Theoretical and Applied Genetics

Scald, caused by the fungus Rhynchosporium graminicola Heinsen 1897, is a major foliar disease in winter malting barley (Hordeum vulgare L). Resistance to scald in winter malting barley is controlled by major and minor resistance genes. We used a large population of lines derived from biparental crosses among five winter malting barley parents to analyze resistance to scald and associated agronomic traits. Increased winter survival and later heading dates were negatively correlated with increased resistance, whereas increased height was positively correlated with resistance. A genome-wide association study (GWAS) for resistance to scald was analyzed with multiple models, using 15,463 SNPs. The similarities and differences between the models were identified in SNP trait associations and phenotypic effect sizes. SNP associations identified a large region on chromosome 3H across models. FarmCPU identified additional associations on chromosomes 2H, 3H, and 4H. Linkage disequilibrium on chromosome 3H and GWAS for resistance to scald using the Rrs1-linked marker, HVS3, as a covariate confirmed Rrs1 was segregating in this population. GWAS for winter survival, heading date and plant height identified associations across the genome, with chromosome 2H showing SNP-trait colocalizations between resistance to scald, winter survival, heading date and plant height. Breeding for durable resistance to scald in winter malting barley can include pyramiding major resistance loci, such as Rrs1, as well as QTL for disease resistance and agronomic traits. PLAIN LANGUAGE SUMMARYO_ST_ABSGenetic architecture of resistance to scald in winter malting barleyC_ST_ABSScald is an important foliar pathogen in winter malting barley, affecting both grain yield and quality. While resistance to scald is controlled by major and minor resistance genes, agronomic traits are also known to limit the spread of scald in barley. We determined the genetic architecture using a large multiparent population of winter malting barley. The FarmCPU genome-wide association model proved optimal for defining the resistance genes, with the major resistance gene, Rrs1, conferring 27% of the variation in this population. Fewer days to heading and taller plants contributed to plant avoidance of scald. Reduced canopy coverage in plants with low winter survival led to less scald severity. A region of the genome contributing a minor resistance effect was co-localized with a region for plant height, heading date and winter survival. Core IdeasO_LIResistance to scald in a large multiparent population was derived from a major resistance gene (Rrs1) and several smaller effect QTLs C_LIO_LIRrs1 resistance was derived from Lightning and is located within a large linkage block on Chromosome 3H C_LIO_LIFewer days to heading and taller plants were correlated with less disease in a large multiparent winter malting barley population in NY state C_LIO_LIA QTL for resistance to scald co-localized on chromosome 2H with winter survival, heading date, and plant height C_LIO_LIFarmCPU was an optimal model for association analysis for resistance to scald in the large unbalanced diallel population. C_LI

Introducing variations in inflorescence architecture, such as the Miracle-Wheat (Triticum turgidum convar. compositum (L.f.) Filat.) with a branching spike, has relevance for enhancing wheat grain yield. However, in the spike-branching genotypes, the increase in spikelet number is generally not translated into grain yield advantage because of reduced grains per spikelet and grain weight. Here, we investigated if such trade-offs might be a function of source-sink strength by using 385 RILs developed by intercrossing the spike-branching landrace TRI 984 and CIRNO C2008, an elite durum (T. durum L.) cultivar; they were genotyped using the 25K array. Various plant and spike architectural traits, including flag leaf, peduncle and spike senescence rate, were phenotyped under field conditions for two consecutive years. On Chr 5AL, we found a new modifier QTL for spike-branching, branched headt 3 (bht-A3), which was epistatic to the previously known bht-A1 locus. Besides, bht-A3 was associated with more grains per spikelet and a delay in flag leaf senescence rate. Importantly, favourable alleles viz., bht-A3 and grain protein content (gpc-B1) that delayed senescence are required to improve grain number and grain weight in the spike-branching RILs. In summary, achieving a balanced source-sink relationship might minimise grain yield trade-offs in Miracle-Wheat. HIGHLIGHTGenetic interplay between sink number and post-anthesis source activity limits grain yield in the spike-branching Miracle-Wheat.

The competitive ability of domesticated plants, which may have conferred a fitness advantage in the wild, may result in a reduction of yield in agricultural and forestry contexts, as what matters is the group rather than the individual performance. Traits related to competitive ability can be affected by the presence or absence of related individuals in their neighborhood. Consequently, local relatedness might reveal plant-to-plant interaction that can enhance the predictive abilities of genomic models when accounted for, though it remains difficult to measure. To overcome this difficulty, we analyzed data from the French breeding program of Populus nigra L., where 1,452 genotypes were replicated six to eight times, each time encountering a different neighborhood. We assessed local relatedness and investigated genomic estimated breeding values on tree height and vulnerability to rust with a single-step GBLUP incorporating local relatedness as a covariate. The results indicate that incorporating local relatedness as an additional factor in GBLUP models has a significantly greater influence on resistance to rust than on tree height, though its overall effect on genomic predictions themselves was limited. The influence of local relatedness is small but likely trait-specific, and the genetic architecture of the trait under selection could attenuate or improve the efficacy of breeding for group performance.

Multiple studies have identified genes affecting grain morphology, yet their capacity to deliver yield gains under field conditions remains unclear. We performed a multiyear, multilocation factorial evaluation of GRAIN WIDTH2 (TaGW2) mutants in hexaploid wheat using BC4 near-isogenic lines, sowing-density treatments and semi-dwarfing RHT1 backgrounds. Loss-of-function mutations in TaGW2 increased grain size and thousand grain weight (TGW) additively; with the aaBBDD single mutant showing the most stable singlelocus effect, while the aabbdd triple mutant achieved ~20% higher TGW across twelve field trials. However, overall grain yield remained unchanged or slightly reduced, reflecting a compensatory trade-off with grain number. Spike phenotyping of both main and secondary tillers showed comparable increases in TGW and spike yield despite fewer grains per spike, indicating that limited yield gain primarily reflects reduced spike number per unit area rather than decreased spike-level productivity. Effects were stable across sowing densities, whereas interactions with semi-dwarfing alleles were allele-specific: RHT-B1b partially suppressed TGW gains and accentuated yield penalties, whereas RHT-D1b maintained the large-grain phenotype and productivity. Across experiments, the TaGW2-A1D1 double mutant increased TGW (~14%) while maintaining yield stability, identifying it as a promising genotype for breeding. We conclude that TaGW2 is a reliable modifier of grain size but not yield in isolation.

Rice breeding programs globally have worked to release increasingly productive and climate-smart cultivars, but the genetic gains have been limited for some reasons. One is the capacity for field phenotyping, which presents elevated costs and an unclear approach to defining the number and allocation of multi-environmental trials (MET). To address this challenge, we used soil information and ten years of historical weather data from the USA rice belt, which was translated into rice response based on the rice cardinal temperatures and crop stages. Next, we eliminated those highly correlated Environmental Covariates (ECs) (>0.95) and applied a supervised algorithm for feature selection using two years of data (2021-22) and 25 genotypes evaluated for grain yield in 18 representative locations in the Southern USA. To test the trials optimization, we performed the joint analysis using prediction-based models in four different scenarios: I) considering trials as non-related, ii) including the environmental relationship matrix calculated from ECs, iii) within clusters; iv) sampling one location per cluster. Finally, we weigh the trials allocation considering the counties economic importance and the environmental group to which they belong. Our findings show that eight ECs explained 58% of grain yield variation across sites and 53% of the observed GxE. Moreover, it is possible to reduce 28% the number of locations without significant loss in accuracy. Furthermore, the US Rice belt comprises four clusters, with economic importance varying from 13 to 45%. These results will help us better allocate trials in advance and reduce costs without penalizing accuracy.

Spikelet number per spike (SNS) is an important yield component in wheat that determines the maximum number of grains that can be formed in a wheat spike. In wheat, loss-of-function mutations in LEAFY (LFY) or its interacting protein WHEAT ORTHOLOG OF APO1 (WAPO1) significantly reduce SNS by reducing the rate of formation of spikelet meristems. In previous studies, we identified a natural amino acid change in WAPO1 (C47F) that significantly increases SNS in hexaploid wheat. In this study, we searched for natural variants in LFY that were associated with differences in SNS, and detected significant effects in the LFY-B region in a nested association mapping population. We generated a large mapping population and confirmed that the LFY-B polymorphism R80S is linked with the differences in SNS, suggesting that LFY-B is the likely causal gene. A haplotype analysis revealed two amino acid changes P34L and R80S, which were both enriched during wheat domestication and breeding suggesting positive selection. We also explored the interactions between the LFY and WAPO1 natural variants using biparental populations and identified significant interaction, in which the positive effect of the 80S and 34L alleles from LFY-B was only detected in the WAPO-A1 47F background but not in the 47C background. Based on these results we propose that the allele combination WAPO-A1-47F / LFY-B 34L 80S can be used in wheat breeding programs to maximize SNS and increase grain yield potential in wheat. Key messageSpecific combinations of LFY and WAPO1 natural alleles maximize spikelet number per spike in wheat.

The genetics of interspecific groups remains largely unexplored, despite the central role of social (or indirect) genetic effects in shaping phenotypic expression within communities. Intercropping, i.e. the simultaneous cultivation of multiple crop species in the same field, offers a powerful model to harness these interspecific social effects. Such species mixtures provide well-documented agricultural benefits, yet few breeding frameworks have integrated the genetics of social interactions. Here, we address this gap by extending quantitative genetic theory to interspecific groups, with intercropping as a concrete and applied model case. We propose a quantitative genetic model that jointly analyzes intra and interspecific interactions within a unifying framework. Breeding values are decomposed into a direct component, shared in mono and mixed-crops, an interspecific social component corresponding to the effect of one species on another, and an intraspecific component that captures the social effects within a mono-genotypic stand of cloned plants. Statistically, this consists in simultaneously fitting several linear mixed models, one per stand type, all having direct breeding values in common. As no open-source software can fit such a complex mixed model, we provide such an implementation in R/C++. Simulations across various genetic (co)variance structures and sparse experimental designs showed accurate estimation of all genetic (co)variances and breeding values. With an incomplete, yet balanced design combining sole crops and intercrops, genetic gains in both systems were achievable simultaneously, enabling breeding strategies that progressively integrate intercropping into existing, sole-crop-only schemes. More broadly, this framework allows dissecting direct and social genetic effects when genotypes are observed in mono- and mixed-species situations, cultivated or not.

Extending the duration of the stem elongation (SE) phase between terminal spikelet (TS) and anthesis has often been proposed as an avenue to increase wheat yield. However, accurate determination of TS is labour intensive, and existing evidence is often based on a limited number of genotypes observed under controlled conditions. Here, a Buster x Charger population comprising 108 doubled haploid lines was grown across four year-sites under UK field conditions. TS was recorded through meristem dissection and SE duration was measured as the time between TS and ear emergence (EE). Mixed model analysis across year-sites revealed high heritabilities (H2yield = 0.66, H2TS = 0.93, H2SE = 0.89, H2EE = 0.95) and strong genetic correlations between yield and the phenology traits SE and EE (rg = 0.56 and rg = 0.6, respectively). While SE duration was mainly driven by EE, independent QTL for TS suggest that SE could be modified without affecting EE. The positive effect of SE duration on yield was attributed to increased grain number per area as well as increased grain weight, through independent QTL. Although validation in broader genetic backgrounds is needed, these QTL may offer opportunities for further yield increase in a physiological breeding framework. HighlightsO_LILonger stem elongation duration increases grain number. C_LIO_LILonger stem elongation duration increases grain weight. C_LIO_LIIndependent QTL suggest the timing of stem elongation as well as its effect on yield components may be independently selectable. C_LI

The genetic basis of adaptation is a fundamental question in evolutionary genetics. Environmental association analysis (EAA) and various allele frequency comparisons in genomic environmental association (GEA) have become standard approaches for investigating the genetic basis of adaptation to natural environments. While these analyses provide insight into local adaptation, they have not been widely adopted in breeding or conservation programs. This may be attributable to the difficulty in identifying the best individuals for transplantation/relocation in conservation efforts or identification of the best parents in breeding programs. To explore the use of EAA and GEA for future breeding programs, we used a cereal crop - barley (Hordeum vulgare L.) as our case-study species due to its wide adaptability to different environments and agro-ecologies, ranging from marginal and low input fields to high-productive farms. Here, we use publicly available data to conduct environmental genomic selection (EGS) on 753 landrace barley accessions using a mini-core of 31 landrace accessions and a de-novo core of 100 as the training populations. Environmental genomic selection is to environmental association analysis (EAA) what genomic selection is to genome-wide association studies (GWAS). Since local adaptation to the environment is polygenic, a whole-genome approach is likely to be more accurate for selecting for environmental adaptation. Here we show distinct genetic background and population differences and how an integrative approach coupling environmental genomic selection and species distribution modelling can help identify key parents for breeding for adaptation to specific environmental variables and geographies to minimize linkage drag.

In breeding programs, the selection of cultivars with the highest yield potential consisted in the selection of the yield per se, which resulted in cultivars with a higher grain number per spike (GN) and occasionally higher grain weight (GW) (main numerical components of the yield). This task could be facilitated with the use of molecular markers such us single nucleotide polymorphism (SNP). In this study, quantitative trait loci (QTL) for GW, GN and spike fertility traits related to GN determination were mapped using two double haploid (DH) populations (Baguette Premium 11 x BioINTA 2002 and Baguette 19 x BioINTA 2002, BP11xB2002 and B19xB2002). Both populations were genotyped with the iSelect 90K SNP array and evaluated in four (BP11xB19) or five (B19xB2002) environments. We identify a total of 305 QTL for 14 traits, however 28 QTL for 12 traits were considered significant with an R2 > 10% and stable for being present at least in three environments. There were detected eight hotspot regions on chromosomes 1A, 2B, 3A, 5A, 5B, 7A and 7B were at least two major QTL sheared confident intervals. QTL on two of these regions have previously been described, but the other six regions were never observed, suggesting that these regions would be novel. The R5A1 (QSL.perg-5A, QCN.perg-5A,QGN.perg-5A) and R5A.2 (QFFTS.perg-5A, QGW.perg-5A) regions together with the QGW.perg-6B resulted in a final higher yield suggesting them to have high relevance as candidates to be used in MAS to improve yield. Author contribution statement Key message28 stable and major QTL for 12 traits associated to spike fertility, GN and GW were detected. Two regions on 5A Ch., and QGW.perg-6B showed direct pleiotropic effects on yield.

Wheat production is threatened by numerous fungal diseases, but the potential to breed for multiple disease resistance (MDR) mechanisms is yet to be explored. Here, significant global genetic correlations and underlying local genomic regions were identified in the Vavilov wheat diversity panel for six major fungal diseases, including biotrophic leaf rust (LR), yellow rust (YR), stem rust (SR), hemibiotrophic crown rot (CR), and necrotrophic tan spot (TS) and Septoria nodorum blotch (SNB). By adopting haplotype-based local genomic estimated breeding values, derived from an integrated set of 34,899 SNP and DArT markers, we established a novel haplotype catalogue for resistance to the six diseases in over 20 field experiments across Australia and Ethiopia. Haploblocks with high variances of haplotype effects in all environments were identified for three rusts and pleiotropic haploblocks were identified for at least two diseases, with four haploblocks affecting all six diseases. Through simulation we demonstrated that stacking optimal haplotypes for one disease could improve resistance substantially, but indirectly affected resistance for other five diseases, which varied depending on the genetic correlation with the non-target disease trait. On the other hand, our simulation results combining beneficial haplotypes for all diseases increased resistance to LR, YR, SR, CR, TS and SNB, by up to 48.1%, 35.2%, 29.1%, 12.8%, 18.8% and 32.8%, respectively. Overall, our results highlight the genetic potential to improve MDR in wheat. The haploblock-based catalogue with novel forms of resistance provides a useful resource to guide desirable haplotype stacking for breeding future wheat cultivars with MDR.

The cassava (Manihot esculenta) genome has two large introgressions from its wild relative M. glaziovii on chromosomes 1 and 4 that originate from historical hybridization efforts. The 10 Mbp chromosome 1 introgression has been increasing in frequency in African breeding populations due to its statistical association with higher dry matter content and root number. However, the region also exhibits suppressed recombination, hindering breeders ability to combine favorable glaziovii alleles with the cultivated esculenta background. Since homozygous introgressed lines are rarely selected for advanced trials, dominance effects have not been well-characterized. To analyze the effects of the introgression with higher resolution, we generated a population of over 5000 seedlings from crosses between heterozygous introgressed parents and screened for recombinants using ten KASP markers tagging glaziovii-specific alleles. An optimized subset of 453 lines was then selected and evaluated over two years for yield and vigor traits. Unlike previous studies, composite interval mapping and mixed linear models showed no significant associations between glaziovii alleles and dry matter content or root number. Small, opposing effects on clonal vigor were observed at different ends of the introgression. The region showed significant segregation distortion and enrichment of putative deleterious alleles. Genome alignment of M. esculenta and M. glaziovii assemblies did not show any major structural variants in the introgression region, suggesting that suppressed recombination is likely driven by sequence-level divergence rather than structural rearrangements. These results indicate that the glaziovii introgression does not directly contribute to dry matter, supporting the need for recombination and purging of the glaziovii introgression to aid cassava improvement. Plain language summaryA large chromosome segment from a wild relative of cassava is an important structural aspect in the cassava genome. Since the chromosome segment tends to be inherited as one block, its effects on cassava traits were not well resolved. Through genetic mapping at higher resolution, we identified that the wild segment impacts early vigor and does not appear to impact dry yield, as was previously thought. While there are no major structural differences between the wild and cultivated chromosome segments, their overall divergence seems to suppress the wild chromosome segment from pairing with the cultivated chromosome segment during reproduction. In the apparent absence of any major benefits from the wild segment, removing it from the breeding population may be beneficial. Core ideasO_LIA set of glaziovii allele-specific markers were designed to track the chromosome 1 introgression haplotype. C_LIO_LISegregation distortion suggests the presence of recessive deleterious or lethal alleles in the introgression. C_LIO_LIIncreased recombination is needed to purge deleterious alleles enriched in introgression region. C_LIO_LIThe glaziovii introgression was associated with slightly lower vigor rating and stem diameter. C_LIO_LIThe effects of the previously-identified glaziovii DM QTL were not detected in this population. C_LI

The improvement of crop yield has long been a major breeding target and is increasingly becoming a goal in many areas of plant research. Yield has been shown to be a complex trait, depending on multiple genes, plant architecture and plant-environment interactions. This complexity is frequently reduced by focussing on contributing factors to yield (yield traits). However, a quantitative understanding of the interplay between yield traits, and the effect of these relationships on yield is largely unexplored. Consequently, the extent to which crop varieties achieve their optimal morphology in a given environment and how this impacts on seed yield is unknown. Here we use causal inference to model the hierarchically structured effects of 27 macro and micro yield traits on each other over the course of plant development, and on seed yield in Spring and Winter oilseed rape plants. We perform Bayesian optimisation on the modelled yield potential, identifying the morphology of ideotype plants which are expected to be higher yielding than the existing varieties in the studied panels. We find that existing Spring varieties occupy the optimal regions of trait-space, but that potentially high yielding strategies are unexplored in extant Winter varieties. In addition to concrete recommendations for varietal improvement in oilseed rape, this work provides a novel, general methodological framework for the study of crop breeding as an optimisation problem.

Early-stage sparse testing can significantly increase genetic gain in plant breeding programmes, facilitating the development of varieties with high and stable performance across farmers fields. This is achieved through (1) increased selection accuracy, enabled by broader sampling of trial sites across the Target Population of Environments (TPE), and (2) increased selection intensity by testing more selection candidates at a reduced replication rate. Early-stage agronomic testing typically involves evaluating a large number of selection candidates at one or a few experimental sites. Although these sites may poorly represent the TPE, strong selection pressure is generally applied. However, if the genetic correlation between performance at the experimental sites and in the TPE is low, most of the genetic gain achieved through selection will not be expressed under farmers conditions. Sparse testing addresses this challenge by using farm-as-incomplete-block designs, in which different subsets of selection candidates are evaluated across sites. By leveraging a genomic relationship matrix (GRM) to connect genotypes across environments, sparse testing enables early-stage multi-environment trials with broader coverage of the TPE. Here, we used stochastic simulation to compare various partially replicated sparse testing strategies to three fully replicated conventional early-stage testing strategies, with and without GRM. All sparse testing strategies achieved substantially higher and more stable genetic gain than the conventional strategies. Our results show that sparse testing provides breeders with a powerful and flexible framework to rethink early-stage trials and design cost-effective, multi-location experiments that lay the foundation for increased genetic gains in farmers fields. Key messageEarly-stage sparse testing can significantly increase genetic gain by (1) improving selection accuracy through broader sampling of the Target Population of Environments (TPE), and (2) increasing selection intensity.

The presence or absence of awns - whether wheat heads are "bearded" or "smooth"- is the most visible phenotype distinguishing wheat cultivars. Previous studies suggest that awns may improve yields in heat or water-stressed environments, but the exact contribution of awns to yield differences remains unclear. Here we leverage historical phenotypic, genotypic, and climate data to estimate the yield effects of awns under different environmental conditions over a 12-year period in the Southeast US. Lines were classified as awned or awnless based on sequence data, and observed heading dates were used to associate grain fill periods of each line in each environment with climatic data and grain yield. In most environments, awn suppression was associated with higher yields, but awns were associated with better performance in heat-stressed environments more common at southern locations. Wheat breeders in environments where awns are only beneficial in some years may consider selection for awned lines to reduce year-to-year yield variability, and with an eye towards future climates.

Improving rice (Oryza sativa L.) yield requires a balanced enhancement of both sink size and source capacity. While many QTLs for sink size have been identified, only a few are known for source capacity, which is essential for achieving high yield. Here we identified qHP10 as a major QTL for increased photosynthetic rate by using chromosome segment substitution lines derived from a cross between the high-yielding indica cultivar Takanari and the average-yielding japonica cultivar Koshihikari. High-resolution mapping combined with CRISPR/Cas9-induced mutagenesis revealed that the causative gene underlying qHP10 is Mitogen-Activated Protein Kinase 4 (OsMPK4). A near-isogenic line carrying the OsMPK4Takanari allele (NIL-OsMPK4) had a 15-25% higher photosynthetic rate than Koshihikari. NIL-OsMPK4 also had higher stomatal conductance than Koshihikari but similar stomatal pore size and density, indicating that increased stomatal aperture increases photosynthetic rate. This enhancement is likely attributable to the down-regulation of OsMPK4 expression, which increases stomatal conductance and thus promotes CO2 uptake. Our findings demonstrate that OsMPK4 is a promising genetic target for increasing source capacity and, potentially, rice yield through molecular breeding. (175 words)

The Dense and erect particle 1 (HvDEP1) gene, located on chromosome 5H in barley (Hordeum vulgare L.), encodes a heterotrimeric G-protein {gamma}-subunit that regulates grain size and stem elongation. Multiple alleles of HvDEP1 have been identified, including the widely utilized semi-dwarf allele HvDEP1.GP, caused by an insertion mutation, and a recently discovered variant, HvDEP1.V, characterized by two deletions in the putative cis-regulatory region. In this study, we evaluated the phenotypic effects of HvDEP1.V relative to HvDEP1.GP and the wild-type allele (HvDEP1.WT) using two BC{square}F{square} populations across multi-environment field trials spanning two locations and three years. HvDEP1.V was associated with plants that were 5-14.6 cm taller, had 3-6.7 higher lodging score, and increased head loss compared to HvDEP1.GP. HvDEP1.V showed comparable agronomic attributes to HvDEP1.WT. Substituting HvDEP1.V for HvDEP1.GP significantly increased all physical grain attributes, including grain width (1.44-4.24% in three out of five environments), grain length (4.88-8.69 %), grain area (6.45-11.06%) and thousand-grain weight (6.75-13.8%). Out of five environments, compared to HvDEP1.WT, HvDEP1.V was associated with wider grain in three environments, shorter grain in four environments, and increased grain roundness in four environments. These findings link allelic variation of the HvDEP1 gene to key agronomic and physical grain traits and demonstrate the functional consequences of HvDEP1.V in diverse genetic backgrounds and field conditions, providing valuable insights for barley improvement. Key messageBy evaluating agronomic performance and physical grain traits in two genetically distinct barley populations across multiple environments, we reveal strong environment- and background-dependent effects of HvDEP1 alleles.

Background and aimsVietnam harnesses a rich diversity of rice landraces adapted to a broad range of conditions, which constitute a largely untapped source of genetic diversity for the continuous improvement of rice cultivars. We previously identified a strong population structure in Vietnamese rice, which is captured in five Indica and four Japonica subpopulations, including an outlying Indica-5 group. Here, we leveraged on that strong differentiation, and the 672 rice genomes generated, to identify genes within genomic regions putatively selected during domestication and breeding of rice in Vietnam. MethodologyWe identified significant distorted patterns in allele frequency (XP-CLR method) and population differentiation scores (FST), resulting from differential selective pressures between native subpopulations, and compared them with QTLs previously identified by GWAS in the same panel. We particularly focused on the outlying Indica-5 subpopulation because of its likely novelty and differential evolution. ResultsWe identified selection signatures in each of the Vietnamese subpopulations and carried out a comprehensive annotation of the 52 regions selected in Indica-5, which represented 8.1% of the rice genome. We annotated the 4,576 genes in these regions, verified the overlap with QTLs identified in the same diversity panel and the comparison with a FST analysis between subpopulations, to select sixty-five candidate genes as promising breeding targets, several of which harboured alleles with non-synonymous substitutions. ConclusionsOur results highlight genomic differences between traditional Vietnamese landraces, which are likely the product of adaption to multiple environmental conditions and regional culinary preferences in a very diverse country. We also verified the applicability of this genome scanning approach to identify potential regions harbouring novel loci and alleles to breed a new generation of sustainable and resilient rice. Key MessageWe localised regions in the rice genome selected during breeding by comparing allele frequency patterns among Vietnamese rice subpopulations. We characterised candidate genes in the Indica-5 subpopulation with breeding potential.

Wheat stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst), remains a major global constraint to wheat production. Rapid pathogen evolution, exemplified by the recent breakdown of Yr15 in Europe, underscores the need to identify diverse and durable resistance loci. The A.E. Watkins landrace collection represents a globally diverse pre-breeding resource with substantial untapped variation for stripe rust resistance. In this study, 297 Watkins landraces were evaluated against six diverse Pst isolates (representing six races and three North American lineages) and subjected to genome-wide association analysis using high-density whole-genome resequencing data. Continuous phenotypic variation was observed across isolates, with several accessions displaying stable resistance across all lineages. A total of 87 QTLs were identified across all 21 wheat chromosomes. Ten loci co-localized with designated or cloned Yr genes, including Yr84, Yr85, Yrq1, Yr71, Yr60, Yr62, Yr50, Yr68, Yr34, and Lr34/Yr18/Sr57. An additional 34 loci overlapped previously reported stripe rust QTL, whereas the majority did not coincide with known loci, suggesting potential novel resistance regions. Eighteen QTLs were supported by multiple isolates, and fourteen showed supports across statistical models, indicating robust genomic signals. Several Watkins accessions carried favorable alleles that co-localized with multiple Yr-aligned loci, identifying promising donor candidates for validation and pre-breeding. Key MessageGenome-wide association mapping of 297 Watkins wheat landraces across diverse stripe rust races & genetic lineages identified 87 QTL, including 10 formally designated Yr genes and 46 novel loci, highlighting Watkins landraces as valuable pre-breeding donors for novel all-stage stripe rust resistance.

A blast-resistance rice mutant, GR978, generated by gamma-irradiation of indica cultivar IR64 was used to characterize the disease resistance transcriptome of rice to gain a better understanding of genes or chromosomal regions contributing to broad-spectrum disease resistance. GR978 was selected from the IR64 mutant collection at IRRI. To facilitate phenotypic characterization of the collection, a set of controlled vocabularies (CV) documenting mutant phenotypes in [~]3,700 entries was developed. In collaboration with the Tos17 rice mutant group at National Institute of Agrobiological Sciences, Japan, a merged CV set with 91 descriptions that map onto public ontology databases (PO, TO, OBO) is implemented in the IR64 mutant database. To better characterize the disease resistance transcriptome of rice, gene expression data from a blast resistant cultivar, SHZ-2, was incorporated in the analysis. Disease resistance transcriptome parameters, including differentially expressed genes (DEGs), regions of correlated gene expression (RCEs), and associations between DEGs and RCEs were determined statistically within and between genotypes using MAANOVA, correlation, and fixed ratio analysis. Twelve DEGs were found within the inferred physical location of the recessive gene locus on a [~]3.8MB region of chromosome 12 defined by genetic analysis of GR978. Highly expressed DEGs ([≥] 2fold difference) in GR978 or SHZ-2 and in common between the two, are mostly defense-response related, suggesting that most of the DEGs participate in causing the resistance phenotype. Comparing RCEs between SHZ-2 and GR978 showed that most RCEs between genotypes did not overlap. However, an 8-gene RCE in chromosome 11 was in common between SHZ2 and GR978. Gene annotations and GO enrichment analysis showed a high association with resistance response. This region has no DEGs nor is it associated with known blast resistance QTLs. Association analyses between RCEs and DEGs show that there was no enrichment of DEGs in the RCEs within a genotype and across genotypes as well. Association analysis of blast-resistance QTL (Bl-QTLs) regions (assembled from published literature; data courtesy of R. Wisser, pers comm., Cornell University) with DEGs and RCEs showed that while Bl- QTLs are not significantly associated with DEGs, they are associated with genotype-specific RCEs; GR978- RCEs are enriched within Bl-QTLs. The analysis suggested that examining patterns of correlated gene expression patterns in a chromosomal context (rather than the expression levels of individual genes) can yield additional insights into the causal relationship between gene expression and phenotype. Based on these results, we put forward a hypothesis that QTLs with small or moderate effects are represented by genomic regions in which the genes show correlated expression. It implies that gene expression within such a region is regulated by a common mechanism, and that coordinated expression of the region contributes to phenotypic effects. This hypothesis is testable by co segregation analysis of the expression patterns in well-characterized backcross and recombinant inbred lines.