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Genotype × environment interaction (GEI) is an important aspect of both plant breeding and the successful introduction of new cultivars. In the present study, additive main effects and multiplicative interactions (AMMI) and genotype (G) main effects and genotype (G) × environment (E) interaction (GGE) biplot analyses were used to identify stable genotypes and to dissect GEI in Plantago. In total, 10 managed field trials were considered as environments to analyze GEI in thirty genotypes belonging to eight Plantago species. Genotypes were evaluated in a drought stress treatment and in normal irrigation conditions at two locations in Shiraz (Bajgah) for three years (2013-2014- 2015) and Kooshkak (Marvdasht, Fars, Iran) for two years (2014-2015). Three traits, seed yield and mucilage yield and content, were measured at each experimental site and in natural Plantago habitats. AMMI2 biplot analyses identified genotypes from several species with higher stability for seed yield and other genotypes with stable mucilage content and yield. P. lanceolata (G26), P. officinalis (G10), P. ovata (G14), P. ampleexcaulis (G11) and P. major (G4) had higher stability for seed yield. For mucilage yield, G21, G18 and G20 (P. psyllium), G1, G2 and G4 (P. major), G9 and G10 (P. officinalis) and P. lanceolata were identified as stable. G13 (P. ovata), G5 and G6 (P. major) and G30 (P. lagopus) had higher stability for mucilage content. No one genotype was found to have high levels of stability for more than one trait but some species had more than one genotype exhibiting stable trait performance. Based on trait variation, GGE biplot analysis identified two representative environments, one for seed yield and one for mucilage yield and content, with good discriminating ability. The identification of stable genotypes and representative environments should assist the breeding of new Plantago cultivars.

Evaluation of forage yield and antioxidant activity in Poa pratensis with high quality and good spring green-up forage might help variety improvement for use under water deficit condition. Germplasm and phenotypic diversity evaluations lay a foundation for genotype selection and improvement of varieties for drought tolerance in P. pratensis . The present study was conducted to assess the genetic potential of a collection of P. pratensis accessions for drought stress and to identify the association between polyphenol compounds and forage yield traits. Vegetative clone samples of 100 accessions collected from a diverse geographical area of Iran were clonally propagated in a greenhouse and evaluated in the field under two moisture regimes (non-stress and drought stress) in 2018 and 2019. Drought stress had negative effects on fresh and dry forage yields and reduced phenotypic variances. On average, drought stress reduced fresh and dry forage yields by 45% and 28%, respectively. The results of Mantel test showed no significant correlation between forage yield traits and geographical distances. Genetic coefficients of variation for forage yield and most of the phytochemicals were lower under drought stress, suggesting that deficit irrigation may reduce genetic variation for the tested traits. The estimates of heritability were higher under non-stress conditions than under drought stress treatment for forage yield traits and few polyphenols. However, the majority of polyphenol compounds had higher heritability than forage yield traits under drought stress, which suggests the potential for indirect selection. The ‘Ciakhor’, ‘Damavand’, ‘Karvandan’, ‘Abrumand’, and ‘Abr2’ accessions had high quantities for polyphenols and yield traits under both moisture regimes. These accessions are promising candidates for use in variety crossing programs and for developing high-yielding varieties under water-deficit conditions.

Zinc and iron are essential micronutrients for the growth, development, and maintenance of the immune system at high levels. Analysis of genetic control of grain Zn and Fe through identification of QTLs helps to identify linked markers for use in marker- assisted breeding and biofortification of wheat grain in breeding programs. Meta-QTL analysis (MQTL analysis) is a robust method to integrate information on QTLs in independent populations, which is useful for understanding the genetic architecture of quantitative traits. In this meta-analysis, information on QTLs for iron and zinc contents in seven independent segregating populations was used to develop a reference consensus map. The consensus map consisting of 558 DNA markers covered 1028 cM of the wheat genome and seven MQTLs were identified on six wheat chromosomes. The MQTLs identified possessed a narrower (7.03 cM) confidence interval (CI) than the original QTLs with a mean CI of 17.60 cM. Of the MQTLs identified, three MQTLs covering at least four initial QTLs from independent studies were the most important hot spots for the genetic control of grain Zn and Fe traits over different genetic backgrounds and environments. The identified MQTLs were predominantly distributed in the non-telomeric and sub-telomeric chromosomal regions. Functional analysis of the identified MQTLs suggested that the genomic regions of the most identified MQTLs were associated with the position of candidate genes (CGs) for Zn and Fe homeostasis. Overall, the results of the meta-analysis showed that QTLs for Zn and Fe contents were highly co-located (57.1%), suggesting the simultaneous improvement of both micronutrients and biofortification of wheat.

Comparative genomics and meta-quantitative trait loci (MQTLs) analysis are important tools for the identification of reliable and stable QTLs and functional genes controlling quantitative traits. We conducted a meta-analysis to identify the most stable QTLs for grain yield (GY), grain quality traits, and micronutrient contents in wheat. A total of 735 QTLs retrieved from 27 independent mapping populations reported in the last 13 years were used for the meta-analysis. The results showed that 449 QTLs were successfully projected onto the genetic consensus map which condensed to 100 MQTLs distributed on wheat chromosomes. This consolidation of MQTLs resulted in a three-fold reduction in the confidence interval (CI) compared with the CI for the initial QTLs. Projection of QTLs revealed that the majority of QTLs and MQTLs were in the non-telomeric regions of chromosomes. The majority of micronutrient MQTLs were located on the A and D genomes. The QTLs of thousand kernel weight (TKW) were frequently associated with QTLs for GY and grain protein content (GPC) with co-localization occurring at 55 and 63%, respectively. The co- localization of QTLs for GY and grain Fe was found to be 52% and for QTLs of grain Fe and Zn, it was found to be 66%. The genomic collinearity within Poaceae allowed us to identify 16 orthologous MQTLs (OrMQTLs) in wheat, rice, and maize. Annotation of promising candidate genes (CGs) located in the genomic intervals of the stable MQTLs indicated that several CGs (e.g., TraesCS2A02G141400, TraesCS3B02G040900, TraesCS4D02G323700, TraesCS3B02G077100 , and TraesCS4D02G290900 ) had effects on micronutrients contents, yield, and yield-related traits. The mapping refinements leading to the identification of these CGs provide an opportunity to understand the genetic mechanisms driving quantitative variation for these traits and apply this information for crop improvement programs.

Pot marigold ( Calendula officinalis L.) is an ornamental-medicinal plant commonly planted in green spaces, and it has various industrial and medicinal applications. It is widely cultivated in semi-arid and Mediterranean regions, where it often faces drought stress. This research was conducted to evaluate the impact of moderate and severe drought stress during the flowering stage and to determine the drought response mechanisms in pot marigold. Therefore, the pot marigold plants were treated with control (100%), 60% and 30% of field capacity (FC) in the greenhouse, starting from the blooming stage, when usually the decrease in rainfall occurs during its life cycle. The impacts of different levels of stress were evaluated on eight plant water content parameters, seventeen morpho-physiological and phenological traits, and nine biochemical factors. Restricted maximum likelihood (REML) by best linear unbiased estimates (BLUEs) indicated that reducing water supply at moderate stress still led to satisfactory growth of pot marigold, where most of the morpho-physiological and phenological traits, including days from budding to flowering and pollination, flowers number, flower weight and diameter, and plant height, were not significantly affected at 60% of FC in comparison to 100% of FC. However, severe drought stress significantly reduced plant height, flower diameter, and flower weight by 31%, 20%, and 38%, respectively. In addition, the factor analysis demonstrated that pot marigold employs a combination of avoidance and tolerance mechanisms, including root system elongation, adjustment in antioxidant enzymes activity, and chlorophyll and carotenoid content to cope with drought stress. Our results represent a significant advance in understanding the level of tolerance and the responsive mechanisms to drought stress in pot marigold during the most critical stage of its life cycle, when reduced rainfall usually occurs in its cultivation area.

Ionome contributes to maintain cell integrity and acts as cofactors for catalyzing regulatory pathways. Identifying ionome contributing genomic regions provides a practical framework to dissect the genetic architecture of ionomic traits for use in biofortification. Meta-QTL (MQTL) analysis is a robust method to discover stable genomic regions for traits regardless of the genetic background. This study used information of 483 QTLs for ionomic traits identified from 12 populations for MQTL analysis in Arabidopsis thaliana . The selected QTLs were projected onto the newly constructed genetic consensus map and 33 MQTLs distributed on A. thaliana chromosomes were identified. The average confidence interval (CI) of the drafted MQTLs was 1.30 cM, reduced eight folds from a mean CI of 10.88 cM for the original QTLs. Four MQTLs were considered as stable MQTLs over different genetic backgrounds and environments. In parallel to the gene density over the A. thaliana genome, the genomic distribution of MQTLs over the genetic and physical maps indicated the highest density at non- and sub-telomeric chromosomal regions, respectively. Several candidate genes identified in the MQTLs intervals were associated with ion transportation, tolerance, and homeostasis. The genomic context of the identified MQTLs suggested nine chromosomal regions for Zn, Mn, and Fe control. The QTLs for potassium (K) and phosphorus (P) were the most frequently co-located with Zn (78.3%), Mn (76.2%), and Fe (88.2% and 70.6%) QTLs. The current MQTL analysis demonstrates that meta-QTL analysis is cheaper than, and as informative as genome-wide association study (GWAS) in refining the known QTLs.

Leaf rust, caused by Puccinia triticina Eriks., is the most common rust disease of wheat ( Triticum aestivum L.) worldwide. Owing to the rapid evolution of virulent pathotypes, new and effective leaf rust resistance sources must be found. Aegilops tauschii , an excellent source of resistance genes to a wide range of diseases and pests, may provide novel routes for resistance to this disease. In this study, we aimed to elucidate the transcriptome of leaf rust resistance in two contrasting resistant and susceptible Ae. tauschii accessions using RNA-sequencing. Gene ontology, analysis of pathway enrichment and transcription factors provided an apprehensible review of differentially expressed genes and highlighted biological mechanisms behind the Aegilops – P. triticina interaction. The results showed the resistant accession could uniquely recognize pathogen invasion and respond precisely via reducing galactosyltransferase and overexpressing chromatin remodeling, signaling pathways, cellular homeostasis regulation, alkaloid biosynthesis pathway and alpha-linolenic acid metabolism. However, the suppression of photosynthetic pathway and external stimulus responses were observed upon rust infection in the susceptible genotype. In particular, this first report of comparative transcriptome analysis offers an insight into the strength and weakness of Aegilops against leaf rust and exhibits a pipeline for future wheat breeding programs.

Evaluation of genetic biodiversity for micronutrients is crucial for breeding high-quality crops and addressing the negative impacts of mineral deficiencies. The objectives of this research were to assess genetic variation and the relationship between grain Fe and Zn levels and agronomic traits in a diverse collection of wheat varieties. Additionally, the study aimed to determine the correlation between microsatellite markers (SSR) and micronutrient quantities. A total of 42 genotypes (Iranian commercial cultivars, landraces, and Afghan and Swiss varieties) were evaluated over a two-year period. Fe and Zn levels were measured using two semi quantitative staining assays and atomic absorption spectrophotometry (AAS) facility. Semi-quantitative staining methods and AAS showed high correlations for micronutrient contents. Landraces exhibited higher Fe (63.79 mg/kg) and Zn (44.76 mg/kg) but lower grain yield compared with commercial cultivars. Heritability estimates ranged 53%-79.43%, suggesting that genetic variance played a higher contribution in the phenotypic variation of traits than environmental factors. Notably, Fe content displayed significant correlations with days to maturity. Canonical correlation analysis (CCA) revealed that Zn content was correlated with four agronomic traits. Evaluation of genetic diversity using SSR markers demonstrated high genetic variation among the genotypes tested. The analysis of polymorphism information content (PIC) indicated that SSR primers had an average PIC of 0.75, with the Xgwm192 primer exhibiting higher PIC than others. Several SSR markers revealed association with micronutrient content that can be used in marker-assisted selection (MAS) programs aimed at selection of high micronutrient genotypes. In conclusion, the findings underscored the substantial genetic diversity present in micronutrient levels among global wheat genotypes, the potential of landraces for micronutrients biofortification of wheat cultivars through cross hybridization, the utility of staining methods for screening high/low micronutrient genotypes, and use of microsatellite markers for marker-assisted breeding aiming to micronutrient improvement in breeding programs.

Biochemical and metabolic processes help plants tolerate the adverse effects of drought. In plants accumulating bioactive compounds, understanding the genetic control of the biosynthesis of biochemical pathways helps the discovery of candidate gene (CG)-metabolite relationships. The metabolic profile of flowers in 119 rapeseed ( ) accessions was assessed over two irrigation treatments, one a well-watered (WW) condition and the other a drought stress (DS) regime. We integrated information gained from 52,157 single-nucleotide polymorphism (SNP) markers, metabolites, and transcriptomes to identify linked SNPs and CGs responsible for the genetic control of flower phenolic compounds and regulatory elements. In a genome-wide association study (GWAS), of the SNPs tested, 29,310 SNPs were qualified to assess the population structure and linkage disequilibrium (LD), of which several SNPs for radical scavenging activity (RSA) and total flavanol content (TFLC) were common between the two irrigation conditions and pleiotropic SNPs were found for chlorogenic and coumaric acids content. The principal component analysis (PCA) and stepwise regression showed that chlorogenic acid and epicatechin in WW and myricetin in DS conditions were the most important components for RSA. The hierarchical cluster analysis (HCA) showed that vanillic acid, myricetin, gallic acid, and catechin were closely associated in both irrigation conditions. Analysis of GWAS showed that 60 CGs were identified, of which 18 were involved in stress-induced pathways, phenylpropanoid pathway, and flavonoid modifications. Of the CGs, , , , , , and contributed to flavonoid biosynthetic pathways. The results of RNA sequencing (RNA-seq) revealed that the transcript levels of , , and known as early flavonoid biosynthesis-related genes and , , and related to the later stages were increased during drought conditions. The transcription factors (TFs) and related to flavonoids and phenolic acids were upregulated under drought conditions. These findings expand our knowledge on the response mechanisms to DS, particularly regarding the regulation of key phenolic biosynthetic genes in rapeseed. Our data also provided specific linked SNPs for marker-assisted selection (MAS) programs and CGs as resources toward realizing metabolomics-associated breeding of rapeseed.

IntroductionEvaluation of the effects of water-limited conditions on the photosynthetic characteristics and forage yield is important for enhancing the forage productivity and drought tolerance in Kentucky bluegrass ( Poa pratensis L.).MethodsIn the present study, 100 P . pratensis ecotypes collected from different geographical areas in Iran were assessed under well-watered and drought stress conditions. Genetic variation and response to selection for the photosynthetic characteristics [i.e., net photosynthesis rate (A), stomatal conductance ( gs ), transpiration rate (Tr), chlorophyll content (Chl), and photochemical efficiency (Fv/Fm)] and forage yield [fresh forage yield (FY) and dry forage yield (Dy)] traits were analyzed during the 2018 and 2019 growing seasons.Results and discussionDrought stress had negative effects on evaluated photosynthesis parameters and significantly reduced dry and fresh forage yields. On average, FY with a 45% decrease and gs with a 326% decrease under drought stress conditions showed the highest reduction rate among forage yield and photosynthesis traits, respectively. Genotypic coefficients of variation (GCV) for FY were lower under drought stress. The estimates of heritability, genetic advance, and genetic advance as percentage of mean showed the predominance of additive gene action for the traits. Overall, the results showed that “Ciakhor”, “Damavand”, “Karvandan”, “Basmenj”, “Abr2”, “Abrumand”, “Borhan”, “Hezarkanian”, “LasemCheshmeh”, “Torshab”, and “DoSar” have higher forage yield production with little change between two irrigation regimes, which makes them promising candidates for developing high-yielding drought-tolerant varieties through breeding programs.