Leaf antioxidant activity in Colombian elite Hevea brasiliensis genotypes as a breeding strategy for water deficit tolerance under Amazonia conditions.

This study evaluated the foliar antioxidant activity in nine Hevea brasiliensis genotypes from the ECC-1 (Élite Caquetá Colombia) selection and IAN 873 cultivar (control) in trees in the growth stage in two large-scale clonal trials in response to different climatic (semi-humid warm and humid warm sites) and seasonal (dry and rainy periods) conditions in the Colombian Amazon. The results indicated that Reactive Oxygen Species (ROS) production increased under conditions of lower water availability (dry period), leading to lipid peroxidation, high defense of photosynthetic pigments, and development of better osmotic adjustment capacity in the ECC 64, IAN 873, ECC 90, and ECC 35 genotypes due to high concentrations of carotenoids (0.40 mg g-1), reducing sugars (65.83 µg mg-1), and malondialdehyde (MDA) (2.44 nmol ml-1). In contrast, during the rainy period, a post-stress action was observed due to high contents of proline and total sugars (39.43 µg g-1 and 173.03 µg g-1, respectively). At the site level, with high Photosynthetically Active Radiation (PAR) values (1143 moles photons m-2 s-1), temperature (32.11°C), and lower precipitation (135 mm), higher antioxidant activity (chlorophylls a, b and total, carotenoids, and proline) was recorded at the humid warm site, demonstrating that the ECC 90, ECC 64, and ECC 66 genotypes are tolerant to water deficit compared to IAN 873. The ECC 64 genotype, independent of seasonal changes and site conditions, presented the highest contents in Chl a, total Chl, reducing sugars, total sugars, and MDA, showing a tendency to adapt to fluctuating conditions. This study showed that water fluctuations do not cause the same metabolic responses, these vary within the same species, depending on their developmental stage and the climatic and seasonal variations characteristic of the Colombian Amazon.

QTL Mapping of Fiber- and Seed-Related Traits in Chromosome Segment Substitution Lines Derived from Gossypium hirsutum × Gossypium darwinii.

A narrow genetic basis limits further the improvement of modern Gossypium hirsutum cultivar. The abundant genetic diversity of wild species provides available resources to solve this dilemma. In the present study, a chromosome segment substitution line (CSSL) population including 553 individuals was established using G. darwinii accession 5-7 as the donor parent and G. hirsutum cultivar CCRI35 as the recipient parent. After constructing a high-density genetic map with the BC1 population, the genotype and phenotype of the CSSL population were investigated. A total of 235 QTLs, including 104 QTLs for fiber-related traits and 132 QTLs for seed-related traits, were identified from four environments. Among these QTLs, twenty-seven QTLs were identified in two or more environments, and twenty-five QTL clusters consisted of 114 QTLs. Moreover, we identified three candidate genes for three stable QTLs, including GH_A01G1096 (ARF5) and GH_A10G0141 (PDF2) for lint percentage, and GH_D01G0047 (KCS4) for seed index or oil content. These results pave way for understanding the molecular regulatory mechanism of fiber and seed development and would provide valuable information for marker-assisted genetic improvement in cotton.

Realizing visionary goals for the International Year of Millet (IYoM): accelerating interventions through advances in molecular breeding and multiomics resources.

MAIN CONCLUSION: Leveraging advanced breeding and multi-omics resources is vital to position millet as an essential "nutricereal resource," aligning with IYoM goals, alleviating strain on global cereal production, boosting resilience to climate change, and advancing sustainable crop improvement and biodiversity. The global challenges of food security, nutrition, climate change, and agrarian sustainability demand the adoption of climate-resilient, nutrient-rich crops to support a growing population amidst shifting environmental conditions. Millets, also referred to as "Shree Anna," emerge as a promising solution to address these issues by bolstering food production, improving nutrient security, and fostering biodiversity conservation. Their resilience to harsh environments, nutritional density, cultural significance, and potential to enhance dietary quality index made them valuable assets in global agriculture. Recognizing their pivotal role, the United Nations designated 2023 as the "International Year of Millets (IYoM 2023)," emphasizing their contribution to climate-resilient agriculture and nutritional enhancement. Scientific progress has invigorated efforts to enhance millet production through genetic and genomic interventions, yielding a wealth of advanced molecular breeding technologies and multi-omics resources. These advancements offer opportunities to tackle prevailing challenges in millet, such as anti-nutritional factors, sensory acceptability issues, toxin contamination, and ancillary crop improvements. This review provides a comprehensive overview of molecular breeding and multi-omics resources for nine major millet species, focusing on their potential impact within the framework of IYoM. These resources include whole and pan-genome, elucidating adaptive responses to abiotic stressors, organelle-based studies revealing evolutionary resilience, markers linked to desirable traits for efficient breeding, QTL analysis facilitating trait selection, functional gene discovery for biotechnological interventions, regulatory ncRNAs for trait modulation, web-based platforms for stakeholder communication, tissue culture techniques for genetic modification, and integrated omics approaches enabled by precise application of CRISPR/Cas9 technology. Aligning these resources with the seven thematic areas outlined by IYoM catalyzes transformative changes in millet production and utilization, thereby contributing to global food security, sustainable agriculture, and enhanced nutritional consequences.

Revolutionizing soybean genomics: How CRISPR and advanced sequencing are unlocking new potential.

Soybean Glycine max L., paleopolyploid genome, poses challenges to its genetic improvement. However, the development of reference genome assemblies and genome sequencing has completely changed the field of soybean genomics, allowing for more accurate and successful breeding techniques as well as research. During the single-cell revolution, one of the most advanced sequencing tools for examining the transcriptome landscape is single-cell RNA sequencing (scRNA-seq). Comprehensive resources for genetic improvement of soybeans may be found in the SoyBase and other genomics databases. CRISPR-Cas9 genome editing technology provides promising prospects for precise genetic modifications in soybean. This method has enhanced several soybean traits, including as yield, nutritional value, and resistance to both biotic and abiotic stresses. With base editing techniques that allow for precise DNA modifications, the use of CRISPR-Cas9 is further increased. With the availability of the reference genome for soybeans and the following assembly of wild and cultivated soybeans, significant chromosomal rearrangements and gene duplication events have been identified, offering new perspectives on the complex genomic structure of soybeans. Furthermore, major single nucleotide polymorphisms (SNPs) linked to stachyose and sucrose content have been found through genome-wide association studies (GWAS), providing important tools for enhancing soybean carbohydrate profiles. In order to open up new avenues for soybean genetic improvement, future research approaches include investigating transcriptional divergence processes, enhancing genetic resources, and incorporating CRISPR-Cas9 technologies.

Biotechnological studies towards improvement of finger millet using multi-omics approaches.

A plethora of studies have uncovered numerous important genes with agricultural significance in staple crops. However, when it comes to orphan crops like minor millet, genomic research lags significantly behind that of major crops. This situation has promoted a focus on exploring research opportunities in minor millets, particularly in finger millet, using cutting-edge methods. Finger millet, a coarse cereal known for its exceptional nutritional content and ability to withstand environmental stresses represents a promising climate-smart and nutritional crop in the battle against escalating environmental challenges. The existing traditional improvement programs for finger millet are insufficient to address global hunger effectively. The lack of utilization of high-throughput platforms, genome editing, haplotype breeding, and advanced breeding approaches hinders the systematic multi-omics studies on finger millet, which are essential for pinpointing crucial genes related to agronomically important and various stress responses. The growing environmental uncertainties have widened the gap between the anticipated and real progress in crop improvement. To overcome these challenges a combination of cutting-edge multi-omics techniques such as high-throughput sequencing, speed breeding, mutational breeding, haplotype-based breeding, genomic selection, high-throughput phenotyping, pangenomics, genome editing, and more along with integration of deep learning and artificial intelligence technologies are essential to accelerate research efforts in finger millet. The scarcity of multi-omics approaches in finger millet leaves breeders with limited modern tools for crop enhancement. Therefore, leveraging datasets from previous studies could prove effective in implementing the necessary multi-omics interventions to enrich the genetic resource in finger millet.

Strategies and bibliometric analysis of legumes biofortification to address malnutrition.

MAIN CONCLUSION: Biofortification of legumes using diverse techniques such as plant breeding, agronomic practices, genetic modification, and nano-technological approaches presents a sustainable strategy to address micronutrient deficiencies of underprivileged populations. The widespread issue of chronic malnutrition, commonly referred to as "hidden hunger," arises from the consumption of poor-quality food, leading to various health and cognitive impairments. Biofortified food crops have been a sustainable solution to address micronutrient deficiencies. This review highlights multiple biofortification techniques, such as plant breeding, agronomic practices, genetic modification, and nano-technological approaches, aimed at enhancing the nutrient content of commonly consumed crops. Emphasizing the biofortification of legumes, this review employs bibliometric analysis to examine research trends from 2000 to 2023. It identifies key authors, influential journals, contributing countries, publication trends, and prevalent keywords in this field. The review highlights the progress in developing biofortified crops and their potential to improve global nutrition and help underprivileged populations.

Unraveling genotypic interactions in sugar beet for enhanced yield stability and trait associations.

The interaction between genotype and environment (GEI) significantly influences plant performance, crucial for breeding programs and ultimately boosting crop productivity. Alongside GEI, breeders encounter another hurdle in their quest for yield improvement, notably adverse and negative correlations among pivotal traits. This study delved into the stability of white sugar yield (WSY), root yield (RY), sugar content (SC), extraction coefficient of sugar (ECS), and the interplay among essential traits including RY, SC, alpha amino nitrogen (N), sodium (Na+), and potassium (K+) across 15 sugar beet hybrids and three control varieties. The investigation spanned two locations over two consecutive years (2022-2023), employing a randomized complete block design with four replications to comprehensively analyze these factors. The analysis of variance highlighted the significant effects of environment, genotype, and GEI at the 1% probability level. Notably, the AMMI analysis of GEI revealed the significance of the first component for WSY, RY, and SC, with the first two components proving significant for ECS. Within the linear mixed model (LMM), WSY, RY, SC, and ECS demonstrated significant effects from both genotype and GEI. In the WAASB biplot, genotypes 10, 8, 17, 6, 13, 14, 15, 7, 12, and 16 exhibited stability in WSY, while genotypes 9, 10, 6, 14, 7, 8, 13, 12, 18, and 15 displayed stability in RY. Additionally, genotypes 10, 15, 12, 13, 16, 17, 6, and 14 were stable for SC, and genotypes 8, 10, 7, 6, 13, 12, 16, 17, 15, 14, and 18 showcased stability in ECS, boasting above-average yield values. In the genotype by yield × trait (GYT) biplot, genotypes 15, 18, and 16 emerged as top performers when combining RY with SC, Na+, N, and K+, suggesting their potential for inclusion in breeding programs.

Cytogenetic analysis and visualization of genetic relationships in wild lilies.

Lilies are highly regarded for their ornamental appeal and striking flowers, which are of significant importance in horticulture. Understanding the genetic makeup of these plants is crucial for breeding and developing new cultivars. This study presents a comprehensive cytogenetic analysis of 45 S and 5 S rDNA loci in 34 wild Lilium species. To reveal the genetic relationships within the genus, advanced visualization methods, such as heatmaps and 3D network plots, were utilized. The results of this study identified both conserved and divergent genetic features, which offer insights into the evolutionary history and potential genetic compatibility of these species. Notably, the clustering of species based on rDNA locus patterns highlights the need for potential taxonomic re-evaluation and reveals candidates for cross-breeding. This integrated approach emphasizes the importance of combining cytogenetic data with traditional morphological classifications to refine our understanding of the Lilium species. Future research should expand the range of analyzed species, incorporate additional molecular markers to further elucidate genetic relationships, and support the development of resilient and diverse ornamental crops. The findings of this study provide a novel framework for genetic analysis of Lilium, offering valuable insights for both scientific understanding and practical breeding programs.

QTL mapping for seed vigor-related traits under artificial aging in common wheat in two introgression line (IL) populations.

Background: Seed vigor recognized as a quantitative trait is of particular importance for agricultural production. However, limited knowledge is available for understanding genetic basis of wheat seed vigor. Methods: The aim of this study was to identify quantitative trait loci (QTL) responsible for 10 seed vigor-related traits representing multiple aspects of seed-vigor dynamics during artificial aging with 6 different treatment times (0, 24, 36, 48, 60, and 72 h) under controlled conditions (48 °C, 95% humidity, and dark). The mapping populations were two wheat introgression lines (IL-1 and IL-2) derived from recipient parent (Lumai 14) and donor parent (Shaanhan 8675 or Jing 411). Results: A total of 26 additive QTLs and 72 pairs of epistatic QTLs were detected for wheat seed-vigor traits. Importantly, chromosomes 1B and 7B contained several co-located QTLs, and chromosome 2A had a QTL-rich region near the marker Xwmc667, indicating that these QTLs may affect wheat seed vigor with pleiotropic effects. Furthermore, several possible consistent QTLs (hot-spot regions) were examined by comparison analysis of QTLs detected in this study and reported previously. Finally, a set of candidate genes for wheat seed vigor were predicted to be involved in transcription regulation, carbohydrate and lipid metabolism. Conclusion: The present findings lay new insights into the mechanism underlying wheat seed vigor, providing valuable information for wheat genetic improvement especially marker-assisted breeding to increase seed vigor and consequently achieve high grain yield despite of further investigation required.

Wheat improvement through advances in single nucleotide polymorphism (SNP) detection and genotyping with a special emphasis on rust resistance.

KEY MESSAGE: Single nucleotide polymorphism (SNP) markers in wheat and their prospects in breeding with special reference to rust resistance. Single nucleotide polymorphism (SNP)-based markers are increasingly gaining momentum for screening and utilizing vital agronomic traits in wheat. To date, more than 260 million SNPs have been detected in modern cultivars and landraces of wheat. This rapid SNP discovery was made possible through the release of near-complete reference and pan-genome assemblies of wheat and its wild relatives, coupled with whole genome sequencing (WGS) of thousands of wheat accessions. Further, genotyping customized SNP sites were facilitated by a series of arrays (9 to 820Ks), a cost effective substitute WGS. Lately, germplasm-specific SNP arrays have been introduced to characterize novel traits and detect closely linked SNPs for marker-assisted breeding. Subsequently, the kompetitive allele-specific PCR (KASP) assay was introduced for rapid and large-scale screening of specific SNP markers. Moreover, with the advances and reduction in sequencing costs, ample opportunities arise for generating SNPs artificially through mutations and in combination with next-generation sequencing and comparative genomic analyses. In this review, we provide historical developments and prospects of SNP markers in wheat breeding with special reference to rust resistance where over 50 genetic loci have been characterized through SNP markers. Rust resistance is one of the most essential traits for wheat breeding as new strains of the Puccinia fungus, responsible for rust diseases, evolve frequently and globally.

Enhancing genetic diversity in Pelargonium: insights from crossbreeding in the gene pool.

This study aimed to enrich the Pelargonium gene pool through crosses and assess genetic variation among 56 genotypes from five Pelargonium species. Seventeen morphological descriptors were used, and NTSYS-pc software was employed to define genetic relationships, and a UPGMA-generated dendrogram reflected these relationships. Moreover, principal component analysis (PCA) was performed to determine which parameter was more effective in explaining variation. Results showed wide variation in genetic similarity rates, with the most similar genotypes being P. zonale 'c1' and a hybrid of P. zonale 'c1' x P. zonale 'c2' (90% similarity). According to the dendrogram results, it was observed that the genotypes were distributed in six clusters. In contrast, the most distant genotypes were P. zonale 'c11' and a hybrid of P. zonale 'c10' x P. zonale 'c11' (0.04% similarity). Hybrids from the female parent P. x hortorum 'c1' exhibited unique placement in the dendrogram. In the crossing combinations with this genotype, the individuals obtained in terms of flower type, flower color, flower size, bud size, early flowering, and leaf size characters showed different characteristics from the parents. Surprising outcomes in flower types, colors, and shapes contributed to gene pool enrichment, promising increased breeding variation success. The study holds practical implications for commercial breeding and serves as a valuable guide for future research endeavors.

Molecular approaches for the management of papaya ringspot virus infecting papaya: a comprehensive review.

Papaya ringspot virus (PRSV) is a catastrophic disease that causes huge yield losses in papaya cultivation around the world. Yield losses in severely infected plants can be upto 100%. Because of this disease, papaya cultivation has been shifted to other crops in some areas of the world. Many conventional methods and breeding approaches are used against this disease, which turns out to be less effective. Considering the yield loss caused by PRSV in papaya, it is high time to focus on alternative control methods. To implement effective management strategies, molecular approaches such as Marker Assisted Breeding (MAS) or transgenic methods involving post-transcriptional gene silencing targeting the genome viz., coat protein, replicase gene, or HC Pro can be pursued. However, the public's reluctance to widely accept the transgenic approach due to health and environmental concerns necessitates a consideration of non-transgenic alternatives. Prioritizing safety and ensuring efficient virus control, non-transgenic approaches which encompass cross-protection, genome editing, and topical applications of dsRNA to induce gene silencing within the host, can be adopted. This review aims to provide comprehensive insights of various molecular tools used in managing PRSV which in turn will help in sustainable agriculture.

Embryo recovery(rescue) studies in different Vitis species.

BACKROUND: In recent years, with the increasing demand for seedless grape varieties that have lower production costs, are disease resistant/tolerant and require less chemical pesticides, the embryo recovery technique has begun to be used more in table grape breeding studies. However, the desired high success rate has not yet been achieved in these studies. Although there are different reasons for this, especially the grape varieties selected for cross-breeding and the timing of transferring the embryos to medium are among the most important reasons. In this study, focusing on these two important factors, the embryos obtained from different hybridization combinations were transferred to agar medium at different weeks for 4 years and the most successful combination and time were determined. In addition, seedless and large berry grape varieties and some seeded varieties that are resistant/tolerant to fungal diseases were selected as parents because they can provide resistance to disease infections in vitro and thus increase the success rate. RESULTS: The results obtained from the study showed that the selected variety and combination significantly affected the success rate in embryo rescue. Especially in combinations with the 'Yalova Seedless' variety as the female parent, more successful results were obtained compared to combinations of other varieties. When 'Yalova Seedless' variety was pollinated with pollen of 'Red Globe', 'Muscat Bailey A' and 'Exalta' varieties, more seedlings were obtained with the help of embryo rescue. The results obtained over four years showed that the best sampling time after pollination was the eighth week and then the seventh week. CONCLUSIONS: According to the results obtained, it has been shown that the selected varieties and the sampling time significantly affect the success rate in embryo rescue studies. Therefore, higher success rates can be achieved in comprehensive breeding studies in which they will be included as pollinators, especially in different seeded varieties that are resistant to diseases and have larger berry size.

Advances in breeding, biotechnology, and nanotechnological approaches to combat sheath blight disease in rice.

Sheath blight, caused by the fungus Rhizoctonia solani, is a major problem that significantly impacts rice production and can lead to substantial yield losses. The disease has become increasingly problematic in recent years due to the widespread use of high-yielding semi-dwarf rice cultivars, dense planting, and heavy application of nitrogenous fertilizers. The disease has become more challenging to manage due to its diverse host range and the lack of resistant cultivars. Despite utilizing traditional methods, the problem persists without a satisfactory solution. Therefore, modern approaches, including advanced breeding, transgenic methods, genome editing using CRISPR/Cas9 technology, and nanotechnological interventions, are being explored to develop rice plants resistant to sheath blight disease. This review primarily focuses on these recent advancements in combating the sheath blight disease.

Fertile grounds: exploring male sterility in cotton and its marker development.

The high cost of producing conventional hybrid cotton seeds led to more research efforts on cotton male sterility systems. There is a lack of studies on cytology, histology, morphological variation, yield, and altered restorer backgrounds to identify and develop male sterility markers in cotton hybrids. Hybrid cotton can be efficiently produced by exploiting genetic male sterility. Among the 19 Genetic Male Sterility (GMS) genes discovered, the lines with ms5ms6 genes are mostly utilised to establish successful hybrid cotton in India. Molecular markers closely associated with the MS alleles are identified to facilitate the efficient and rapid backcrossing of male-sterility genes into elite lines or cultivars by marker-assisted backcrossing. The majority of the markers which are random DNA markers (RDMs), are probably lost, when recombination occurs. In contradiction, molecular markers (functional markers, or FMs) within the genic region can be identified and employed in crops for diverse traits, if prospective characteristic genes are known. In this review, the mechanism of male sterility, its gene expression level, and the need for functional markers for the male sterility trait in cotton have been put forward.

De novo domestication in the Solanaceae: advances and challenges.

The advent of highly efficient genome editing (GE) tools, coupled with high-throughput genome sequencing, has paved the way for the accelerated domestication of crop wild relatives. New crops could thus be rapidly created that are well adapted to cope with drought, flooding, soil salinity, or insect damage. De novo domestication avoids the complexity of transferring polygenic stress resistance from wild species to crops. Instead, new crops can be created by manipulating major genes in stress-resistant wild species. However, the genetic basis of certain relevant domestication-related traits often involve epistasis and pleiotropy. Furthermore, pan-genome analyses show that structural variation driving gene expression changes has been selected during domestication. A growing body of work suggests that the Solanaceae family, which includes crop species such as tomatoes, potatoes, eggplants, peppers, and tobacco, is a suitable model group to dissect these phenomena and operate changes in wild relatives to improve agronomic traits rapidly with GE. We briefly discuss the prospects of this exciting novel field in the interface between fundamental and applied plant biology and its potential impact in the coming years.

An insight into heat stress response and adaptive mechanism in cotton.

The growing worldwide population is driving up demand for cotton fibers, but production is hampered by unpredictable temperature rises caused by shifting climatic conditions. Numerous research based on breeding and genomics have been conducted to increase the production of cotton in environments with high and low-temperature stress. High temperature (HT) is a major environmental stressor with global consequences, influencing several aspects of cotton plant growth and metabolism. Heat stress-induced physiological and biochemical changes are research topics, and molecular techniques are used to improve cotton plants' heat tolerance. To preserve internal balance, heat stress activates various stress-responsive processes, including repairing damaged proteins and membranes, through various molecular networks. Recent research has investigated the diverse reactions of cotton cultivars to temperature stress, indicating that cotton plant adaptation mechanisms include the accumulation of sugars, proline, phenolics, flavonoids, and heat shock proteins. To overcome the obstacles caused by heat stress, it is crucial to develop and choose heat-tolerant cotton cultivars. Food security and sustainable agriculture depend on the application of genetic, agronomic, and, biotechnological methods to lessen the impacts of heat stress on cotton crops. Cotton producers and the textile industry both benefit from increased heat tolerance. Future studies should examine the developmental responses of cotton at different growth stages, emphasize the significance of breeding heat-tolerant cultivars, and assess the biochemical, physiological, and molecular pathways involved in seed germination under high temperatures. In a nutshell, a concentrated effort is required to raise cotton's heat tolerance due to the rising global temperatures and the rise in the frequency of extreme weather occurrences. Furthermore, emerging advances in sequencing technologies have made major progress toward successfully se sequencing the complex cotton genome.

An artificially evolved gene for herbicide-resistant rice breeding.

Discovering and engineering herbicide-resistant genes is a crucial challenge in crop breeding. This study focuses on the 4-hydroxyphenylpyruvate dioxygenase Inhibitor Sensitive 1-Like (HSL) protein, prevalent in higher plants and exhibiting weak catalytic activity against many ß-triketone herbicides (ß-THs). The crystal structures of maize HSL1A complexed with ß-THs were elucidated, identifying four essential herbicide-binding residues and explaining the weak activity of HSL1A against the herbicides. Utilizing an artificial evolution approach, we developed a series of rice HSL1 mutants targeting the four residues. Then, these mutants were systematically evaluated, identifying the M10 variant as the most effective in modifying ß-THs. The initial active conformation of substrate binding in HSL1 was also revealed from these mutants. Furthermore, overexpression of M10 in rice significantly enhanced resistance to ß-THs, resulting in a notable 32-fold increase in resistance to methyl-benquitrione. In conclusion, the artificially evolved M10 gene shows great potential for the development of herbicide-resistant crops.

Prediction of resistance, virulence, and host-by-pathogen interactions using dual-genome prediction models.

KEY MESSAGE: Integrating disease screening data and genomic data for host and pathogen populations into prediction models provides breeders and pathologists with a unified framework to develop disease resistance. Developing disease resistance in crops typically consists of exposing breeding populations to a virulent strain of the pathogen that is causing disease. While including a diverse set of pathogens in the experiments would be desirable for developing broad and durable disease resistance, it is logistically complex and uncommon, and limits our capacity to implement dual (host-by-pathogen)-genome prediction models. Data from an alternative disease screening system that challenges a diverse sweet corn population with a diverse set of pathogen isolates are provided to demonstrate the changes in genetic parameter estimates that result from using genomic data to provide connectivity across sparsely tested experimental treatments. An inflation in genetic variance estimates was observed when among isolate relatedness estimates were included in prediction models, which was moderated when host-by-pathogen interaction effects were incorporated into models. The complete model that included genomic similarity matrices for host, pathogen, and interaction effects indicated that the proportion of phenotypic variation in lesion size that is attributable to host, pathogen, and interaction effects was similar. Estimates of the stability of lesion size predictions for host varieties inoculated with different isolates and the stability of isolates used to inoculate different hosts were also similar. In this pathosystem, genetic parameter estimates indicate that host, pathogen, and host-by-pathogen interaction predictions may be used to identify crop varieties that are resistant to specific virulence mechanisms and to guide the deployment of these sources of resistance into pathogen populations where they will be more effective.

A framework for simulating genotype-by-environment interaction using multiplicative models.

KEY MESSAGE: The simulation of genotype-by-environment interaction using multiplicative models provides a general and scalable framework to generate realistic multi-environment datasets and model plant breeding programmes. Plant breeding has been historically shaped by genotype-by-environment interaction (GEI). Despite its importance, however, many current simulations do not adequately capture the complexity of GEI inherent to plant breeding. The framework developed in this paper simulates GEI with desirable structure using multiplicative models. The framework can be used to simulate a hypothetical target population of environments (TPE), from which many different multi-environment trial (MET) datasets can be sampled. Measures of variance explained and expected accuracy are developed to tune the simulation of non-crossover and crossover GEI and quantify the MET-TPE alignment. The framework has been implemented within the R package FieldSimR, and is demonstrated here using two working examples supported by R code. The first example embeds the framework into a linear mixed model to generate MET datasets with low, moderate and high GEI, which are used to compare several popular statistical models applied to plant breeding. The prediction accuracy generally increases as the level of GEI decreases or the number of environments sampled in the MET increases. The second example integrates the framework into a breeding programme simulation to compare genomic and phenotypic selection strategies over time. Genomic selection outperforms phenotypic selection by ∼ 50-70% in the TPE, depending on the level of GEI. These examples demonstrate how the new framework can be used to generate realistic MET datasets and model plant breeding programmes that better reflect the complexity of real-world settings, making it a valuable tool for optimising a wide range of breeding methodologies.