Mapping of flumioxazin tolerance in a snap bean diversity panel leads to the discovery of a master genomic region controlling multiple stress resistance genes.

Introduction: Effective weed management tools are crucial for maintaining the profitable production of snap bean (Phaseolus vulgaris L.). Preemergence herbicides help the crop to gain a size advantage over the weeds, but the few preemergence herbicides registered in snap bean have poor waterhemp (Amaranthus tuberculatus) control, a major pest in snap bean production. Waterhemp and other difficult-to-control weeds can be managed by flumioxazin, an herbicide that inhibits protoporphyrinogen oxidase (PPO). However, there is limited knowledge about crop tolerance to this herbicide. We aimed to quantify the degree of snap bean tolerance to flumioxazin and explore the underlying mechanisms. Methods: We investigated the genetic basis of herbicide tolerance using genome-wide association mapping approach utilizing field-collected data from a snap bean diversity panel, combined with gene expression data of cultivars with contrasting response. The response to a preemergence application of flumioxazin was measured by assessing plant population density and shoot biomass variables. Results: Snap bean tolerance to flumioxazin is associated with a single genomic location in chromosome 02. Tolerance is influenced by several factors, including those that are indirectly affected by seed size/weight and those that directly impact the herbicide's metabolism and protect the cell from reactive oxygen species-induced damage. Transcriptional profiling and co-expression network analysis identified biological pathways likely involved in flumioxazin tolerance, including oxidoreductase processes and programmed cell death. Transcriptional regulation of genes involved in those processes is possibly orchestrated by a transcription factor located in the region identified in the GWAS analysis. Several entries belonging to the Romano class, including Bush Romano 350, Roma II, and Romano Purpiat presented high levels of tolerance in this study. The alleles identified in the diversity panel that condition snap bean tolerance to flumioxazin shed light on a novel mechanism of herbicide tolerance and can be used in crop improvement.

A cell-based fluorescent system and statistical framework to detect meiosis-like induction in plants.

Genetic gains made by plant breeders are limited by generational cycling rates and flowering time. Several efforts have been made to reduce the time to switch from vegetative to reproductive stages in plants, but these solutions are usually species-specific and require flowering. The concept of in vitro nurseries is that somatic plant cells can be induced to form haploid cells that have undergone recombination (creating artificial gametes), which can then be used for cell fusion to enable breeding in a Petri dish. The induction of in vitro meiosis, however, is the largest current bottleneck to in vitro nurseries. To help overcome this, we previously described a high-throughput, bi-fluorescent, single cell system in Arabidopsis thaliana, which can be used to test the meiosis-like induction capabilities of candidate factors. In this present work, we validated the system using robust datasets (>4M datapoints) from extensive simulated meiosis induction tests. Additionally, we determined false-detection rates of the fluorescent cells used in this system as well as the ideal tissue source for factor testing.

Understanding the Genetic Basis of Blueberry Postharvest Traits to Define Better Breeding Strategies.

Blueberry (Vaccinium spp.) is among the most-consumed soft fruit and has been recognized as an important source of health-promoting compounds. Highly perishable and susceptible to rapid spoilage due to fruit softening and decay during postharvest storage, modern breeding programs are looking to maximize quality and extend the market life of fresh blueberries. However, it is uncertain how genetically controlled postharvest quality traits are in blueberries. This study aimed to investigate the prediction ability and genetic basis of the main fruit quality traits affected during blueberry postharvest to create breeding strategies for developing cultivars with an extended shelf life. To achieve this goal, we carried out target genotyping in a breeding population of 588 individuals and evaluated for several fruit quality traits after one day, one week, three weeks, and seven weeks of postharvest storage at 1 °C. Using longitudinal genome-based methods, we estimated genetic parameters and predicted unobserved phenotypes. Our results showed large diversity, moderate heritability, and consistent predictive accuracies along the postharvest storage for most of the traits. Regarding fruit quality, firmness showed the largest variation during postharvest storage, with a surprising number of genotypes maintaining or increasing their firmness even after seven weeks of cold storage. Our results suggest that we can effectively improve blueberry postharvest quality through breeding and use genomic prediction to maximize the genetic gains in the long term. We also emphasize the potential of using longitudinal genomic prediction models to predict fruit quality at extended postharvest periods by integrating known phenotypic data from harvest.

Genome-wide association studies of root system architecture traits in a broad collection of Brassica genotypes.

The root systems of Brassica species are complex. Eight root system architecture (RSA) traits, including total root length, total root surface area, root average diameter, number of tips, total primary root length, total lateral root length, total tertiary root length, and basal link length, were phenotyped across 379 accessions representing six Brassica species (B. napus, B. juncea, B. carinata, B. oleracea, B. nigra, and B. rapa) using a semi-hydroponic system and image analysis software. The results suggest that, among the assessed species, B. napus and B. oleracea had the most intricate and largest root systems, while B. nigra exhibited the smallest roots. The two species B. juncea and B. carinata shared comparable root system complexity and had root systems with larger root diameters. In addition, 313 of the Brassica accessions were genotyped using a 19K Brassica single nucleotide polymorphism (SNP) array. After filtering by TASSEL 5.0, 6,213 SNP markers, comprising 5,103 markers on the A-genome (covering 302,504 kb) and 1,110 markers on the C-genome (covering 452,764 kb), were selected for genome-wide association studies (GWAS). Two general linear models were tested to identify the genomic regions and SNPs associated with the RSA traits. GWAS identified 79 significant SNP markers associated with the eight RSA traits investigated. These markers were distributed across the 18 chromosomes of B. napus, except for chromosome C06. Sixty-five markers were located on the A-genome, and 14 on the C-genome. Furthermore, the major marker-trait associations (MTAs)/quantitative trait loci (QTLs) associated with root traits were located on chromosomes A02, A03, and A06. Brassica accessions with distinct RSA traits were identified, which could hold functional, adaptive, evolutionary, environmental, pathological, and breeding significance.

Genetic study of Camelina sativa oilseed crop and selection of a new variety by the bulk method.

Camelina sativa, commonly referred to as camelina or false flax, has emerged as a promising cover crop with the potential to mitigate climate change-a pressing global challenge that demands urgent and sustainable solutions. Belonging to the Brassicaceae family and native to Europe and Central Asia, camelina is an oilseed crop known for its resilience in diverse climates, including arid and semi-arid regions, making it adaptable to various environments. A breeding program started from a study of six winter varieties and five spring varieties of camelina is described: these genetic materials were characterized by SSRs molecular markers and by GBS technique. Molecular data clearly showed all spring varieties were genetically similar and distinguishable from the winter varieties, which, in turn, clustered together. Using molecular data, parental varieties belonging to the two different clusters were selected to generate new genetic variability. The new variety obtained, selected through the bulk method based on three parameters: yield, earliness, and weight of 1000 seeds, has allowed the generation of the new genetic material provisionally named C1244. Chemical characterization was performed (bromatological and glucosinolates analysis) to better describe C1244 in comparison with benchmark varieties. The new variety exhibited early maturity, similar to spring varieties, making this genetic material promising for use in intercropping systems, a high weight of 1000 seeds (1.46 g) which improves and facilitates seeding/harvesting operations and a high oil content (33.62%) akin to winter varieties making it valuable for human and animal food purposes.

Determining the footprint of breeding in the seed microbiome of a perennial cereal.

BACKGROUND: Seed endophytes have a significant impact on plant health and fitness. They can be inherited and passed on to the next plant generation. However, the impact of breeding on their composition in seeds is less understood. Here, we studied the indigenous seed microbiome of a recently domesticated perennial grain crop (Intermediate wheatgrass, Thinopyrum intermedium L.) that promises great potential for harnessing microorganisms to enhance crop performance by a multiphasic approach, including amplicon and strain libraries, as well as molecular and physiological assays. RESULTS: Intermediate wheatgrass seeds harvested from four field sites in Europe over three consecutive years were dominated by Proteobacteria (88%), followed by Firmicutes (10%). Pantoea was the most abundant genus and Pantoea agglomerans was identified as the only core taxon present in all samples. While bacterial diversity and species richness were similar across all accessions, the relative abundance varied especially in terms of low abundant and rare taxa. Seeds from four different breeding cycles (TLI C3, C5, C704, C801) showed significant differences in bacterial community composition and abundance. We found a decrease in the relative abundance of the functional genes nirK and nifH as well as a drop in bacterial diversity and richness. This was associated with a loss of amplicon sequence variants (ASVs) in Actinobacteria, Alphaproteobacteria, and Bacilli, which could be partially compensated in offspring seeds, which have been cultivated at a new site. Interestingly, only a subset assigned to potentially beneficial bacteria, e.g. Pantoea, Kosakonia, and Pseudomonas, was transmitted to the next plant generation or shared with offspring seeds. CONCLUSION: Overall, this study advances our understanding of the assembly and transmission of endophytic seed microorganisms in perennial intermediate wheatgrass and highlights the importance of considering the plant microbiome in future breeding programs.

Public perception of new plant breeding techniques and the psychosocial determinants of acceptance: A systematic review.

Advancements in New Plant Breeding Techniques have emerged as promising tools for enhancing crop productivity, quality, and resilience in the face of global challenges, such as climate change and food security. However, the successful implementation of these techniques relies also on public acceptance of this innovation. Understanding what shapes public perception and acceptance of New Plant Breeding Techniques is crucial for effective science communication, policymaking, and the sustainable adoption of these innovations. The objective of this systematic review was to synthesize existing research on the public perception of New Plant Breeding Techniques applied to food crops and explore the psychosocial determinants that influence acceptance. Twenty papers published between 2015 and 2023 were included on various New Plant Breeding Techniques and their reception by the general public. Determinants affecting the acceptance of food crops derived from New Plant Breeding Techniques were categorized into six areas: sociodemographic factors, perceived benefits and risks, attitudes toward science, communication strategies, personal values, and product characteristics.

Genetic Heterogeneity in Cowpea Genotypes (Vigna unguiculata L. Walp) Using DArTseq (GBS)-Derived Single Nucleotide Polymorphisms.

Cowpeas (Vigna unguiculata L. Walp) have been credible constituents of nutritious food and forage in human and animal diets since the Neolithic era. The modern technique of Diversity Array Technology (DArTseq) is both cost-effective and rapid in producing thousands of high-throughputs, genotyped, single nucleotide polymorphisms (SNPs) in wide-genomic analyses of genetic diversity. The aim of this study was to assess the heterogeneity in cowpea genotypes using DArTseq-derived SNPs. A total of 92 cowpea genotypes were selected, and their fourteen-day-old leaves were freeze-dried for five days. DNA was extracted using the CTAB protocol, genotyped using DArTseq, and analysed using DArTsoft14. A total of 33,920 DArTseq-derived SNPs were recalled for filtering analysis, with a final total of 16,960 SNPs. The analyses were computed using vcfR, poppr, and ape in R Studio v1.2.5001-3 software. The heatmap revealed that the TVU 9596 (SB26), Orelu (SB72), 90K-284-2 (SB55), RV 403 (SB17), and RV 498 (SB16) genotypes were heterogenous. The mean values for polymorphic information content, observed heterozygosity, expected heterozygosity, major allele frequency, and the inbreeding coefficient were 0.345, 0.386, 0.345, 0.729, and 0.113, respectively. Moreover, they validated the diversity of the evaluated cowpea genotypes, which could be used for potential breeding programmes and management of cowpea germplasm.

Alien introgression to wheat for food security: functional and nutritional quality for novel products under climate change.

Crop yield and quality has increased globally during recent decades due to plant breeding, resulting in improved food security. However, climate change and shifts in human dietary habits and preferences display novel pressure on crop production to deliver enough quantity and quality to secure food for future generations. This review paper describes the current state-of-the-art and presents innovative approaches related to alien introgressions into wheat, focusing on aspects related to quality, functional characteristics, nutritional attributes, and development of novel food products. The benefits and opportunities that the novel and traditional plant breeding methods contribute to using alien germplasm in plant breeding are also discussed. In principle, gene introgressions from rye have been the most widely utilized alien gene source for wheat. Furthermore, the incorporation of novel resistance genes toward diseases and pests have been the most transferred type of genes into the wheat genome. The incorporation of novel resistance genes toward diseases and pests into the wheat genome is important in breeding for increased food security. Alien introgressions to wheat from e.g. rye and Aegilops spp. have also contributed to improved nutritional and functional quality. Recent studies have shown that introgressions to wheat of genes from chromosome 3 in rye have an impact on both yield, nutritional and functional quality, and quality stability during drought treatment, another character of high importance for food security under climate change scenarios. Additionally, the introgression of alien genes into wheat has the potential to improve the nutritional profiles of future food products, by contributing higher minerals levels or lower levels of anti-nutritional compounds into e.g., plant-based products substituting animal-based food alternatives. To conclude, the present review paper highlights great opportunities and shows a few examples of how food security and functional-nutritional quality in traditional and novel wheat products can be improved by the use of genes from alien sources, such as rye and other relatives to wheat. Novel and upcoming plant breeding methods such as genome-wide association studies, gene editing, genomic selection and speed breeding, have the potential to complement traditional technologies to keep pace with climate change and consumer eating habits.

Enhancing genetic variability in Trigonella species through sodium azide induction: morpho-physiological and chromosomal amelioration.

Plant breeding, aimed at enhancing desired traits, depends on genetic diversity. Mutation breeding is a powerful method of rapidly expanding genetic diversity, facilitating crop improvement, and ensuring food security. In a recent study, researchers evaluated the genetic variability of Trigonella species using different doses of sodium azide (SA) (0.2%, 0.4%, 0.6%, 0.8%, and 1.0%) through morphological, physiological, and cytogenetic studies. Morphological variations were observed in cotyledonary leaves, vegetative leaves, and overall plant growth and habit. Several quantitative parameters, such as plant height, fertile branches per plant, pods per plant (or clusters), seeds per pod, and seed yield, increased when treated with 0.2% and 0.4% SA compared to the control. Furthermore, the total chlorophyll content and carotenoids increased in the sample treated with 0.2% SA over the control but decreased with higher concentrations. Scanning electron microscopy revealed that stomatal aperture and seed dimensions increased at lower concentrations of sodium azide treatment. The study found a positive correlation between the different parameters studied in the Trigonella species, as indicated by high r-values. Based on their findings, it was concluded that the genotype of fenugreek can be improved by using 0.2% and 0.4% concentrations of sodium azide. However, the evaluation of observed variants in successive generations is a critical and necessary process to validate their potential as keystones for crop genetic improvements.

Advancing utilization of diverse global carrot (Daucus carota L.) germplasm with flowering habit trait ontology.

Biennial vegetable crops are challenging to breed due to long breeding cycle times. At the same time, it is important to preserve a strong biennial growth habit, avoiding premature flowering that renders the crop unmarketable. Gene banks carry important genetic variation which may be essential to improve crop resilience, but these collections are underutilized due to lack of characterization for key traits like bolting tendency for biennial vegetable crops. Due to concerns about introducing undesirable traits such as premature flowering into elite germplasm, many accessions may not be considered for other key traits that benefit growers, leaving crops more vulnerable to pests, diseases, and abiotic stresses. In this study, we develop a method for characterizing flowering to identify accessions that are predominantly biennial, which could be incorporated into biennial breeding programs without substantially increasing the risk of annual growth habits. This should increase the use of these accessions if they are also sources of other important traits such as disease resistance. We developed the CarrotOmics flowering habit trait ontology and evaluated flowering habit in the largest (N=695), and most diverse collection of cultivated carrots studied to date. Over 80% of accessions were collected from the Eurasian supercontinent, which includes the primary and secondary centers of carrot diversity. We successfully identified untapped genetic diversity in biennial carrot germplasm (n=197 with 0% plants flowering) and predominantly-biennial germplasm (n=357 with <15% plants flowering). High broad-sense heritability for flowering habit (0.81 < H2< 0.93) indicates a strong genetic component of this trait, suggesting that these carrot accessions should be consistently biennial. Breeders can select biennial plants and eliminate annual plants from a predominantly biennial population. The establishment of the predominantly biennial subcategory nearly doubles the availability of germplasm with commercial potential and accounts for 54% of the germplasm collection we evaluated. This subcollection is a useful source of genetic diversity for breeders. This method could also be applied to other biennial vegetable genetic resources and to introduce higher levels of genetic diversity into commercial cultivars, to reduce crop genetic vulnerability. We encourage breeders and researchers of biennial crops to optimize this strategy for their particular crop.

Harnessing monocrop breeding strategies for intercrops.

Intercropping is considered advantageous for many reasons, including increased yield stability, nutritional value and the provision of various regulating ecosystem services. However, intercropping also introduces diverse competition effects between the mixing partners, which can negatively impact their agronomic performance. Therefore, selecting complementary intercropping partners is the key to realizing a well-mixed crop production. Several specialized intercrop breeding concepts have been proposed to support the development of complementary varieties, but their practical implementation still needs to be improved. To lower this adoption threshold, we explore the potential of introducing minor adaptations to commonly used monocrop breeding strategies as an initial stepping stone towards implementing dedicated intercrop breeding schemes. While we acknowledge that recurrent selection for reciprocal mixing abilities is likely a more effective breeding paradigm to obtain genetic progress for intercrops, a well-considered adaptation of monoculture breeding strategies is far less intrusive concerning the design of the breeding programme and allows for balancing genetic gain for both monocrop and intercrop performance. The main idea is to develop compatible variety combinations by improving the monocrop performance in the two breeding pools in parallel and testing for intercrop performance in the later stages of selection. We show that the optimal stage for switching from monocrop to intercrop testing should be adapted to the specificity of the crop and the heritability of the traits involved. However, the genetic correlation between the monocrop and intercrop trait performance is the primary driver of the intercrop breeding scheme optimization process.

Reviewing the essential roles of remote phenotyping, GWAS and explainable AI in practical marker-assisted selection for drought-tolerant winter wheat breeding.

Marker-assisted selection (MAS) plays a crucial role in crop breeding improving the speed and precision of conventional breeding programmes by quickly and reliably identifying and selecting plants with desired traits. However, the efficacy of MAS depends on several prerequisites, with precise phenotyping being a key aspect of any plant breeding programme. Recent advancements in high-throughput remote phenotyping, facilitated by unmanned aerial vehicles coupled to machine learning, offer a non-destructive and efficient alternative to traditional, time-consuming, and labour-intensive methods. Furthermore, MAS relies on knowledge of marker-trait associations, commonly obtained through genome-wide association studies (GWAS), to understand complex traits such as drought tolerance, including yield components and phenology. However, GWAS has limitations that artificial intelligence (AI) has been shown to partially overcome. Additionally, AI and its explainable variants, which ensure transparency and interpretability, are increasingly being used as recognised problem-solving tools throughout the breeding process. Given these rapid technological advancements, this review provides an overview of state-of-the-art methods and processes underlying each MAS, from phenotyping, genotyping and association analyses to the integration of explainable AI along the entire workflow. In this context, we specifically address the challenges and importance of breeding winter wheat for greater drought tolerance with stable yields, as regional droughts during critical developmental stages pose a threat to winter wheat production. Finally, we explore the transition from scientific progress to practical implementation and discuss ways to bridge the gap between cutting-edge developments and breeders, expediting MAS-based winter wheat breeding for drought tolerance.

Feature engineering of environmental covariates improves plant genomic-enabled prediction.

Introduction: Because Genomic selection (GS) is a predictive methodology, it needs to guarantee high-prediction accuracies for practical implementations. However, since many factors affect the prediction performance of this methodology, its practical implementation still needs to be improved in many breeding programs. For this reason, many strategies have been explored to improve the prediction performance of this methodology. Methods: When environmental covariates are incorporated as inputs in the genomic prediction models, this information only sometimes helps increase prediction performance. For this reason, this investigation explores the use of feature engineering on the environmental covariates to enhance the prediction performance of genomic prediction models. Results and discussion: We found that across data sets, feature engineering helps reduce prediction error regarding only the inclusion of the environmental covariates without feature engineering by 761.625% across predictors. These results are very promising regarding the potential of feature engineering to enhance prediction accuracy. However, since a significant gain in prediction accuracy was observed in only some data sets, further research is required to guarantee a robust feature engineering strategy to incorporate the environmental covariates.

Hyperspectral Proximal Sensing for Estimating Photosynthetic Capacities at Leaf and Canopy Scales.

Agronomists, plant breeders, and plant biologists have been promoting the need to develop high-throughput methods to measure plant traits of interest for decades. Measuring these plant traits or phenotypes is often a bottleneck since skilled personnel, resources, and ample time are required. Additionally, plant phenotypic traits from only a select number of breeding lines or varieties can be quantified because the "gold standard" measurement of a desired trait cannot be completed in a timely manner. As such, numerous approaches have been developed and implemented to better understand the biology and production of crops and ecosystems. In this chapter, we explain one of the recent approaches leveraging hyperspectral measurements to estimate different aspects of photosynthesis. Notably, we outline the use of hyperspectral radiometer and imaging to rapidly estimate two of the rate-limiting steps of photosynthesis: the maximum rate of the carboxylation of Rubisco (Vcmax) and the maximum rate of electron transfer or regeneration of RuBP (Jmax).

Effects of trimer repeats on Psidium guajava L. gene expression and prospection of functional microsatellite markers.

Most research on trinucleotide repeats (TRs) focuses on human diseases, with few on the impact of TR expansions on plant gene expression. This work investigates TRs' effect on global gene expression in Psidium guajava L., a plant species with widespread distribution and significant relevance in the food, pharmacology, and economics sectors. We analyzed TR-containing coding sequences in 1,107 transcripts from 2,256 genes across root, shoot, young leaf, old leaf, and flower bud tissues of the Brazilian guava cultivars Cortibel RM and Paluma. Structural analysis revealed TR sequences with small repeat numbers (5-9) starting with cytosine or guanine or containing these bases. Functional annotation indicated TR-containing genes' involvement in cellular structures and processes (especially cell membranes and signal recognition), stress response, and resistance. Gene expression analysis showed significant variation, with a subset of highly expressed genes in both cultivars. Differential expression highlighted numerous down-regulated genes in Cortibel RM tissues, but not in Paluma, suggesting interplay between tissues and cultivars. Among 72 differentially expressed genes with TRs, 24 form miRNAs, 13 encode transcription factors, and 11 are associated with transposable elements. In addition, a set of 20 SSR-annotated, transcribed, and differentially expressed genes with TRs was selected as phenotypic markers for Psidium guajava and, potentially for closely related species as well.

Data Augmentation Enhances Plant-Genomic-Enabled Predictions.

Genomic selection (GS) is revolutionizing plant breeding. However, its practical implementation is still challenging, since there are many factors that affect its accuracy. For this reason, this research explores data augmentation with the goal of improving its accuracy. Deep neural networks with data augmentation (DA) generate synthetic data from the original training set to increase the training set and to improve the prediction performance of any statistical or machine learning algorithm. There is much empirical evidence of their success in many computer vision applications. Due to this, DA was explored in the context of GS using 14 real datasets. We found empirical evidence that DA is a powerful tool to improve the prediction accuracy, since we improved the prediction accuracy of the top lines in the 14 datasets under study. On average, across datasets and traits, the gain in prediction performance of the DA approach regarding the Conventional method in the top 20% of lines in the testing set was 108.4% in terms of the NRMSE and 107.4% in terms of the MAAPE, but a worse performance was observed on the whole testing set. We encourage more empirical evaluations to support our findings.