Coming of age for Microbiome gene breeding in plants.

The plant microbiota can complement host functioning, leading to improved growth and health under unfavorable conditions. Microbiome engineering could therefore become a transformative technique for crop production. Microbiome genes, abbreviated as M genes, provide valuable targets for shaping plant-associated microbial communities.

Genetic diversity analysis of tropical and sub-tropical maize germplasm for Striga resistance and agronomic traits with SNP markers.

Striga hermonthica (Sh) and S. asiatica (Sa) are major parasitic weeds limiting cereal crop production and productivity in sub-Saharan Africa (SSA). Under severe infestation, Striga causes yield losses of up to 100%. Breeding for Striga-resistant maize varieties is the most effective and economical approach to controlling the parasite. Well-characterized and genetically differentiated maize germplasm is vital to developing inbred lines, hybrids, and synthetic varieties with Striga resistance and desirable product profiles. The objective of this study was to determine the genetic diversity of 130 tropical and sub-tropical maize inbred lines, hybrids, and open-pollinated varieties germplasm using phenotypic traits and single nucleotide polymorphism (SNP) markers to select Striga-resistant and complementary genotypes for breeding. The test genotypes were phenotyped with Sh and Sa infestations using a 13x10 alpha lattice design with two replications. Agro-morphological traits and Striga-resistance damage parameters were recorded under a controlled environment. Further, high-density Diversity Array Technology Sequencing-derived SNP markers were used to profile the test genotypes. Significant phenotypic differences (P<0.001) were detected among the assessed genotypes for the assessed traits. The SNP markers revealed mean gene diversity and polymorphic information content of 0.34 and 0.44, respectively, supporting the phenotypic variation of the test genotypes. Higher significant variation was recorded within populations (85%) than between populations using the analysis of molecular variance. The Structure analysis allocated the test genotypes into eight major clusters (K = 8) in concordance with the principal coordinate analysis (PCoA). The following genetically distant inbred lines were selected, displaying good agronomic performance and Sa and Sh resistance: CML540, TZISTR25, TZISTR1248, CLHP0303, TZISTR1174, TZSTRI113, TZDEEI50, TZSTRI115, CML539, TZISTR1015, CZL99017, CML451, CML566, CLHP0343 and CML440. Genetically diverse and complementary lines were selected among the tropical and sub-tropical maize populations that will facilitate the breeding of maize varieties with Striga resistance and market-preferred traits.

Physiological and antioxidant responses of synthetic hexaploid wheat germplasm under drought.

BACKGROUND: As a result of the world population and climate change impact increases (especially in arid environments), there is a critical need for high-yield, drought-tolerant wheat. Synthetic hexaploid wheat derived lines (SHW-DL), were created artificially by crossing different durum wheat cultivars (AABB) with accessions of Aegilops tauschii (DD), a beneficial source of new genes for common bread wheat (Triticum aestivum L). Here, we studied the response of a panel of 91 SHW-DL for drought tolerance based on physiological, antioxidant enzyme activities, and drought tolerance indices. RESULTS: A wide range of variation and high values of heritability observed for grain yield, physiological and antioxidant traits indicating that the SHW-DL panel constitutes a valuable gene source for drought tolerance improvement of wheat. Despite decreases in grain yield (YLD), leaf area index (LAI), and relative water content (RWC) an increase in the content of malondialdehyde (MDA) was observed. Moreover, drought streass increased the antioxidant enzyme activities of ascorbate peroxidase (APX), catalase (CAT) and peroxidase (POD), and also photosynthetic pigments, proline (Pro), and MDA content. With higher values of grain yield, physiological and biochemical traits such as photosynthetic pigments, and RWC, and lower content of MDA, and peroxidase (H2O2) activity, SHW-DL performed better compared to common wheat lines under water stress conditions. CONCLUSIONS: Different responses to water stress within the germplasm and between synthetic and common wheat suggest that selection for adaptive and suitable genotypes is possible for drought tolerance in synthetic wheat germplasm. Genotypes 54, 98, 102, 105, 122, 124, 143, 159, 196, and 198 were identified to be directly used in breeding programs or indirectly by crossing them with other wheat germplasm collections.

GA-GBLUP: leveraging the genetic algorithm to improve the predictability of genomic selection.

Genomic selection (GS) has emerged as an effective technology to accelerate crop hybrid breeding by enabling early selection prior to phenotype collection. Genomic best linear unbiased prediction (GBLUP) is a robust method that has been routinely used in GS breeding programs. However, GBLUP assumes that markers contribute equally to the total genetic variance, which may not be the case. In this study, we developed a novel GS method called GA-GBLUP that leverages the genetic algorithm (GA) to select markers related to the target trait. We defined four fitness functions for optimization, including AIC, BIC, R2, and HAT, to improve the predictability and bin adjacent markers based on the principle of linkage disequilibrium to reduce model dimension. The results demonstrate that the GA-GBLUP model, equipped with R2 and HAT fitness function, produces much higher predictability than GBLUP for most traits in rice and maize datasets, particularly for traits with low heritability. Moreover, we have developed a user-friendly R package, GAGBLUP, for GS, and the package is freely available on CRAN (https://CRAN.R-project.org/package=GAGBLUP).

Genetic diversity and genome-wide association study of partial resistance to Sclerotinia stem rot in a Canadian soybean germplasm panel.

KEY MESSAGE: Developing genetically resistant soybean cultivars is key in controlling the destructive Sclerotinia Stem Rot (SSR) disease. Here, a GWAS study in Canadian soybeans identified potential marker-trait associations and candidate genes, paving the way for more efficient breeding methods for SSR. Sclerotinia stem rot (SSR), caused by the fungal pathogen Sclerotinia sclerotiorum, is one of the most important diseases leading to significant soybean yield losses in Canada and worldwide. Developing soybean cultivars that are genetically resistant to the disease is the most inexpensive and reliable method to control the disease. However, breeding for resistance is hampered by the highly complex nature of genetic resistance to SSR in soybean. This study sought to understand the genetic basis underlying SSR resistance particularly in soybean grown in Canada. Consequently, a panel of 193 genotypes was assembled based on maturity group and genetic diversity as representative of Canadian soybean cultivars. Plants were inoculated and screened for SSR resistance in controlled environments, where variation for SSR phenotypic response was observed. The panel was also genotyped via genotyping-by-sequencing and the resulting genotypic data were imputed using BEAGLE v5 leading to a catalogue of 417 K SNPs. Through genome-wide association analyses (GWAS) using FarmCPU method with threshold of FDR-adjusted p-values < 0.1, we identified significant SNPs on chromosomes 2 and 9 with allele effects of 16.1 and 14.3, respectively. Further analysis identified three potential candidate genes linked to SSR disease resistance within a 100 Kb window surrounding each of the peak SNPs. Our results will be important in developing molecular markers that can speed up the breeding for SSR resistance in Canadian grown soybean.

Adaptive gene loss in the common bean pan-genome during range expansion and domestication.

The common bean (Phaseolus vulgaris L.) is a crucial legume crop and an ideal evolutionary model to study adaptive diversity in wild and domesticated populations. Here, we present a common bean pan-genome based on five high-quality genomes and whole-genome reads representing 339 genotypes. It reveals ~234 Mb of additional sequences containing 6,905 protein-coding genes missing from the reference, constituting 49% of all presence/absence variants (PAVs). More non-synonymous mutations are found in PAVs than core genes, probably reflecting the lower effective population size of PAVs and fitness advantages due to the purging effect of gene loss. Our results suggest pan-genome shrinkage occurred during wild range expansion. Selection signatures provide evidence that partial or complete gene loss was a key adaptive genetic change in common bean populations with major implications for plant adaptation. The pan-genome is a valuable resource for food legume research and breeding for climate change mitigation and sustainable agriculture.

Factor analytic selection tools and environmental feature-integration enable holistic decision-making in Eucalyptus breeding.

Understanding the genotype-by-environment interaction (GEI) and considering it in the selection process is a sine qua non condition for the expansion of Brazilian eucalyptus silviculture. This study's objective is to select high-performance and stable eucalyptus clones based on a novel selection index that considers the Factor Analytic Selection Tools (FAST) and the clone's reliability. The investigation explores the nuances interplay of GEI and extends its insights by scrutinizing the relationship between latent factors and real environmental features. The analysis, conducted across seven trials in five Brazilian states involving 78 clones, employs FAST. The clonal selection was performed using an extended FAST index weighted by the clone's reliability. Further insights about GEI emerge from the integration of factor loadings with 25 environmental features through a principal component analysis. Ten clones, distinguished by high performance, stability, and reliability, have been selected across the target population of environments. The environmental features most closely associated with factor loadings, encompassing air temperature, radiation, and soil characteristics, emerge as pivotal drivers of GEI within this dataset. This study contributes insights to eucalyptus breeders, equipping them to enhance decision-making by harnessing a holistic understanding-from the genotypes under evaluation to the diverse environments anticipated in commercial plantations.

Phenotypic diversity in qualitative and quantitative traits for selection of high yield potential field pea genotypes.

Field pea (Pisum sativum L.) needs improvement to increase productivity due to its high price and demand. However, the incidence of powdery mildew (PM) disease limits its production. This study aimed to analyze the diversity of qualitative and quantitative traits against powdery mildew resistance by utilizing cluster and principal component analysis to explore PM resistance high-yield potential field peas. Shannon-Weaver's diversity index (H') displayed high intra-genotype diversity for quantitative and qualitative aspects. Heterogeneity was identified for resistance against powdery mildew infections. Eighty-five genotypes were divided into five groups using Mohalanobis generalized distance (D2) statistics. The highest inter-cluster D2 value was observed between clusters 2 and 3 (11.89) while the lowest value was found between clusters 3 and 4 (2.06). Most of the genotypes had noticeable differences, so these could be employed in a crossing scheme. Twelve genotypes were extremely resistant, 29 genotypes were resistant, 25 genotypes were moderately resistant, 18 genotypes were fairly susceptible, and 1 genotype was susceptible to powdery mildew disease. Among 29 resistant genotypes, BFP77, BFP74, BFP63, BFP62, BFP43, and BFP80 were high yielders and, could be used directly and/or transferred through hybridization to high-yielding disease-susceptible genotypes. Among the 25 moderately resistant genotypes, BFP78, BFP45, BFP79, and BFP48 were found to be high yielders. In principal component analysis (PCA), the first four PCs with Eigen values > 1 accounted for 88.4% variability for quantitative traits. Clustering sorted genotypes into five groups, where groups 1 to 5 assembled 37, 28, 1, 8, and 11 genotypes, respectively. Genotypes of cluster 4 were identified as high yielders with its attributes. Pearson correlation significantly and positively correlated across all traits except for PM. This variation suggested that there is a mechanism to select promising genotypes for field pea breeding. Considering all features, BFP78, BFP77, BFP74, BFP63, BFP62, BFP45, BFP79, and BFP80 could be preferred as high yielders and PM resistance owing to longer pod lengths, seeds per pod and pods per plant.

Assessment and phenotypic identification of millet germplasm (Setaria italica L.) in Liaoning, China.

Aims: This study evaluated millet germplasms in Liaoning Province to support the collection, preservation and innovation of millet germplasm resources. Methods: The study was conducted from 2018 to 2020, involved the selection of 105 millet germplasm resources from the Germplasm Bank of the Liaoning Academy of Agricultural Sciences (LAAS), the observation and recording of 31 traits, and the application of multivariate analysis methods to assess phenotypic diversity. Results: From the diversity analysis and correlation analysis, it was found that the tested traits had abundant diversity and complex correlations among them. Principal component analysis (PCA) comprehensively analyzed all quantitative traits and extracted seven principal components. Grey relational analysis (GRA) highlighted the varied contributions of different traits to yield. Through systematic cluster analysis (SCA), the resources were categorized into six groups at Euclidean distance of 17.09. K-mean cluster analysis determined the distribution interval and central value of each trait, then identified resources with desirable traits. Conclusion: The results revealed resources that possess characteristics such as upthrow seedling leaves, more tillers and branches, larger and well-formed ears, and lodging resistance prefer to higher grain yield. It was also discovered that the subear internode length (SIL) could be an indicator for maturity selection. Four specific resources, namely, Dungu No. 1, Xiao-li-xiang, Basen Shengu, and Yuhuanggu No. 1, were identified for further breeding and practical applications.

Localization of potato browning resistance genes based on BSA-seq technology.

Browning is a common problem that occurs during potato processing; it is typically resolved by adding chemicals during the production process. However, there is a need to develop potato varieties that are resistant to browning due to a growing consumer interest in healthier diets. This study initially identified 275 potato varieties that are resistant to browning; these were narrowed down to eight varieties, with four of them being highly resistant. A hybrid population was developed by crossing the highly resistant CIP395109.29 with the easily browned Kexin 23. Bulked segregant analysis (BSA) was conducted, which identified 21 potato genes associated with anti-browning properties through sequencing data analysis and organization. The findings of this study lay a solid groundwork for future research on breeding potatoes with anti-browning traits, offer molecular markers for identifying anti-browning varieties, and serve as a valuable reference for further investigations into potato browning mechanisms.

Wheat genetic resources have avoided disease pandemics, improved food security, and reduced environmental footprints: A review of historical impacts and future opportunities.

The use of plant genetic resources (PGR)-wild relatives, landraces, and isolated breeding gene pools-has had substantial impacts on wheat breeding for resistance to biotic and abiotic stresses, while increasing nutritional value, end-use quality, and grain yield. In the Global South, post-Green Revolution genetic yield gains are generally achieved with minimal additional inputs. As a result, production has increased, and millions of hectares of natural ecosystems have been spared. Without PGR-derived disease resistance, fungicide use would have easily doubled, massively increasing selection pressure for fungicide resistance. It is estimated that in wheat, a billion liters of fungicide application have been avoided just since 2000. This review presents examples of successful use of PGR including the relentless battle against wheat rust epidemics/pandemics, defending against diseases that jump species barriers like blast, biofortification giving nutrient-dense varieties and the use of novel genetic variation for improving polygenic traits like climate resilience. Crop breeding genepools urgently need to be diversified to increase yields across a range of environments (>200 Mha globally), under less predictable weather and biotic stress pressure, while increasing input use efficiency. Given that the ~0.8 m PGR in wheat collections worldwide are relatively untapped and massive impacts of the tiny fraction studied, larger scale screenings and introgression promise solutions to emerging challenges, facilitated by advanced phenomic and genomic tools. The first translocations in wheat to modify rhizosphere microbiome interaction (reducing biological nitrification, reducing greenhouse gases, and increasing nitrogen use efficiency) is a landmark proof of concept. Phenomics and next-generation sequencing have already elucidated exotic haplotypes associated with biotic and complex abiotic traits now mainstreamed in breeding. Big data from decades of global yield trials can elucidate the benefits of PGR across environments. This kind of impact cannot be achieved without widescale sharing of germplasm and other breeding technologies through networks and public-private partnerships in a pre-competitive space.

Combining ability analysis of Cucurbita moschata D. in Côte d'Ivoire and classification of promising lines based on their gca effects.

Cucurbita moschata varieties grown in Africa have very low yield. They have been neglected, and totally ignored in agricultural research programs. However, interest in their fruits, seeds, flowers and leaves is growing nowadays due to their nutritional and medicinal potentials. That growing interest has prompted plant breeders and agronomists to develop research programs for their improvement. A complete diallel cross analysis of four parental lines, Long, Zouan-H, Oval, and Soubre and their twelve F1 hybrids, was carried out in a farming environment at the University Nangui Abrogoua, Abidjan, Côte d'Ivoire. The four parental lines and the F1 hybrids were evaluated for their general performances, combining abilities, potency ratio and heterosis effects. The investigated traits included plant height, and eleven fruit- and seed-related characters. The analysis of variance showed significant differences for all traits studied. In addition, the diallel model yielded highly significant gca effects of the female parents. The gca effects of the male parents were significant for all traits except plant height, length of the fruit, width of the fruit and length of the seed. Highly significant sca effects were observed in the crosses for all the traits. Strong maternal effects were observed for the weight and diameter of the fruit, weight of the pulp, number of seeds per fruit, weight of the fresh seeds and 100-seed weight. The general predictive ratio approached the value 1 for all the traits except weight of the fresh seed and width of the dry seed. Most of the characters under this study are predominantly determined by the effects of additive genes. But, weight of the fresh seed and width of the dry seed may be controlled by non-additive genes. Mid-parent heterosis was significant for all measured traits in the crosses, except the length of the fruit. And better-parent heterosis was significant for all traits except plant height, number of fruits per plant and length of the fruit. Gene expression is described by a super-dominance for many traits, and partial dominance for some other traits in all twelve F1 hybrids. Classification of the parental lines based on the effects of their general combining ability grouped the Soubre lines as promising contributors to fruit yield. The parental lines Long and Oval formed another group likely on the basis of the small size of their fruits, the small pulps, the smaller number of fruits per plant and the large number of seeds per fruit. However, Long would be a candidate parent for the development of cultivars with longer vegetative growth. The parental line Zouan-H formed the third group and it was mostly characterized by its large number of seeds per fruit and relatively large fruits.

Pan-genome and phylogenomic analyses highlight Hevea species delineation and rubber trait evolution.

The para rubber tree (Hevea brasiliensis) is the world's sole commercial source of natural rubber, a vital industrial raw material. However, the narrow genetic diversity of this crop poses challenges for rubber breeding. Here, we generate high-quality de novo genome assemblies for three H. brasiliensis cultivars, two H. brasiliensis wild accessions, and three other Hevea species (H. nitida, H. pauciflora, and H. benthamiana). Through analyzing genomes of 94 Hevea accessions, we identify five distinct lineages that do not align with their previous species delineations. We discover multiple accessions with hybrid origins between these lineages, indicating incomplete reproductive isolation between them. Only two out of four wild lineages have been introduced to commercial rubber cultivars. Furthermore, we reveal that the rubber production traits emerged following the development of a large REF/SRPP gene cluster and its functional specialization in rubber-producing laticifers within this genus. These findings would enhance rubber breeding and benefit research communities.

Exploring the genetic diversity and population structure of aerial yams (Dioscorea bulbifera L.) DArT-seq and agronomic traits.

Dioscorea bulbifera is an edible yam specie with aerial bulbils. Assessing the genetic diversity of D. bulbifera accession for cultivation and breeding purposes is essential for it genetic improvement, especially where the crop faces minimal attention. The aims of this study was to assess the genetic diversity of Dioscorea bulbifera accessions collected from Nigeria and accessions maintained at the genebank of International Institute of Tropical Agriculture (IITA) Ibadan. Accessions were profiled using quatitative and qualitative phenotypic traits and Diversity Array Technology SNP-markers. Multivariate analysis based phenotypic traits revealed high variability among the evaluated accessions and all phenotypic traits assessed were useful in discriminating the aerial yam accessions. Clustering analysis based phenotypic traits revealed the presence of two well defined clusters. Using DArT-Seq marker, the 94 accessions were classified into three genetic group through the admixture and the phylogeny analysis. The comparision of phenotypic and genotypic clustering revealed inconsistency membership across the two clustering methods. The study established a baseline for the selection of parental lines from the genetic groups for genetic improvement of the D. bulbifera.

Allelic variation in rice blast resistance: a pathway to sustainable disease management.

Rice blast is a major problem in agriculture, affecting rice production and threatening food security worldwide. This disease, caused by the fungus Magnaporthe oryzae, has led to a lot of research since the discovery of the first resistance gene, pib, in 1999. Researchers have now identified more than 50 resistance genes on eight of the twelve chromosomes in rice, each targeting different strains of the pathogen.These genes are spread out across seventeen different loci. These genes, which primarily code for nucleotide-binding and leucine-rich repeat proteins, play an important part in the defense of rice against the pathogen, either alone or in combination with other genes. An important characteristic of these genes is the allelic or paralogous interactions that exist within these loci. These relationships contribute to the gene's increased capacity for evolutionary adaptation. The ability of resistance proteins to recognize and react to novel effectors is improved by the frequent occurrence of variations within the domains that are responsible for recognizing pathogen effectors. The purpose of this review is to summarize the progress that has been made in identifying these essential genes and to investigate the possibility of utilizing the allelic variants obtained from these genes in future rice breeding efforts to increase resistance to rice blast.

Harnessing the Power of an Extensive EMS-Induced Sorghum Population for Rapid Crop Improvement.

Plant breeders leverage mutagenesis using chemical, biological, and physical mutagens to create novel trait variations. Many widely used sorghum genotypes have a narrow genetic base, which hinders improvements using classical breeding. Enhancing the diversity of the sorghum genome thus remains a key priority for sorghum breeders. To accelerate the genetic enhancement of sorghum, an extensive library comprised of seeds from 150,000 individual mutant plants of the Sorghum bicolor inbred line BTx623 was established using ethyl methanesulphonate (EMS) as a mutagen. The sorghum mutant library was bulked into 1498 pools (~100 seed heads per pool). In each pool, DNA was extracted from a subset of the seed and screened using the FIND-IT technology based on droplet digital PCR. All 43 nucleotide substitutions that were screened using FIND-IT were identified, demonstrating the potential to identify any EMS-derived mutation in an elite line of sorghum within days. This diverse library represents the largest collection of sorghum mutants ever conceived, estimated to cover 240% of all possible EMS-induced mutation points within the Sorghum genome. Using FIND-IT, the speed at which a specific desired EMS-derived mutation can be identified is a major upgrade to conventional reverse genetic techniques. Additionally, the ease at which valuable variants can be integrated into elite commercial lines is a far simpler and less expensive process compared to genome editing. Genomic variations in the library will have direct utility as a breeding resource for commercial sorghum applications, allowing enhanced adaptation to climate change and enhanced yield potential in marginal environments.

Characterization of flag leaf morphology identifies a major genomic region controlling flag leaf angle in the US winter wheat (Triticum aestivum L.).

KEY MESSAGE: Multi-environmental characterization of flag leaf morphology traits in the US winter wheat revealed nine stable genomic regions for different flag leaf-related traits including a major region governing flag leaf angle. Flag leaf in wheat is the primary contributor to accumulating photosynthetic assimilates. Flag leaf morphology (FLM) traits determine the overall canopy structure and capacity to intercept the light, thus influencing photosynthetic efficiency. Hence, understanding the genetic control of these traits could be useful for breeding desirable ideotypes in wheat. We used a panel of 272 accessions from the hard winter wheat (HWW) region of the USA to investigate the genetic architecture of five FLM traits including flag leaf length (FLL), width (FLW), angle (FLANG), length-width ratio, and area using multilocation field experiments. Multi-environment GWAS using 14,537 single-nucleotide polymorphisms identified 36 marker-trait associations for different traits, with nine being stable across environments. A novel and major stable region for FLANG (qFLANG.1A) was identified on chromosome 1A accounting for 9-13% variation. Analysis of spatial distribution for qFLANG.1A in a set of 2354 breeding lines from the HWW region showed a higher frequency of allele associated with narrow leaf angle. A KASP assay was developed for allelic discrimination of qFLANG.1A and was used for its independent validation in a diverse set of spring wheat accessions. Furthermore, candidate gene analysis for two regions associated with FLANG identified seven putative genes of interest for each of the two regions. The present study enhances our understanding of the genetic control of FLM in wheat, particularly FLANG, and these results will be useful for dissecting the genes underlying canopy architecture in wheat facilitating the development of climate-resilient wheat varieties.

Integrative genomics reveals the polygenic basis of seedlessness in grapevine.

Seedlessness is a crucial quality trait in table grape (Vitis vinifera L.) breeding. However, the development of seeds involved intricate regulations, and the polygenic basis of seed abortion remains unclear. Here, we combine comparative genomics, population genetics, quantitative genetics, and integrative genomics to unravel the evolution and polygenic basis of seedlessness in grapes. We generated the haplotype-resolved genomes for two seedless grape cultivars, "Thompson Seedless" (TS, syn. "Sultania") and "Black Monukka" (BM). Comparative genomics identified a ∼4.25 Mb hemizygous inversion on Chr10 specific in seedless cultivars, with seedless-associated genes VvTT16 and VvSUS2 located at breakpoints. Population genomic analyses of 548 grapevine accessions revealed two distinct clusters of seedless cultivars, and the identity-by-descent (IBD) results indicated that the origin of the seedlessness trait could be traced back to "Sultania." Introgression, rather than convergent selection, shaped the evolutionary history of seedlessness in grape improvement. Genome-wide association study (GWAS) analysis identified 110 quantitative trait loci (QTLs) associated with 634 candidate genes, including previously unidentified candidate genes, such as three 11S GLOBULIN SEED STORAGE PROTEIN and two CYTOCHROME P450 genes, and well-known genes like VviAGL11. Integrative genomic analyses resulted in 339 core candidate genes categorized into 13 functional categories related to seed development. Machine learning-based genomic selection achieved a remarkable prediction accuracy of 97% for seedlessness in grapevines. Our findings highlight the polygenic nature of seedlessness and provide candidate genes for molecular genetics and an effective prediction for seedlessness in grape genomic breeding.

Fine mapping of stem rust resistance derived from soft red winter wheat cultivar AGS2000 to an NLR gene cluster on chromosome 6D.

The Puccinia graminis f. sp. tritici (Pgt) Ug99-emerging virulent races present a major challenge to global wheat production. To meet present and future needs, new sources of resistance must be found. Identification of markers that allow tracking of resistance genes is needed for deployment strategies to combat highly virulent pathogen races. Field evaluation of a DH population located a QTL for stem rust (Sr) resistance, QSr.nc-6D from the breeding line MD01W28-08-11 to the distal region of chromosome arm 6DS where Sr resistance genes Sr42, SrCad, and SrTmp have been identified. A locus for seedling resistance to Pgt race TTKSK was identified in a DH population and an RIL population derived from the cross AGS2000 × LA95135. The resistant cultivar AGS2000 is in the pedigree of MD01W28-08-11 and our results suggest that it is the source of Sr resistance in this breeding line. We exploited published markers and exome capture data to enrich marker density in a 10 Mb region flanking QSr.nc-6D. Our fine mapping in heterozygous inbred families identified three markers co-segregating with resistance and delimited QSr.nc-6D to a 1.3 Mb region. We further exploited information from other genome assemblies and identified collinear regions of 6DS harboring clusters of NLR genes. Evaluation of KASP assays corresponding to our co-segregating SNP suggests that they can be used to track this Sr resistance in breeding programs. However, our results also underscore the challenges posed in identifying genes underlying resistance in such complex regions in the absence of genome sequence from the resistant genotypes.

Evaluation of effectiveness resistance genes in wheat genotypes using marker-assisted selection for stripe rust resistance breeding".

Stripe rust, induced by Puccinia striiformis f. sp. tritici, is the most harmful and prevalent disease in temperate regions worldwide, affecting wheat production areas globally. An effective strategy for controlling the disease involves enhancing genetic resistance against stripe rust, achieved through Egyptian breeding efforts not previously conducted on wheat genotypes. The resistance level to stripe rust in thirty-eight wheat genotypes was assessed using marker-assisted selection methods. The investigation suggests that wheat breeding programs can utilize slow-rusting Yr genes, which are effective resistance genes, to develop novel genotypes with stripe rust resistance through marker-assisted breeding. Based on the four disease responses of the wheat genotypes under investigation, the results categorized the genotypes into three groups. The first group included resistant genotypes, the second group exhibited a slow-rusting character with the lowest disease symptom rates, and the last group displayed the highest disease characteristics rates throughout the three seasons, comprising fast-rusting genotypes. The rust-resistant genes identified were Yr5, Yr9, Yr10, Yr15, Yr17, Yr18, Yr26, Yr29, Yr30, and Yr36. Genes Yr26, Yr30, and Yr36 were present in all genotypes. Genotypes Misr3, Misr4, Giza168, Giza167, Giza170, Giza171, Gemmeiza9, and Gemmeiza10 carried the Yr9 gene. Only one genotype, Sids13, was found to have the Yr17 gene. Genes Yr18 and Yr29 were identified in Sids14, Giza168, Giza170, Gemmeiza9, and Gemmeiza10. However, none of the wheat genotypes showed the presence of Yr5, Yr10, or Yr15. Several backcrossing generations were conducted to introduce the Yr5 and Yr10 genes into susceptible genotypes (Misr1, Misr2, and Gemmeiza11). These genotypes are cultivated globally and are known for producing high-quality flour, making them of great importance to farmers. The study demonstrates significant potential for enhancing wheat genotypes for stripe rust resistance and increased production.