Theoretical and Applied Genetics

Multi-trait genomic prediction offers a practical route to improve selection for costly, complex traits in clonally propagated crops such as cassava. In a Brazilian breeding panel of 1,078 cassava clones genotyped with 25,923 SNPs and phenotyped for six agronomic traits, we compared single-trait (ST) and multi-trait (MT) GBLUP models. Stage-wise mixed models produced BLUEs that fed into ST and MT-GBLUP. We tested five cross-validation schemes that mimic breeder realities: ST baseline (CV1); naive all-traits MT prediction for unphenotyped candidates (CV2); MT prediction using auxiliary trait phenotypes in the test set (CV3); and two sparse-phenotyping regimes with missingness by trait (CV4) or by clone (CV5) at 25%, 50%, and 75% levels. The main results were that, under the ST baseline (CV1), predictive ability ranged from 0.50 for DMC and 0.45 for FRY down to 0.13 for Le.Dis. A naive full MT model (CV2) performed approximately on par with ST-GBLUP. In contrast, MT designs (CV3) that included informative auxiliary traits, such as shoot yield and combinations with plant vigor and leaf disease severity, yielded small gains for DMC with predictive ability of approximately 0.51 (+2%), while FRY predictive ability increased to approximately 0.65 (+44%), accompanied by RMSE reductions for FRY up to approximately 13.5% (e.g. RMSE approximately 6.2). Sparse-phenotyping simulations (CV4/CV5) demonstrated that MT models sustain or even improve predictive ability under realistic missing-data regimes (PA {approx} 0.62 - 0.65). Selection concordance between MT and ST top-10% sets was generally high (>0.80), and MT configurations produced measurable improvements in expected selection response and genetic gain per cycle for several target traits. These results indicate that strategically implemented MT-GBLUP, using a small set of biologically and operationally informative auxiliary traits and optimized sparse phenotyping, can materially increase predictive accuracy and selection efciency for economically critical cassava traits while reducing phenotyping burden.

Background: Germplasm collections contain wide genetic diversity that is valuable for plant breeding, but conducting phenotypic evaluation for all genotypes in field trials is rarely feasible. Bayesian optimization offers a way to decide, season by season, which genotypes to cultivate in order to identify superior genotypes with fewer evaluations. However, standard Bayesian optimization commonly starts from randomly selected genotypes and mainly relies on surrogate models built from marker genotype information, while the text-based passport information that accompanies germplasm is not fully used. We examined whether pre-trained large language models can provide prior knowledge that improves these decisions in germplasm evaluation. Results: We constructed a large-language-model-guided Bayesian optimization framework that introduces large language models into two parts of the Bayesian optimization workflow. In zero-shot warmstarting, a large language model proposes initial genotypes using passport information such as cultivar name, country of origin, and subpopulation, optionally together with principal component scores derived from genome-wide single-nucleotide-polymorphism markers. In addition, we evaluated a large-language-model-based surrogate model that predicts phenotypic values for untested genotypes using in-context learning from previously evaluated genotypes. Using a rice germplasm panel and two target traits (seed number per panicle for maximization and protein content for minimization), we compared strategies. For seed number per panicle, zero-shot warmstarting with a general-purpose instruction-following model reduced the number of evaluated genotypes needed to reach the best genotype, whereas improvements were small for protein content. When genomic information was available, Gaussian-process-based Bayesian optimization was the strongest overall approach, while the large-language-model-based surrogate model outperformed random baselines and was competitive in some settings. When genomic information was not available, predictions based on passport information improved efficiency compared with fully random strategies. Conclusions: Pre-trained large language models can inject useful agronomic knowledge into Bayesian optimization for germplasm evaluation, particularly by improving early-stage genotype selection, and can also support optimization when genomic information is unavailable. As models better handle long genomic sequences together with passport information, large-language-model-guided Bayesian optimization may become a practical and explainable decision-support approach for agricultural optimization.

Haplotype-based breeding strategies have emerged as promising approaches to maximize long-term genetic gain by identifying complementary parental combinations while maintaining genetic diversity. However, these methods typically require phased genotypes and more intensive workflow pipelines and skillsets. We developed a novel local genomic estimated breeding value (localGEBV) fitness function with similar intent to the optimal haplotype stacking (OHS) framework fitness function and implemented both in the novel R package, HapSelect. Our aim was to evaluate whether phased haplotypes provide additional benefit over the more easily available dosage-based unphased genotypes in highly inbred crops. A subset of bread wheat nested association mapping (NAM) population comprising 444 lines genotyped with 6,054 DArT-Seq markers was analysed. Marker effects were estimated using rrBLUP, localGEBV and haplotype effects were calculated across linkage disequilibrium-defined haploblocks, and genetic algorithms (GA) were used to identify optimal sets of 30 founders using either a localGEBV derived fitness function with unphased, dosage inputs or the OHS fitness function with phased inputs. Selected parental sets were compared with conventional truncation selection (TS) through 150 generations of forward simulation. The OHS fitness function achieved a marginally greater optimized ultimate GEBV than the localGEBV fitness function during GA optimization, with only 18 of the 30 selected founders overlapped between the two methods. Despite these differences, forward simulations demonstrated nearly identical long-term genetic gain for localGEBV and OHS-selected founders, with both approaches outperforming conventional truncation selection by maintaining greater genetic diversity and delaying the genetic plateau. The minimal difference between localGEBV and OHS is likely attributable to the high homozygosity of the population, where localGEBV and haplotype effects are nearly confounded. These results demonstrate that dosage-based localGEBV provides a practical alternative to phased haplotype approaches for parent selection in inbred crops, substantially simplifying genomic workflows while maintaining long-term breeding performance. Future work should evaluate these methods in more diverse inbred populations and outbred species, where great haplotypic diversity may increase the advantage of true haplotype-based optimizations.

Lima bean (Phaseolus lunatus) is a broadly adapted, economically important leguminous crop and a susceptible host of root-knot nematodes (Meloidogyne spp.; RKN), which are a devastating plant pathogen in agricultural systems worldwide. To date, there have been few studies to elucidate the genetic determinants of RKN resistance in lima beans. Understanding the genetic mechanisms underlying resistance is essential for improving resistance traits and incorporating them into lima bean breeding programs. To assist in marker-assisted selection, we aimed to identify and map quantitative trait loci (QTLs) conferring RKN resistance-related traits. Three recombinant inbred line (RIL) populations were used in this study. Three populations were derived by crossing two RKN-resistant parents with the same RKN-susceptible parent and with each other. All populations were genotyped using genome-wide single-nucleotide polymorphism (SNP) markers. Each population was screened for root galling (RG) and RKN egg reproduction (ER) in response to M. incognita and M. javanica in greenhouse experiments. Three major QTLs were detected and mapped on chromosome Pl04 (QRk-pl04.1), Pl05 (QRk-pl05.1) and Pl10 (QRk-pl10.1) across populations. Among them, QRk-pl05.1 and QRk-pl10.1 affected levels of RG and ER of both RKN species, while QRk-pl04.1 suppressed root galling and reproduction responses of M. incognita but not of M. javanica. These chromosomal regions defined by flanking markers will help guide marker-assisted breeding and gene discovery for broad-based RKN resistance in lima beans.

Nitrogen-use efficiency (NUE) is a pivotal breeding target in tomato (Solanum lycopersicum L.) to sustain production under reduced N inputs. Here, we leveraged a recently developed tomato multi-parent advanced generation inter-cross (ToMAGIC) population to identify lines with superior performance under reduced N availability. The eight founders and a core subset of 118 ToMAGIC lines were characterized with 10,684 SNP markers and evaluated under optimal (opN, 15 mM) and suboptimal (subN, 8 mM) N supply in an experiment totalling 1,576 plants, generating 48,068 data points across 61 phenotypic variables. Under both N treatments, ToMAGIC lines exhibited transgressive segregation for most traits, confirming the value of this population as a reservoir of untapped variation. Notably, under subN conditions, harvest index (Hi) increased by 29-44%, suggesting adaptive resource redistribution toward reproductive sinks. Variance partitioning revealed that agronomic and NUE-related traits were largely under genetic control, with heritability estimates frequently above 0.80 and broadly conserved across N treatments. Multivariate trait analysis identified fruit yield N concentration (NUE component, CN,y), shoot biomass N content (NAb), and shoot growth-related traits as the main drivers of treatment differentiation. Finally, proxy traits were prioritized by integrating response magnitude, heritability, trait correlations, and treatment-discriminatory power into multi-trait selection indices. This strategy generated favorable predicted genetic gains, reaching 158% for high-performance lines and 170% for subN-adapted lines, and consistently identified lines 402, 428, 518, 800, and 816 as promising pre-breeding materials. Overall, this study supports ToMAGIC as a powerful resource for developing N-efficient cultivars suited for sustainable agriculture.

Multi-environment trials are central to cultivar evaluation because they reveal how candidate cultivars perform across locations, years, management conditions, and stress environments. The resulting yield matrix is a rich source of data on genotype-by-environment interaction, and a wide literature on estimation, decomposition, visualisation, and prediction of yield potential and stability has flourished. However the ultimate question of which cultivar to recommend on the basis of such a matrix is often left implicit. The question is far from trivial, and in this paper we formulate cultivar recommendation as an axiomatic ranking problem. This framework is rich enough to encompass the existing literature on stability indices, as well as any other deterministic ranking procedure. We show that many commonly used stability-based procedures can violate minimal criteria of efficiency or consistency. The result of such violations is that a cultivar with uniformly high yield could be ranked below a cultivar with uniformly low yield, or the relative ranks of two cultivars could depend on whether or not a third cultivar is present in the matrix. Our results prove that under a small number of such criteria the space of admissible rules collapses to the family of power means and their limiting cases. If we further wish to allow multiplication normalisation of yield, we are left with the geometric mean as the unique solution.

Celiac disease (CeD) is an immune-mediated condition triggered by wheat gluten in genetically predisposed individuals. The immune reaction in people with CeD is driven by particular gluten amino acid sequences, or immunogenic epitopes. Some of these epitopes elicit strong immune responses in the majority of CeD patients and are designated as immunodominant epitopes. Previous research has shown correlations between the amount of immunogenic wheat epitopes consumed and the onset of CeD, suggesting that reducing wheat immunogenic epitopes may reduce CeD incidence at the population level. Gluten consists of gliadins and glutenins, with gliadins having the majority of the immunodominant epitopes and glutenins playing a major role in dough strength and breadmaking quality (BMQ). This study used radiation-induced deletions, chemical mutagenesis, and natural variation in wheat (Triticum aestivum) to generate genetic stocks with reduced immunogenic epitope content. Most lines were developed in the wheat cultivar Summit, for which we produced a full genome assembly and annotation. We used exome capture to characterize these deletions and identify prolamins located within and outside the deletions. We combined different deletions and developed molecular markers to facilitate their deployment. For chromosome arms 1BS and 1DS, we generated two alternative lines: one lacking immunogenic epitopes for the development of CeD-safe genetic stocks for research purposes, and another retaining selected glutenins for breeding commercial lines with reduced immunogenicity and adequate BMQ. By making these non-transgenic genetic stocks publicly available, we aim to accelerate the development of wheat varieties with reduced immunogenicity and, eventually, a fully CeD-safe wheat.

In plant breeding and genetics, recent advances in high-throughput phenotyping are beginning to meet the growing demand for large-scale, high-quality phenotypic data that emerged after the development of next-generation sequencing technologies. Recent developments in phenomics have been incorporated into almond breeding programs, facilitating the large-scale acquisition of quantitative phenotypes and the dissection of the genetic architecture underlying morphological and quality-related traits. The implementation of a high-throughput phenotyping platform integrating RGB and hyperspectral imaging with genotyping using the 60K almond SNP array enabled the large-scale characterization of almond populations and the identification of 567 robust marker-trait associations across 66 traits. These analyses revealed two major genomic hotspots on chromosomes 2 and 5 associated with morphological and quality-related traits. These regions harbored biologically relevant candidate genes, including genes associated with OVATE family proteins, brassinosteroid signaling, protein ubiquitination, and acyl-CoA metabolism, as well as other regulators of organ growth, cell proliferation, hormone signaling, and seed development. Furthermore, a novel candidate gene encoding a COMT-like O-methyltransferase involved in lignin biosynthesis was identified and proposed to contribute to shell hardness, a major genetically controlled trait in almond. Together, these findings demonstrate the potential of integrating high-throughput phenomics and genomics to dissect complex traits, identify candidate genes, and accelerate genomics-informed breeding in almond.

Metribuzin is a versatile herbicide effective against various annual grasses and broadleaf weeds found in wheat fields. However, it can cause foliar damage to wheat, impacting plant health and yield. A clearer understanding of the genetic architecture associated with metribuzin tolerance is necessary to guide marker-based breeding strategies. This study evaluated 351 historic Gulf Atlantic Wheat Nursery (GAWN) wheat breeding lines representative of southern US soft red winter wheat (SRWW) germplasm. Field trials were conducted at Winnsboro (WN) and Baton Rouge (BR), Louisiana, in 2016 and 2017. Metribuzin was applied at specific growth stages[DN1.1], and tolerance was assessed based on visual foliar damage. Genomic data from 6,252 filtered single nucleotide polymorphism (SNP) markers were used to estimate narrow-sense heritability, conduct genome-wide association (GWAS), and assess genomic prediction accuracy using genomic best linear unbiased prediction (GBLUP). Broad-sense heritability ranged from 0.54 to 0.69 within environments and reached 0.77 across environments, while narrow-sense heritability ranged from 0.35 to 0.47, indicating moderate additive genetic control. No SNP surpassed the significance threshold, but genomic prediction (GP) showed moderate to strong predictive ability (PA) across environments, with the highest accuracy (r = 0.62) observed between BR17 and WN17. These results indicate that metribuzin tolerance in SRWW is primarily controlled by multiple small-effect loci and that GS provides a more effective breeding strategy than marker-assisted selection for improving tolerance in southern wheat germplasm.

AbstractTomato production faces a persistent challenge from the tomato leaf miner, Phthorimaea absoluta, a pest that severely limits yields while effective resistance in cultivated varieties remains scarce. To address this gap, wild tomato relatives represent a promising reservoir of resistance traits. In this study, 24 tomato accessions, including both cultivated types and wild species, were evaluated under greenhouse (no-choice) and tunnel (choice) conditions. Resistance mechanisms were characterized through measures of antibiosis such as leaflet lesion type, proportion of attacked leaflets, and mine density. The results revealed substantial variation between and within species, allowing classification of accessions into resistant, intermediate, and susceptible groups through multivariate analysis. Notably, the wild accession Solanum habrochaites PI248707 exhibited strong resistance, in contrast to susceptible cultivated varieties such as Rose de Berne. Under choice conditions, PI248707 sustained limited damage and disrupted larval development, with early instar larvae present but few reaching advanced stages, indicating an inhibitory defense response. Untargeted metabolomic profiling further highlighted pronounced constitutive differences between wild and cultivated accessions, with S. pennellii and S. habrochaites displaying higher metabolic diversity. By integrating phenotypic and metabolic data, specific metabolite classes associated with resistance were identified. These findings underscore the potential of wild tomato germplasm in breeding programs, with PI248707 standing out as a strong candidate for resistance introgression.

Far-red light (FR; 700-750 nm) is increasingly incorporated into controlled-environment lighting because it can improve photosynthetic efficiency when combined with comparatively shorter wavelengths. In long-day leafy crops such as spinach, however, FR may also promote the transition from vegetative to reproductive growth and thereby reduce marketable yield. Most studies have evaluated FR fraction, intensity or end-of-day exposure, whereas the developmental timing of FR has rarely been tested, particularly in spinach. Here, we evaluated six commercial spinach cultivars (Amador, Harp, Renegade, Responder, Rubino and Santa Cruz) in an indoor vertical farm under a common red-green-blue background (PPFD 260-264 {micro}mol m-{superscript 2} s-{superscript 1}, 12 h photoperiod, 24 {degrees}C) and four FR timing treatments: no FR (Control), FR throughout production (FullFR), FR during early development only (EarlyFR), and FR during late development only (LateFR). LateFR increased marketable fresh weight relative to Control (244 vs 224 g) and reduced flowering incidence, whereas far-red supplied during early development reduced fresh weight (158 g) and increased flowering. The magnitude of the timing response differed among cultivars: switching from EarlyFR to LateFR recovered 0 % fresh weight in Amador but 107 % in Renegade and Rubino, with the largest penalties occurring in otherwise bolt-resistant cultivars. EarlyFR also increased total chlorophyll and reduced the chlorophyll a:b ratio. These results show that FR response in spinach is strongly conditioned by developmental stage and cultivar. Although LateFR received more total far-red than EarlyFR, it behaved like the Control, indicating that the penalty was set by far-red timing rather than dose. Treatment differences in bolting and yield tracked an estimated phytochrome photostationary-state deficit during early development: a phytochrome-deficit model markedly outperformed a cumulative-dose model ({Delta}AIC = 441), and the deficit x cultivar interaction was strong (p < 0.001), with bolt-resistant cultivars losing most yield when far-red coincided with the early developmental window. We therefore propose that FR should be treated as a genotype-dependent management variable rather than as a fixed spectral input, with late application and bolt-resistant cultivars offering the most favourable combination for vertical-farm spinach production. Framed within the breeders equation, the close match between the trial and production environment and the scope for shorter breeding cycles indoors suggest that genotype and far-red timing can be optimised jointly to accelerate genetic gain.

Globe artichoke (Cynara cardunculus var. scolymus L.) comprises a broad range of local ecotypes and varietal groups whose genetic diversity has been investigated through different molecular markers. However, recent advances in next-generation sequencing and pangenomics approaches provide new opportunities to capture genome-wide variation at higher resolution and to develop practical tools for varietal discrimination, traceability, and germplasm conservation. In this study, we developed the first pangenomic framework for cultivated artichoke and evaluated pangenome-informed SNP markers for varietal fingerprinting. Whole-genome resequencing data from the Italian local ecotype Asti Sori were integrated with publicly available genomic data from representative globe artichoke and cultivated cardoon accessions to construct and annotate a pangenome. Genome-wide SNP and presence/absence variation (PAV) analyses were combined with pangenome-anchored genotyping-by-sequencing (GBS) data from 45 accessions representing the main cultivated varietal groups. The pangenome revealed a largely conserved core gene repertoire alongside a smaller accessory component, with gene accumulation curves suggesting a tendency toward saturation within the sampled cultivated germplasm. SNP- and PAV-based analyses provided complementary views of accession relationships and consistently resolved the principal cultivated groups. Across the broader germplasm panel, pangenome-anchored GBS-derived SNPs identified well-supported phylogenetic clusters corresponding to recognized varietal types. A reduced panel of 50 SNPs, selected through iterative random subsampling, retained at least 90% of the genetic diversity captured by the full dataset and reproduced its main population structure. This compact pangenome-anchored marker set provides a practical foundation for varietal fingerprinting, DUS-oriented applications, traceability, and conservation of traditional globe artichoke germplasm. Validation across independent collections will be required before routine deployment.

The availability of pangenome and resequencing of wheat collections have facilitated the discovery of gene-trait associations in wheat. Yellow stripe-like (YSL) proteins play a key role in the uptake and translocation of metals and yet have not been fully identified and analyzed at the genome-wide level in wheat. In this study, 26 TaYSL genes were identified and divided into four distinct clades, each clade sharing similar domains and motif compositions. Most genes were upregulated under iron deficiency, whereas homoeologs of TaYSL1 were downregulated. Both SNP-based and haplotype-based association studies were used to dissect the role of TaYSLs underpinning grain iron contents (GFeC) and zinc contents (GZnC) in wheat. TaYSL6-2B and TaYSL16-1A haplotypes showed strong association with GFeC, and TaYSL14-6A showed strong association with GZnC in multiple field trials. The distribution of favorable haplotypes in global wheat collection of [~]3000 accessions showed that majority of haplotypes were more prevalent in landraces and winter wheat compared to modern cultivars and spring types, indicating their potential for use in breeding. The combination of favorable haplotypes of three YSL genes associated with GFeC and GZnC were very rare, and most of the wheat accessions has single or double favorable haplotypes. These findings provide the first comprehensive characterization of the TaYSL gene family in wheat and identify significant SNPs and elite haplotypes that can be utilized for genetic improvement and biofortification.

Background. DNA-based molecular markers underpin plant genetic diversity assessment, germplasm characterisation, and conservation prioritisation. Four marker systems dominate the field: Amplified Fragment Length polymorphisms (AFLPs), simple sequence repeats (SSRs), single nucleotide polymorphisms (SNPs), and random amplified polymorphic DNA (RAPDs). No quantitative meta-analysis had pooled their performance on the canonical diversity metrics: polymorphism information content (PIC), expected heterozygosity (He), and resolution power, across plants. Existing reviews are narrative, marker-restricted, or qualitatively conclusive of infeasibility. Methods. A PRISMA 2020-compliant systematic review (registered at the Open Science Framework) was executed. Eligible studies were within-study paired comparisons genotyping the same accession panel with at least two of {SNP, SSR, AFLP, RAPD} and reporting at least one diversity metric. Effect sizes were paired standardised mean differences (Hedges' g) computed under the Bernoulli-variance approximation. Random-effects REML meta-analysis used metafor 5.0.1 with Knapp-Hartung adjustment, leave-one-out, and r-sensitivity. Results. Fifteen within-study paired contrasts were eligible, distributed across three pools. Pool 2 (SSR vs SNP, He, k = 5) yielded a pooled Hedges' g of 0.494 (95% CI: -0.078 to 1.066, p = 0.075; I-squared = 90.2%; 95% PI [-0.82, 1.81]). SSRs exceeded SNPs on He in 4 of 5 studies; leave-one-out removal of the panel-size-asymmetric outlier raised the estimate to g = 0.644 (p = 0.025). Pool 3a (dominant-marker stratum, k = 6) yielded g = 0.419 (95% CI: -0.121 to 0.960, p = 0.103; I-squared = 56.5%); five of six contrasts showed SSR or AFLP exceeding RAPD on per-locus PIC. Pool 1 (PIC, k = 3, exploratory) gave a consistent direction (g = 0.453). All three pools point in the same direction: codominant or AFLP markers carry more per-locus information than the alternative being compared. Conclusions. SSR markers reported higher per-locus diversity than SNP and RAPD markers in plant within-study paired comparisons, mechanistically grounded in the SNP biallelic ceiling and the multi-allelic richness of SSRs. The effect attenuated or reversed in selfing/low-diversity panels and at the per-panel level when SNP panels exceeded approximately 1000 loci. RAPDs show the lowest per-locus information content of the four classes.

Light leaf spot (LLS), caused by subcuticular hemibiotrophic ascomycete fungus Pyrenopeziza brassicae, is a major constraint on oilseed rape (Brassica napus) production, yet the genetic and biochemical mechanisms of quantitative disease resistance (QDR) remain poorly defined. Here, disease phenotyping, pathogen quantification, microscopy, gene expression profiling and glucosinolate (GSL) analysis were integrated to dissect resistance mechanisms in B. napus. Disease assays of 19 diverse lines revealed clear contrasts between susceptible and resistant genotypes, with the commercial cultivar Ambassador showing a phenotype inconsistent with the UK Recommended List rating. Microscopy demonstrated that resistance within doubled haploid line Cubs Root does not inhibit spore germination or penetration but restricts hyphal branching and subcuticular colonisation from 4 to 8 days post-inoculation. Expression profiling of seven candidate gene expression markers (GEMs) and pathogenesis-related PR1 showed that cinnamate-4-hydroxylase, phospholipase C4, {beta}-adaptin, universal stress protein and the 40S ribosomal subunit protein S24 were strongly pathogen-induced in resistant lines, whereas a BAHD acyltransferase, a putative susceptibility factor, was induced only in susceptible cultivars. GSL profiling identified negative correlations between disease severity and total GSLs, particularly aliphatic and aromatic GSLs, with 2{square}phenylethyl and 7-methylsulfinyl heptyl GSLs showing the strongest associations with resistance. Together, these results highlight coordinated transcriptional and metabolic responses that limit pathogen proliferation and provide targets for breeding durable LLS resistance in B. napus.

Applications of tissue culture are critical for Cannabis sativa L. (cannabis), supporting clonal propagation, germplasm preservation, pathogen elimination, among other biotechnological applications. However, extensive genetic diversity associated with cannabis results in highly variable responses to in vitro conditioning, and no consensus basal media formulation exists to support reproducible micropropagation across genotypes. To address these limitations, a hybridized ensemble-NSGA-II approach was employed for concurrent optimization of individual media components to create a species specific, cultivar inclusive basal salt formulation for cannabis micropropagation. The resulting PHJ media represents a unique formulation that overcomes recalcitrance across a wide array of cannabis cultivars, facilitating improved growth and uniformity for the nine cultivars used in its development and validation. These results remain consistent from explant initiation through multiple rounds of subculture. The ability of PHJ to overcome genotypic recalcitrance is telling of its potential applicability with an array of plant species beyond cannabis. Additionally, robust performance both with and without plant growth regulators underscores the plausible use of PHJ for diverse applications beyond standard micropropagation. Ultimately, this cultivar-inclusive basal medium demonstrates utility for both scientific research and industrial-scale operations.

Flax (Linum usitatissimum L.) has been domesticated for dual end uses as linseed and fiber flax, yet the genomic basis of morphotype divergence remains unclear. Here, we constructed a morphotype-resolved pangenome by integrating three newly generated near telomere-to-telomere genome assemblies with 14 previously published ones. Despite substantial variation in assembly size, driven primarily by DNA transposons, gene content was highly conserved, with little evidence for significant morphotype-specific gene presence-absence variation. Population genomic analyses of 407 accessions revealed that fiber flax had reduced nucleotide diversity, extended linkage disequilibrium, and a more compact population structure relative to linseed, consistent with stronger selection and a narrower genetic base. Genome-wide differentiation was heterogeneous and concentrated in discrete regions. Integration of FST, nucleotide diversity ratios, Tajimas D, and genome-wide association signals identified morphotype-enriched genomic blocks distributed across the genome. Many candidate regions are primarily supported by directional shifts in nucleotide diversity rather than extreme differentiation, indicating selection on standing genetic variation. Genome-wide association analyses identified 1,712 unique quantitative trait nucleotides (QTNs), with predominantly small effect sizes and strong enrichment in gene-proximal regions, consistent with a polygenic architecture. Overall, fiber flax traits tend to be controlled by fewer loci with moderate-to-large effects, whereas linseed traits exhibit a more diffuse genetic architecture. Patterns of Tajimas D further support non-classical selection dynamics, with predominantly positive values in linseed and localized negative values in fiber flax, consistent with selection on standing genetic variation. Together, our results suggest that flax morphotype divergence is driven primarily by selection on pre-existing allelic variation within a conserved gene repertoire. This study provides a comprehensive framework linking genome structure, population genomics, and trait architecture, and highlights the importance of standing genetic variation as a key resource for flax breeding and improvement.

O_LIHybridisation is frequently associated with plant invasions; however, its consequences for genome organisation and chromosome evolution remain poorly understood in invasive species. We investigated the extent of hybridisation in the invasive Carpobrotus edulis--acinaciformis hybrid complex and determined the cytogenomic contribution of parental species in hybrid accessions. C_LIO_LIWe combined whole-genome sequencing, population genomic analyses, genome size estimation, repeatome characterisation, chromosome counting and fluorescence in situ hybridisation to compare parental species and hybrid accessions from South Africa and the Mediterranean Basin. C_LIO_LIPopulation genomic analyses revealed widespread hybridisation and introgression, with most invasive accessions showing admixed ancestries. Pattersons D-statistic supported asymmetric allele sharing towards C. edulis. Hybrid accessions displayed genome sizes indistinguishable from C. edulis, whereas C. acinaciformis possessed significantly larger genomes. Repeatome analyses identified marked differences in repetitive DNA composition, particularly in satellite DNA abundance and chromosomal distribution. A newly identified satellite repeat (CarpoSat) showed contrasting chromosomal patterns between parental species, whereas hybrids resembled C. edulis satellite pattern. C_LIO_LIOur results demonstrate that Carpobrotus hybrid accessions are a swarm of later-generation hybrids and backcrosses showing a strong bias towards C. edulis, indicating asymmetric introgression. These findings highlight the value of integrating cytogenetic and genomic approaches to understand genome evolution in invasive hybrid complexes. C_LI

Bacterial leaf blight (BB), caused by Xanthomonas oryzae pv. oryzae (Xoo), causes yield losses exceeding 50% in affected areas, including the Bagre rice plain in Burkina Faso. Genome-edited (GEd) rice lines have been successful in tackling BB. Modifications in the Xoo virulence protein target site upstream of three SWEET susceptibility genes in two elite rice varieties, IR64 and Ciherang-Sub1, have been demonstrated to confer broad-spectrum resistance to Asian and East African Xoo strains. Here, we evaluate the potential of the GEd lines as a solution for BB management in Burkina Faso. We challenged the GEd lines against five locally collected Burkinabe Xoo strains under controlled green-house conditions and assessed their agro-morphological performance under field conditions representative of local agroecological conditions. Greenhouse pathogen assays demonstrated that GEd IR64 and Ciherang-Sub1 lines were resistant to all tested local Xoo strains across three successive generations. We identified TalC as the primary disease-causing effector in the local Xoo populations. Irrigated field trials conducted over two seasons in the Kou Valley, Burkina Faso, revealed absence of agro-morphological penalties in GEd lines compared to their parental wild-type lines. Observed trait variation was attributable to environmental fluctuations rather than genomic modifications. Collectively, our findings demonstrate that genome editing of the rice lines does not impose growth penalties, and support the suitability of GEd IR64 and Ciherang-Sub1 for large-scale adoption in Burkina Faso, pending multi-location validation and introgression into locally adapted varieties.

Rising winter temperatures threaten deciduous fruit tree productivity by depleting carbohydrate reserves during dormancy. This study investigated Stem Photosynthetic Capacity (SPC), a rare adaptive trait from wild Prunus arabica, as a mechanism to enhance almond carbon economy. Using extreme segregating groups from the F1 population (P. dulcis X P. arabica), we evaluated physiological performance through high-resolution lysimetric and multi-year orchard monitoring. High-SPC [SPC(+)] genotypes maintained significantly greater stem CO2 assimilation and transpiration during leafless periods compared to low-SPC [SPC(-)] progenies. Over five successive seasons, SPC(+) trees exhibited a 33.3% increase in trunk secondary growth and reached 10% bloom approximately 8 days earlier. Most importantly, the SPC(+) group achieved a 4.6-fold increase in mean kernel yield when compared to SPC(-) group. These findings demonstrate that SPC provides a flexible, supplementary winter carbon source that directly supports both vegetative and reproductive development. Integrating SPC into commercial almond breeding programs may offer a valuable strategy to improve climate resilience and help sustain yields under warming conditions. HighlightIntegrating stem photosynthesis into commercial almond hybrids provides a winter carbon source that advances blooming, expands trunk growth by [~]33%, and increases kernel yields by more than 4.5-fold.