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Crop wild resources are excellent sources of new genetic variation for resilience against climate extremes. However, detailed characterization of the desirable phenotypes is essential before using these crop wild resources in breeding programs. This current study was, therefore, conducted to investigate the water stress responses of eight wild Elymus species and two wheat cultivars. The experiment was carried out under varying levels of osmotic stress induced by polyethylene glycol and progressive water stress through different field capacities. Water stress significantly reduced both physiological and biochemical traits compared to control, ranging from7.1% (protein content) to 34.5% (chlorophyll) under moderate stress and 9.1-45.8% under severe stress. The anatomical features were also affected under progressive water stress, including a reduction in xylem vessel diameter (7.92 and 16.50%), phloem length (4.36 and 7.18%), vascular bundle length (3.09 and 6.04%), and ground tissue thickness (2.36 and 5.52%), respectively. Conclusively, Elymus borianus (endemic to Swat, Pakistan), E. russelli, E. caninus, E. longioristatus, and E. dauhuricus outperformed the check wheat cultivar, Pirsabak 2005, which is a rainfed variety. The results revealed that Elymus species belonging to the tertiary gene pool of bread wheat could be an excellent drought tolerance source for use in a breeding program. [ABSTRACT FROM AUTHOR]

Grain yield (GY) prediction for wheat based on canopy spectral reflectance can improve selection efficiency in breeding programs. Time-series spectral information from different growth stages such as flowering to maturity is considered to have high accuracy in predicting GY and combining this information from multiple growth stages could effectively improve prediction accuracy. For this, 207 wheat cultivars and breeding lines were grown in full and limited irrigation treatments, and their canopy spectral reflectance was measured at the flowering, early, middle, and late grain fill stages. The potential of temporal spectral information at multiple growth stages for GY prediction was evaluated by a new method based on stacking the multiple growth stages data. Twenty VIs derived from spectral reflectance were used as the input feature of a support vector regression (SVR) to predict GY at each growth stage. The predicted GY values at multiple growth stages were trained by multiple linear regression (MLR) to establish a second-level prediction model. Results suggested that the prediction accuracy (R2) of VIs data from single growth stages ranged from 0.60 to 0.66 and 0.35 to 0.42 in the full and limited irrigation treatments, respectively. The prediction accuracy was increased by an average of 0.06, 0.07, and 0.07 after stacking the VIs of two, three, and four growth stages, respectively, under full irrigation. Similarly, under limited irrigation, the prediction accuracy was increased by 0.03, 0.04, and 0.04 by stacking the VIs of two, three, and four growth stages, respectively. Stacking of VIs of multiple important growth stages can increase the accuracy of GY prediction and application of a stable stacking model could increase the usefulness of data obtained from different phenotyping platforms. [ABSTRACT FROM AUTHOR]

Synthetic hexaploid wheats and their derived advanced lines were subject to empirical selection in developing genetically superior cultivars. To investigate genetic diversity, patterns of nucleotide diversity, population structure, and selection signatures during wheat breeding, we tested 422 wheat accessions, including 145 synthetic-derived wheats, 128 spring wheat cultivars, and 149 advanced breeding lines from Pakistan. A total of 18,589 high-quality GBS-SNPs were identified that were distributed across the A (40%), B (49%), and D (11%) genomes. Values of population diversity parameters were estimated across chromosomes and genomes. Genome-wide average values of genetic diversity and polymorphic information content were estimated to be 0.30 and 0.25, respectively. Neighbor-joining (NJ) tree, principal component analysis (PCA), and kinship analyses revealed that synthetic-derived wheats and advanced breeding lines were genetically diverse. The 422 accessions were not separated into distinct groups by NJ analysis and confirmed using the PCA. This conclusion was validated with both relative kinship and Rogers' genetic distance analyses. EigenGWAS analysis revealed that 32 unique genome regions had undergone selection. We found that 50% of the selected regions were located in the B-genome, 29% in the D-genome, and 21% in the A-genome. Previously known functional genes or QTL were found within the selection regions associated with phenology-related traits such as vernalization, adaptability, disease resistance, and yield-related traits. The selection signatures identified in the present investigation will be useful for understanding the targets of modern wheat breeding in Pakistan. [ABSTRACT FROM AUTHOR]

Karnal bunt caused by Tilletia indica is a quarantine disease of wheat causing huge economic losses due to the ban on the import of bunted grains. This study was designed to characterize pathogenicity, aggressiveness and genetic diversity of 68 Tilletia indica isolates collected from different geographic regions of Pakistan. Forty-six isolates were tested for their pathogenicity on eight wheat varieties, out of which three were non-aggressive. The coefficient of infection (CI) ranged from 15.73% (PB-25) to 10% (PB-68, PB-60, and PB-43). The isolates collected from central Punjab showed higher infestation compared to other isolates. Among the wheat varieties used for the aggressiveness study, WL-711 showed susceptible reaction with 10.88% CI, while NIFA-Barsat, HD-29, Janbaz, Bakhtawar-92, Tatara, and AARI 2011 showed resistance to the highly resistant response. These isolates were amplified using 31 random amplified polymorphic DNA (RAPD) markers and 32 inter-simple sequence repeat (ISSR) markers for diversity analysis. The principal component analysis (PCA) and analysis of molecular variance (AMOVA) showed greater divergence among isolates collected from Punjab and Khyber Pakhtunkhwa (KPK), with a moderate level of admixture. The isolates from Faisalabad (Punjab) were more aggressive compared to isolates from KPK and were clearly separated based on PCA, indicating the significant genetic distance in the populations. Our findings will assist breeders and pathologists in better understanding the pathogenic variability in Tilletia indica and in subsequent disease management. [ABSTRACT FROM AUTHOR]

Background and aims: Chromium (Cr) toxicity is a rapidly increasing environmental concern and poses a major threat to plant growth as well as food chain. This study was carried out to screen spring wheat diversity panel against Cr toxicity to assess yield reduction, grain contamination extents and genomic regions associated with tolerance to Cr toxicity.Methods: The diversity panel was planted in control and Cr stress (26 mg Cr/kg soil) in paved plots, and several morphological and physiological traits were recorded. Wheat 90 K Infinium iSelect SNP array was used to identify genomic regions underpinning tolerance to Cr toxicity.Results: Some wheat cultivars (Khosar-95, Miraj-08, Millet-11, Sarsabaz and NARC-11) had Cr concentration within international edible threshold limit (1 ppm), but showed greater reduction to grain yield (63–95%) due to higher leaf Cr concentrations (2.35–8.95 ppm). Contrastingly, wheat cultivars Auqab-00 and Pakistan-13 had lower yield reduction up to 9% and 39%, respectively but had higher concentration of Cr in seeds (2.1 and 3.5 ppm, respectively). Genome-wide association studies identified 71 loci linked with yield related traits under Cr stress and 48 loci for differences between control and Cr stress treatments. Further, gene ontology of trait-associated SNPs revealed proteins with significant importance in plant development and tolerance against heavy metal stress.Conclusion: To our knowledge, this is the first study for identification of genomic regions linked to Cr stress, suggesting that this could be useful to identify complex architecture of genetic factors as well as molecular breeding opportunities for tolerance to Cr stress. [ABSTRACT FROM AUTHOR]

Genome-wide association studies (GWAS) were undertaken to identify SNP markers associated with yield and yield-related traits in 123 Pakistani historical wheat cultivars evaluated during 2011-2014 seasons under semi-arid field conditions. The population was genotyped in a high-density Illumina iSelect 90K single nucleotide polymorphism (SNP) assay, and finally 14,960 high quality SNPs were used in GWAS. Population structure examined using 1000 unlinked markers identified seven subpopulations (K=7) that were representative of different breeding programs in Pakistan, in addition to local landraces. Forty four stable marker-trait associations (MTAs) with -- log p >4 were identified for nine yield-related traits. Nine multi-trait MTAs were found on chromosomes 1AL, 1BS, 2AL, 2BS, 2BL, 4BL, 5BL, 6AL and 6BL, and those on 5BL and 6AL were stable across two seasons. Gene annotation and syntey identified that 14 trait-associated SNPs were linked to genes having significant importance in plant development. Favorable alleles for days to heading (DH), plant height (PH), thousand grain weight (TGW) and grain yield (GY) showed minor additive effects and their frequencies were slightly higher in cultivars released after 2000. However, no selection pressure on any favorable allele was identified. These genomic regions identified have historically contributed to achieve yield gains from 2.63 million tonnes in 1947 to 25.7 million tonnes in 2015. Future breeding strategy can be devised to initiate marker-based breeding to accumulate these favorable alleles of SNPs associated with yield-related traits to increase grain yield. Additionally, in silico identification of 454-contigs corresponding to MTAs will facilitate fine mapping and Provisional subsequent cloning of candidate genes and functional marker development. [ABSTRACT FROM AUTHOR]

Detection of senescence’s dynamics in crop breeding is time consuming and needs considerable details regarding its rate of progression and intensity. Normalized difference red-edge index (NDREI) along with four other spectral vegetative indices (SVIs) derived from unmanned aerial vehicle (UAV) based spatial imagery, were evaluated for rapid and accurate prediction of senescence. For this, 32 selected winter wheat genotypes were planted under full and limited irrigation treatments. Significant variations for all five SVIs: green normalize difference vegetation index (GNDVI), simple ratio (SR), green chlorophyll index (GCI), red-edge chlorophyll index (RECI), and normalized difference red-edge index (NDREI) among genotypes and between treatments, were observed from heading to late grain filling stages. The SVIs showed strong relationship (R2 = 0.69 to 0.78) with handheld measurements of chlorophyll and leaf area index (LAI), while negatively correlated (R2 = 0.75 to 0.77) with canopy temperature (CT) across the treatments. NDREI as a new SVI showed higher correlations with ground data under both treatments, similarly as exhibited by other four SVIs. There were medium to strong correlations (r = 0.23–0.63) among SVIs, thousand grain weight (TGW) and grain yield (GY) under both treatments. Senescence rate was calculated by decreasing values of SVIs from their peak values at heading stage, while variance for senescence rate among genotypes and between treatments could be explained by SVIs variations. Under limited irrigation, 10% to 15% higher senescence rate was detected as compared with full irrigation. Principle component analysis corroborated the negative association of high senescence rate with TGW and GY. Some genotypes, such as Beijing 0045, Nongda 5181, and Zhongmai 175, were selected with low senescence rate, stable TGW and GY in both full and limited irrigation treatments, nearly in accordance with the actual performance of these cultivars in field. Thus, SVIs derived from UAV appeared as a promising tool for rapid and precise estimation of senescence rate at maturation stages. [ABSTRACT FROM AUTHOR]

The wheat gene pool has a tremendous amount of genetic diversity for salinity tolerance. During the last few decades, several wheat genetic stocks have been developed showing all three types of tolerance mechanisms, i.e., tissue tolerance, osmotic tolerance and ion (Na+) exclusion. However, delivery of improved crop varieties adapted to saline conditions has been lagging behind due to several reasons including the huge knowledge gap in understanding genetic basis of salinity tolerance in wheat, and then applying the available knowledge to deliver salt-resilient crop varieties. We review the research around salinity tolerance in wheat in context of historical and rapidly evolving breeding technologies and discuss the future prospects. The extensive research on identifying promising resources of salinity tolerance in durum wheat, synthetic hexaploid wheats and tertiary gene pool species such as those of Thinopyrum have been explored to transfer salinity tolerance traits to bread wheat. As the last few years witnessed leading-edge transformations where we have now (i) new and improved genotyping assays in form of SNP arrays and next-generation sequencing to facilitate gene discovery, (ii) new generation turn-over methods to get five to six generations per year by "speed breeding" facilitating gene deployment, (iii) gene-editing tools to precisely manipulate the effects of causal genes, and (iv) new phenomic platforms for capturing salinity effects in field and glass-house conditions. Integration of all these technologies will help in understanding the complex genetic architecture of wheat adaptability in saline soils and will accelerate the delivery of our future potential wheat cultivars. [ABSTRACT FROM AUTHOR]