiveness of breeding strategies. This review also addresses the challenges in utilizing the wheat wild genetic resources, such as the linkage drag and cross-compatibility issues. Finally, we culminate the review with future perspectives, advocating for a combined approach of high-throughput phenotyping tools and advanced genomic techniques to comprehensively understand the genetic and regulatory architectures of wheat under stress conditions, paving the way for more precise and efficient breeding strategies.

Pearl millet (Pennisetum glaucum R. Br.) is an important staple and nutritious food crop in the semiarid and arid ecologies of South Asia (SA) and Sub-Saharan Africa (SSA). In view of climate change, depleting water resources, and widespread malnutrition, there is a need to accelerate the rate of genetic gains in pearl millet productivity. This review discusses past strategies and future approaches to accelerate genetic gains to meet future demand. Pearl millet breeding in India has historically evolved very comprehensively from open-pollinated varieties development to hybrid breeding. Availability of stable cytoplasmic male sterility system with adequate restorers and strategic use of genetic resources from India and SSA laid the strong foundation of hybrid breeding. Genetic and cytoplasmic diversification of hybrid parental lines, periodic replacement of hybrids, and breeding disease-resistant and stress-tolerant cultivars have been areas of very high priority. As a result, an annual yield increase of 4% has been realized in the last three decades. There is considerable scope to further accelerate the efforts on hybrid breeding for drought-prone areas in SA and SSA. Heterotic grouping of hybrid parental lines is essential to sustain long-term genetic gains. Time is now ripe for mainstreaming of the nutritional traits improvement in pearl millet breeding programs. New opportunities are emerging to improve the efficiency and precision of breeding. Development and application of high-throughput genomic tools, speed breeding, and precision phenotyping protocols need to be intensified to exploit a huge wealth of native genetic variation available in pearl millet to accelerate the genetic gains.

Aroma is an important characteristic of apples, contributing significantly to fruit flavor and consumer acceptance. The aroma profile in apple fruits results from the interaction of multiple volatiles, including esters, alcohols, aldehydes, terpenoids, and others, which are mainly derived from the fatty acid, amino acid, terpenoid, and phenylpropanoid metabolic pathways. With progress in omics technologies, it is of practical significance to uncover the biosynthetic pathway and regulatory mechanism underlying the formation of volatiles, not only for elucidating the apple molecular mechanisms underlying key genetic pathways and in advancing the development of novel apple varieties with optimized fragrance profiles through precision breeding techniques. In this review, the aroma composition in apple fruits and the biosynthesis pathways for volatile formation are summarized. Furthermore, the breeding strategies with molecular techniques and the regulation measures about application engineering on apple aroma are also discussed. This review provides valuable insights for the improvement of apple aroma quality in the future.

Lentil is an important cool season pulse crops and it is cultivated world-wide in diverse agro ecological conditions. Several varieties have been developed adopting conventional breeding methodologies. Significant progress in genetic improvement for yield has been made by using different breeding strategies including molecular marker based precise breeding strategy in lentil. However, lentil production and productivity has not increased to its potential due to several biotic and abiotic stresses affect its growth and development. Utilization of wild species may provide useful genes for broadening the genetic base of lentil in respect of disease resistance, abiotic stresses and desirable agronomic traits. In present article, we have reviewed the breeding strategies used for improving lentil genotypes adapted under diverse agro-climatic conditions.

Watermelon [Citrullus lanatus (Thunb.) Matsum. & Nakai] is a globally important vegetable crop valued for its taste, hydration, and nutritional benefits. Recent advances in multi-omics technologies have accelerated the identification of genes controlling key fruit metabolites that impact fruit quality traits such as sweetness, bitterness, sourness, aroma, texture, and color. This review synthesizes the current knowledge on watermelon genes regulating and transporting fruit metabolites, including sugars, cucurbitacin, organic acids, carotenoids, amino acids, flavonoids, and volatile organic compounds that impact fruit quality. Both forward and reverse genetics approaches, coupled with high-throughput phenotyping, have been instrumental in these gene discoveries. Breeding applications, including marker-assisted selection (MAS) and genomic selection (GS), are highlighted, emphasizing their potential to enhance fruit metabolites that improve fruit quality and nutritional value. Emerging technologies, such as CRISPR/Cas9-mediated gene editing, have been employed to uncover and validate CIVST1, PSY1, and PEPCK genes, enabling precision breeding for improved fruit metabolite profile. However, challenges persist due to the environmental sensitivity and polygenic nature of fruit metabolites, the narrow genetic base, and the limited adoption of molecular breeding methods like CRISPR/Cas9. Future directions emphasize leveraging wild germplasm, integrating AI-driven phenotyping, and applying precision breeding strategies. These approaches will enable the development of next-generation watermelon cultivars with improved multi-trait quality and nutritional profiles to meet evolving market demands.

Rapeseed and mustard are important oilseed crops cultivated worldwide for their high oil content and versatile applications in food, feed, and industrial sectors. The quality of oil derived from these crops is influenced by various genetic, environmental, and agronomic factors. Breeding efforts aimed at improving oil quality traits in rapeseed and mustard have garnered significant attention in recent years due to their impact on market value, nutritional attributes, and industrial utility. In this review, we provide a comprehensive overview of breeding strategies and methodologies employed to enhance oil quality traits in rapeseed and mustard. We explore the genetic basis of oil quality traits, including fatty acid composition, erucic acid content, glucosinolate content, and tocopherol content, and discuss the importance of these traits for different end-uses. Furthermore, we highlight the role of molecular markers, genomics-assisted breeding, and biotechnological approaches in accelerating the breeding process and achieving targeted improvements in oil quality. The review also addresses the challenges and constraints associated with breeding for oil quality in rapeseed and mustard, including genotype-environment interactions, trait stability, and regulatory considerations. Additionally, we discuss emerging trends and future prospects in oil quality breeding, such as genome editing, metabolic engineering, and precision breeding, which offer novel avenues for achieving desired oil quality profiles while addressing sustainability and consumer preferences. Overall, this review underscores the significance of breeding for oil quality in rapeseed and mustard and provides insights into the latest advancements, challenges, and opportunities in this field. By integrating multidisciplinary approaches and harnessing the power of modern breeding tools and technologies, rapeseed and mustard breeders can continue to drive innovation and deliver oilseed crops with enhanced nutritional value, functional properties, and market competitiveness.

Environmental challenges such as drought, salinity, heavy metal contamination, and nutrient deficiencies threaten global agricultural productivity and food security. These stressors drastically reduce crop yields, necessitating innovative solutions. Recent advancements in omics-based research-spanning genomics, metabolomics, proteomics, transcriptomics, epigenomics, and phenomics-have transformed our understanding of plant stress responses at the molecular level. High-throughput sequencing, mass spectrometry, and computational biology have facilitated the identification of stress-responsive genes, proteins, and metabolites critical for enhancing plant resilience. This review evaluates omics-driven strategies for improving crop performance under environmental stress. It emphasizes multi-omics data integration, precision breeding, artificial intelligence (AI) in crop modeling, and genome-editing technologies. Notably, breakthroughs in machine learning and AI have refined predictive modeling, enabling precise selection of stress-tolerant traits and optimizing breeding strategies. Despite these advancements, challenges remain, including the complexity of multi-omics data analysis, high technology costs, and regulatory barriers. Bridging the gap between research and practical applications requires developing cost-effective platforms, enhancing AI-driven models, and conducting large-scale field validations. This review highlights the transformative potential of omics technologies to develop climate-resilient crops. By integrating these advanced methodologies, agriculture can achieve sustainable food production and bolster global food security in the face of climate change and environmental stressors.

Improving rice salt tolerance by precision breeding in a new era

MicroRNAs (miRNAs) are small non-coding RNA molecules that play a central role in the post-transcriptional regulation of gene expression. They are essential regulators of key physiological processes in animals, including development, immunity, metabolism, and reproduction, thereby maintaining cellular homeostasis. In recent years, miRNA research in livestock has advanced rapidly, revealing that these molecules are not only fundamental biological regulators but also hold significant practical potential for applications such as monitoring reproductive performance, enhancing heat-stress tolerance, and enabling early detection of metabolic disorders. This review provides a comprehensive and comparative overview of recent miRNA studies conducted in major livestock species, including cattle, sheep, goats, chickens, and honey bees, highlighting species-specific regulatory patterns, molecular mechanisms, and emerging biotechnological applications. The reviewed evidence demonstrates that miRNA expression profiles vary across developmental stages, physiological conditions, and tissue types, offering valuable insights for the development of diagnostic biomarkers, molecular breeding strategies, and production optimization tools. However, the majority of existing studies remain focused on expression profiling, while the functional validation of miRNA-mRNA interactions is still underrepresented. As a result, many conclusions regarding miRNA function are limited to bioinformatic predictions rather than experimental verification. This review critically evaluates these methodological limitations and outlines future perspectives within the frameworks of functional genomics, systems biology, and molecular breeding. In conclusion, a deeper understanding of miRNA-mediated regulatory networks will not only advance fundamental biological knowledge but also drive practical innovations in sustainable livestock production, precision breeding, and animal health management.

Bean crops can be displaced to marginal areas or face abiotic stresses such as water deficit. Physiological responses allow the identification of tolerant genotypes and lead to more precise breeding strategies. The objective of this research was to evaluate the physiological (leaf gas exchange properties, leaf water content, and leaf thickness) and biochemical [proline and malondialdehyde (MDA)] responses of five common bush bean ( Phaseolus vulgaris L.) cultivars (ICA-Cerinza, ICA-Bachue, NUA35, Bianca, and Bacatá) under a water shortage period by irrigation suspension (15 days) at two different phenological stages [vegetative: 40–55 days after seed emergence (DAE) or reproductive: (50–65 DAE)]. A completely randomized block design was carried out with a factorial arrangement (the phenological stage as the main factor and the cultivars as the secondary factor) for a total of 10 treatments with four repetitions per treatment. Leaf photosynthesis ( P n ) showed equal photosynthesis values in control plants of all cultivars (≈20 μmol·m −2 ·s −1 ). The water deficit period reduced P n close to 55% (≈12 μmol·m −2 ·s −1 ) at both, vegetative, or reproductive stage in all cases. Similar results were also observed on leaf thickness, with a reduction of ≈10% in water-stressed plants at either vegetative or reproductive stage in all evaluated cultivars. A higher MDA and proline production were observed in plants affected by a 15-day water deficit period, mainly at the vegetative stage. The obtained results suggest that the vegetative stage presented a more negative impact on the evaluated physiological variables in most of the cultivars used. Cultivar Bachue showed lower gas exchange properties affectation and higher proline content, which may indicate that this cultivar can be tolerant to water deficit stress conditions. This study allows suggesting that proline and MDA estimation are simple, fast, and low-cost techniques to screen cultivars to obtain more precise breeding selection in common bean. Finally, common bean cultivar selection through the use of biochemical markers can be complemented by the estimation of leaf gas exchange parameters at different phenological stages.

Simple SummaryImproving beef quality in Hanwoo cattle requires a comprehensive understanding of the genetic regulation of fat accumulation in adipose tissue. In this study, we performed expression quantitative trait loci (eQTL) analysis using RNA-Seq data from backfat tissue of Hanwoo steers to identify regulatory variants influencing gene expression. We identified 5362 significant cis-eQTLs, including key genes associated with muscle development and fat accumulation. Several genomic loci were found to act as regulatory hotspots, controlling the expression of multiple genes. Notably, a variant at chromosome 21:17035557 emerged as a major hub where both cis- and trans-regulatory signals converge. These findings provide valuable insights into the regulatory architecture of adipose tissue in Hanwoo and offer molecular targets for precision breeding strategies aimed at enhancing meat quality.Understanding the genetic regulatory mechanisms of fat accumulation is crucial for improving beef quality. Hanwoo (Korean native cattle) is renowned for its high intramuscular fat (marbling), yet the genetic regulation of adipose gene expression remains insufficiently understood. In this study, we performed expression quantitative trait loci (eQTL) analysis using RNA-Seq data and genotype data from backfat tissue of 75 Hanwoo steers to identify regulatory variants associated with adipose deposition. A total of 25,042 significant cis-eQTL associations (FDR < 0.05) were identified, and 5362 unique top cis-eQTL pairs were retained after gene-wise filtering. Key cis-regulated genes included AGBL1, CACNG1, MYO18B, and DUSP29, which are involved in cytoskeletal organization, muscle development and calcium signaling. Three major cis-regulatory hotspots were located on BTA15 (BTA15:50354741) and BTA21 (BTA21:21526143, and BTA21:21541921). Permutation-based analysis (100,000 iterations) was conducted to control false positives, identifying 12 statistically significant trans-eQTL hotspots (FDR q < 0.05), of which SNP 6:60512276 and SNP 21:17035557 exhibited extensive trans-regulatory activity influencing 429 and 161 genes, respectively. In particular, SNP 21:17035557 acted as a shared cis- and trans-regulatory hub, indicating hierarchical control of adipose gene networks. Functional enrichment analyses revealed significant involvement of cytoskeleton- and calcium-dependent pathways, highlighting the interplay between structural remodeling and metabolic regulation in adipose tissue. These findings provide a comprehensive, system-level view of adipose gene regulation in Hanwoo cattle and highlight candidate molecular targets for genome-assisted and precision breeding. Moreover, this study offers quantitative genomic resources that can support the development of prediction models and decision-support systems for improving carcass traits in Hanwoo breeding programs.

Sugarcane (Saccharum spp. hybrids) is a major feedstock for commercial bioethanol production. The recent integration of conversion technologies that utilize lignocellulosic sugarcane residues as well as sucrose from stem internodes has elevated bioethanol yields. RNAi suppression of lignin biosynthetic enzymes is a successful strategy to improve the saccharification of lignocellulosic biomass. 4-coumarate:coenzyme A ligase (4CL) is a key enzyme in the biosynthesis of phenylpropanoid metabolites, such as lignin and flavonoids. Identifying a major 4CL involved in lignin biosynthesis among multiple isoforms with functional divergence is key to manipulate lignin biosynthesis. In this study, two full length 4CL genes (Sh4CL1 and Sh4CL2) were isolated and characterized in sugarcane. Phylogenetic, expression and RNA interference (RNAi) analysis confirmed that Sh4CL1 is a major lignin biosynthetic gene. An intragenic precision breeding strategy may facilitate the regulatory approval of the genetically improved events and was used for RNAi suppression of Sh4CL1. Both, the RNAi inducing cassette and the expression cassette for the mutated ALS selection marker consisted entirely of DNA sequences from sugarcane or the sexually compatible species Sorghum bicolor. Field grown sugarcane with intragenic RNAi suppression of Sh4CL1 resulted in reduction of the total lignin content by up to 16.5 % along with altered monolignol ratios without reduction in biomass yield. Mature, field grown, intragenic sugarcane events displayed 52-76 % improved saccharification efficiency of lignocellulosic biomass compared to wild type (WT) controls. This demonstrates for the first time that an intragenic approach can add significant value to lignocellulosic feedstocks for biofuel and biochemical production.