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Abstract Root system architecture (RSA) plays an important role in plant adaptation to drought stress. However, the genetic basis of RSA in sorghum has not been adequately elucidated. This study aimed to investigate the genetic bases of RSA traits through genome-wide association studies (GWAS) and determine genomic prediction (GP) accuracy in sorghum landraces at the seedling stage. Phenotypic data for nodal root angle (NRA), number of nodal roots (NNR), nodal root length (NRL), fresh shoot weight (FSW), dry shoot weight (DSW), and leaf area (LA) were collected from 160 sorghum accessions grown in soil-based rhizotrons. The sorghum panel was genotyped with 5,000 single nucleotide polymorphism (SNP) markers for use in the current GWAS and GP studies. A multi-locus model, Fixed and random model Circulating Probability Unification (FarmCPU), was applied for GWAS analysis. For GP, ridge-regression best linear unbiased prediction (RR-BLUP) and five different Bayesian models were applied. A total of 17 SNP loci significantly associated with the studied traits were identified, of which nine are novel loci. Among the traits, the highest number of significant marker-trait associations (MTAs) was identified for nodal root angle on chromosomes 1, 3, 6, and 7. The SNP loci that explain the highest proportion of phenotypic variance (PVE) include sbi32853830 (PVE = 18.2%), sbi29954292 (PVE = 18.1%), sbi24668980 (PVE = 10.8%), sbi3022983 (PVE = 7%), sbi29897704 (PVE = 6.4%) and sbi29897694 (PVE = 5.3%) for the traits NNR, LA, SDW, NRA, NRL and SFW, respectively. The genomic prediction accuracy estimated for the studied traits using five Bayesian models ranged from 0.30 to 0.63 while it ranged from 0.35 to 0.60 when the RR-BLUP model was used. The observed moderate to high prediction accuracy for each trait suggests that genomic selection could be a feasible approach to sorghum RSA-targeted selection and breeding. Overall, the present study provides insights into the genetic bases of RSA and offers an opportunity to speed up breeding for drought-tolerant sorghum varieties.

The multi-environment evaluation of wheat genotypes for grain yield is an integral part of germplasm enhancement since it plays a pivotal role in sustainable production. A total of 178 winter wheat cultivars were evaluated across 20 environments in Sweden from 2016 to 2020, with 52 to 59 cultivars tested per year as part of the Swedish National Trials (Sverigeförsöken). The genotypes were evaluated for grain yield performance with and without fungicide treatments. Additive main-effects and multiplicative interaction (AMMI) and genotype plus genotype-by-environment interaction (GGE) biplot methods were explored to estimate the genotype-by-environment interaction (GEI) for grain yield performance. ANOVA revealed a significant variation between treatments, genotypes in all years, and GEI in all years except 2018. The majority of the explained variance came from the environment, with a range of 61–88% across the five-year trial. The 20 sites were grouped into two to four mega-environments in the yearly studies. From the fungicide-treated trials, G 0512LT3, Informer, SG SU1563-15, LG Imposanto, and Pondus were identified as the most stable and high-yielding cultivars each year. From the fungicide-untreated trials, Informer, Ancher Greece, RGT Saki, and Pondus were the best-performing cultivars and could be good candidates for organic wheat cultivation.

IntroductionTurnip rape is recognized as an oilseed crop contributing to environmentally sustainable agriculture via integration into crop rotation systems. Despite its various advantages, the crop’s cultivation has declined globally due to a relatively low productivity, giving way to other crops. The use of genomic tools could enhance the breeding process and accelerate genetic gains. Therefore, the present research investigated 170 turnip rape accessions representing its global gene pool to identify SNP markers associated nine phenological and agro-morphological traits and estimate the genomic breeding values (GEBVs) of the germplasm through GWAS and genomic prediction analyses, respectively.MethodsField trials were conducted at two sites in northern and southern Sweden to obtain the phenotypic data while genotyping was conducted via the genotyping-by-sequencing (GBS) method. The traits studied include days to flowering (DTF) and maturity (DTM), plant height (PH), seed yield (YLD), thousand seed weight (TSW), silique length (SL), number of siliques (NS), number of seeds per silique (SS), and pod shattering resistance (PSHR).Results and conclusionAnalysis of variance revealed substantial variation among accessions, with significant genotype-by-environment interaction for most traits. A total of 25, 17, 16, 14, 7, 5, 3, and 3 MTAs were identified for TSW, DTF, PH, PSHR, SL, YLD, SS and DTM, respectively. An 80%–20% training-test set genomic prediction analysis was conducted using the ridge regression – BLUP (RR-BLUP) model. The accuracy of genomic prediction for most traits was high, indicating that these tools may assist turnip rape breeders in accelerating genetic gains. The study highlights the potential of genomic tools to significantly advance breeding programs for turnip rape by identifying pivotal SNP markers and effectively estimating genomic breeding values. Future breeding perspectives should focus on leveraging these genomic insights to enhance agronomic traits and productivity, thereby reinstating turnip rape as a competitive and sustainable crop in Sweden and broader global agriculture.

Abstract Septoria tritici blotch (STB) is a destructive foliar diseases threatening wheat grain yield. Wheat breeding for STB disease resistance has been identified as the most sustainable and environment-friendly approach. In this work, a panel of 316 winter wheat breeding lines from a commercial breeding program were evaluated for STB resistance at the seedling stage under controlled conditions followed by genome-wide association study (GWAS) and genomic prediction (GP). The study revealed a significant genotypic variation for STB seedling resistance, while disease severity scores exhibited a normal frequency distribution. Moreover, we calculated a broad-sense heritability of 0.62 for the trait. Nine single- and multi-locus GWAS models identified 24 marker-trait associations grouped into 20 quantitative trait loci (QTLs) for STB seedling-stage resistance. The seven QTLs located on chromosomes 1B, 2A, 2B, 5B (two), 7A, and 7D are reported for the first time and could potentially be novel. The GP cross-validation analysis in the RR-BLUP model estimated the genomic-estimated breeding values (GEBVs) of STB resistance with a prediction accuracy of 0.49. Meanwhile, the GWAS assisted wRR-BLUP model improved the accuracy to 0.58. The identified QTLs can be used for marker-assisted backcrossing against STB in winter wheat. Moreover, the higher prediction accuracy recorded from the GWAS-assisted GP analysis implies its power to successfully select superior candidate lines based on their GEBVs for STB resistance.

Abstract Background Genetic improvement of root system architecture is essential to improve water and nutrient use efficiency of crops or to boost their productivity under stress or non-optimal soil conditions. One hundred ninety-two Ethiopian durum wheat accessions comprising 167 historical landraces and 25 modern cultivars were assembled for GWAS analysis to identify QTLs for root system architecture (RSA) traits and genotyped with a high-density 90 K wheat SNP array by Illumina. Results Using a non-roll, paper-based root phenotyping platform, a total of 2880 seedlings and 14,947 seminal roots were measured at the three-leaf stage to collect data for total root length (TRL), total root number (TRN), root growth angle (RGA), average root length (ARL), bulk root dry weight (RDW), individual root dry weight (IRW), bulk shoot dry weight (SDW), presence of six seminal roots per seedling (RT6) and root shoot ratio (RSR). Analysis of variance revealed highly significant differences between accessions for all RSA traits. Four major (− log10 P ≥ 4) and 34 nominal (− log10 P ≥ 3) QTLs were identified and grouped in 16 RSA QTL clusters across chromosomes. A higher number of significant RSA QTL were identified on chromosome 4B particularly for root vigor traits (root length, number and/or weight). Conclusions After projecting the identified QTLs on to a high-density tetraploid consensus map along with previously reported RSA QTL in both durum and bread wheat, fourteen nominal QTLs were found to be novel and could potentially be used to tailor RSA in elite lines. The major RGA QTLs on chromosome 6AL detected in the current study and reported in previous studies is a good candidate for cloning the causative underlining sequence and identifying the beneficial haplotypes able to positively affect yield under water- or nutrient-limited conditions.

Grain shape and color strongly influence yield and quality of durum wheat. Identifying QTL for these traits is essential for transferring favorable alleles based on selection strategies and breeding objectives. In the present study, 192 Ethiopian durum wheat accessions comprising 167 landraces and 25 cultivars were genotyped with a high-density Illumina iSelect 90K single-nucleotide polymorphism (SNP) wheat array to conduct a genome-wide association analysis for grain width (GW), grain length (GL), CIE (Commission Internationale l'Eclairage) L* (brightness), CIE a* (redness), and CIE b* (yellowness) traits. The accessions were planted at Sinana Agricultural Research Center, Ethiopia in the 2015/2016 cropping season in a complete randomized block design with three replications. Twenty homogeneous and healthy seeds per replicate were used for trait measurement. Digital image analysis of seeds with GrainScan software package was used to generate the phenotypic data. Analysis of variance revealed highly significant differences between accessions for all traits. A total of 46 quantitative trait loci (QTL) were identified for all traits across all chromosomes. One novel major candidate QTL (−lg P ≥ 4) with pleiotropic effects for grain CIE L* (brightness) and CIE a* (redness) was identified on the long arm of chromosome 2A. Eighteen nominal QTL (−lg P ≥ 3) and 26 suggestive QTL (−lg P ≥ 2.5) were identified. Pleiotropic QTL influencing both grain shape and color were identified.

Estimating the allelic variation and exploring the genetic basis of quantitatively inherited complex traits are the two foremost breeding scenarios for sustainable crop production. The current study utilized 188 wrinkled vining pea genotypes comprising historical varieties and breeding lines to evaluate the existing genetic diversity and to detect molecular markers associated with traits relevant to vining pea production, such as wrinkled vining pea yield (YTM100), plant height (PH), earliness (ERL), adult plant resistance to downy mildew (DM), pod length (PDL), numbers of pods per plant (PDP), number of peas per pod (PPD), and percent of small wrinkled vining peas (PSP). Marker-trait associations (MTAs) were conducted using 6902 quality single nucleotide polymorphism (SNP) markers generated from the diversity arrays technology sequencing (DArTseq) and Genotyping-by-sequencing (GBS) sequencing methods. The best linear unbiased prediction (BLUP) values were estimated from the two-decades-long (1999–2020) unbalanced phenotypic data sets recorded from two private breeding programs, the Findus and the Birds eye, now owned by Nomad Foods. Analysis of variance revealed a highly significant variation between genotypes and genotype-by-environment interactions for the ten traits. The genetic diversity and population structure analyses estimated an intermediate level of genetic variation with two optimal sub-groups within the current panel. A total of 48 significant (P < 0.0001) MTAs were identified for eight different traits, including five for wrinkled vining pea yield on chr2LG1, chr4LG4, chr7LG7, and scaffolds (two), and six for adult plant resistance to downy mildew on chr1LG6, chr3LG5 (two), chr6LG2, and chr7LG7 (two). We reported several novel MTAs for different crucial traits with agronomic importance in wrinkled vining pea production for the first time, and these candidate markers could be easily validated and integrated into the active breeding programs for marker-assisted selection.

Abstract Background Ethiopia has been considered as a center of diversity and the second possible center of domestication of durum wheat. Genetic diversity and population structure analysis in the existing Ethiopian durum wheat germplasm have enormous importance in enhancing breeding effort and for sustainable conservation. Hence, 192 Ethiopian durum wheat accessions comprising 167 landraces collected from major wheat-growing areas of the country and 25 improved varieties released from Debre Zeit and Sinana Agricultural Research Centers, Ethiopia in different years (1994–2010) were assembled for the current study. Results The panel was genotyped with a High-density 90 K wheat SNP array by Illumina and generated 15,338 polymorphic SNPs that were used to analyze the genetic diversity and to estimate the population structure. Varied values of genetic diversity indices were scored across chromosomes and genomes. Genome-wide mean values of Nei’s gene diversity (0.246) and polymorphism information content (0.203) were recorded signifying the presence of high genetic diversity within this collection. Minor allele frequency of the genome varied with a range of 0.005 to 0.5 scoring a mean value of 0.175. Improved varieties clustered separately to landraces in population structure analysis resulted from STRUCTURE, PCA and neighbor joining tree. Landraces clustering was irrespective of their geographical origin signifying the presence of higher admixture that could arise due to the existence of historical exchanges of seeds through informal seed system involving regional and countrywide farming communities in Ethiopia. Conclusions Sustainable utilization and conservation of this rich Ethiopian durum wheat genetic resource is an irreplaceable means to cope up from the recurrent climate changes and biotic stresses happening widely and thereby able to keep meeting the demand of durum productivity for the ever-growing human population.

Septoria tritici blotch (STB) caused by the fungal pathogen Zymoseptoria tritici and powdery mildew (PM) caused by Blumeria graminis f.sp tritici (Bgt) are among the forefront foliar diseases of wheat that lead to a significant loss of grain yield and quality. Resistance breeding aimed at developing varieties with inherent resistance to STB and PM diseases has been the most sustainable and environment-friendly approach. In this study, 175 winter wheat landraces and historical cultivars originated from the Nordic region were evaluated for adult-plant resistance (APR) to STB and PM in Denmark, Estonia, Lithuania, and Sweden. Genome-wide association study (GWAS) and genomic prediction (GP) were performed based on the adult-plant response to STB and PM in field conditions using 7,401 single-nucleotide polymorphism (SNP) markers generated by 20K SNP chip. Genotype-by-environment interaction was significant for both disease scores. GWAS detected stable and environment-specific quantitative trait locis (QTLs) on chromosomes 1A, 1B, 1D, 2B, 3B, 4A, 5A, 6A, and 6B for STB and 2A, 2D, 3A, 4B, 5A, 6B, 7A, and 7B for PM adult-plant disease resistance. GP accuracy was improved when assisted with QTL from GWAS as a fixed effect. The GWAS-assisted GP accuracy ranged within 0.53–0.75 and 0.36–0.83 for STB and PM, respectively, across the tested environments. This study highlights that landraces and historical cultivars are a valuable source of APR to STB and PM. Such germplasm could be used to identify and introgress novel resistance genes to modern breeding lines.