Resistance to Leaf and Yellow Rust in a Collection of Spanish Bread Wheat Landraces and Association with Ecogeographical Variables

A collection of 84 bread wheat Spanish landraces were inoculated with three isolates of leaf rust and one of yellow rust at the seedling stage in controlled conditions. The latency period of leaf rust on the susceptible landraces was also assessed. An extended collection of 149 landraces was planted in three locations in field trials to evaluate the naturally occurring leaf and yellow rust severity. Several landraces (36) were resistant to one leaf rust isolate at the seedling stage, but only one was resistant to all three isolates. Landraces resistant to PG14 leaf rust isolate originated from areas with higher precipitation and more uniform temperatures. Many resistant landraces were from the north-west zone of Spain, a region with high precipitation and uniform temperatures. Results from the field trials also confirmed this trend. Landraces from the north-west also possessed a longer latency period of leaf rust, an important component of partial resistance. Regarding yellow rust, 16 landraces showed a lower disease severity in the seedling tests. Again, the resistant landraces mostly originated from areas with higher precipitation (especially in winter) and more uniform temperature.

De Novo Transcriptome Assembly and SNP Discovery for the Development of dCAPS Markers in Oat

Cultivated oat (Avena sativa L.) is an important cereal crop that has captured interest worldwide due to its nutritional properties and associated health benefits. Despite this interest, oat has lagged behind other cereal crops in genome studies and the development of DNA markers due to its large and complex genome. RNA-Seq technology has been widely used for transcriptome analysis, functional gene study, and DNA marker development. In this study, we performed the transcriptome sequencing of 10 oat varieties at the seedling stage using the Illumina platform for the development of DNA markers. In total, 31,187,392~41,304,176 trimmed reads (an average of 34,322,925) were generated from 10 oat varieties. All of the trimmed reads of these varieties were assembled and generated, yielding a total of 128,244 assembled unigenes with an average length of 1071.7 bp and N50 of 1752 bp. According to gene ontology (GO) analysis, 30.7% of unigenes were assigned to the “catalytic activity” of the parent term in the molecular function category. Of the 1273 dCAPS markers developed using 491 genotype-specific SNPs, 30 markers exhibiting polymorphism in 28 oat varieties were finally selected. The transcriptome data of oat varieties could be used for functional studies about the seedling stage of oat and information about sequence variations in DNA marker development. These 30 dCAPS markers will be utilized for oat genetic analysis, cultivar identification, and breeders’ rights protection.

Evaluation of Achillea, Matricaria, and Anthemis plants following selection for drought tolerance at seedling stages

The genetic potentials of eight species of Achillea (A. millefolium, A. fillipendulla, A. biebersteinii, A. nobilis, A. eriophora), Matricaria (M. ricotita), and Anthemis (An. haussknechtii and An. tinctoria) under drought conditions during the seedling stage were measured. Non-ionic water-soluble polymer polyethylene glycol (PEG, molecular weight 6000) was used to simulate water stress at five osmotic potential levels (0, –0.3, –0.6, –0.9, and –1.2 MPa). An acceptable threshold value for germination was osmotic potential –0.6 MPa, and the modest osmotic potential was –1.2 MPa for studied taxa. Seedlings of germinated at two control and osmotic potential –0.6 MPa (as an acceptable threshold value for germination) treatments were sowed in a field under rainfed conditions. Genetic differentiation of control plants (CP) versus early selected plants (ESP, germinated at osmotic potential –0.6 MPa) was studied using morphological, physiological, and molecular (ISSR) markers. No significant differences were observed between morphological traits of CP and ESP in all species, however, days to full flowering shortened in ESP. The physiological results demonstrate that under rainfed conditions, the ESP, in a quick response, collect osmolytes and amplify the activity of antioxidative enzymes to survive drought. The genetic relationship in the group of genotypes, that ISSR marker set it out, is affiliated to taxon even though AMOVA showed a partial differentiation between CP and ESP groups (21%). It was concluded that the selection of tolerating individuals at the seedling stage represents a likely positive strategy to have higher drought tolerance feature in plants under rainfed conditions.

Seed Halopriming Improves Salinity Tolerance of Some Rice Cultivars During Seedling Stage

Background Saline land in coastal areas has great potential for crop cultivation. Improving salt tolerance in rice is a key to expanding the available area for its growth and thus improving global food security. Seed priming with salt (halopriming) can enhance plant growth and decrease saline intolerance under salt stress conditions during the subsequent seedling stage. However, there is little known about rice defense mechanisms against salinity at seedling stages after seed halopriming treatment. This study focused on the effect of seed halopriming treatment on salinity tolerance in susceptible cultivars, IR 64, resistant cultivars, Pokkali, and two pigmented rice cultivars, Merah Kalimantan Selatan (Merah Kalsel) and Cempo Ireng Pendek (CI Pendek). We grew these cultivars in hydroponic culture, with and without halopriming at the seed stage, under either non-salt or salt stress conditions during the seedling stage. Results The SES scoring assessment showed that the level of salinity tolerance in susceptible cultivar, IR 64, and moderate cultivar, Merah Kalsel, improved after seed halopriming treatment. Furthermore improved the growth performance of IR 64 and Merah Kalsel rice seedlings. Quantitative PCR revealed that seed halopriming induced expression of the OsNHX1 and OsHKT1 genes in susceptible rice cultivar, IR 64 and Merah Kalsel thereby increasing the level of resistance to salinity. The level expression of OsSOS1 and OsHKT1 genes in resistant cultivar, Pokkali, also increased but not affected on the level of salinity tolerance. On the contrary, seed halopriming decreased the level expression of OsSOS1 genes in pigmented rice cultivar, CI Pendek, but not affected on the level of salinity tolerance. The transporter gene expression induction significantly improved salinity tolerance in salinity-susceptible rice, IR 64, and moderate tolerant rice cultivar, Merah Kalsel. Induction of expression of the OsSOS1 gene in susceptible rice, IR 64, after halopriming seed treatment leads to balance the osmotic pressure by ion exclusion mechanisms, so that be tolerant to salinity stress. Conclusion These results suggest that seed halopriming can improves salinity tolerance of salinity-susceptible and moderate tolerant rice cultivars.

Genomic Prediction of Drought Tolerance during Seedling Stage in Maize using Low-Cost Markers

Drought tolerance in maize is a complex and polygenic trait, especially in the seedling stage. In plant breeding, such traits can be improved by genomic selection (GS), which has become a practical and effective tool. In the present study, a natural maize population named Northeast China core population (NCCP) consisting of 379 inbred lines were genotyped with diversity arrays technology (DArT) and genotyping-by-sequencing (GBS) platforms. Target traits of seedling emergence rate (ER), seedling plant height (SPH), and grain yield (GY) were evaluated under two natural drought environments in northeast China. adequate genetic variants have been found for genomic selection, they are not stable enough between two years. Similarly, the heritability of the three traits is not stable enough, and the heritabilities in 2019 (0.88, 0.82, 0.85 for ER, SPH, GY) are higher than that in 2020 (0.65, 0.53, 0.33) and cross-two-year (0.32, 0.26, 0.33). The current research obtained two kinds of marker sets: the SilicoDArT markers were from DArT-seq, and SNPs were from the GBS and DArT-seq. In total, a number of 11,865 SilicoDArT, 7,837 DArT's SNPs, and 91,003 GBS SNPs were used for analysis after quality control. The results of phylogenetic trees showed that the population was rich in consanguinity. Genomic prediction results showed that the average prediction accuracies estimated using the DArT SNP dataset under the 2-fold cross-validation scheme were 0.27, 0.19, and 0.33, for ER, SPH, and GY, respectively. The result of SilicoDArT is close to the SNPs from DArT-seq, those were 0.26, 0.22, and 0.33. For SPH, the prediction accuracies using SilicoDArT were more than ones using DArT SNP, In some cases, alignment to the reference genome results in a loss to the prediction. The trait with lower heritability can improve the prediction accuracy using filtering of linkage disequilibrium. For the same trait, the prediction accuracy estimated with two types of DArT markers was consistently higher than those estimated with the GBS SNPs under the same genotyping cost. Our results show the prediction accuracy has been improved in some cases of controlling population structure and marker quality, even when the density of the marker is reduced. In the initial maize breeding cycle, Silicodart markers can obtain higher prediction accuracy with a lower cost. However, higher marker density platforms i.e. GBS may play a role in the following breeding cycle for the long term. The natural drought experimental station can reduce the difficulty of phenotypic identification in a water-scarce environment. The accumulation of more yearly data will help to stabilize the heritability and improve predictive accuracy in maize breeding. The experimental design and model for drought resistance also need to be further developed.

Estimation of Aboveground Biomass For Winter Wheat In The Later Growth Stage By Combining Digital Texture And Spectral Analysis

Background: Aboveground biomass (AGB) is an important indicator to predict crop yield. Traditional spectral features or image textures have been proposed to estimate the AGB of crops, but they perform poorly in estimation of AGB at high biomass levels. The present study thus evaluated the ability of spectral features, image textures, combinations thereof to estimate winter wheat AGB. Result: The spectral features were obtained from the wheat canopy reflectance spectra of 400–1000 nm including original wavelengths and seven vegetation indices (VIs), then we screened effective wavelengths (EWs) through successive projection algorithm (SPA) and the optimal vegetation index selected by correlation analysis. The image textures features were extracted by gray level co-occurrence matrix including texture features (TEX) and normalized difference texture index (NDTI), then we selected effective variables including the optimal texture subset (OTEXS) and the optimal normalized difference texture index subset (ONDTIS) through the ranking of feature importance of random forest (RF). Linear regression (LR), partial least squares regression (PLS) and random forest (RF) were established to evaluate the relationship between each calculated feature and AGB. The results demonstrate that the ONDTIS with PLS based on validation datasets exhibited better performance in estimating AGB for the post-seedling stage (R2 = 0.75, RMSE = 0.04). Moreover, the combinations of OTEXS and EWs with LR based on validation datasets exhibited the highest prediction accuracy for the post-seedling stage (R2 = 0.78, RMSE = 0.05). Conclusion: The findings show that the combined use of spectral features and image textures can effectively improve the accuracy for AGB estimation especially in post-seeding stage.